Knowledge Area Module 1 Principles of Societal ...

Knowledge Area Module 1 Principles of Societal Development Societal Influences Affecting Teens Entering High-Tech Fields

Cecilia D. Craig [email protected] Student ID # A00094048 Program: Ph.D. in Education Specialization: General

KAM Assessor: Dr. Sharon Johnson [email protected] Faculty Mentor: Dr. Sharon Johnson [email protected]

Walden University November 28, 2009

ABSTRACT BREADTH In the United States, the number of engineering and computer science graduates has been stagnant or declining in recent decades, potentially affecting U.S. economic health with lost innovations. Exploring societal influences for this trend, the current study analyzes collapse theories to develop an evaluation framework for high-tech innovation health in the United States. Filtering selected technology sector epiphenomena, any with the potential to influence adolescent career selections are identified. Finally, these two seemingly disparate threads are connected, synthesizing the societal change models with the technology epiphenomena findings to surface opportunities to influence teen career selection, setting the stage for social change actions to improve the future innovation health in the United States.

ABSTRACT DEPTH A literature review builds on the Breadth section foundation ideas: societal change and technology epiphenomena, using engineering, computer science, and innovation filters. Three themes emerge from the annotated bibliographies. First, the study identifies society and technology epiphenomena with the potential to influence adolescents, noting any specific gender nuances: the rise of computers, the Internet, and globalization. Next, certain innovation metrics for high-tech are integrated with societal change theories. Finally, connections to the original social change problem of declining or stagnant numbers of engineering and computer science graduates shine a spotlight on what this might portend for the United States and teen career selections.

ABSTRACT APPLICATION Technology innovation is critical to a vibrant economy; unfortunately, the current state of innovation in the United States could be in decline. Selected metrics (Federal spending in research and development, patent applications) to measure the health of United States research and development in engineering and computer science were analyzed to investigate that social change impact question. Against a backdrop of societal change theories, this study provides visual perspectives of innovation metrics and degree graduate number trends. Ultimately, this section concludes by linking the metrics to adolescent career selections and to programs that might affect those outcomes in the future, all through a lens of societal change theory.

TABLE OF CONTENTS OVERVIEW OF KAM 2 ................................................................................................................ 1 BREADTH ...................................................................................................................................... 2 Setting the Stage ....................................................................................................................... 2 Links to KAM 2 and STEM Focus ..................................................................................... 2 Societal Change Models ........................................................................................................... 2 Definition of Collapse ......................................................................................................... 4 Civilization or Society Formation ....................................................................................... 5 Collapse Causes .................................................................................................................. 6 The Last Stages: Reverse, Decline, or Collapse ............................................................... 10 Societal Changes and Technology Events Affecting Technical Talent Pool ......................... 13 Societal Changes of Interest.............................................................................................. 13 Technology Events of Interest .......................................................................................... 17 Internet and Social Paradigm Shifts .................................................................................. 32 Synthesize Society Change Models with Technology Epiphenomena ................................... 34 Linking Ideas from Change Theorists to High-Tech Talent Pool..................................... 34 Linking Ideas from Change Theorists to High-Tech Industry Development ................... 35 Breadth Summary ................................................................................................................... 38 DEPTH.......................................................................................................................................... 41 Annotated Bibliography .......................................................................................................... 41 Literature Review Essay ......................................................................................................... 74 Society and Technology Epiphenomena With Respect to Teens ........................................... 74 Advent of Computers, Laptops, and the Internet .............................................................. 74 Generation Y Characteristics ............................................................................................ 76 Career Influences, Math and Science Education .............................................................. 77 Links to Globalization Affecting Teen Decisions ............................................................ 78 Gender Differences ........................................................................................................... 78 Summarizing Epiphenomena Influences .......................................................................... 81 Globalization Trends for Engineering and Computer Science ............................................... 81 Innovation Center Moving Away from United States ...................................................... 82 Specifics on Women and Globalization ............................................................................ 85 Collapse or Decline Connections for STEM .......................................................................... 85 Decline in Math and Science Ability May Presage Decline for United States ................. 86 Who Values Engineers and Scientists............................................................................... 86 Does the United States Face a Shortage in Engineers and Scientists? ............................. 87 Depth Summary ...................................................................................................................... 88 APPLICATION ............................................................................................................................ 90 Globalization Impacts on Technology Talent Pool and U.S. Innovation ............................... 90 Silicon Valley and High-tech as a State or Nation ........................................................... 91 R&D Health Metrics and Measures .................................................................................. 92 Challenges Facing High-Tech......................................................................................... 103 Programs that Encourage Teens to Study Engineering and Computer Science ................... 104 Application Summary ........................................................................................................... 107 REFERENCES ........................................................................................................................... 109

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TABLE OF FIGURES Figure 1. Technology Epiphenomena Candidates versus U.S. Bachelor Degrees, 1966 – 2006, adapted from National Science Foundation Science and Engineering Degree data (NSF, 2008)................................................................................................................. 18 Figure 2. PC Use in Selected Countries (United Nations Data, from 1981 to 2004) ................. 24 Figure 3. Bachelor’s Degrees for physical sciences, 1966 – 2006, from National Science Foundation (2008)....................................................................................................... 42 Figure 4. Metropolitan Statistical Area (MSA) patent share, as percent of Total, Ethnic, and Chinese MSAs (data from Kerr, 2007, Table 3); matched San Francisco peak for similarity on percent scale. ......................................................................................... 59 Figure 5. Metropolitan Statistical Area (MSA) patent share, as percent of Total, Ethnic, and Chinese MSAs (data from Kerr, 2007, Table 3); same percentage scale used. .......... 60 Figure 6. Category shifting patterns data, focused on STEM changes (data adapted from Rion, 2007, Table 10, p. 74) ................................................................................................. 67 Figure 7. Category shifting patterns data, including Unknown at Intended data, focused on STEM changes (data adapted from Rion, 2007, Tables 10 and 11, pp. 74 & 76) ...... 67 Figure 8. Bachelor’s Degrees, Four-Year Programs, Engineering, Computer Science, and Information Technology from China, India, and the United States. Graph created from data found in Wadhwa, Gereffi, Rissing, & Ong, 2007, p. 75 ........................... 72 Figure 9. NSF data (1987 - 2004), master’s degrees, native vs. non-native recipients .............. 83 Figure 10. NSF data (1987 - 2004), PhD degrees, native vs. non-native recipients .................... 84 Figure 11. Federal Agency Obligations, Research and Development dollars, in millions, specific areas, spent between 1970 and 2003 (adapted from NSF, 2004)................................ 93 Figure 12. Federal Agency Obligations, Research and Development dollars, as a percent of total spending, specific areas, between 1970 and 2003 (adapted from NSF, 2004) ........... 93 Figure 13. Federal Agency Obligations, in terms of Research and Development dollars, as a percent of total spend, for all areas, between 1970 and 2003 (adapted from NSF, 2004) ........................................................................................................................... 94 Figure 14. Comparisons by country of R&D investments, circa early 1970s .............................. 97 Figure 15. NSF data, 1966 - 2006, Computer Science PhD degrees in the United States. .......... 99 Figure 16. NSF data, 1986 - 2006, Computer Science PhD degrees in the United States. .......... 99 Figure 17. NSF data, 1966 - 2006, Mathematics PhD degrees in the United States. ................. 100 Figure 18. NSF data, 1986 - 2006, Mathematics PhD degrees in the United States. ................. 100 Figure 19. NSF data, 1966 - 2006, Physical Sciences PhD degrees in the United States. ......... 101 Figure 20. NSF data, 1986 - 2006, Physical Sciences PhD degrees in the United States. ......... 101 Figure 21. NSF data, 1966 - 2006, Engineering Sciences PhD degrees in the United States. ... 102 Figure 22. NSF data, 1986 - 2006, Engineering PhD degrees in the United States. .................. 102

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LIST OF TABLES Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7 Table 8 Table 9 Table 10

Computer Developments from 1943 – 2008 ............................................................... 23 Electronics, LASERs, and other Key Hardware Developments, 1954 – 2008 ........... 26 Air and Space Developments, 1957 – 1976 ................................................................ 28 Air and Space Developments, 1981 – 2006 ................................................................ 29 Biology, Medicine, and Environment Developments, 1953 – 2008 ........................... 31 Internet Developments (1969 – 1994) ........................................................................ 33 Summary of Collapse Theorists Considered............................................................... 39 Population metrics of six nations, from the early 1970s............................................. 95 Technology metrics of five nations, from the early 1970s ......................................... 95 Education metrics of five nations, from the early 1970s ............................................ 96

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Running head: KNOWLEDGE AREA MODULE 1

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OVERVIEW OF KAM 2 High-tech industries, which depend on physical science, computer science, and engineering graduates, might be declining in the United States, possibly rapidly: the definition for collapse. This KAM analyzes the state of high-tech from various perspectives and considers the impact of high-tech health changes on teen career choices. The researcher will compare and contrast common themes from societal change theorists who have studied formation, decline, and collapse of societies and groups from seemingly disparate points of view. Epiphenomena or technological breakthroughs that might have influenced teen career choices in past decades are analyzed. Finally, relevant globalization influences are integrated with collapse theory and epiphenomena, with a description of experiential programs that might counteract any negative influences.


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BREADTH SBSF 8110: THEORIES OF SOCIETAL DEVELOPMENT Setting the Stage Links to KAM 2 and STEM Focus In KAM 2 Breadth, this author explored reasons for teen career selection, specifically Science, Engineering, Technology, and Mathematics (STEM) careers, analyzing career development theories and examining influences from experiential programs on teen career decisions. (Craig, 2009a). In this KAM, by shifting the focus to societal influences, broader civilization or national level societal changes are analyzed, as well as certain epiphenomena that might influence teen career decisions from an orthogonal view. In this Breadth section, theorists who have studied societal declines and collapses will be evaluated, followed by an overview of key events in the study period (1966 – 2006), summarizing with a synthesis of connections between collapse theorists and relevant data. Societal Change Models Jared Diamond’s Pulitzer Prize winning book, Guns, Germs, and Steel (1999), outlined reasons for civilization formation from an evolutionary and geography point of view. Many of Europe’s nations, the United States, and Canada, per Diamond, owed their success to the ability of prior civilizations to share ideas, domesticated grains and animals, and other new techniques or knowledge across easily passable latitude (East-West) lines in Europe and North America, not possible in Africa or Central and South America with deserts and mountains as barriers. Some societies almost disappeared, certainly lost strength, because they did not have domesticated animals in their history. Thus, they did not develop immunities to the disease and plague from those domesticated animals that arrived later to decimate their societies. With a consistent food


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source throughout the year, year over year, from domesticated grains and animals, civilizations had the extra resources and labor to build up technology, allowing them to grow in size and complexity. Guns, Germs, and Steel demonstrated Diamond’s hypotheses with analyses of available wild animals and grains, concluding why domestication was possible in some cases and not in others, and how these domesticated food products influenced society formation. Diamond’s subsequent book, Collapse (2005), took the ideas put forward in Guns, Germs, and Steel and turned the focus on environmental misuse pathways as explanations for collapsed societies, such as Greenland and Easter Island, and suggested thought provoking links to current issues, such as, global warming, water scarcity, and the rising number of endangered species. The concepts in Collapse were the catalyst for this KAM’s theory focus. By synthesizing themes from Diamond and other collapse theorists, using them as a lens to view the state of high-tech innovation in the United States, the researcher aims to conclude if it is in a state of collapse or not. All theorists spoke of non-linear events—catastrophes, disasters, traps, invading armies, or shocks—that seemingly precipitated a rapid decline or collapse. Nevertheless, the response pattern that the society or a polity developed, or conversely did not develop, was the significant factor (Diamond, 2005; Dosh, 2009). Example after example showed how humans responded to unexpected, essentially non-linear or outlier, events, and a decline or collapse did not occur, or conversely, did not respond and collapse ensued. Many theorists (Brunk, 2002; Dosh, 2009; Tainter, 1988) described a life cycle with a potential to trend positive or negative, depending on events and reactions to events. Seemingly, small events could be the tipping point for a recovery or continuation to a collapse or decline. Brunk (2002), with his self-organized criticality model, described the influence of small events especially well: “All aggregate-level, monumental events


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are somehow ‘caused’ by the process of self-organized criticality” (p. 197). What mattered most were two factors: (a) response pattern and (b) current state of affairs (i.e., how weak?) (Motyl, 2001, p. 28). Definition of Collapse In Collapse (2005), Jared Diamond described causes for civilization or society collapse resulting from environmental factors: first, an internal factor, a society unable to develop a response to a second or external factor, an environmental challenge of some type. Reviewers Menocal and Cook (2005) aptly described these factors as “vulnerabilities” (p. S91). Demeritt, in a 2005 review, asserted that Diamond’s extensive use of islands, or other “relatively isolated groups [Anasazi]…tends to treat them as cases of endogenous collapse within essentially closed systems” (p. S93). The scholarly world viewed Collapse as a popular book, albeit with significant merit to the average reader, but not a scholarly book. Nevertheless, Kirch (2005), an academic reviewer whose research data Diamond heavily drew upon, applauded Diamond’s effort to take “disparate and formerly disconnected set of academic research studies together” (p. S96), stating he agreed with most of Diamond’s conclusions. Tainter (1988), decades earlier, defined societal collapse as “when [the society] displays a rapid, significant loss of an established level of sociopolitical complexity” (loc. 149). The process change had to occur over “no more than a few decades…and must [be] substantial” (loc. 151), otherwise the change was a decline. Ultimately, “collapse is a process of decline in complexity” (loc. 580). Diamond used similar but somewhat different language: “a drastic decrease in human population size and/or political/economic/social complexity, over a considerable area, for an extended time” (2005, p. 3). Collapse is a rapid version of decline; both are negative trends for a society’s health.


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Civilization or Society Formation To understand collapse or decline, one can learn by examining the formation of a society, its creation (Tainter, 1988). Other theorists, described by Tainter had seemingly opposite viewpoints for why civilizations or societies formed; one group believed they formed from conflict, to resolve problems; the other group concluded that factions integrated to solve those problems. Tainter saw merit in both views: conflict or integration as a process for problem resolution. Motyl (2001) described empire formation using a center and spoke wheel analogy. The center core was the empire elite, connecting through a spoke either continuously (nearby) or discontinuously to peripheral entities, each with its own elites. However, no significant communications or structures existed between the hub peripheral entities (Motyl, 2001). Empires specifically depended on the lack of a hub joining the peripheral entities. All communication, requests for support, support provisions, economic or political intercourse went through the empire’s core. Decline or collapse of empires revolved around the state of the spokes and changing relationships among hub points. (Motyl, 2001). Brunk agreed, “Unless societies can evolve and innovate…eventually they no longer have enough resources to address their problems (Olson, 1982; Tainter, 1995); [collapsing] from what would have been an insignificant event in any other circumstances” (2002, p. 219). In Motyl’s parlance, the spoke essentially disappeared. Complexity developed in organizations (and societies) to manage complexity: a need for leadership arose and resource—people and assets—management needs came to the forefront. Conversely, when one of these control processes (leadership or resource management) was not present, either a decline or collapse could occur simply because the society had lost the ability to respond to obstacles (Tainter, 1988, loc. 2700). Tainter’s crisp description of this scenario was


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“complexity increases as systems differentiate in structure and increase in organization. Humans employ complexity as a response to problems” (De Menocal, et al., 2005, p. S98). Thus, as societies grew larger, they became more complex. As some point, that complexity level became a quagmire. Collapse Causes Tainter stated unless a “power vacuum” (2005, loc. 3147) existed, collapse cannot occur; instead then it was simply a change of leadership, though possibly a significant one. If no power existed to continue to take over, the society could collapse. Similar to Motyl (2001), Tainter (1988) asserted that for a society to be complex, it must have a center. The center was “the location of legal and governmental institutions,…the source of order, and the symbol of moral authority and social continuity” (loc. 521). If the society’s center was not able to support its spoke entities or react positively to problems, then a decline did occur (loc. 535) Besides the classic situations—Roman Empire fall, Mayan civilizations collapse, Chachoan tribes disappearance—one might consider other situations as collapses, such as the decline of Spain after the loss of the Spanish Armada, or England or France at various times in their history. However, Tainter stated those society changes were simply examples of “retrenchment” (1988, loc. 388) from a level of central organization or multi-national scope to something smaller. Tainter (1988) did not give much credence to catastrophe as a cause for collapse, in particular, not as the prime cause; societies overcome similar disasters frequently, in his mind. “Thus, catastrophe arguments present an incomplete causal chain: the basic assumption… must be that the catastrophes in question somehow exceeded the abilities of the societies to absorb and recover from disaster” (loc. 938) Whether the catastrophe is resource depletion, natural event, or


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invading army, societies can and have found ways to respond to challenges and obstacles. However, if a civilization was experiencing stress and it continued doing the same things, not finding new pathways, the society was less able to overcome any disastrous event (loc. 1013). Additionally, theories attributing collapse to an overthrow by the barbarian hordes needed further explanation in Tainter’s mind. How can a complex society with a standing army lose to the tribally organized upstart, unless the society is weak in some part of its foundation: economically, politically, or socially. On the other hand, Tainter did not discuss or seem to consider possible results from of a series of disasters or a virtually parallel set of problems. Sometimes issues can hit at the same time and become the proverbial straw that broke the camel’s back. Another common theory that Tainter (1988) debunked was collapse as a result of internal conflict or mismanagement. He suggested that societies can overcome conflicts and mismanagement; again, pointing to a more elemental weakness in the society as one cause for collapse. In other words, a single ruler or governing body or elite can be bad or good with resulting impacts; however, it takes a truly ill governing process or economic foundation or social construct to cause a society’s collapse or irreversible decline. Governments and other complex structures seemingly collapsed under their own weight, becoming too expensive to operate, too inflexible to respond to calamities, or too burdensome to the people it supported. (Tainter, 1988). Consider the Roman Empire fall for those three areas. “Literacy and mathematical training apparently declined during the third century. … As fewer people could read or count, the quality and quantity of information reaching the government during this critical time would have declined” (loc. 2134); thus, the Roman government lost touch with its periphery and needed more money to mend that. When invaders began to nibble at


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the edges, ultimately reaching Rome’s center, the Roman armies and government were not able to respond effectively, instead giving up territory piece by piece. Rome began to tax its citizens when previously it had not; debasing currency to pay armies; farmers taxed more, regardless of success, making farm production untenable; inheritance taxes were put in place. As the root cause for the collapse of Rome, Tainter asserted that “the resulting low standard of living restricted internal markets, and when the economy could no longer grow by spatial expansion, it began to decline” (loc. 1196). Ultimately, Rome began to lose its ability to function and feed its people. The Empire’s government was simply too expensive, too inflexible, and too burdensome; further conquests added cost versus providing income, control was too diffuse, and by 250 CE, the Empire had collapsed (Tainter, 1988, loc. 1197). With fewer people and less wealth, the invaders were able to conquer more easily; the more the invaders took, the weaker the Roman Empire became (loc. 2317). Considering the Roman Empire example, the parallels between Tainter’s theory of marginality and the U.S. situation today are thought provoking: increasing taxes, focus on taxing the elite, increasing social entitlements, currency (and rate) manipulation, loss of math and science knowledge in the general populace, and beset by invaders. Overall, many possible connections exist that might ultimately affect the technology resource pool. Considering the reasons for society or polity collapse from another point of view, Dosh (2009) recently studied land invasion communities in South America, as a political force. He developed a theory with three predictive factors for the collapse or continuation of land invasion communities: “tactical innovation, democratic neighborhood governance, and mixed motives that combine material and nonmaterial goals” (p. 88). Dosh found that movements continued because of self-interest (p. 88), all the same, he described a mixture of motives was more likely to have


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existed, in addition to self-interest: for example, “altruism, morality and social norms” (p. 91). He posited that a security trap was a key determinant for an inflexion point, up or down, in the community’s life cycle: when these communities obtained their goal of title to land or purchase, some became complacent or fell into the “security trap” (p. 92), they lost their raison d’être. If instead the community, for example, became passionate about helping other communities, who were driving for what the mature community had already achieved, those role model, or mentor, communities became resilient, mixing self-interest with altruism and expanding social norms (p. 94). They survived by developing a new or expanded mission. Brunk (2002) developed a theory for societal collapse using a relatively new (at that time) mathematical construct of self-organized criticality, or SOC, found in self-organizing systems. After reviewing the concept of chaos theory and rejecting it as not predicative or reliable enough, he described an SOC model using aggregate historical data (e.g., voter turnout). Per Bak’s analogy as stated by Brunk, of a sand pile is apt. The addition of one grain of sand over and over again results in different responses within the sand pile: grains of sand adjust, finally becoming sensitive to small additions, then small collapses can occur, and sometimes the whole pile will collapse (Brunk, 2002). This fits well with Tainter’s theory of marginality (1988). As societies become more complex, eventually marginal returns drive a collapse. Nevertheless, Tainter never adequately explained why some societies collapse quickly and others took centuries. Brunk’s SOC theory provided an explanation for those different pathways. “Frequency of occurrence of SOC events is a linear function of the log of their magnitude” (Brunk, 2002, p. 206) or log (F) = - log (M), where F is frequency and M is magnitude. Analyzing Tainter’s data with this mathematical construct might be instructive.


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Brunk (2002) posited that social scientists have difficulty understanding this mathematical paradigm, since in the past they deemed cause and effect relationships to be linear. That is, small events did not cause large results; only large events caused large results. If human system change is modeled using SOC as the basis, then cataclysmic change will be part of the relationship, not an outlier or a specific cause of a discontinuity or shock (pp. 207-208). Thus, shock size was less important than how the system handled the shock; again, the response pattern was critical. One might describe this model as one with tipping points. Diamond, in Third Ape (1993), made an analogous point on the gene change for speech. If an individual did not have that gene, then she or he was not successful in those times; a sea change occurred in human evolution when that gene arose (pp. 54-56), a tipping point. All theorists studied did describe possible divergent directions from that tipping point. The Last Stages: Reverse, Decline, or Collapse Most theorists suggested selected declines could reverse direction. Diamond in Collapse (2005) certainly expressed a hope that the world and national declines he described will yet see reversal. Dosh (2009) suggested, in his studies of invasion communities, “Movement success depends partly on a group’s capacity to build a sense of citizenship, rather than an exclusive focus on material needs.” (p. 91) and in his research, certain inflexion points were followed by growth. He concluded that communities needed to develop a larger vision quickly after achieving their main objective (p. 113). On the other hand, innovative tactics provided a foundation for success as well, as Dosh saw it; having a mixed motives mission simply helped an organization maintain viability and health, in the long term. From ancient times, Tainter (1988) described a classic turnaround. Around 284 C.E., Rome staved off its ultimate collapse, even experiencing a rebirth, after Diocletian (reigned 284-


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305) helped the empire continue by instituting significant changes, both politically and economic in nature (loc. 2192). The resulting government was a structure more complex than before with a larger military, focusing on “survival of the State” (loc. 2198). The Roman Empire lasted for centuries thereafter, albeit with recurring financial issues, a declining population, and a lack of reserves. Romulus Augustulus, in 476, was the last Roman Emperor. Ultimately, as Tainter stated from an economic viewpoint: “the strategy had been to tax the future to pay for the present, [whereas the later rulers] paid for the present by undermining the future’s ability to pay taxes” (loc. 2366). Thus, in Tainter’s mind, Rome collapsed because its economic foundation eroded and filled with dry rot. On the other hand, after the defeat of the Spanish Armada, Spain had a situation with similar economic roots, coupled with a series of inept rulers, and did not collapse (Tainter, 1998). While many theorists, per Tainter (1988), believed that decline or collapse was almost inevitable, like the end of life of a product in its life cycle, he suggested the answer was not that simple. Tainter’s theory for root causes for a society’s collapse used four concepts: 1. 2. 3. 4.

Human societies are problem-solving organizations; Sociopolitical systems require energy for their maintenance; Increased complexity carries with it increased costs per capita; and Investment in sociopolitical complexity as a problem-solving response often reaches a point of declining marginal returns (loc. 1582).

In addition, Tainter suggested that collapse in and of itself was not necessarily bad; instead, the steps taken after a collapse might help the society’s people develop a more economical and prosperous state, in the longer term (loc. 3084). As a society developed further intricate processes to handle growth and a larger size, each subsequent investment the society made, gained less and less. (Tainter, 1988). In due course, though repeated investment in complex society processes continued to generate “increased


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returns, [it was] at a declining marginal rate [emphasis added] [and the society] became increasingly vulnerable to collapse” (loc. 1913-1914). At that point, economically, a society reaped insufficient returns for the investments it made. Tainter and Brunk both used mathematical concepts in their models to predict direction. Tainter (1988) noted that collapse, as well as formation, was “a continuous variable” (loc. 700). By looking at exogenous and internal causes for change, more broadly describing a collapse situation, Tainter asserted economic causes would be evident. Whereas in Brunk’s mind, not all SOCs were similar or fractal throughout their range, calling them “eipoc or ‘ever increasing probability of cascade’ processes” (2002, pp. 209-210). These “complexity cascades” (p.221) were analyzed by examining either the “short-run component” or the “long-term trend” (p. 210) to determine if a cascade would stop or continue. Essentially, for human systems, when people became more sensitive to the actions of others, then systems became more similar, whereas when individuals acted more independently, a weak SOC connection existed. (Brunk., 2002, p. 211). As a rationale for why civilizations today appear to be lasting longer, Brunk suggested that governments have put in place response systems that address these complexity cascades, for example, FDIC insurance and such like systemic responses. Tainter (1988) obliquely discussed this in his final chapter, asking why no collapse has occurred in recent times. Brunk (2002) iterated that societies might simply have found more ways to “dampen complexity cascades” (p. 221) and not spiral downwards. In summary, whatever the model—groups responding to their environment or spokes without hubs or self-organizing systems or overcoming the security trap—theorists suggested societies can respond to challenges and overcome them, at least for a period of time, depending


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on resources and response patterns. Nevertheless, a single critical event—that last grain of sand—can cause decline to occur, sometimes quite quickly. Societal Changes and Technology Events Affecting Technical Talent Pool This section examines research on society’s responses to technological change and then certain epiphenomena in specific technology areas. In addition, this section addresses selected social fabric changes as well as certain movements in the latter part of the 20th century. Societal Changes of Interest A noted professor of public policy, Francis Fukuyama, in The Great Disruption: Human Nature and the Reconstitution of Social Order (1999), described cycles of social adjustment following periods of major technological change and how these are related. For example, after the rise of technology and industry in the mid to late 1800s, societies around the world became more open socially—the Roaring Twenties—followed by a period of entrenchment. Decades later, with the explosion of computers and information in the mid 1960s, the societal fabric in the industrialized world markedly changed, considering many measures. Crime and divorce rates began to rise; nuclear families became more common than large multi-generation families; and people began to distrust governments and institutions (Fukuyama, 1999). Thus from the 1960s into the latter part of the twentieth century, the social fabric became broadly different from earlier decades, some could say it had decayed. Nonetheless, by the end of the 20th century, those same metrics changed direction as society adjusted and developed new pathways. Social capital or “society’s stock of shared values” (Fukuyama, 1999, p. 14) is needed by societies to foster cooperation and community and thereby effectively adjust to changing circumstances (pp. 13-15). Fukuyama hypothesized that the social capital decline in the Western nations occurred as those same nations moved “from the industrial to the information era” (p. 5).


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The individual innovation fed a rise in technological innovation and was, to some extent, the catalyst for weaker family bonds in the latter half of the 20th century; society was mending the impacts from these disruptions and was constructing a different and stronger fabric. While recognizing that measuring these factors—crime, families, and trust—can be challenging, the case for his hypothesis of linking society capital change with technology change is solid (Fukuyama, 1999). A “renorming” (p. 271), begun in the 1990s, resulted in improvements in the crime, family, and trust metrics resulting in higher social capital values. Feminism and the sexual revolution during the decades of the 1960s and 1970s “were stimulated…by…technological and economic developments related to the end of the industrial era” (Fukuyama, 1999, p. 92). Certain situations provided a fertile ground for societal change to occur. While the nuclear family was common throughout history and its definition may not have changed, the role of men in those families has varied significantly across time and societies (Fukuyama, 1999, p. 100), whereas women’s role as mother in that grouping had not changed much. Fukuyama (1999) posited that the Pill’s invention along with the growing entry of women into the work force ultimately altered the male role, as provider, for better or worse. Another trend marker (Fukuyama, 1999) was the decline of manufacturing jobs, as a percent of employment. This transition of jobs from a lower skill, physical basis to a higher skilled, less physical base required higher education levels (pp. 105-100). Net result was a rising average income for women in all levels of jobs (p. 111). In contrast to what has been thought, women in higher paying positions benefited by this society change; however, women in lower paying roles had seen “the floor collapse under them as they try to raise children by themselves in low-paying, dead-end jobs…[while] men have, on balance, come out about even” (p. 121).


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Fukuyama (1999) considered informal networks as social capital as well. He ascribed the Silicon Valley’s R&D success to those many networks of engineers and scientists across companies, making that area a fertile location for continued innovation. Thus, while manufacturing globalized, R&D had not. Arguably, the R&D situation has begun to change since 1999 when Fukuyama wrote this, moving its locations outside the United States. What is not clear is if the rate of change will rise or fall for the United States in future decades (pp. 206-211). The effectiveness of this social capital concept for virtual and face-to-face networks might be different. For example in the virtual world, email etiquette standards (Horowitz & Barchilon, 1994) warn that when a person flames someone in email, the reader usually considers the flame message as a hostile action. A flame email “refers to angry or otherwise unsuitable wording” (Horowitz & Barchilon, 1994, “Rule 4”) in an email; putting a message in all capital letters is another example, perceived as shouting. Considering the distances and the need for electronic communication in today’s world, people can find it easy to flame someone in email without realizing the impact and not work to develop a trust relationship or positive social capital. (Horowitz & Barchilon, 1994). Fukuyama asserted for positive social capital to develop, a solid trust relationship was essential. Individuals living next to each other or working together face-to-face may not as frequently use the flame approach, face-to-face. This is an area for future research to evaluate the virtual world’s social capital state. Assessing Fukuyama’s social capital concept, by studying virtual interactions over variables of virtual instrument use (e.g., PDAs, texting, and email), generation (e.g., Baby Boomer, Gen X, Gen Y, and Millennial), and training. Adaptation may be occurring, as theorists predicted (Pytlik, Lauda, & Johnson, 1978). Phillips (2000) postulated that causes for innovation were more prevalent in Europe, Canada, and the United States when compared to China, and were not those outlined by


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Diamond (latitude lines, domestication leading to innovation and technology). Instead, beginning with the telegraph, to the telephone, and next to the rise of computers, Phillips stated, “the captains of industry [became] firmly in control of producing wealth” (p. 280). With the Internet, potentially more individuals (versus business leaders) were in control, and the economic processes were changing rapidly. While never specifically stating why this happened in the United States, not China, Phillips described specific funding in R&D (e.g., telegraph industry, ARPANET) that drove innovation and growth in the United States and Western world, fueled by that investment. (Phillips, 2000). Implicit in this analysis is the lack of R&D funding in China, until recent years. On this issue, Brunk believed this lack was due to China maintaining “traditional values” (2002, p. 223) versus supporting a more complex, non-traditional value set. With another view, Marshall McLuhan (in Pytlik, Lauda, & Johnson, 1978) suggested that human’s primary sensory use has migrated with the arrival of various technological changes. Before the printing press, humans were primarily aural or “hearing-oriented” (p.19) since communication and learning was principally transferred by talking and listening; only a few privileged people could afford the hand-printed books in those times. After the printing press allowed lower cost and higher volume availability of books, information exchange moved to the visual arena. “People because disposed to think that seeing is believing.…Habitual reading created people who were detached, critical, even skeptical” (p.19). For centuries, reading was a prime path for learning and communication, until the explosion of telephone, radio, and television over the late 1800s through mid 1900s. Then, humans began receiving information from the airwaves again however, not directly human to human, but instead somewhat distanced by a box. (Pytlik, Lauda, & Johnson, 1978).


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Extrapolating to today’s communication and learning processes, these new pathways for dialogue—computer-to-computer email, then internet, followed by instant messaging and now MySpace and FaceBook—have the potential to transform human communication. As described above, sensory changes had occurred in prior generations (aural to visual to aural); extrapolating that same sensory change concept to include the recent rise of digital media (sight orientation or visual sense) could be evidence of a similar change. People use aural communication (phones, TVs, movies, and the like) extensively today; nevertheless, coupled with visual media accessed by computers and phones, humans might be experiencing a synergy across both senses; only research can validate this hypothesis. On counterpoint, Ito (2005) asserted, “the mobile phone…enable[s] communication…but this does not mean…that the devices erode the integrity of…social identities” (p. 131). McLuhan, as early as the 1970s, posited that human “values, wishes, styles of life, and human goals” (p. 20) change as a result of sensory changes, with the potential for more invasive changes in government and society, certainly a prescient point. To integrate the social changes described above with technology epiphenomena, first an analysis of technology events with the potential to connect to those social changes is necessary. The next paragraphs provide five technology sector overviews explored for this paper. Technology Events of Interest Legendary technology initiatives influenced career selections in the past. “President John F. Kennedy announced on May 25, 1961 that the U.S. intended to land on the moon within the decade” (Singer, 1998, p. 171). By February 1962, John Glenn orbited the earth and by July 20, 1969, the United States had landed on the moon. In the 1960s, teens decided to become engineers and scientists desiring to participate in the moon race. Rachel Carson published Silent Spring in 1962 and influenced environmental practice for decades thereafter. Biologists and


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chemists read that one book, setting them on their life’s course. Dr. Christian Barnard on December 3, 1967 performed the first heart transplant and arguably prompted many to enter medicine or engineering to develop tools for medicine (p. 327). The next section shows events that could have similar potential to influence teen career decisions, like those just described. For the five sectors—computers, electronics, biology, Internet, and social paradigm shifts—potential exemplars (Figure 1) are described, noting specific epiphenomena that likely had an influence on career choices.

Figure 1. Technology Epiphenomena Candidates versus U.S. Bachelor Degrees, 1966 – 2006, adapted from National Science Foundation Science and Engineering Degree data (NSF, 2008)


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Computers. Pytlik, Lauda, and Johnson in Technology, Change, and Society (1978) described the birth of digital computing as beginning during World War II with the Mark I, developed by Aiken. “The Mark I followed a programmed sequence of instructions contained on punched tape…the first automatic, digital computer, but it could not branch and its speed was limited because its operation was electromechanical” (p. 66). However, Aiken’s efforts were not well-known, when compared to the launch of the ENIAC or Electronic Numerical Integrator and Calculator. ENIAC, “the first fully electronic computer” (p. 66), was the brainchild of a team from University of Pennsylvania’s Moore School of Engineering and the U.S. Army. This large computer built from “eighteen thousand vacuum tubes” (p. 66) had a large influence on both hardware and software development in future decades, in terms of architecture, design, and engineering curriculum (Pytlik, Lauda, & Johnson, 1978). Until the invention of the transistor, circa 1947, and then its implementation into a computer design, the cost and size of computers would not shrink. Turing proposed a computing machine in 1936 “to compute all mathematical elements” (Singer, 1998, p. 92), later followed by his 1945 paper describing the Turing machine. Then in 1945, von Neumann designed a general-purpose computer with a Memory Unit, an Arithmetic Unit, and a Control or Processing Unit; at this point, memory was the significant technology limiter (pp. 95-97). Von Neumann’s architecture became the basis for future computers for decades, still providing that foundation today. The ENIAC was developed, using the Turing concept and von Neumann architecture, to perform ballistic calculations “completed in November 1945…100 feet long, 8 feet high, 3 feet deep, and weighed thirty tons [with] 18,000 vacuum tubes and cost over $50,000” (p. 95). However, to implement a new program, rewiring of the computer’s cables was required. Eckert and Mauchly, known for inventing this first digital


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computer, founded the first business to sell electronic computers. [Rear Admiral Grace Murray Hopper was one of the programmers on ENIAC; later, she described a compiler for the first time and COBOL (Common Business Oriented Language) has its origins in her first compilers at UNIVAC.] (Singer, 1998). Only a few years later, in 1954, IBM launched the 650, the “first moderately priced computer” (p. 98), followed by the ubiquitous and strongly influential Systems/360 in April 1964. The age of mainframes was underway and computer science became a college curriculum focus by the mid-1960s. Mainframes led to minicomputers in the 1960s, principally at companies outside IBM, like Digital Equipment Corporation (DEC), Data General (DG), and others. Several minicomputers whose influence went beyond simple computing were the Honeywell DDP-516 (the first 16-bit minicomputer in 1964), Nova from DG (1968) followed by SuperNova (first IC memory in 1971), DEC’s PDP-11 (universal bus architecture in 1970), and the Cray-1 (1976, a pivotal supercomputer). These smaller, less expensive machines, influenced another generation, giving birth to a new paradigm of company formation (building on brainpower versus equipment), and ultimately led to the personal computer. Ceruzzi stated, “1974 was the annus mirabilis of personal computing” [emphasis present] (1998, p. 226). Beginning with the seminal launch of the Altair personal computer in 1974, computers moved from mainframes and minicomputers to become personal, though it took more than ten years for the world to embrace the term personal computer, or PC. Using an 8-bit Intel 8080, Ed Roberts designed the Altair as a “set of parts….no keyboard and no screen” (Singer, 1998, p.105). Micro Instrumentation and Telemetry Systems sold the Altair 8800 for less than $400 (Ceruzzi, 1998, p. 226). Users manipulated switches on the front to program the unit. Other companies attempted to make (and many did) a large profit in this new market: Wang, Radio


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Shack, Apple, and Commodore, to name a few. The years between 1974 and 1977 “saw a burst of energy and creativity in computing that had almost no equal in its history” (Ceruzzi, 1998, p. 230). Two major weaknesses of the Altair and its initial followers were: (a) the lack of a reliable storage device and (b) no easy way for users to write application software for this new small device (Ceruzzi, 1998, p. 232). In 1977, the Apple II, developed by Steve Wozniak and marketed by Steve Jobs via their new company, Apple, added even more fuel to the personal computer revolutionary fire. It used a cassette tape for storing programs; initially it did not reliably store programs (Tim Craig, personal communication, May 16, 2009) and until Wozniak developed an external floppy drive, the computer was, more or less, useless: nonetheless, influential. In 1981, IBM launched its 16bit Personal Computer, with PC-Disk Operating Systems (PC-DOS, licensed from Microsoft), rapidly followed by Dell, Compaq, HP, and others. The race was on, leading to laptops, electronic book readers, personal digital assistants, bringing the computer in less than 60 years from room-size to wallet-size. Lowering costs and a growing number of applications made these attractive to college students outside of engineering and computer science. Software development showed parallel growth, with hardware and software developments frequently feeding each other, back and forth. One of the first disk operating systems (OS) designed for use on early personal computers was CP/M (Control Program for Microcomputers), developed by Gary Kildall at the Naval Postgraduate School (Tim Craig, personal communication, May 16, 2009). Kildall founded Digital Research to market CP/M. The Apple II did not use CP/M initially, providing its own proprietary operating system, a practice Apple continued over time. In 1981, the Xerox 820 (code named “Worm” to eat the Apple, Z80 based) used CP/M (as did many others), one of the first standard PC operating systems. Neither


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the Xerox 820 nor CP/M survived long after Microsoft developed the Microsoft DOS, or MSDOS, and IBM launched its PC-DOS. From these computer events (described above and in Table 1) the primary stand out, with the potential as an epiphenomenon and possibly influencing teen career choices, was the birth of personal computing. It began in 1974 with Altair 8800, followed by the Apple II, TRS-80, and others, until IBM changed the landscape forever in 1981, making the PC less geeky and eminently attainable. The peripherals, languages, and internet developed to fuel the PC’s adoption did not typically capture public interest, but provided the glue and decorations, so to speak. As shown in Figure 2, PC use in the United States has been rising fast, and not linearly, ever since.


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Table 1 Computer Developments from 1943 – 2008 Year

Key Milestones

1943-45

ENIAC development by Mauchly and Eckert. Von Neumann architecture developed.

1947

First bipolar transistor.

1951

First UNIVAC delivered to the Census Bureau by Remington Rand (ENIAC origins).

1954

IBM launches the 650, the “first moderately priced computer” (Singer, 1998, p. 98).

1954

Integrated circuits begin to replace vacuum tubes.

1964

System/360 from IBM: pivotal mainframe design.

1964

BASIC language (Beginner’s All-purpose Symbolic Instruction Code) developed by Kemeny and Kurtz at Dartmouth (Singer, 1998, p. 99).

1971

Super Nova from Data General used IC based memory for the first time.

1973

The Xerox Alto, arguably the first personal computer, built at a price tag of $18,000 (to build) (Ceruzzi, 1998, p. 261), using Ethernet.

1974

Altair 8800, known as the first truly personal computer, sold for less than $400.

1976

Cray-1, “world’s fastest supercomputer” (Singer, 1998, p. 114), used in cold war.

1977

Commodore PET, Radio Shack’s TRS-80, and Apple II kick-start the PC revolution.

1981

IBM Personal Computer (PC) arrives.

1981

Xerox STAR 8010, personal computer with integrated office software (~$10K), and a Graphical User Interface (GUI), mouse, and operating in an integrated network.

1984

Macintosh, $2,495 with “elegant system software” (Ceruzzi, 1998, p. 275).

Note. From 20th century revolutions in technology by E. N. Singer, 1998, Commack, NY: Nova Science Publishers; and A history of computing by P. E. Ceruzzi, 1998, Cambridge, MA: MIT Press.


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Figure 2. PC Use in Selected Countries (United Nations Data, from 1981 to 2004)

Electronics and associated technology. Early computers used vacuum tubes resulting in large computers. One singular invention—the transistor and its progeny—moved computers to the size of a wallet over the next decades. Shockley, Bardeen, and Brattain created the first bipolar transistor in 1947 for which they received the Nobel Prize for Physics in 1956. Shockley founded Shockley Semiconductor Lab (SSL); future luminaries, Noyce and Moore, joined SSL, later leaving to found (with others) Fairchild Semiconductor in 1956, and later founding Intel. Thus began the transformation of the beautiful Blossom Valley of San Jose and its environs into


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Silicon Valley, both figuratively and literally. National Semiconductor, AMD, and Intel rose from that one parent, Fairchild (Singer, 1998, p. 61), along with many, many other Silicon Valley companies over subsequent decades. The next major chip breakthrough was in 1971 when Ted Hoff (Intel) conceived of an IC as a general-purpose microcomputer (Singer, 1998, p. 100); and Intel announced the Intel 4004 microprocessor. Computer, semiconductor, and storage companies pioneered technology advances that drove the size and cost of computers down over subsequent decades. Data General’s Super Nova, in 1971 (Ceruzzi, 1998), launched the concept of IC-based memory (versus magnetic media, an earlier innovation from vacuum tubes). Memory chip size rapidly reduced in size in the later 20th century decades: 1974, 0.02 in.2; 1984, 0.69 in.2; and 1989, 0.12 in.2. IBM designed the so-called Winchester drive with two spindles of 30 megabytes each, or 30-30, like the Winchester rifle (p. 200). The 8” floppy drive, invented by IBM in 1971 (p. 232) as a way to store programs, led to smaller versions, fueling more powerful mainframes, minicomputers, and personal computers. Input and output devices fed the entire computing spectrum. A notable input device still in use was the mouse, brainchild of Englebart at ARPA in 1967, and designed by Xerox engineer, Bill English, at Palo Alto Research Center (PARC) (p. 260); the mouse was a key enabler for Internet growth in latter decades. These inventions along with several others shown in Table 2 provide a picture of growth and impact across many STEM disciplines, influencing many in their engineering career choice.


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Table 2 Electronics, LASERs, and other Key Hardware Developments, 1954 – 2008 Year 1954

Key Milestones Shockley Semiconductor Lab formed leading to Fairchild Semiconductor. Fairchild was the patriarch of many Silicon Valley companies over the following decades.

1960

Maiman, at Hughes, built first working ruby red LASER (Light Amplification by Stimulated Emission of Radiation). (Singer, 1998, pp. 123-126).

1961

Integrated circuit (IC) developed by Jack St. Clair Kilby in 1958 led to first commercial IC in 1961. (p. 66)

1962

Semiconductor laser invented (GE, IBM, & Lincoln Lab, about same time (p. 132).

1964

Argon Ion Laser, used in eye surgery, developed at Bridges at Hughes Research Laboratories (p. 130).

1965

Audiocassette developed by Philips (Netherlands).

1967

Mouse concept first formulated (Ceruzzi, 1998, p. 260)

1970s

Fiber optics developed, small lasers, leading to digital networks

1970

Intel announced 1,024-bit dynamic RAM semiconductor memory chip.

1971

Intel 4004—“first [four bit] commercial microprocessor” (Singer, 1998, p. 100).

1972

HP-35 calculator, $400, first sold.

1984

Computer Disc or CD, an optical storage device, arrived.

Early

Operator used goggles on a helmet, walking on a treadmill, enabling computer to

1990s

identify an operator’s position; developed by Brooks and Fuchs at University of North Carolina (p. 110).

Note. From 20th century revolutions in technology by E. N. Singer, 1998, Commack, NY: Nova Science Publishers; and A history of computing by P. E. Ceruzzi, 1998, Cambridge, MA: MIT Press.


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Space. When the Soviet Union was the first in space with its successful launch and orbit of Sputnik on October 4, 1957, the United States followed rapidly. First by an unsuccessful attempt (Vanguard) on December 6 that same year, then a successful attempt on January 31, 1958 with Explorer I. Teens began to see human space exploration as a possibility in their lifetime. Subsequent launches by both the United States and Soviet Union lit a fire in many people’s minds, but it was not until President Kennedy’s announcement in 1961 that the race began in earnest to land a human on the moon, with a successful Apollo 11 moon landing in 1969. (Singer, 1988). Next in 1970, with President Nixon’s announcement of the space shuttle program, a new wave of engineers grew, working on the Space Shuttle and more expansive interplanetary unmanned missions, such as Viking destined for Mars and Pioneer 11 for Saturn. One of those college students in 1970, Dr. Dunbar, NASA Mission Specialist and Payload Commander (retired 2005), (NASA, 2005) earned her bachelor and master in ceramic engineering, with a vision to be an astronaut [later earning a PhD in engineering] (Bonnie Dunbar, personal communication, circa 1978). She developed processes to manufacture the ceramic tile used in the Space Shuttle “thermal protection system” (para. 5), while at Rockwell International in the mid1970s. Joining the astronaut program in 1981, ultimately orbiting in five Space Shuttle missions, she had a distinguished career at the NASA Johnson Space Center. The vision of exploring space inspired other engineers from those times, beyond Dr. Dunbar (see

Running head: KNOWLEDGE AREA MODULE 1 Table 3 and Table 4 for more and similar events); she was but one example.

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Table 3 Air and Space Developments, 1957 – 1976 Year 1957

Key Milestones Sputnik launched by Soviet Union. US Vanguard launch is unsuccessful

1958

Explorer 1 caused “discovery of the Van Allen radiation belts” (p. 192).

1960

Pioneer 5 orbited the sun, the world’s first interplanetary probe.

1960

Weather satellite, Television and InfraRed Observation Satellite (p. 183).

1961

Vostok 1, first human in orbit, Yrui Gagarin, April 1, 1961 (Soviet Union)

1961

Space race officially began with President Kennedy’s announcement.

1962

John Glenn was first to orbit earth for the United States in February 1962.

1962

Mariner 2 did a fly-by of Venus on December 14, 1962 (p. 195)

1965

First spacewalk, March 18, 1965, Lt. Colonel Aleksei A. Leonov.

1969

Neil A. Armstrong and Edwin E. Aldrin, Jr. walked on the moon, July 20, 1969.

1970

President Nixon approved shuttle program in March 1970

1971

Soviet Union Space station, Salyut 1

1972

Pioneer 10 launched going to Jupiter, sending images 20 years later, then leaving the solar system to take a message to others outside the system

1973

Pioneer 11 went to Saturn, and eventually left the solar system.

1973

Skylab: May 14, 1973 orbited earth, falling out of orbit and burning up in 1979.

1976

Viking 1 went into orbit around Mars and landed a vehicle, followed by Viking 2 within weeks, both capturing data, but finding no life signs.

Note. From 20th century revolutions in technology by E. N. Singer, 1998, Commack, NY: Nova Science Publishers.


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Table 4 Air and Space Developments, 1981 – 2006 Year 1981

Key Milestones First space shuttle, STS-1, orbited for 54 hours landing on glide at Edwards AFB

1986

After flying nine missions successfully, space shuttle Challenger explodes during takeoff January 28, 1986

1986

Hubble telescope was supposed to launch, but benched by Challenger incident

1989

Galileo orbited Jupiter in late 1995, providing data on Jupiter’s gases. (p. 197).

1990

Hubble placed in orbit by Discovery on April 25, 1990. (p. 193)

1994

Shuttle flights resumed

1997

On July 4, 1997, Pathfinder landed on Mars with Sojourner analyzing rocks. (p. 197).

2002

International Space Station established

2003

NASA rovers, Spirit and Opportunity, landed on Mars, still capturing data in 2009.

2003

Columbia disintegrates during reentry after a successful mission


However, the year 1986 brought the Challenger disaster followed by the Columbia disintegration in 2003; it is unclear if these were negative or positive influences on teens and college students, who might have been considering STEM careers. Certainly, 1986 was a peak for engineering and computer science (see Figure 1) followed by a rapid decline in graduates until a small rise began in 2004: correlation possibly, but not causality. Other factors were potentially of influence in those years. For example, the economic conditions during the mid1980s were likely a factor; engineering positions were not plentiful Chuck Dosh, (personal communication, August 1, 2009).


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Medicine, environment, and biology. In those same go-go computer technology and space explorations decades, medicine and biology experienced similar epiphenomena. Following the discovery of DNA structure (1950s), lasers (1960s), and heart transplants (1960s), the 1970s saw a significant rise in medical developments. The United States rapidly adopted Computerized Axial Tomography (CAT) scan methodology, though it originated in the United Kingdom (Singer, 1998, pp. 307-308). Pacemaker implants, developed in 1983, reached 300,000 per year (p. 329); hip replacements reached 120,000 in 1993 (p. 330). Cancer chemotherapy use rose (p. 338). Much was happening in the last quarter of the twentieth century in the biotechnology area. Society has not often recognized women scientists for their contributions. For example, after Franklin received a doctorate in physical chemistry from Cambridge in 1945, she began the road to understanding DNA’s helical structure in France versus in England because “women scientists in France had long been recognized as prominent contributors in the intellectual fields unlike England” (Singer, 1998, p. 347). Watson and Crick, who received a 1962 Nobel Prize for discovery of DNA, used her 1951 research notes. Most believe the Nobel Committee would have recognized her as well, if she had been alive in 1962; Nobel Prizes are not awarded posthumously; she died in 1958 (pp. 347-351). After Carson wrote Silent Spring in 1962, the environmental science field blossomed. Rowland and Molina in 1973 described how chlorinated fluorocarbons, or CFCs, contributed to ozone depletion and, along with Cratzen, received a Nobel Prize in Chemistry in 1995 for their research. (Singer, 1998, pp. 13-15). These two areas—DNA and environment—have influenced teens. Science fair projects consistently focus on environmental subjects (personal observations as a judge over many events); in many conversations with teen researchers, they have described how they want to help the world be a greener place. Table 5 shows these and other events of interest to the life sciences.


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Table 5 Biology, Medicine, and Environment Developments, 1953 – 2008 Year 1953

Key Milestones Watson and Crick publish their seminal article on DNA structure in Nature (Singer, 1998, p. 349).

1960

First pacemaker successfully installed in 1960 (p. 328).

1962

Rachel Carson published Silent Spring.

1967

Dr. Christian Barnard transplanted a human heart, (p. 327).

1970s

Computerized Axial Tomography (CAT) scans; pacemakers, hip replacements, chemotherapy, and birth control pills.

1973

Chlorinated fluorocarbons, or CFCs, found to contribute to ozone depletion, leading to a ban on aerosol use of CFCs in 1978 (p. 15).

1978

February 5, 1978, the first Magnetic Resonance Image (MRI), developed by Raymond Damadian, detected a known cancerous tumor (pp. 310-313).

1989

Dr. Phillipe Mouret performed the first gall bladder removal operation laparoscopically (p. 325).

1990s

Human Genome Project began to completely map human DNA

1993

Three important discoveries made involving genes involving “colon cancer, Lou Gehrig’s disease, and Huntington’s disease” (p. 365).

~1995

United States began a phase out of CFCs

1996

Dolly: first cloned sheep (p. 357), one example of genetic engineering



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Internet and Social Paradigm Shifts Though many think the Internet began in the early 1990s, computer networks had their origins much earlier. In the late 1960s, the Advanced Research Project Agency (ARPA was in the Department of Defense) funded ARPANET to connect various research groups across the country. The first four nodes used Honeywell DDP-516 minicomputers as the Interface Message Processors (IMP) connecting other computer hardware and locations. First demonstrated to the public in 1972 with 30 nodes, the IMP nodes needed hardware connectors for the nascent network, ultimately hardware and software standards and other developments made the use of dedicated hardware nodes unnecessary (Ceruzzi, 1998, pp. 194-195). The Internet needed several tools to grow from ARPANET: identifying names (URL or Uniform Resource Locator), a process (HTTP or HyperText Transfer Protocol), a language (HTML or HyperText Markup Language), and last an application to view it all: a browser. Tim Berners-Lee developed the first three tools while working at CERN in Switzerland in 1991; Marc Andreesen and Jim Clark (founder of Silicon Graphics, a major workstation company) founded Netscape to provide a browser in 1994, building upon the Mosaic browser that Andreesen had developed in 1992 while at University of Illinois, Champaign-Urbana (another ARPA funded project). (Ceruzzi, 1998). Table 6 describes some key internet events and suggested possible epiphenomena of interest for the United States and the world. As an example of influence, Abhijit Kumbhare, currently a software development manager in networking, originally from India, shared how the internet’s birth, in the early 1990s, affected his choice of a career and in mid-stream too. He was studying metallurgical engineering in India, in his sophomore year of a bachelor’s program, and when the Internet arrived, he moved into computer science (personal communication, May 19, 2009).


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Table 6 Internet Developments (1969 – 1994) Year 1969

Key Milestones ARPANET allowed Advanced Research Project Agency users to share both software and hardware across a network, lasting until 1991 (Singer, 1998, pp. 212-213).

1975

Public key encryption developed by Whitefield Diffie and Martin Hellman (p. 209).

1975

Homebrew Computer Society forms in the California Bay Area to study computers

1980

Xerox, with Intel and Digital, launches Ethernet as a networking standard

1991

Tim Berners-Lee at CERN in Geneva invented the concept of the World Wide Web, a dumb network with smart devices, in 1991.

1994

Netscape, first commercially available internet browser, launched in November.


Hobbyists influenced the nascent personal computer market after the Altair launched in 1974. The California Bay Area based Homebrew Computer Club formed in 1975 (Singer, 1998, p. 106) to bring like-minded individuals together around personal computers (Wozniak, one of the Apple founders and its first hardware designer, was an early member). This kind of social networking continued in Silicon Valley via many Special Interest Groups (SIG), prolific in the 1980s, 1990s, and today. The Silicon Valley Computer Society in the 1980s, based also around PCs, had SIGs focused on operating systems, languages, computers, technologies, and disciplines. Professional organizations, like Institute of Electrical and Electronic Engineers (IEEE) and Association for Computing Machinery (ACM), have SIGs of similar intent today even though both the Homebrew Club and Silicon Valley Computer Society do not exist today.


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The educator and career counseling communities possibly do not yet fully understand the impact of the Internet on children and teens. With the rise of social networking tools, such as FaceBook, Linked In, Twitter, and Second Life, teens today are experiencing changes that will undoubtedly influence their future careers and career selections. The Depth section explores recent research in these areas. Synthesize Society Change Models with Technology Epiphenomena This section includes a synthesis of connections between the societal change models and technology and social trends, highlighting specific epiphenomena, outlined in prior sections, as well as specific data points relevant to the application section. The collapse theorists studied have provided several insights: From Tainter’s broad perspective of civilization economic marginality to Dosh’s analysis of small land invasion communities and their growth or decline over time to Brunk’s pointed self-organized criticality point of view, the state of high tech talent pool will be described using those concepts. Linking Ideas from Change Theorists to High-Tech Talent Pool Dosh described the “stages of development and the security trap” (2009, Figure 1) where a Nascent Organization can branch to either a Mature or Defeated stage. If the branch was made to mature, then a future branch was made to either Moribund (an organization in collapse or decline) or Resilient stage. (p. 93). Many companies, high-tech in particular, have followed the same branches of organizational development that invasion communities did as documented by Dosh. In the Depth section, this researcher will evaluate high-tech within this life cycle and assess its state using Dosh’s stages. Another example involves FIRST. FIRST Robotics Competition (FRC) teams that have mixed motives may be more likely to be resilient than moribund as well. Studying the state


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change of teams using Dosh’s model may provide interesting insights for future research. If FRC teams focused on mentoring new teams and the more junior FIRST Tech Challenge (FTC) or FIRST Lego League (FLL) teams, individual FRC teams might avoid decline and grow to be resilient. Whereas FRC teams that remain focused on exclusively self-interest are more likely to become moribund or collapse after the seniors depart, according to the Dosh model. An example researched by Tainter (1988) and used by Brunk (2002) to demonstrate a “self-organizing criticality [SOC] situation” (p. 219) was the 12th century Chacoan society collapse. First developing safety nets for their society (grain stores, irrigation), the Chacoan society next allowed other groups without those safety nets to join them. When a severe drought occurred, and they had lost the flexibility to respond successfully, the system collapsed (pp. 219220). Perhaps the Tainter-Brunk model can be an analogy for the United States technical talent pool and its concomitant innovation growth. With the global safety nets for manufacturing and service now used by United States industry, that is, outsourcing manufacturing and service to lower cost regions in the world, if a shock of some type occurred, the Tainter-Brunk model would predict a potential system collapse. In this context, complexity must be measured by the closely related influences that individuals have on each other today versus in decades past. To use concepts from Brunk, “dampening” (p. 221) forces and shocks would need definition: one possible such force or shock is the quota for H1B visas Use of Brunk’s SOC model could be instructive when analyzing the high tech talent pool. Linking Ideas from Change Theorists to High-Tech Industry Development Describing three types of land invasion communities—Old Guard, Next Gen, and Innovators—Dosh (2004) outlined their characteristics: Old Guard were experienced, with strict preferences; the Next Gen, though inspired by the Old Guard, cultivated flexible approaches and


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ideas; and the Innovators moved beyond the Next Gen by developing a mission and purpose. “Innovators…[were] driven by a sense of mission and [made] a break from the unoriginal tactics” (Chapter 1, p. 7) of others. The Old Guard was more “pragmatic” and the Next Gen had a “sense of entitlement”, while the Innovators had a “sense of mission” (Table 1.1). Dosh’s (2004) three types described above have parallels in the high-tech computer community. Early software development was proprietary, developed by Old Guard type companies. From the computer’s birth years during World War II, exemplified by ENIAC that required rewiring for each program change, until the early 1960s, software developed for computers sold by one company did not work on computers sold by another. In particular, IBM dominated the mainframe computer industry through many of the computer industry’s first decades, holding a 70% market share, with revenues of $1.2 billion in 1963, growing to $7.5 billion in 1970; the nearest competitor was Sperry-Rand with $145 million (Ceruzzi, 1998, p. 143). Almost all of Snow White (IBM) and the Seven Dwarfs (NCR, Control Data, Honeywell, Philco, Burroughs, RCA and General Electric) designed computers using IBM’s model of “large centralized mainframe installations, running batches of programs submitted as decks of punched cards” (p. 143). Companies entered and exited the computer industry, notably RCA and General Electric leaving the BUNCH (Burroughs, UNIVAC, NCR, Control Data, and Honeywell) through the 1970s and into the 1980s, until the personal computer revolution began. At the computer’s most basic input and output level, IBM’s first mainframe computers made use of Extended Binary Coded Decimal Interchange Code (EBCDIC); other computer manufacturers (e.g., PDP-8 from DEC) used American Standard Code for Information Interchange, or ASCII, instead (Ceruzzi, 1998, p.152 & p.133). Unfortunately, these two character definitions did not


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merge into one for decades. Recapitulating, the Old Guard companies were pragmatic and rigid, developing what worked for them individually, not for the industry or consumer as a whole. Two activities demonstrate a growth from the Old Guard approach to a Next Gen approach: standards and specific business decisions. As software engineers began to develop standards for languages, input and output devices, even for the types of integrated circuits from which to build computers, the resulting operating systems and applications became portable across hardware systems, losing their dependence on a specific computer company’s hardware. In addition, in 1969, IBM decoupled software pricing from hardware, recognizing “that the computer industry has irrevocably changed, that software and services were becoming a separate industry” (Ceruzzi, 1998, p. 169). [Arguably, court decisions influenced IBM’s decision more so than self-interest]. IBM’s business decision was the catalyst for the formation of many new companies. These new software—Oracle, Microsoft, Borland, SAP, and more—and service— Automatic Data Processing or ADP and Electronic Data Systems, or EDS, founded by Ross Perot in 1962 (pp. 168-169)— companies grew and flourished with this new independence of software from hardware. Nevertheless, these Next Gen software providers, in some cases, have a tight hold on consumers and businesses that use their software; an archetype example could be Microsoft Windows and Microsoft Office. More recently, with the advent of Open Source software projects, led by Stallman in the 1970s with GNU (a recursive acronym for Gnu, Not UNIX), flowering into Linux, Open Office, and VMware, software Innovators shifted software to a new level of independence, away from any one place. While companies can and do make a profit using open source operating systems and software (e.g. Linux) in their kernels (unlike proprietary UNIX operating systems where a licensing fee are assessed), a “sense of mission” (Dosh, 2004, Table 1.1) is mandated for open


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source integrators. If a company makes improvements in Linux, sharing with other users is required: for free. Sometimes businesses can obtain a commercial use fee-version to maintain a more privileged control for open source code. Essentially with this innovative open source paradigm, software has become more open and non-proprietary, and multiple companies can and do develop unique software using it, an example of how Dosh’s expanded mission idea helped software to continue growing. Breadth Summary For this KAM, two axes of societal development were researched, analyzed, and synthesized, with an eye to identifying reasons for the stagnation in the U.S. high tech talent pool. STEM graduates, in particular engineering and computer science graduates feed the U.S. high tech talent pool, coming from the U.S. and around the world. These two axes were collapse theories and technology epiphenomena. The first axis investigated was collapse theory. For a summary, view

Running head: KNOWLEDGE AREA MODULE 1 Table 7 showing Tainter’s economic model, Brunk’s mathematical self-organizing criticality, Diamond’s geopolitical view, Dosh’s political analysis, and Motyl’s visual model. The models each provided thought provoking insights leading to parallels in the high tech industry segment and its associated talent pool

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Table 7 Summary of Collapse Theorists Considered Author

Summary Description

Model Type

Brunk

Self-organizing Criticality in Self-Organizing

Mathematical model. Shocks

(2002)

Systems.

and dampening forces analyzed.

Diamond Environmental factors and catastrophes, on islands Geopolitical analysis approach. (2005)

or along latitudinal lines.

Dosh

Lifecycles: Nascent-Mature-Moribund; Nascent-

Political model using a society

(2009)

Mature-Resilient; and Nascent-Defeated.

or organization’s mission or

Community types: Old Guard, Next Gen, and

passion at different points in

Innovators.

time.

Motyl

Simple analogy with core or hub being the elite

Hub and spoke analogy.

(2001)

and spokes connecting to other peripheral entities.

Tainter

The most well documented model, analyzing

Economic analysis, a theory of

(1988)

many prior instances of society and national

marginality.

collapse through economics.

The second axis considered was technology epiphenomena that had the potential to influence STEM career decisions. While it is likely that other events, political or economic in nature, also affected the rises and declines of STEM graduate numbers, certain technologyoriented events were influential. Development of computers and associated industries, the race to


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the moon and space exploration, the birth of the PC and the Internet, certain disasters (e.g., Challenger crash), the environment movement, and DNA definition are probably epiphenomena that did affect many STEM career decisions. In the Depth section, those two axes will be explored using recent research and results concerning the high tech talent pool, gender and high tech, and globalization. Finally, in the Application section, using National Science Foundation data on STEM graduates, filtered by degree level and native versus non-native graduates, these seemingly disparate axes of collapse theory and technology epiphenomena will be woven into a single fabric. Using threads of globalization across the warp of collapse theories and weft of epiphenomena, the reader will gain a vision of the health of the U.S. high tech talent pool.


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DEPTH SBSF 8120: CURRENT RESEARCH IN SOCIETAL DEVELOPMENT Annotated Bibliography Baker, J., & Marks, A. (2005, January 1). Women in physics in the U.K.: Update 2002-2005. AIP Conference Proceedings, 173-174. Available from American Institute of Physics, 07354-0278-7/05. Summary of Findings This brief article summarized programs in the UK aimed at increasing the amount of women in physics at all levels: professors, graduate students; in industry, and students. Baker and Marks spoke of a turnaround point in 2002 after the seminal “Roberts Report, SET for Success” (p. 173) projected a shortage of science, engineering and technology graduates for the UK in future years. Several professional organization, educational institutions, and government efforts enacted efforts thereafter. The Institute of Physics appeared to be a strong proponent of programs to bring more women in to physics. Specific programs discussed by the authors included those for encouraging girls to consider physics careers, re-entry fellowships, mentoring programs, career-break grants, and investigating university environments for supportiveness and bias, or lack thereof (pp. 173174). A key statistic provided was “UK physics has an ‘old’ age profile. In 2002–2003, 40% of academics were over 50 and only 11% were younger than 34” (p. 174). Baker and Marks conclude on a positive note stating that in only two years, from 2002 to 2004, the number of women physics professors had risen from 2% to 4% and was “rising steadily: (p. 174). In addition, girls continued to study physics, while, unfortunately, boys interest had continued to decline. This UK data is consistent with the U.S. situation as reported by NSF (2008): the quantity of physics bachelor degrees has stayed roughly steady over forty years (1966 – 2006),


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while the share of women in that number during that same period had increased markedly to almost 50% as show in Figure 3 below. Critique of Methodology This is simply a survey article of various efforts aimed at increasing the number of women in physics. The authors performed no studies, presenting this paper at an American Institute of Physics conference and publishing in the conference proceedings. The authors, Baker and Marks, were from the University of Oxford and the Institute of Physics Women in Physics group, respectively. Usefulness to Depth and Future Research Certain interesting ideas and contacts will be retained for future use. In particular the point on retiring physics professors in that 41% over 50 is worthy of further data gathering in the Science, Engineering, Technology, and Mathematics areas in the U.S. Bachelor's Degrees: Physical Sciences 1966-2006 25

20

ty it n a u Q

PHYS-Men PHYS-Total TREND (PHYS-Women)

PHYS-Women TREND (PHYS-Men) TREND (PHYS-Total) R² = 0.6803

s ) 15 0 0 0 (

R² = 0.943

10

5 R² = 0.9534

1965

1975

1985

1995

2005

Figure 3. Bachelor’s Degrees for physical sciences, 1966 – 2006, from National Science Foundation (2008)


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Berry, K. D. (2008). Motivating and maintaining girls' interest in science through the use of an after school science club (Master's thesis). Available from Dissertations & Theses: Full Text database. (Publication No. AAT 1458263). Summary of Findings Berry, a fourth grade teacher in a Central Texas school, in this master’s thesis, explored if “an effective method to promote social acceptance of science for girls” (p. 13) was an all-girls after-school science club. Her study showed the effectiveness of this type of hands-on, field trip, after-school approach and demonstrated more girls had an interest in science classes and activities after the five-week club experience than prior to it. One outcome unexpected by Berry was the impact in the girl’s home lives. Parents reported an increase in science at home as well as an excitement that had not been present in their daughter before. Most laudable, Berry’s initial project was so well received by the school district that it sponsored two full-year single-sex (boys club; girls club) science clubs the following year; these were so successful and well received by parents, teachers, and students that more were planned for the 2008-2009 school year. Critique of Methodology This qualitative apparent case study, conducted in the spring of 2007 at a Central Texas public school with a 12:1 student-to-teacher ratio, involved 17 fourth-grade girls from two science classes (20 were invited). Berry used a Student Attitude Questionnaire developed by Ornstein in 2006 to assess interest in science prior to the program as well as afterwards; she reported the instrument’s reliability and validity was well established. “Response journals” (p. 25) were used as well; girls wrote responses to weekly discussion questions and were required to communicate at least three times a week with other girls in the journals providing “evidence of tracking emotional changes toward science [and were] reflective of the participants becoming a


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means of support and encouragement toward each other” (p. 25). The use of both a test instrument and journals supported a richly textured case study approach. The second part of Berry’s research involved working female scientists; unfortunately, of the numbers with whom she made contact, only four responded and participated. Thus, conclusions from this portion of her work could not be usable without further samples. Usefulness to Depth and Future Research Berry’s research questions and outline for evaluating success will be very useful in my dissertation work. The thesis provided new evaluation techniques ideas: response journal and Ornstein’s Student Attitude Questionnaire. Additionally, several studies she described on mother’s toy type purchases and science museum parent-child interactions provided insights worthy of future thought. Her thesis model has much to recommend it for use in my dissertation. Blum, L., & Frieze, C. (2005, March). The evolving culture of computing. Frontiers: A Journal of Women Studies, 26(1), 110-125. Available from http://www.nebraskapress.unl.edu/search/JournalSearch Summary of Findings Blum and Frieze, in a qualitative study funded by an Alfred P. Sloan grant, analyzed Carnegie Mellon’s approach to Computer Science (CS) given an increasingly gender-balanced student body. This study did a partial follow-up to the Margolis and Fisher longitudinal study (1995-1999) mentioned in KAM 1 research (Craig, 2009), as described by Singh. Blum and Frieze found certain findings to be similar to that earlier study; however, most interesting were the differences. For example, they found male and female CS students often shared interests more than they differed; many women were molding a new image: “both geeky and feminine” (p. 112). They categorized the changes as “stereotypes, programming versus applications, the expanding view of the field, and meeting the challenges of diversity” (p. 112).


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The authors recommended specific tactics to increase diversity in a CS program as shown below, some in contrast to the findings of Margolis and Fisher provided below: 1. 2. 3. 4.

Outreach in the form of summer workshops for high-school computer-science teachers; Changes in the admissions criteria to more closely reflect SCS goals and more rational prerequisites for success in the major Providing effective access to the computer science curriculum in the form of various entry routes into the entry-level programming sequence Creating a professional organization and community for students to provide collegiality, role models, mentors, and leadership opportunities. (pp. 117-118).

In particular, the authors asserted that making curriculum changes to supposedly help genderneutrality might, in fact, reinforce gender stereotypes. They go on to posit any observed gender differences were more a result of admission criteria: “admissions criteria were set to select people who would become hot-shot programmers for the high-tech industry” (p. 120) and thus men and women without high-school programming classes were less likely to be selected. Critique of Methodology The study cohort consisted of students who began the CS program in 1998 (just as Margolis and Fisher completed their study), and who saw a marked increase in women in that degree program by the time they graduated. The study authors did not share the data statistics per se, only the size of the cohort in a note (“note 6”), thirty-three students, essentially split evenly men and women out of 153 students in the 2002 senior class. The primarily interview based instrument was a questionnaire developed from the earlier Margolis-Fisher study. The authors asserted “although this research represents a qualitative, interview-based case study, we note that with open-ended questions and a small number of participants, the presence of as few as two or three similar responses takes on magnified significance” (p. 122). This type of case study is an accepted qualitative process (Yin, 2009).


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Usefulness to Depth and Future Research While Blum and Frieze suggested solid intervention and support approach for university CS programs, they did not explore any societal context or influences. Their data could be evaluated orthogonally and other conclusions or suggested causals might be possible. Dunleavy, M., & Heinecke, W. (2007, September). The impact of 1:1 laptop use on middle school math and science standardized test scores. Computers in the Schools, 24(3/4), 722. doi:10.1300/J025v24n03-02 Summary of Findings This quantitative study contributed to a growing body of research on the use of laptops in student classrooms and the impact of that use on student achievement scores. This particular program involved about 300 students over three grade levels. Laptop access was partially limited; students had 24-hours access during the school week, though use was not provided on the weekends. In addition, the laptops had wireless access throughout the school and included an in-depth set of online resources and application software. Dunleavy and Heinecke found that for students in laptop classes (versus the control group), boys demonstrated an increase in science achievement scores, more so than girls did; and no difference was seen for either boys or girls in math achievement scores. In addition, the authors observed that male students using laptops showed increased achievement in English and writing skills as well, when compared to female students. In the discussion, the authors questioned why improvement was seen in the science scores but not in the mathematics scores; however, they did not suggest an answer. Critique of Methodology Using longitudinal data from two years, authors did an analysis of covariance (ANCOVA) looking at scores from achievement tests, examining both pre- and posttest scores; the control group was students who did not use laptops. The mid-Atlantic 6-8 grade school was primarily African-American (81%), with smaller percentages in other groups: White (13%),


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Asian (2%), and Hispanic (3%) (p. 9); about 60% were on free or reduced lunch fee programs; roughly 60% in both groups was female. In prior years, the school had lower than average test scores and in fact “the [state had notified] the school that its accreditation was at risk” (p. 10). Pretest scores included State Standardized Test (SST) scores for both fifth grade math and science; posttest SST scores were from eighth grade. The authors noted two methodology limitations: no control for teacher variance across the different groups and small sample size (20) of male cohort for the laptop group. Usefulness to Depth and Future Research Interesting data and ideas for future testing with respect to laptop use is not directly applicable to my interest; nonetheless, the gender disparities observed are instructive and this student recorded this article for future use. Freeman, R. (2006a, January). Does globalization of the scientific/engineering workforce threaten U.S. economic leadership? NBER Innovation Policy & the Economy (MIT Press), 6(1), 123-157. Available from http://www.mitpressjournals.org/ Summary of Findings Freeman asserted four conclusions: (a) The rest of the world, in particular China, is producing more science and engineering (S&E) graduates than before “while U.S. production has stagnated” (p. 123); (b) while available positions in S&E are less attractive to young people than in years past, many immigrants still flock to them; (c) with the larger populations of India and China, they may graduate less S&E per capita, but the amount they are producing threatens the typical pattern of “advanced countries domina[ting] high tech” (p. 123); and (d) these changes will result in “long period of adjustment” (p. 123) for U.S. high tech workers. Freeman suggested certain policies and actions to help the United States to adapt to being one of many, instead of the premier technology source.


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The United States had built and held this premier position due in no small part to its position after WW II when compared to other nations it built a vibrant economy, postsecondary education system, while other countries were either rebuilding or under some non-supportive regime. However, the world is catching up and the United States is slowing down. In 1970, the United States had 30% of all college students worldwide. Thirty years later, the United States was down to 17%. (p. 126). By 2001, the European Union had produced 40% more S&E graduates than the United States. (Freeman, 2006a) In addition, Freeman analyzed the doctoral degree situation in the United States and other parts of the world. Obtaining a doctoral degree in professions outside of STEM does not have the same lifetime earning potential as a doctorate in medicine or law. In addition, doctorates are being earned at faster rate outside the United States and Ph.D.s in the United States earned by foreign born students leaped from 24 % in 1990 to over a third (37%) in 2004 (p. 128). Freeman asserts that foreign-born students overall see a degree in STEM as a ticket to a green-card. Native born have other higher paying options available to them, like finance, business, or medicine. (p. 138). Women and minorities showed a different, more positive, trend. Freeman (2006a) then asked the question, as this student has in prior work: “Why have women and minorities chosen to enter science and engineering whereas white men have shifted to other fields?” (p. 139). He suggested only two causes: (a) less discrimination and thus a more accepting environment; and (b) a lower opportunity cost loss, that is, other options available to women and minorities do not pay as well (pp.139-140). Arguably, other causes do exist, such as, the women and minorities may not have seen themselves being successful in those careers before, and many programs have now shown these options do exist for them.


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“Research and technology activity and production are moving where the people are…to China because China is graduating huge numbers of scientists and engineers” (Freeman, 2006a, p. 147). To maintain its edge, or slow the decline, the United States should increase the supply of S&E talent, whether native born or foreign born (pp. 148-149); otherwise, a collapse could occur rapidly. Critique of Methodology Freeman’s data gathering was well documented as to source and validity. He is a recognized researcher in this area, being a professor at both Harvard University and the London School of Economics. Nonetheless, this was not a qualitative research study, per se. Usefulness to Depth and Future Research This seminal article, used in KAM 1 (Craig, 2009) as a reference for the Application PowerPoint briefing, presented a balanced perspective on the impacts of outsourcing engineering positions, well researched, and cited, providing many sources and ideas for future use. Monitoring of Freeman’s work is an ongoing process. Freeman, R. (2006b, Spring). People flows in globalization. Journal of Economic Perspectives, 20(2), 145-170. Available from http://www.mitpressjournals.org/ Summary of Findings In this study, Freeman examined people flows between countries, delving into a hot topic in the media today: immigration. By analyzing immigration from an economic point of view, Freeman posited that immigration policies need to take into account gains made by immigrants as well as losses of the native population: “The key issue in getting citizens of advanced countries to look more favorably on immigration is to design policies that give a larger share of the benefits to receiving countries” (2006b, p. 166). Beginning with broad data on immigration levels in 2000, the United States is the number one receiving country with 35 million immigrants


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and the top sending countries are China, India, and the Philippines. He looked at flows of trade, people, and capital, sharing various data points, concluding that the “labor market is the least developed part of globalization” (p. 150). People immigrate for many reasons, only some of them economic. Freeman asked how immigration affected native born. Since immigrants tended to be younger in age, average age decreased somewhat (Freeman, 2006b, p. 155): not a large effect. Other effects were economic, like lower wages in the receiving country; nevertheless, not as significant as the average nativeborn worker might think. “For the United States, Freidberg and Hunt (1995) report that a 10 percent increase in the fraction of immigrants in the population reduces native wages by at most 1 percent” (p. 157). Freeman asserted, “Restrict immigration, and trade should increase. Restrict trade, and immigration should increase” (p. 160), the essence of NAFTA. Freeman concluded with questions similar to those raised in prior article: Will United States innovation lose its edge if insufficient highly skilled immigrants arrive in the United States? Will teens not study engineering because of a large influx of immigrants studying those same careers? Will industry establish offshore R&D centers because insufficient skilled workers are present in the United States at a viable price point? One solution proposed was a immigrant financial tax or levy to offset losses experienced by native-born as a result of immigrant flow. Critique of Methodology The author is a recognized economist at Harvard University, the London School of Economics, and he is Program Director for the National Bureau of Economic Research. He is the “Herbert Ascherman Chair in Economics [at] Harvard…[and] Senior Research Fellow, Centre for Economic Performance, London School of Economics” (p. 145). Credible, well researched; this article has an extensive reference list.


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Usefulness to Depth and Future Research Freeman’s style and approach have been of interest from first reading his work for the Application section of KAM 2 (Craig, 2009). He brings an objective bent to a difficult subject, not taking the most popular approach or the most critical, both useful traits to remember. Gereffi, G., Wadhwa, V., Rissing, B., & Ong, R. (2008, January). Getting the numbers right: International engineering education in the United States, China, and India. Journal of Engineering Education, 97(1), 13-25. Available from http://www.asee.org/ Summary of Findings Duke University continued, in this study (Gereffi, Wadhwa, Rissing, & Ong, 2008), their record of advocacy asserting the United States engineering and computer science pool, when compared to China and India, was not in as much trouble as most could state; in this article, the authors posited that graduate quality deserved more focus than graduate quantity “since quality factors have the biggest impact on innovation and entrepreneurship” (p. 13). United States, China, and India data was analyzed, making apples-to-apples comparisons of similar degree types and levels. While the authors use these graphs to prove their assertions, the graphs clearly showed a much steeper increase rate at all degree levels in India and China when compared to the United States (“Figure 1” and “Figure 2”). In addition, the data showed high percents of nonnative degree earners in the United States data, with roughly 40% of master degrees and 50-60% of doctoral degrees earned by non-native students (“Figure 4”). As the authors (Gereffi, Wadhwa, Rissing, & Ong, 2008), outlined, China’s policies have driven these rising numbers of graduates; however, the outcomes were different than one might expect. Outcomes were: (a) lower salaries for bachelor degree holders in China: companies can hire today, 2008, a master’s level engineer for the same salary as that of a late 1990s salary for a bachelor degree holder (p. 19); and (b) higher unemployment for graduates of mid-tier or lower universities. Somewhat similarly in India, though not necessarily as strongly national policy


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driven, unemployment of engineers has been an outcome of the rise in the number of private institutions offering degrees and the number of students overall in these programs. While the authors (Gereffi, Wadhwa, Rissing, & Ong, 2008), provided data on multinational corporations (MNC) establishing R&D centers in China and India, they depicted the MNC’s hiring of native engineers to be limited to students from a small list of top tier universities in those countries. The researchers did not expand on the growing numbers of MNCs expanding their R&D reach into those countries, and the impact that major force might be having on college student degree decisions or jobs available at the entry level in the United States. Beyond their emphasis on quality metrics versus quantity metric, the authors make several effective closing points. In particular, asking if “the incentives provided to undergraduate engineering students are sufficient to attract enough talented individuals from other more lucrative professions” (p. 23). Gereffi, Wadhwa, Rissing, and Ong continued to make strong statements on their quality not quantity motif. Critique of Methodology The four authors represented both engineering and sociology perspectives, apropos to this subject. The data mining they performed was extensive and well thought out, involving both government and private institution sources in India and China. In addition, they explored the situation with people from MNCs as well as with research counterparts in India and China. One concern is their passion and prolific writing may bring about a certain amount of bias in their conclusions. For example, in this quote, “Despite the wide circulation of these statistics for engineering graduates, multiple authors and articles have questioned their statistical validity (Bialik, October 2005; Gereffi, Wadhwa, and Rissing, 2005; Wadhwa, Gereffi, Rissing, and Ong, 2007; Wadhwa, 2006)” (p. 14), three of the four references contain work by the authors


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themselves, that is Gereffi, Wadhwa, Rissing, and Ong. Nevertheless, their points on quality being more important than quantity are worthy of consideration. Usefulness to Depth and Future Research Consideration for this point of view will be important in this author’s future research. Duke University appears to have continued this research focus over a period of time and thus may have data in the future worth using. Geyer, R. W. (2008). Attitudes, beliefs, and behaviors of academically talented and well-abled middle school children in their use of the Internet (Doctoral dissertation). Available from ProQuest Dissertations database. (UMI No. 3302214). Summary of Findings For his doctoral dissertation, Geyer (2008) assessed teen Internet savviness and demonstrated a relationship between the level of Internet skill and knowledge with these domains: “Creative expression…Internet self-efficacy…Internet fluency…social collaboration…computer mediated communication...[and] information gathering” (pp. 18-20). A Prensky study from 2001 (as cited by Geyer) defined a “digital native” as an Internet savvy teen and who posited that teens were increasingly disengaging from school as a place of learning, instead, obtaining their learning on the Internet (p. 23). Geyer related this learning type to Dewey’s constructivism and Vygostsky’s zones of proximal development (pp. 27-29). Geyer shared statistics on Internet access, though recent—2003 and 2005—all are somewhat dated given the explosion of Internet use. Nevertheless, one study in 2005 showed 68% of teens, aged 12-17, used the Internet for schoolwork; one Silicon Valley study in 2003 showed 89% had used it for schoolwork (2008, p. 7). Not surprisingly, Geyer stated Internet access was more limited in lower socioeconomic level homes and that African-American homes usage of Internet trailed the averages (p. 13). He concluded that children are ahead of teachers in their use of the Internet as a learning tool (pp. 14-15) and from a 2007 Pew study stated adult


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users were much less likely to have a practical understanding of the Internet and were primarily men (p. 39). In addition, teens were more likely to have a social network on the Internet than adults were (pp. 47-49). Within his specific doctoral study, older teens did score higher than younger teens, as Geyer expected (p. 103), though he observed no statistical difference across ages until age 13 (p. 126). Girls and boy scored consistently in internet savviness at age 12 and higher, with boys scoring higher at younger ages (p. 104). Critique of Methodology Study (Geyer, 2008) cohort included eight to fourteen-year-old gifted children. Geyer believed this type of gifted pool was representative of all teens sometime in the future, assuming that “evidence of Internet-savviness would more readily and distinctly emerge in the gifted and academically talented group” (p. 15). Nevertheless, Geyer advised caution about drawing any inferences for all teens. Significant effort to obtain parental approval and several follow-up approached helped Geyer obtain a solid quantity of data. Beginning with a small, IRB approved, pilot study to test the survey instrument, Geyer then went on to study 222 (142 females, 80 males) (p. 83) from a base of 677 students in a 2007 summer program. Several doctoral level education students first reviewed and tested the survey instrument providing internal validity. The instrument was an online survey, voluntary and anonymous, with specific choice questions and two open ended essay questions, those delving into student’s favorite Internet activities and what they thought about using the Internet more for studying and learning (p. 74). Experimental data was evaluated using ANOVA and MANOVA processes, with regression analyses; missing data was analyzed as well. Throughout the dissertation, the researcher shared the instrument question, data pertinent to it, the statistical evaluation performed, and what conclusions might be drawn from the data (and what not).


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Usefulness to Depth and Future Research Research done by Geyer on the Internet was similar to what was accomplished in the Breadth section with several similar as well as different references. In addition, the survey instrument development and validation was instructive and is likely to be useful in the future. Grimes, D., & Warschauer, M. (2008, January 1). Learning with laptops: A multi-method case study. Journal of Educational Computing Research, 38(3), 305-332. (ERIC Document Reproduction Service No. EJ796562). Summary of Findings Working closely with “a semi-urban school district in California,” (Grimes & Warschauer, 2008, p. 309) assessment was performed at three school sites within the district providing “diverse student populations” (p. 308) with a variance in socioeconomic level, ethnicity, academic ability. In this mixed method study, the authors researched three questions: did the use of laptops change how teachers taught or how students learned; what did both student and teacher think about the use of laptops in school; and did student test scores change measurably. (p. 309). The three schools were characterized as follows: (a) Nancy: 7-8 grade, primarily Hispanic (66%), lower SES, 554 students; (b) Flower: 3-7 grades, higher SES, primarily Asian-American or Asian (65%), 395 students, school has a science and technology focus; and (c) Henry: two Gifted and Talented Education (GATE) classes, 3/4 and 5/6 grade levels, diverse class (53% white, diverse SES), 62 students. Both Henry (GATE teachers had prior interest in technology instruction) and Flower (science-technology focused school) classes had teachers that were technology-literate and focused; whereas at Nancy, teachers participated in the program or had to transfer to other schools. “Laptop use [at Henry and Flower] was constant and extensive” ((Grimes & Warschauer, 2008, p. 312); at Nancy, usage ramped up slower for many reasons (size of program


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was larger and had logistical challenges, more English language learners—“25.3% of student population” (p. 312), and students had less home computer or Internet access). (p. 312). Grimes and Warschauer (2008) used both quantitative and qualitative techniques. Students took state tests, for the quantitative assessment, three times across two years providing a longitudinal view; both laptop and non-laptop students were analyzed. The qualitative data included a survey, “data from teacher interviews, student focus groups, classroom observations, and written documents” (p. 309) with no qualitative data from non-laptop classrooms. Study results (Grimes & Warschauer, 2008) showed laptops used more frequently in science and liberal arts classes when compared to use in mathematics classes (p. 312); analyzing Table 1 data (p. 313), 31% of Flower students used it for math three or more hours versus 34% for science, very close, but much less than liberal arts at 41% or 52% for language arts. The researchers observed positive changes in four areas: “writing, information literacy, multimedia skills, and autonomy” (p. 314). Teachers (88%) generally favored the program. Students agreed: 74% stated with laptops schoolwork was more interesting, they were better organized, and revisions were easier. Test results did not show any dramatic improvement per se; only at Flower did math scores improve more for laptop students versus non-laptop students. One point made by the authors: results improved more at grade levels requiring higher-order thinking. (p. 328). Overall, Grimes and Warschauer found that a one-on-one laptop program: (a) influenced the way teachers taught and how students learned; (b) saw a positive reaction from both students and teachers; and (c) observed declines in test scores in first year followed by a rebound to same or higher levels after the tool was inculcated into the learning process.


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Critique of Methodology Through the study, quality practices were evident. Funding was independent of the school district technology provider; the authors (Grimes & Warschauer, 2008) made this point to demonstrate steps taken to avoid bias. Though teachers did support program continuation, the authors mentioned that teachers could be positively biased to show support for an administration program (p. 329). Qualitative data gathered included: Online survey performed six months after study began; classroom observations (157 hours); interviews of students (10), teachers (28), and school administration; documentation gathered: e.g. specific laptop centric learning plans, standardized tests, student work (selected small group), and district reports on program. Usefulness to Depth and Future Research Certain points about how students were more autonomous with laptops and grew higherorder thinking skills suggest connections to hands-on activities controlled by students and learning science and other technology skills. The grant funder: Ada Byron Research Center for Diversity in Computing & Information Technology (ABRC), was filed for future reference. The researchers used HyperResearch program to analyze qualitative data (p. 311). Henrico County Schools in Virginia may have future research published on their county-wide laptop program. Kerr, W.R. (2007). The ethnic composition of U.S. inventors [Working paper]. Retrieved from Harvard Business Review Working Papers: http://hbswk.hbs.edu/item/5761.html Summary of Findings Kerr (2007) used United States Patent and Trademark Office (USPTO) data from 1975 – 2007, to analyze ethnicity derived via an ethnic name mapping process. This paper was a workin-process report, as he will continue to add data as he obtains it. He described the strengths and weaknesses of this name mapping approach and suggested how researchers could use the data.


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Indian inventors have declined as a percentage of U.S. inventors total since 2000, after about a ten-year rise, for both electrical engineering and computer science patents (Kerr, 2007, Figure 4 & 6). European ethnic U.S. inventors have declined from 175 to 2005 as measured by the percentage of U.S. domestic patents from ~8.5% to ~6.5% (Figure 1) while Chinese and Indian share in that same period rose from 2% to 8% and 4% respectively (though Indian had been up to almost 5% in 2001). In addition, in the early decades, Kerr observed that ethnic inventors were more commonly from government, university research, or public institutions; beginning in the 1990s, the numbers in private companies began to rise (p. 7). Critique of Methodology Kerr (2007) categorized using two approaches: (a) using the Melissa Data Corporation database (pp. 1-2) of ethnic names, representing “Chinese, English, European, Hispanic/Filipino, Indian/Hindi, Japanese, Korean, Russian, and Vietnamese” (p. 2) names; the database is most strong in the Asian ethnicities and less so for continental Europe (p. 2); and (b) “a uniform name database using only the 3000 and 200 most common surnames and first names, respectively for each ethnicity” (p. 2). Neither approach supported separating by national interest (e.g. being from Taiwan versus the People’s Republic of China) nor did either approach manage origins of ethnic scientists-engineers born in the United States. His approach was methodical and objective, worthy of note. Usefulness to Depth and Future Research Monitoring this researcher’s reports could be useful, depending on ultimate dissertation topic, for future research. For the depth essay, two figures shown here might be useful in PowerPoint application; Figure 4 and Figure 5 were developed using data from Kerr’s article.


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Total Patenting Share by MSA New York, NY Chicago, IL

MSAs declining in share

Philadelphia, PA

San Francisco, CA MSAs rising in share

Los Angeles, CA Dallas-Fort Worth, TX

Total Patenting Share 1995 - 2004 Total Patenting Share 1985 - 1994 Total Patenting Share 1975 -1984

San Diego, CA Seattle, WA Austin, TX

MSA with steady share

Boston, MA 0%

5%

10%

15%

Percent share of total patents across all MSAs

Ethnic Patenting Share by MSA New York, NY Chicago, IL


Philadelphia, PA San Francisco, CA

MSAs rising in share


Ethnic Patenting Share 1995 - 2004 Ethnic Patenting Share 1985 - 1994 Ethnic Patenting Share 1975 -1984


MSAs with steady share

Boston, MA 0%

6% 12% 18% Percent share of total patents across all MSAs

24%

Chinese Patenting Share by MSA New York, NY MSAs declining in share

Chicago, IL Philadelphia, PA San Francisco, CA Los Angeles, CA


Dallas-Fort Worth, TX Chinese Patenting Share 1995 - 2004 Chinese Patenting Share 1985 - 1994 Chinese Patenting Share 1975 -1984



Boston, MA 0%

6%

12% 18% 24% 30% Percent share of total patents across all MSAs

36%

Figure 4. Metropolitan Statistical Area (MSA) patent share, as percent of Total, Ethnic, and Chinese MSAs (data from Kerr, 2007, Table 3); matched San Francisco peak for similarity on percent scale.


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Total Patenting Share by MSA New York, NY


Chicago, IL Philadelphia, PA

San Francisco, CA MSAs rising in share


Total Patenting Share 1995 - 2004 Total Patenting Share 1985 - 1994

San Diego, CA Seattle, WA

Total Patenting Share 1975 -1984

Austin, TX MSA with steady share

Boston, MA 0%

5%

10%

15%

20%

25%

30%

Percent share of total patents across all MSAs

Ethnic Patenting Share by MSA New York, NY


Chicago, IL Philadelphia, PA San Francisco, CA



Ethnic Patenting Share 1995 - 2004 Ethnic Patenting Share 1985 - 1994 Ethnic Patenting Share 1975 -1984



Boston, MA 0%

5%


30%

Chinese Patenting Share by MSA New York, NY


Chicago, IL Philadelphia, PA San Francisco, CA Los Angeles, CA


Dallas-Fort Worth, TX Chinese Patenting Share 1995 - 2004 Chinese Patenting Share 1985 - 1994 Chinese Patenting Share 1975 -1984



Boston, MA 0%

5%


30%

Figure 5. Metropolitan Statistical Area (MSA) patent share, as percent of Total, Ethnic, and Chinese MSAs (data from Kerr, 2007, Table 3); same percentage scale used.


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Lucena, J. (2006, June). Globalization and organizational change: engineers’ experiences and their implications for engineering education. European Journal of Engineering Education, 31(3), 321-338. doi:10.1080/03043790600644040 Summary of Findings Lucena (2006) described challenges for engineering education: First, traditional engineering education focused on problem solving and did not grow flexible engineers; and next, how engineering educators have not been preparing engineers for organizational changes in their careers. Last, decades after teams became ubiquitous in manufacturing plants, graduating engineers, as described by Lucena, were not prepared to work in teams (p. 323). With the increasing globalization, mergers and acquisition occurred at a faster rate. From 1993 – 2000, Alkhafaji (2001) stated (as cited by Lucena, 2006, p. 325), “the merger [was] merely done for sharing the research and development activity, sharing technology, expansion, and for building competitive advantage. Most…were completed to create sustainable competitive advantage in a global market.” Thus, the supposition that engineers are likely to experience some organizational change in their career was Lucena’s raison d’être for this qualitative research. Lucena’s hypothesis (2006) developed from the qualitative study was: any engineer whose education and identity were “strongly shaped by engineering problem solving (EPS)” (p. 334) were likely to have difficulty dealing in integrated product teams (IPTs) or cross-functional teams that those engineers who had less EPS in their curriculum. He recommended a quantitative study to prove his hypothesis; however, went on to propose modifying existing engineering curriculums by incorporating team problem solving processes into each year, beginning with the freshman survey course, followed by internships and courses in years two and three, finally using the concept of IPTs in the senior capstone course.


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Critique of Methodology Lucena (2006) provided a synopsis of four interviews of working engineers out of a 130interview base. Three of the four did not have engineering degrees, having worked their way into those positions; only one of the four was a degreed engineer. He provided no other data to support his proposals for curriculum changes in engineering and since three of the four examples did not even finish any engineering studies, how curriculum changes could have affected them was not clear. Though the 130-interview database may have been of high quality and he used NVivo software to do the qualitative analysis of the interviews, the four selected did not demonstrate his case sufficiently. While engineers could benefit from learning techniques for working within a team, this is not a new thought, as Lucena seemed to state. A quick search found several peer reviewed articles suggesting team problem solving in engineering classes, prior to Lucena’s article; two are mentioned here. As early as 1994, Levasseur recommended consensus-making skills for operations research students. In 2000, Lovgren and Racer developed a Civil Engineering course project including grading depending on team efforts as well as individual work; they shared qualitative data on the outcomes from the course team based curriculum. Usefulness to Depth and Future Research Little of relevance was noted for future use by this reader. Miskec, J. M. (2005). User friendly: Generation Y, teens, and technology (Doctoral dissertation). Available from Dissertations & Theses: Full Text database. (Publication No. AAT 3196639). Summary of Findings Miskec’s dissertation (2005) analyzed Gen Y (born after 1978 and before 1997) teens, from the perspective of young adult (YA) literature, suggesting thought-provoking pathways for the dealing with that generation. She described two narratives: traditional where a teen “is [in] a


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state of becoming, always tenuous as it is always in transition from and to something else” (p. 35), still remaining a “narrative of fear and immorality” (p. 54); and, alternatively a commercial narrative seeking to capitalize on Gen Y’s knowledge and use of technology. The traditional narrative saw a Gen Y teen or adult as “having no fixed center…incapable of being…moral” (Miskec, 2005, p. 39). She described a theme of fear running through these narratives. The young adult fiction written for Gen Y, written by adults, in narrative form using a teenaged voice, pushed an adult “top-down power relationship” (p. 46) agenda. The commercial oriented narrative embraced the frenetic nature of Gen Y teens. Both narratives were about control. The second, commerce based narrative, first sought to understand Gen Y teens, asserting that they were different than generations before and thus the sell process must be different (pp. 57-58); it was important to “embrac[e their] perceived belief in their own multiplicity” (p. 60). Turning to young adult fiction written by young adults, or Gen Yers, she found many that embraced this idea of multiplicity of selves as an empowering approach for a Gen Y teen. (p. 89). By writing about it, they gained control of “the spectacle and how media contribute to that” (p. 101). She posited that technology itself, helped the Gen Y teen become a writer, with the plethora of media available to use, concluding with a prescription for connecting to Gen Y teens: through their literature, helping them “think critically” (p. 141) by getting involved with the individuals and not only viewing them in the aggregate (p. 141). Critique of Methodology Miskec read numerous examples of young adult literature and effectively analyzed them. She critically evaluated their strengths, weaknesses, and relevance to Gen Y teens. No quantitative analysis was present, no surveys of teens or writers, only her analysis and comparisons to sociologists and psychologists theories on adolescence.


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Usefulness to Depth and Future Research The qualitative based dissertation provided an outline for Gen Y teens and young adults how to connect with people from that generation, providing ideas for effective communication. Mumford, D. (2006). Mathematics belongs in a liberal education. Arts and Humanities in Higher Education 5(21), 21-32. doi: 10.1177/1474022206059995 Summary of Findings This quote sums up this lovely article (2006): “[Mumford’s] belief is that if math is taught more loosely, in everyday language, with examples, history and numerics, it will be quite accessible and can resume its rightful place in the education of the next generation” (p. 32). Mumford argued that mathematics has become the purview of a narrow group of people, scientists, engineers, and mathematicians, versus the expansive domain it was decades, possibly a century ago, where any learned person, regardless of discipline understood mathematics. He illustrated his assessment of today’s situation from two perspectives. First, with data showing that people in the United States do not know fundamental mathematics and its applications anywhere near the level that people outside the United States do. Secondly, he provided specific cogent examples of mathematics usage in people’s everyday lives that all, per Mumford, should be familiar with and understand their application. Examples (Mumford, 2006) ranged from Newton “who taught the world how to make precise descriptions of a dynamic universe” (p. 25) to Oresme’s development in the 14th century of graphing equations to probability to double entry bookkeeping. Mumford lucidly explained their relevance and ease of understanding, as well as the importance of them to the layperson. He ended with a proposal to require mathematics be taught “as an integral part” (p. 29) of more classes, notably science, technology, and history classes.


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Critique of Methodology This article by a Brown University applied mathematics professor (with many decades before this at Harvard) was primarily an opinion essay with telling data and examples written for the Arts and Humanities in Higher Education journal. Usefulness to Depth and Future Research Beyond using it in a History of Mathematics course, Mumford’s points about making mathematics relevant to more than an elite few are important to remember. Rion, C. (2007). Major changes: Student shifts among liberal arts, S.T.E.M. and occupational majors, (Doctoral dissertation). Available from Dissertations & Theses: Full Text database. (Publication No. AAT 3270276). Summary of Findings Rion’s (2007) study researched student degree changes versus an intent identified in high school through the first declaration of degree in college until a degree was earned, providing insights at a national level beyond any one institution. She examined Liberal Arts, Occupational, and STEM degrees. She used the National Educational Longitudinal Study (NELS) database of students that were in eighth grade in 1988 where they were evaluated every two years thereafter (1990 – 1996) and then in 2000, nominally two to four years after college (p. 9). Initially NELS contained a cohort of greater than 24,000 students; by 2000, the cohort had dropped to some 12,000 cases. From the NELS database, to limit the variables, she analyzed students who had stayed in one institution and earned a bachelor degree, leaving a sample size of 2,369. She categorized three kinds of change: Intended to First, First to Degree, and Intended to Degree. Intended was what a student declared as a plan in high school; First was the first declared major in college; and Degree was the final outcome. The independent variables she chose were gender, race or ethnicity, and institutional characteristics (p. 66). Ultimately, she included SES as well.


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In her literature research, Rion (2007) found that students who made degree changes typically had a lower GPA than those who did not change (p. 46); nevertheless, likelihood of graduating rose when a student made a change. Overall, 36% of students shifted from one category to the other between the beginning and ending data points (p. 73). Rion found that those students who shifted degree category over time in general had lower academic performance and “did not have a firm set of attitudes or preferences toward their major decisions” (p. 120). Looking at STEM data, Table 9, student postsecondary performance (Rion, 2007, p. 71), showed 27% of students in high school intended to obtain a STEM degree, 32% of college students declared it as their first major, and 29% graduated with a STEM degree. Rion stated that “STEM persisters differ from STEM leavers in their math and science coursework and proportion of STEM Degrees awarded at their institution” (p. 114). Graduating in STEM correlated with higher academic performance throughout: high school GPAs, SAT quartile, and college grades (p. 135). Notably, STEM lost the most at each shift point, percentage wise (p. 140). Both STEM and OCC category degrees have the tightest pattern of coursework, making shifting into them in the later college years more difficult. STEM students cared about an institution’s academic pedigree and valued having specific courses available and that the degree led to a specific job in which they were interested (p. 145) Another set of nuances emerged when the STEM data from Category shifting patterns (Rion, 2007, p. 74) and Category shifting pattern of initially Unknown students (p. 76) was analyzed (see Figure 6 and Figure 7). This emphasized Rion’s point about high school students who are uncertain of their degree when asked in high school; a large proportion of those students either Declare for STEM at the first opportunity and graduate in STEM. The reasons for this are worthy of further exploration.


Figure 6. Category shifting patterns data, focused on STEM changes (data adapted from Rion, 2007, Table 10, p. 74)

Figure 7. Category shifting patterns data, including Unknown at Intended data, focused on STEM changes (data adapted from Rion, 2007, Tables 10 and 11, pp. 74 & 76)

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Rion found gender variations in some areas. Women with more math and science courses and a higher SAT score in math were more likely to complete a STEM degree. Within the changers group, “high academic preparation is an important component of women's persistence in STEM fields…African American women seem to leave STEM despite having similar academic preparation to those who persist” (pp. 124-125). Critique of Methodology This doctoral thesis (Rion, 2007) completed at the University at Albany, State University of New York included a broad spectrum of statistical analysis, analyzing independent and dependent variables, using Chi squared and ANOVA, along with various other techniques to demonstrate validity. A limitation highlighted by Rion was that the data selected did not take into account students who changed institution and subsequently graduated. Usefulness to Depth and Future Research Rion (2007) reviewed different career development theorists. Her comments on Super’s career development theory were similar to those made in KAM 1 (Craig, 2009), asserting that Super saw “career decisions as intimately tied to an individual’s self-concept” (p. 22). Holland’s approach linked career decisions to personality types and suggested that making degree shifts in college were a result of seeking a higher similarity (p. 23). Her comments on Hu’s research described a multi-variable concept, suggesting that economic and labor market factors were involved in a student’s career decision (pp. 28-29). These career theorist inputs offered interesting ties to my prior research. Rion’s work will be useful in my future research.


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Turchin, P., Adams, J., & Hall, T. (2006, Winter). East—West orientation of historical empires and modern states. Journal of World-Systems Research, 12(2), 218-229. Available from http://www.jwsr.org/ Summary of Findings Turchin, Adams, and Hall (2006) analyzed 62 historical empires of a certain size, greater than or equal to “1 Mm2 = 1,000,000 km2”, (p. 221) attempting to validate Diamond’s theory that empires and civilizations grow along latitudinal versus longitudinal lines. Of those 62, almost 80% showed a larger latitudinal than longitudinal dimension (p. 224). Only three showed strong vertical lines: New Kingdom in Egypt, the Incas, and Khmer empire; those three all have a significant longitudinal environmental factor and “these [were] the proverbial exceptions that prove the rule” (p. 224): a large river, a mountain range, and a rainforest expanse. Thus, their analysis showed “The general rule…[is] expansion is easiest and most lasting when occurring within the same ecological zone” (p. 225) Critique of Methodology Authors (Turchin, Adams, & Hall, 2006) used a mathematical analysis of latitude versus longitude dimensions to study empire occurrence. Using a “measure of the tendency to expand in the latitudinal direction is the log-transformed ratio of the east-west distance to north-south distance” (p. 223) a frequency diagram was developed for the 62 subject nation empires studied. Usefulness to Depth and Future Research This article (Turchin, Adams, & Hall, 2006) provided quantitative data to help prove Diamond’s theory. These two authors appear to be exploring connections to Diamond’s theory that are more current and thus their research may be worth monitoring.


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Vogt, C. (2008). The continuing technological revolution: A comparison of three regions' strategies for creating women-inclusive workplaces. In H. M. G. Watt & J. C. Eccles (Eds.), Gender and occupational outcomes: Longitudinal assessments of individual, social, and cultural influences (pp. 323-351). doi:10.1037/11706-012 Summary of Findings Vogt (2008) analyzed “women’s employment and educational statistics” (p. 323) from Japan, fifteen countries in the European Union, and the United States to develop and “equality profile” (p. 323). She considered this data in light of globalization trends. From this analysis, she concludes that gender discriminatory patterns remain. “Women's biological capacity to produce offspring often creates career incompatibility for women scientists and engineers” (p. 337). Considering the Convention for the Elimination of All Forms of Discrimination Against Women (CEDAW), a United Nations treaty, Japan and most nations within the EU have endorsed this treaty and have worked to implement it (Vogt, 2008). Gender mainstreaming is one approach that pushes CEDAW more actively. Reviewing status of employment, the number of women is rising in the EU 15 and Japan as both implement “gender mainstreaming” (p. 344) approaches while the United States is only slight ahead. She made specific proposals to counter these trends. For example in the United States, she recommended implementing a paid family leave policy; of the countries Vogt studied, the United States was the only one with no paid leave, by law. By implementing a gender-neutral leave law, she posited that more men might take advantage of this leave keeping it from appearing to be only for women, she suggested. Vogt’s (2008) analysis showed that while women work to obtain higher degrees, this may not pay monetarily in the end, and in point of fact, the higher degreed women, on average, had higher level of pay inequity. Throughout the world, “the higher the post, the fewer the women” (p. 345). She suggests that nations may be focusing on women to solve a pending labor shortage versus having a “genuine concern with gender equity” (p. 345); however, she does not


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adequately demonstrate this conclusion. Her final conclusion as noted above showed women continuing to pay in their career growth being their child’s primary parent (pp. 345-346). Critique of Methodology Vogt (2008) used worldwide credible data sources; analysis was quantitative. She developed longitudinal data for career lifetime salaries, normalizing it for women’s years in the workforce and other factors. She demonstrated that female wages continue to be below par of men, ranging from women’s lifetime salary being 60% of men’s for both Japan and the UK to a high of 79% in Sweden. The United States was in the middle at 70%. (p. 340, Table 12.4). Usefulness to Depth and Future Research The article’s reference list is quite rich with potential for future use in upcoming KAMs and dissertation. Vogt used several chapters from Crossing Boundaries: Comparing the History of Women Engineers (1870s-1990s), edited by Oldenziel, for several statistics and ideas, a reference for the Application section of this KAM. Wadhwa, V., Gereffi, G., Rissing, B., & Ong, R. (2007, Spring). Where the engineers are. Issues in Science & Technology, 23(3), 73-84. Available from http://www.issues.org Summary of Findings In this earlier article (see Gereffi, Wadhwa, Rissing, & Ong, 2008, above for follow-on article written for another journal nine months later), the authors shared other perspectives on the much acclaimed shortage of engineers and IT professionals in the United States. For example, China graduated 600,000 engineers annually and the United States maybe only 70,000; however, for over half of the Chinese number, the education consisted of only two to three years of schooling making those engineering graduates equivalent to an associate degree in the United States (p. 74). Regardless of this disparity, what was valid was that the number of engineers and technicians China graduating had been rising dramatically since 1999 when China implemented


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certain policies (see Figure 8). Driving down engineering graduate salaries and creating more average engineers, that is, less elite engineers, were the policy goals; result was a “140% increase over the past five years [2000-2005]” (p. 74) while simultaneously cutting the number of schools by about a quarter, resulting in higher class sizes (pp. 74-75). Meanwhile, again, the graduates from the top schools can find positions and the rest had great difficulty. Thus, the authors predicted a decline in numbers in upcoming years (p. 75). As reported in this article, in India, hiring managers were positive about graduates from almost any University in India, in particular, the Indian Institutes of Technology. Whereas in China, hiring managers from multinational corporations hired primarily from the top 10-15 schools in China (pp. 75 & 77).

Figure 8. Bachelor’s Degrees, Four-Year Programs, Engineering, Computer Science, and Information Technology from China, India, and the United States. Graph created from data found in Wadhwa, Gereffi, Rissing, & Ong, 2007, p. 75 .


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While China has been graduating more engineers and at a faster rate than the United States or India, most Chinese and Indian engineers came to the United States for their graduate degrees (Wadhwa, Gereffi, Rissing, & Ong, 2007). Nevertheless, for China, this trend is changing. Since 2003, China has graduated more engineering and technology PhDs than the United States and since 2004, more master level degrees. Thus, at the graduate level, a more pernicious picture emerges for the United States (p. 79). The bottom line is that China is racing ahead of the United States and India in its production of engineering and technology PhD’s and in its ability to perform basic research. India is in particularly bad shape, as it does not appear to be producing the numbers of PhD’s needed even to staff its growing universities. (p. 82). The authors (Wadhwa, Gereffi, Rissing, & Ong, 2007). also updated a 1999 study by Saxenian, which examined immigrant contributions to high-tech companies in Silicon Valley; they interviewed 2,054 companies from throughout the United States (p. 82). A quarter of those companies had at least one founder born outside the United States and over a third for semiconductor companies. More than 80% of those were in “software and innovation/ manufacturing related services” (p. 82) companies. Indians were the dominant force, founding more companies in the past 10 years than some of the others combined (p. 82). The authors asserted, “Indians are leading the charge in starting new businesses, and Chinese create the most intellectual property” (p. 82). In addition, the authors found that most of those founders had higher-level degrees earned in the United States . Critique of Methodology These four authors (Wadhwa, Gereffi, Rissing, & Ong, 2007). have spent a significant amount of effort to obtain valid data, and in some cases, called out suspicious data, explaining why it was or was not included. Wadhwa and Gereffi have been researching this topic for some time as part of the Center on Globalization, Governance, and Competitiveness and the Pratt


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School of Engineering at Duke. Nevertheless, some questions do not seem to get asked: for example, they suggest that the United States does not need to graduate more engineers at the bachelor level, because salaries will go down and already young people are pursuing other careers instead as a result of salaries inconsistent with other like professions. In the next breath, they state the companies are setting up R&D centers outside the United States because it is cheaper. Granted, the problem is a complex one, but the connections are not always made quantitatively in their articles, only statements in the conclusions. Usefulness to Depth and Future Research Following these authors and the Duke Center on Globalization, Governance and Competitiveness will continue to provide fruitful and provocative data and articles. This writer has been following them for the past 10 years; my scope of interest closely parallels theirs in terms of data gathering and passion for changing the situation in the United States (Craig, 2006). Literature Review Essay From the annotated bibliography of 13 peer-reviewed journal articles and 4 dissertations, three themes emerged. The first of these themes was finding connections between technology epiphenomena and adolescent career selections. The following sections will outline globalization affects relating them to collapse theories, with the last section in this depth essay sharing how these might be affecting STEM career selections of teens. Society and Technology Epiphenomena With Respect to Teens Advent of Computers, Laptops, and the Internet As described in Breadth section, computers and their impact on human lives is a relatively new epiphenomenon; studies on their influence on teens are recent and generally have not been longitudinal. Since their advent on the learning scene, “the overall student-computer


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ratio in the United States has fallen from an estimated 168.0 in 1983 (Anderson & Ronnkvist, 1999) to 3.8 in 2005 (Market Data Retrieval, 2005)” (Grimes & Warschauer, 2008, p.306). In other words, computers are ubiquitous today only twenty-five years after the IBM PC (and its brethren) revolutionized the computer world. With the birth of the Internet in 1992, further technology changes, such as, cell phones, Personal Digital Assistants (PDAs), text messaging, and social networking have bombarded young people; moreover, they have embraced these new pathways in ways not yet fully studied. Geyer, in his recent dissertation evaluating teen Internet savviness, stated that teens who are Internet savvy are “unknowing participants in a series of global transformation that presage significant, disruptive change in our society and in particular, in how we teach learn in our schools” (Geyer, 2008, p. 2). Nonetheless, this digital explosion does not appear to have led to an increase in young people entering STEM careers. Possibly, teens are just not seeing the connections to their digital lives. Blum and Frieze, studying computer science students at Carnegie Mellon University outreach programs for high school, found that “high school students and teachers tend to equate computer science with programming. Thus outreach programs clearly provide an opportunity to…[sell] computer science” (Blum & Frieze, 2005, p. 123) as a career and help teens make those links. Many researchers have been studying the impact of one-laptop to one-student programs. In a large study of Los Angeles public school students, Grimes and Warschauer (2008) first summarized other one-laptop to one-student studies and assessed their efficacy (e.g., sample type, scope of implementation, length of study, for which school subject laptop was used). (pp. 306-308). They found, in their 2007 study, published in 2008, that laptop use supported just in time learning. For example, students were not able to grasp a small poem by Emily Dickinson by


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simply reading it; after quick Web research about her life, the students were then able to understand the poem (pp. 317-318). “82% of the teachers [Grimes and Warschauer] surveyed agreed that students ‘get more involved with in-depth research’ in the laptop classroom” (p. 318). The sense of personalization that a student laptop brought carried over into many facets of learning (p. 318). Students spent more time on homework, developed a sense of pride about their work; it was their tool. The study by Blum and Frieze (2005) at Carnegie Mellon University (CMU) showed changes in attitudes in CMU’s Computer Science (CS) students; the authors believed these changes were in response to Carnegie Mellon programs aimed at retaining CS students. Consider a particularly thought provoking quote from their study: One man acknowledged his own change of attitude: ‘I still find computers to be very interesting. But because the field of computer science has grown as I’ve learned more about it, it’s no longer the computer itself and the programming that is interesting. It’s what can be done with the programs that is now interesting. The computer I see more as a tool now, as opposed to this neat toy’ (Blum & Frieze, 2005 (p. 115). Could society changes happening in the background have been a stronger causal? Generation Y Characteristics Generation Y teens, as defined by Miskec (2005), were born after 1978 and before 1997. Generation Y will have, as stated by Hammel, “31 percent fewer face-to-face interactions” (as cited in Miskec, 2005, p. 11) then Gen X, those born after the baby boom ended in the mid1960s. Miskec asserted that Gen Y teens and adults are typically impatient and frustrated, in particular if something does not advance fast enough technically (2005, p. 30), essentially “perpetual adolescence” (p. 38). Couple this impatience with the fast-paced world of text messaging, tweeting, and FaceBook wall messages, will Gen Y teens develop into the kind of engineer needed in 2020?


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“2020 engineers…will need something that cannot be described in a single word. It involves dynamism, agility, resilience, and flexibility” (Lucena, 2006, p. 322). Lucena found that younger engineers did not always do well in teams. Specifically, “their resistance to [Integrated Products Teams] was also due to their difficulties in dealing with the ambiguities brought about by working with people who solve problems differently than they did” (p. 334). Miskec suggested that much of the media and literature draws a dark picture of Gen Y teens than might be warranted, Gen Y are becoming “increasingly dangerous, unpredictable… due to societal upheaval” (2005, p. 43). If true, this could portend a change in student value emphasis, from a desire to earn a college degree to learn more about life moving to make a lot of money and be well off (Rion, 2007, p. 48). In parallel to this value change, Turner and Bowen (as cited in Rion, 2007) described how in the 1970s, colleges provided more occupational oriented degree programs, as the number of students decreased and those students were concerned about money (p. 51). These changes in characteristics and degree program foci, all could be influences affecting the number of native-born students considering STEM careers. Will these generational characteristics so well explained by Miskec and Rion reflect in career choice trends? Differences found in the literature are next. Career Influences, Math and Science Education Rion, in her dissertation analysis (2007) of the longitudinal study data from National Educational Longitudinal Study (NELS) database of students, in eighth grade in 1988 and evaluated every regularly thereafter until 2000 (p. 9), described how experiential learning had an impact on career choices and changes (pp. 44-45). “Students leaving STEM had lower academic preparation and performance and attended institutions with lower proportions of degrees awarded in STEM than those who stayed in STEM.” (p. iii). The issues in science and math


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education have grown over a generation and will likely take “10 to 15 years before major benefits become apparent” (Wadhwa, Gereffi, Rissing, & Ong, p. 84). The issue cannot wait that long to be resolved or the United States will lose the innovation competition (p. 84). Links to Globalization Affecting Teen Decisions An insufficient quantity of native-born students have been pursuing master and doctorate level degrees in engineering; that is troubling for the United States (see Application section for further details). Moreover, many foreign-born students are now going home after earning those higher degrees and contributing to levels of innovation in their home country. Both India and China offer financial support to their graduate students. The United States needs to develop its own native graduate degree engineers, and more financial support could be a key dynamic (Wadhwa, Gereffi, Rissing, & Ong, p. 84). Freeman asks (2006b, p. 162), with a higher flow of technically competent immigrants, will native teens have incentives to study a difficult course of study like engineering. As Geyer (2008) asserted in his dissertation and as Friedman posited in his popular 2004 book, The World is Flat, beginning in this century, individuals have gained the ability to have a global reach, to gain information on a global basis via the Internet, and interact with others throughout the globe and have the potential to influence career selections. Gender Differences “Girls shouldn’t feel social exclusion for choosing science” (Berry, 2009, p. 14). Nonetheless, many girls do continue to experience this from their male and female peers. Several studies described in the literature about mother’s toy purchases and science museum parent-child interactions showed gender bias factors at play, even in recent times. (Berry, 2009). Societal influences and peer pressures play a part in the complex dynamic of career choice.


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What influences girls. Providing access and projects interesting to girls in elementary and secondary programs can make a difference in what careers they chose. “Regardless of the causes, research suggests that experiences of girls in middle and high school have significant effects for later decisions in science and technology (Barron, 2004)” ( Dunleavy & Heinecke, 2007, p.19). In their 2007 one-laptop to one-student study in the Los Angeles area, Dunleavy and Heinecke examined this in depth (e.g., boys more involved in technology or science or more socialized with computers) and they did not find learning or cognitive style differences as a potential causal for this gender difference (p. 20). Instead, girls seem to “have opted out of the field” (Dean, 2007, para. 28) before they even knew about it. To counteract this trend, universities (e.g. Brown, Harvard, Rutgers, University of California at Los Angeles, and University of Washington) and organizations (e.g., Baker & Marks, 2005) have been developing materials for teachers to share with their students describing the “challenges and opportunities of computer science” (Dean, 2007, para. 28). Many programs exist to expose girls to engineering and science in a positive way at various stages of a girl’s elementary, secondary, and tertiary schooling. For example, in the United Kingdom, “The IoP [Institute of Physics] launched an initiative…Girls into Physics, that resulted in the report Yes She Can! examining best practice” (Baker & Marks, 2005, p. 174). Berry experimented with an after school club for her fourth grade class. She used the concept of a social club (after-school) to foster an interest in science in fourth grade girls. This successful project encouraged the school district to continue it in subsequent years and to enlarge the concept for both boys and girls, with repeated positive results (Berry, 2009). These types of efforts are vital steps, considering the observed declines in computer science graduates, in particular, women graduates (Baker &


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Marks, 2005; Blum & Frieze, 2005; Bolin, 2007; Dean, 2007; Grimes & Warschauer, 2008; Miskec, 2005; & Rion 2007). Gender differences for computer use and career choices. Many studies showed differing results in this area. “Margolis and Fisher note a strong gender difference in computerscience students’ interests: male students focus more on programming and women more on the applications of computers” (Blum & Frieze, 2005, p. 114). Blum and Frieze in their laptop study (2005) of Los Angeles, admittedly younger, students found different results. “In contrast, this was one area in which our cohort exhibit[ed] strong gender similarities” (p. 114). In Geyer’s doctoral research with its cohort of gifted middle school students, “between 30% and 40% of 12 to 17 year-old youths (2008, p. 122) were savvy about the Internet. Girls chatted more; boys played more games (p. 109). “Ninety-seven percent [used] the Internet outside of school” (p. 113) primarily to gather information (~30%) and games (38%) (p. 119). How the teens perceived this information was revealing; some finding it fun, others not so fun (p.125). While boys played games more, girls were “three times more likely to suggest” (Geyer, 2008, p. 137) using games for education (p. 128). Results. From the journal articles and dissertations evaluated, certain specifics emerged at the tertiary level. In Rion’s (2007) study of degree changing, “as many as 75 percent of women” who started in a more female traditional major changed to more “gender neutral or male-dominated majors by graduation” (p.44) when compared with coed schools where about 25 percent changed (p. 44). Analyzing a major change with what classes were taken in high school, “greater numbers of math and science courses in high school increased the probability of majoring in technical fields for all racial groups, but females in all groups had a lower participation in these fields than males” (p.32). Clearly, gender differences exist.


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Summarizing Epiphenomena Influences In this section of Depth, teens and technology epiphenomena were connected. For Gen Y students, the growth of computers and the Internet supplied notable epiphenomena affecting young people, regardless of gender. Computer technology is shrinking its physical size with PDAs and notebooks while growing a worldwide reach via social networking tools (e.g., FaceBook), improved search engines, and broadband connections. Females appear not to have benefited by these changes in some respects, their interest in computer related fields has dropped in recent years. The use of computers in the education process is nascent at best. Only recently are students using a computer for activities beyond its simple word processing and calculation abilities. Research is underway in many venues examining how to better use this new education technology. In the next section of Depth, trends in globalization affecting careers in engineering and computer science will be explored and linked. Globalization Trends for Engineering and Computer Science Since the 1970s when consumers perceived Japan as the manufacturing quality leader, automobiles being only one well-known example, manufacturing has been leaving the United States for other lower cost labor parts of the world. This exodus continued throughout the 1980s and beyond. Today, leadership of two of the largest electronics manufacturing providers in the world is not in the United States. Foxconn (Hon Hai Precision Industry), headquartered in Taiwan (with most of their plants in China) and Flextronics International, founded in Silicon Valley but since 1990 headquartered in Singapore, has manufacturing plants throughout the world and many in China and other Asia-Pacific countries. Finding a computer, consumer product, or other electronic item not made in China is difficult. Though Japanese engineers design many consumer electronics and U.S. engineers still design computers, Chinese engineers


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have been designing all of these, in recent years. For example, IBM, who made the term PC ubiquitous after launching its PC in 1981, sold its PC business to Lenovo, a Chinese company in 2004 (IBM, n.d.). Thus, manufacturing is not the only function whose leaders are outside the United States. Until recently, U.S. engineers were designing computers and associated hardware and U.S.-based computer scientists or software engineers were developing software for them. That paradigm has begun to shift. In 2003, Microsoft opened a major R&D facility in China (Freeman, 2006a, p. 143); in 2004, Cisco, the world leader in networking equipment, opened a major R&D facility in China. Two of the largest high tech companies are now obtaining new technology and new products from China. Arguably, the ability of the United States to adapt “new information and communication technologies [into] production [drove the] rapid productivity growth in the 1990s/2000s” (Freeman, 2006a, p. 124). What is the impact of globalization on the vaunted United States ability to innovate? The next section contains answers gleaned from Depth readings. Innovation Center Moving Away from United States Many indicators show that a shift is occurring for centers of innovation. “Inventions originating outside the US account for just under half of USPTO [US Patent and Trademark Office] patents, with applications from Japan comprising about 48% of this foreign total” (Kerr, 2007, p. 4). Moreover, other shifts are occurring that support further change: “shifts in the concentration of ethnic inventors appear to facilitate changes in the geographic composition of US innovation” (Kerr, 2007, p. 8). Native versus non-native born engineering graduates. Freeman (2006b) reported that in 1990, only one quarter of Ph.D.s in Science and Engineering were foreign-born; and by 2004,


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over one third of those graduates were foreign born. In addition, Freeman stated master degrees earned by foreign-born rose from 19% in 1990 to 32% in 2004. Using the same endpoints, bachelor degree proportions were much lower, 11% and 17% respectively for 1990 and 2004. (Freeman, 2006b, Table 3, p. 153). “Nearly 60 percent of the growth in the number of U.S.-based Ph.D. scientists and engineers over this decade came from the foreign born” (Freeman, 2006b, p. 162). Figure 9 and Figure 10 showed slightly higher percentages that Freeman had; graphs were developed from National Science Foundation databases (NSF, 1997; NSF, 2006) available on the government website. Freeman suggested that if H1B visa restrictions are continued or further tightened, immigrant inflows would be staunched and companies may be driven to establish R&D centers offshore (p. 162). Naidoo determined that the decrease in non-native engineering and computer science degrees can be attributed to “tuition fee increases and improved access to domestic education opportunities” (2007, p. 223).

Figure 9.

NSF data (1987 - 2004), master’s degrees, native vs. non-native recipients


25,000

100% 90%

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U.S. citizens & permanent residents Nonresident aliens Citizenship unknown TOTAL Science & Engr.

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Figure 10.

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NSF data (1987 - 2004), PhD degrees, native vs. non-native recipients

Ties to collapse theorists. Are any of these metrics collapse indicators? Turchin, Adams, and Hall (2006), in their statistical analysis to validate Diamond’s collapse theory (as described in the Breadth section of this paper), stated “the general rule, thus, seems to be that expansion is easiest and most lasting when occurring within the same ecological zone [emphasis added]” (p. 225). Another perspective offered by these authors: The east-west orientation for modern nations or empires was not as strongly demonstrated (p. 226). Four reasons were asserted for this: (a) many modern “colonial states” (p. 226) grew by sea, not land; (b) cost of transportation was less and has been more easily available in modern times than before; (c) many colonial empires grew into unoccupied territories; and (d) nations often went after scarce resources in distant lands (p. 226). Is there an analogy to this ecological zone concept in the directions or pathways for innovations or technology moving from the United States to other parts of the world? In other


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words, considering multinational companies, educated workforce availability, technology infrastructure (networking, knowledge, assets): could any of these be similar to the environmental, biome lines of latitude concept? To answer these questions, further analysis is required. Specifics on Women and Globalization On the other hand, different nuances appear when considering engineering and science graduate metrics in the United States for women: In 1966, U.S.-born males accounted for 71 percent of science and engineering PhDs awarded; 6 percent were awarded to U.S.-born females; and 23 percent were awarded to the foreign-born. In 2000, 36 percent of [science and engineering] PhDs went to U.S.born males, 25 percent to U.S.-born females and 39 percent to the foreign-born” (Freeman, 2006a, p. 127). This rise in women engineers and scientists appeared in other parts of the world. In Japan, from 1985 to 1999, “the rate of increase for women scientists was 3.2, and for women engineers, 7.2” (Vogt, 2008, p. 329). Japanese women have experienced significant growth in engineering and the sciences from less than 1% in the early 1990s to 17% in 2004 (pp. 327 & 329). Whereas U.S. women engineering graduates grew from less than 1% in 1974, to about 15% in 1985, and about 20% in recent years (pp. 328-329). In the European Union, women have much lower percentages in the engineering fields; though if expanded to include Eastern Europe, the numbers are much higher (p. 329). Collapse or Decline Connections for STEM Is the rise in engineering outside the United States, coupled with a declining interest inside the United States among native born presaging a decline (yes) or even a collapse (possibly) of innovation in the United States ? Will the various aspects of globalization hurt the United States in the end? Freeman asserted the answer is yes. “Loss of comparative advantage in


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the high-tech sector to a low wage competitor can substantially harm an advanced country” (Freeman, 2006a, p. 143). Consider the indicators found in the following paragraphs. Decline in Math and Science Ability May Presage Decline for United States Repeating a section from Breadth: Consider the Roman Empire fall for those three areas. “Literacy and mathematical training apparently declined during the third century. … As fewer people could read or count, the quality and quantity of information reaching the government during this critical time would have declined” (Tainter, 1988, loc. 2134); thus, the Roman government lost touch with its periphery and needed more money to mend that. This situation is present today in the United States: U.S. reading and mathematics test scores at the high school level are no higher now than they were 30 years ago (National Assessment of Educational Progress, 2005), inquirybased learning is declining in schools due to pressures of standardized testing (see, for example, Cordes, 2004), and the U.S. workforce remains woefully under-prepared (Eisen, 2003). (Grimes & Warschauer, 2008, p. 306). Similar to the situation in the United States, the number of physics graduates in the United Kingdom is not increasing; a source for much fundamental research influencing innovation and sparking new industries (Baker & Marks, 2005, pp. 173-174). Could one rewrite Tainter’s (1988) thoughts in this manner: “Literacy and mathematical training…declined during the [twentieth century].…As fewer people could [understand complex mathematics or read above a fourth grade level], the quality and quantity of [innovation fueling the United States economy] during this critical time [was declining]” (adapted by author, from loc. 2134). Will the United States respond similarly to how the Roman Empire responded centuries earlier? Who Values Engineers and Scientists Other countries value engineering and science more than the United States seems to today. “Citizens in [India and China] have long viewed engineers as a critical input to their


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national development, and interest in engineering fields runs high among students, government officials and technology leaders alike” (Gereffi, Wadhwa, Rissing, & Ong, 2008, p. 19). Most teens idolize music stars and basketball players, not Berners-Lee, the inventor of the Web, or Franklin, the scientist whose work on DNA’s helical structure enabled Watson and Crick to fully document how DNA worked. China recognizes their engineers who publish in global journals; “U.S. society could certainly offer engineers more respect and recognition” (Wadhwa, Gereffi, Rissing, & Ong, 2007, p. 84). The United States hardly notices. Does the United States Face a Shortage in Engineers and Scientists? Companies could be shouting about a shortage merely to create a better labor market with more options available to them. “The number of jobs requiring a solid technical base has not diminished, but the demand for graduates combining technical knowledge with other skills is growing due to the more complex working environment” (Ramalhoto & Akay, 2006, p. 247). If, as Freeman suggested, the United States does have an adequate supply, he asserted this adequacy depends on immigrant talent (2006a, p. 140). The shortage is native-born engineers; that is the prime issue, in Freeman’s mind. Nevertheless, he asserted that it is better to have immigrant scientists and engineers doing their work in the United States versus back in their native country (with lower salaries), because their work contributes to the United States maintaining itself as a technical center of excellence (Freeman, 2006a, p. 145). By graduating more engineers, Wadhwa, Gereffi, Rissing, and Ong asserted that engineering salaries could become further depressed driving young people into investment banking or other careers. Another perspective that might predict a potential shortage is the average age of STEM workers. A key statistic from the United Kingdom, provided by Baker and Marks, was “UK


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physics has an ‘old’ age profile. In 2002-2003, 40% of academics were over 50 and only 11% were younger than 34” (2005, p. 174). Similar data is available for the United States. In addition, “Many leaders attribute the increasing momentum in outsourcing by U.S. companies to shortages of skilled workers and to weaknesses in the nation’s education systems, without fully understanding why companies outsource” (Wadhwa, Gereffi, Rissing, & Ong, 2007, p. 73). Bottom line, companies are leaving because it is cheaper to have R&D elsewhere and secondarily because it is closer to growing markets for products. Companies will establish R&D centers in China with or without hurdles to obtain sufficiently skilled workers. (p. 84). Whatever the reasons, be it the stagnant or slow growth rates of new engineers and scientists, be it the less than stellar United States math and science test scores, or an aging population, or the desire to locate closer to new markets: “Research and technology activity and production are moving where the people are…to China because China is graduating huge numbers of scientists and engineers” (Freeman, 2006a, p. 147). To maintain its edge, or slow the decline, the United States should increase the supply of engineering and scientific talent, whether native born or foreign-born (pp. 148-149); otherwise, a collapse could occur rapidly. Freeman asked a significant question: Without immigrants, can the United States maintain its competitive technology edge? (Freeman, 2006b, p. 162). Posing one further question: with the outflow of R&D efforts into China and other lower cost developing countries, like China and India (and Vietnam, Taiwan, Malaysia, etc.), can the United States grow or even maintain its competitive technology edge? Depth Summary Two axes of interest, collapsing societies and technology epiphenomena have now been explored from both theoretical and current research viewpoints. Studying collapse theories and


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technology epiphenomena brought convergence to several areas of interest to the high-tech community, educators, and people interested in growing the engineering and computer science skill base in the United States. The findings for young men and women were different in several cases: Generational differences provided more nuanced differentiations. Overarching it all was the globalization of world industries and the accelerating pace of information transfer and connections. The digital explosion characterized by the exponential rise of computer and Internet use is the warp thread that runs through the fabric of United States innovation. The many colored wefts of generational differences, native and non-native population considerations, globalization influences, and a declining interest and ability in math and science in the United States have woven a richly textured fabric from which to view the U.S. innovation fabric. Bringing these far flown connections between technology epiphenomena, adolescent career selections, globalization affects, and collapse theories, to a cogent and understandable view will be attempted in the final Application section, again through filters of STEM, teens, robotics, and gender.


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APPLICATION SBSF 8130: PROFESSIONAL PRACTICE AND SOCIETAL DEVELOPMENT “ ...to transform our culture by creating a world where science and technology are celebrated and where young people dream of becoming science and technology heroes” FIRST vision, as articulated by Dean Kamen (Annual Report, 2008, p. 40)

Globalization Impacts on Technology Talent Pool and U.S. Innovation Globalization impacts are the topics of news today at many levels and from many perspectives. From celebrated New York Times editorial writer and author, Thomas Friedman, in his book, The World is Flat (2005), to Richard Freeman, noted Harvard University and London School of Economics economist and Program Director of Labor Studies for the U.S. National Bureau of Economic Research, to the National Academies research, and from people on the street, the question arises: is the United States losing its premier position as technology innovation leader, and if so, why? Duke University researchers asserted that “many people…do not seem to look ahead and realize that what could be outsourced next is research and design, and that the United States stands to lose its ability to 'invent' the next big technologies” (Wadhwa, Gereffi, Rissing, & Ong, 2007, p. 73). However, research and development (R&D) is already being outsourced by many companies—Cisco, Microsoft, IBM, HP, along with many others, large and small. Innovations are under development in other parts of the world more frequently, and not in the United States. The pace of engineering and science graduates is not keeping up with that of China and India. Many teens ask why go into a field that is being outsourced to another country? Overall, some amount of decline is evident in the United States talent pool. The next question that arises is why and can anything be done to reverse this decline. Circling back to the collapse theorists studied, possible solution paths are evident. Dosh (2004;


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2009) established that if the communities he studied cultivated a new mission, beyond the vision that brought them together in the first place and that they had achieved, those communities could and did thrive. Diamond (2005) suggested with a stronger attention to the resources and environmental impacts from too much population, nations could survive crises. Tainter (1988) described how the Roman Empire lasted for much longer than it might have during and after the reign of Diocletian (reigned 284-305) when he put into action significant political and economic changes (loc. 2192). The theorists suggested that collapse is not inevitable. In the next sections, the state of high tech will be analyzed from collapse theory perspectives, along with specific data that might be perceived as metrics for R&D health. Last, programs aimed at inspiring teens to consider engineering and technology careers will be described. Silicon Valley and High-tech as a State or Nation States and nations drive to keep their territories intact and “are the only kind of human society that does not ordinarily undergo short-term cycles of formation and dissolution (cf. R. Cohen 1978: 4; Claessen and Skalnik 1978b: 632)” (Tainter, 1988, loc. 508). Could Silicon Valley or high-tech industries be evaluated in this manner? Arguably, Silicon Valley is the center for the high-tech world, though it might not fit the definition as Tainter stated it, it is a clear hub using Motyl’s (2001) metaphor. “Newly civilized peripheral populations adopt some competitive advantage (an organizational feature, weapon, tactic, or the like) that the old center is too conservative to adopt, and thereby rise to dominance” (Tainter, 1988, loc. 985). Silicon Valley succeeded because of its very ability to innovate and move in new pathways. While DEC broke the mold, in comparison to IBM and other large companies at the time, with its university-like collaborative approaches, nevertheless, it fell into that same security trap Dosh (2009) described by failing to innovate or change, finding a new mission for itself. The


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ability of Silicon Valley companies to change, grow, develop offshoots, and adapt to challenge is well known. It is not clear if a model as a nation or state is possible for high-tech; nevertheless, its reactions to stressors follow similarly to those in the nations analyzed by all collapse theorists. R&D Health Metrics and Measures Tainter posited that R&D has been declining as measured by U.S. patent applications per R&D engineer and similar metrics in other countries (1988, Figure 9, Figure 10, and associated text). While he suggested research has sufficiently demonstrated patent applications as a reliable and predictive metric for R&D health, several points arise. First, patent applications have become more difficult and complex when compared with the early decades of the 20th century; has this affected the quantity? Second, over time companies have begun to keep intellectual property (IP) in-house versus patenting the IP, and thus making public, critical company IP. Third, the quality or breadth of the patent application is not part of this metric of quantity; thus, the quantity of patents does not measure complexity; complex processes exist in many industries today. Admittedly, patent applications are a measure of output. Another metric, on the input side of R&D efforts, is the R&D dollars spent by U.S. government agencies (NSF, 2004) and industry research labs. Considering both basic and applied research dollars invested by the Federal agencies are shown in Figure 11, R&D dollars spent in engineering, physical sciences, environmental sciences, and the math and computer sciences have been increasing in pure quantity; however, when analyzed as a percent of total Federal R&D expenditures (see Figure 12), the story is somewhat different, showing clearly declining investments in engineering and physical sciences. Where the dollars had been going was into the life and social sciences areas, as shown in Figure 13. Most significant innovation has come from the physical sciences, thus this decline is of particular concern, as noted by the Committee on


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Prospering in the Global Economy of the 21st Century (National Academies, 2006) in their “Sowing the Seeds” recommendation: “Sustain and strengthen the nation’s traditional commitment to long-term basic research... to maintain the flow of new ideas that fuel the economy, provide security, and enhance the quality of life (p. 136).

Federal Obligations, R&D Dollars, (in millions)

10,000 Engineering, total Physical sciences, total Environmental sciences, total Math & computer sciences, total

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Figure 11. Federal Agency Obligations, Research and Development dollars, in millions, specific areas, spent between 1970 and 2003 (adapted from NSF, 2004)

Federal Obligations, R&D Spending as a Percent of Total Spending

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Figure 12. Federal Agency Obligations, Research and Development dollars, as a percent of total spending, specific areas, between 1970 and 2003 (adapted from NSF, 2004)


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Figure 13. Federal Agency Obligations, in terms of Research and Development dollars, as a percent of total spend, for all areas, between 1970 and 2003 (adapted from NSF, 2004)

Pytlik, Lauda, and Johnson (1978) suggested another view of R&D spending, outlining six characteristics for describing societies: education, food production, politics, economics, communications, and technology. These characteristics can be used to place societies as tribal, transitional or emerging, or highly developed or postindustrial. In 1978, India was classified as transitional by these researchers; would it be today? This data (Pytlik, Lauda, & Johnson, 1978) helped generate three tables for key metrics comparisons: Table 8 has population data from five countries (pp. 149-153); Table 9 compares numbers of scientists, engineers, and technicians working on research and development (R&D) projects; and


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Table 10 has educational metrics (pp. 81-106). Figure 14 compares this data, showing R&D investments by nation compared to population and to numbers of engineers, scientists, and technicians working in R&D. Worthy of note: while dollars spent in R&D are low for India and for Peru are low on a per capita basis, Peru’s investment per technical resource was much higher than India’s; and while the UK and Japan were investing less per capita than the U.S.S.R. on a per technical resource point of view, their investments were comparable. Table 8 Population metrics of six nations, from the early 1970s Population Metrics Stage

Country

Year

Population

Growth Rate

Emerging

India

1974

574,216,000

2.1%

Emerging

Peru

1974

14,912,000

3.2%

Highly developed

U.S.S.R. #

1974

187,075,000

0.7 %

Highly developed

United Kingdom *

1974

55,933,000

0.3%

Highly developed

Japan

1974

108,346,000

1.3%

Highly developed

United States

1974

210,404,000

0.9%

Note. Adapted from Technology, change, and society. by E. C. Pytlik, D. P. Lauda, and D. L. Johnson, 1978, Worcester, MA: Davis Publications; from 1974 United Nations Statistical Yearbook data. # USSR data contains European portions only * United Kingdom contained Great Britain and Northern Ireland.

Table 9 Technology metrics of five nations, from the early 1970s Technology Metrics Stage

Country

Year

Numbers of scientists,

R&D


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engineers, and technicians

expenditures

Emerging

India

1972

~103,000

$225,000

Emerging

Peru

1970

~850

$8,000

Highly developed

U.S.S.R.

1972

~1,000,000

$17,000,000

Highly developed

United Kingdom *

1970

149,500

$2,500,000

Highly developed

Japan

1972

314,000

$4,800,000

Note. Adapted from Technology, change, and society. by E. C. Pytlik, D. P. Lauda, and D. L. Johnson, 1978, Worcester, MA: Davis Publications * United Kingdom contained Great Britain and Northern Ireland.


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Table 10 Education metrics of five nations, from the early 1970s Education Metrics Stage

Country

Year

Literacy rate

Compulsory education

Emerging

India

1970s

25%

Until age 14

Emerging

Peru

1970

71%

Until age 14, less than 50% attend

Highly developed

U.S.S.R.

1972

~100%

10 years (virtually all)

Highly developed

United Kingdom *

1970

~100%

Until age 16

Highly developed

Japan

1972

~100%

Until age 15

Note. Adapted from Technology, change, and society. by E. C. Pytlik, D. P. Lauda, and D. L. Johnson, 1978, Worcester, MA: Davis Publications; from 1974 United Nations Statistical Yearbook data. * United Kingdom contained Great Britain and Northern Ireland.

Considering Table 8, Table 9, Table 10, and Figure 14, it is apparent that the globalization of R&D offers both a threat and an opportunity (Segal, 2004). Nonetheless, when one variable in the multifaceted system of innovation creation changes as can be seen from the trends described, like the “complex interactions between firms and universities that drive technological discovery” (Segal, 2004, “Rapid Responses”, para. 3) or multinational companies sending engineering or manufacturing jobs to Asia and other parts of the world, the system can destabilize (Brunk, 2002; Segal, 2004). Another metric to measure R&D health is the number of doctorates graduating the computer science, mathematics, the physical sciences, and engineering. In Figure 15 through Figure 22, these numbers were graphed using two scales. First, trends from 1966 to 2006 are shown followed by a closer view of the past twenty years with data from 1986 – 2006.


Figure 14. Comparisons by country of R&D investments, circa early 1970s Note. Adapted from Technology, change, and society. by E. C. Pytlik, D. P. Lauda, and D. L. Johnson, 1978, Worcester, MA: Davis Publications

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In contrast to bachelor level data for computer science (Craig, 2009), PhD degrees in computer science have slowly risen, in particular in recent years; women’s share in this field at this level has continued to be marginal, with less than a fifth of degrees in recent years being earned by women (Figure 16) though this share at the doctoral level is similar to that of women at the bachelor level (Craig, 2009b, Slide 17). Mathematics doctoral degrees numbers (Figure 17 and Figure 18) appear to follow a sine curve for the past forty years, with peaks and valleys, recent years being on the rise; women’s share here, a little less than a third, is not near the almost 50% share at the bachelor level (Craig, 2009b, Slide 17). In the physical sciences, recent years have resulted in high numbers similar to the early 1970s and mid 1990s, with a slight rise recently; women are earning this level degree in higher numbers, but similar to mathematics, at about a quarter not at the same share as for the bachelor level degree, just less than one half (Craig, 2009a, Figure 15). Engineering doctoral degrees have risen for the most part since 1966 (Figure 21 and Figure 22) and except for a dip in the late 1990s has continued to rise to almost double that of 1966. Women’s share of this degree level, critical for academia tenure and research, has risen from 1% in 1966 to 20% in 2006, mirroring what women earn at the bachelor level (Craig, 2009a, Figure 15). In summary, since all numbers for doctoral degrees are rising, this could be a healthy R&D metric result. For women, the picture is a more nuanced one: for both computer science and engineering, the share of doctoral degrees earned is similar to that of the bachelor level; on the other hand, for mathematics and the physical sciences, women have earned parity at the bachelor level, but not at the doctoral level. Following the metrics comes what to glean from them, the challenges facing high-tech.


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Figure 15. NSF data, 1966 - 2006, Computer Science PhD degrees in the United States. Note. Modified from Science and Engineering Degrees: 1966–2006. Detailed Statistical Tables NSF 08-321. National Science Foundation, Division of Science Resources Statistics, 2008. Available at http://www.nsf.gov/statistics/nsf08321/ and S&E Degrees, by Race/Ethnicity of Recipients: 1995–2004, by National Science Foundation, Division of Science Resources Statistics, 2006. Available at http://www.nsf.gov/statistics/

Figure 16. NSF data, 1986 - 2006, Computer Science PhD degrees in the United States. Note. Modified from Science and Engineering Degrees: 1966–2006. Detailed Statistical Tables NSF 08-321. National Science Foundation, Division of Science Resources Statistics, 2008. Available at http://www.nsf.gov/statistics/nsf08321/ and S&E Degrees, by Race/Ethnicity of Recipients: 1995–2004, by National Science Foundation, Division of Science Resources Statistics, 2006. Available at http://www.nsf.gov/statistics/


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Figure 17. NSF data, 1966 - 2006, Mathematics PhD degrees in the United States. Note. Modified from Science and Engineering Degrees: 1966–2006. Detailed Statistical Tables NSF 08-321. National Science Foundation, Division of Science Resources Statistics, 2008. Available at http://www.nsf.gov/statistics/nsf08321/ and S&E Degrees, by Race/Ethnicity of Recipients: 1995–2004, by National Science Foundation, Division of Science Resources Statistics, 2006. Available at http://www.nsf.gov/statistics/

Figure 18. NSF data, 1986 - 2006, Mathematics PhD degrees in the United States. Note. Modified from Science and Engineering Degrees: 1966–2006. Detailed Statistical Tables NSF 08-321. National Science Foundation, Division of Science Resources Statistics, 2008. Available at http://www.nsf.gov/statistics/nsf08321/ and S&E Degrees, by Race/Ethnicity of Recipients: 1995–2004, by National Science Foundation, Division of Science Resources Statistics, 2006. Available at http://www.nsf.gov/statistics/


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Figure 19. NSF data, 1966 - 2006, Physical Sciences PhD degrees in the United States. Note. Modified from Science and Engineering Degrees: 1966–2006. Detailed Statistical Tables NSF 08-321. National Science Foundation, Division of Science Resources Statistics, 2008. Available at http://www.nsf.gov/statistics/nsf08321/ and S&E Degrees, by Race/Ethnicity of Recipients: 1995–2004, by National Science Foundation, Division of Science Resources Statistics, 2006. Available at http://www.nsf.gov/statistics/

Figure 20. NSF data, 1986 - 2006, Physical Sciences PhD degrees in the United States. Note. Modified from Science and Engineering Degrees: 1966–2006. Detailed Statistical Tables NSF 08-321. National Science Foundation, Division of Science Resources Statistics, 2008. Available at http://www.nsf.gov/statistics/nsf08321/ and S&E Degrees, by Race/Ethnicity of Recipients: 1995–2004, by National Science Foundation, Division of Science Resources Statistics, 2006. Available at http://www.nsf.gov/statistics/


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Figure 21. NSF data, 1966 - 2006, Engineering Sciences PhD degrees in the United States. Note. Modified from Science and Engineering Degrees: 1966–2006. Detailed Statistical Tables NSF 08-321. National Science Foundation, Division of Science Resources Statistics, 2008. Available at http://www.nsf.gov/statistics/nsf08321/ and S&E Degrees, by Race/Ethnicity of Recipients: 1995–2004, by National Science Foundation, Division of Science Resources Statistics, 2006. Available at http://www.nsf.gov/statistics/

Figure 22. NSF data, 1986 - 2006, Engineering PhD degrees in the United States. Note. Modified from Science and Engineering Degrees: 1966–2006. Detailed Statistical Tables NSF 08-321. National Science Foundation, Division of Science Resources Statistics, 2008. Available at http://www.nsf.gov/statistics/nsf08321/ and S&E Degrees, by Race/Ethnicity of Recipients: 1995–2004, by National Science Foundation, Division of Science Resources Statistics, 2006. Available at http://www.nsf.gov/statistics/


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Challenges Facing High-Tech Tainter posited, “New, bountiful resources lead to collapse” (1988, loc. 910). Are the plethora of new resources and cheap tech toys leading to less invention of new ones? Several times, Tainter mentioned the loss of knowledge and its impact on a complex society. Seemingly, the United States is experiencing this loss as well. In 2006, U.S. Congressional “Representative Wolfe recalled meeting with a group of scientists and asking them how well the United States was doing in science and innovation. None of the scientists…said…‘okay’. About 40% said...‘in a stall’, and the remaining 60% said…‘in decline’” (National Academies, 2006, p. vii-viii). Another possible concern is the timing of challenges. Periodicity of needs is another factor common to both Tainter (1988) and Brunk (2002). In other words, if a society’s response abilities have the same peaks and valleys, then when an obstacle occurs, the society is ill equipped to respond. For example, if all food stuffs are harvested at the same time and must be used immediately, humans would not be able to survive; instead, if foodstuffs (e.g., grains, meats, fruits) come to harvest points at different of year or seasons, or alternatively some can be stored for periods of time, then humans can develop a full year’s life cycle of food to survive and a specific major happening (e.g., summer drought). Expanding this idea more broadly, nations or industries that have a balance of input can better meet disasters if during one period, some catastrophe occurs. If a group of nations has the same peaks and valleys, their joint ability to overcome obstacles will be diminished. As many in the industry have argued, “the electronic industry must find ways to preserve [its largest] asset, the engineers who will design and build the next generation of electronic products” (Leopold, 2009, para. 1). As the National Academies wrote in 2006: The optimists and the pessimists…agree on two fundamental points: in the short term, some US workers will lose their jobs and face difficult transitions to new, higher skilled


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careers; and in the long term, America’s only hope for continuing to create new highwage jobs is to maintain our lead in innovation. (National Academies, 2006, p. 9-7). Since 2006, the pace of globalization has only increased and its influences are broader and deeper than ever before. From The Economist in early 2009, The collapse of manufacturing…Industrial production is volatile, but the world has not seen a contraction like this since the first oil shock in the 1970s—an event that was not so widespread. Industry is collapsing in eastern Europe, as it is in Brazil, Malaysia, and Turkey. Thousands of factories in southern China are now abandoned (p. 9).

If this collapse or decline is accepted as a precis for the state of innovation in the United States, the next question is what possible remedies and responses can help grow the health of all these R&D metrics. Answers, developed from career development theories (Craig, 2009), that have the potential for inspiring teens to pursue careers of engineering and computer science include experiential, role model based programs, like For Inspiration and Recognition of Science and Technology (FIRST) robotics. Programs that Encourage Teens to Study Engineering and Computer Science Notable for its longevity and reach (For Inspiration and Recognition of Science and Technology (FIRST) “is one of the best mentoring programs in the country” asserts Barbara Bolin (2007, para. 8), an economics expert and FIRST supporter. In 2008 (FIRST), this remarkable organization reached over 160,000 students, aged 6 through 18, supported by 73,000 volunteers and mentors, making over thirteen-thousand robots, with participants from all 50 states (Annual Report, p. 3). For the 2008 FIRST LEGO® League (FLL) competition, the currently popular energy theme was present; “middle-school teams in the 2007 [competition] identified an estimated $120 million in annual savings from their energy audits” (p. 7). For younger students, use of the Lego robotics kits can provide elementary school teachers a way to help students learn using a science and technology curriculum standard based


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project and “develop scientific inquiry skills, persistence in the face of challenges, and the ability to work collaboratively with others” (Murray & Bartelmay, 2005, p. 40). For example, Murray and Bartelmay used a grant from Tufts University to incorporate Lego and Robolab into their second grade classrooms at Duke School. First, learning about moving Lego parts and the history of Lego (introducing new vocabulary and history to these second grade students), students then formulated a vision and made a plan for their inventions. Next, the building phase began. Tracking of student progress occurred via many classroom displays. (pp. 41-43). After each session, the students shared successes and problems, helping each other in a collaborative way to learn from each other. The students decided to post this sharing in the classroom as a tool throughout the project tasks. After the Lego robots were built, the programming began. Students recorded both failures and successes and kept track of changes made to their Robolab programs. As a culminating event, parents came to see the student projects and help them celebrate the students’ road to invention. Every student learned via this project and all students were successful— Every one of them could talk about what their final product would do were it to exist in real life. More importantly, students could all talk about the process that allowed them to create their final product. They had all invented through the scientific process and gained a true understanding of the importance of each component of the process. (Murray & Bartelmay, 2005, p. 44) Many articles and stories exist describing the FIRST organization and its influence, both scholarly research (e.g., Melchior, Cohen, Cutter, & Leavitt, 2005) and current media articles (e.g., Morrison, 2006; Murray & Bartelmay, 2005). However, companies might ask: Can FIRST prove that its programs make a difference and are more students entering engineering and science as a result of them? In 2002, FIRST asked Brandeis University (Melchior, Cohen, Cutter, & Leavitt, 2005) to study FIRST Robotics Competition (FRC) programs in three areas: impact


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on “student academic and career trajectories” (p. 1); how the programs are implemented in schools; and how have these programs helped the partner school or organization. Funded principally by a Ford Foundation grant, the study had two parts: (a) a longitudinal study using a “retrospective survey” (p. 2) of FRC participants from 1999 to 2003 in two metropolitan areas; and (b) interviews and site visits at 10 schools involved in the survey with one other school from the West Coast, not in the survey. (Melchior et al., 2005) The study cohort was diverse in many ways: gender (59% male, 41% female), socioeconomic level (~50% qualified for free lunch of the 9 out of 11 schools reporting) race and ethnicity (16% African-American, 16% Asian, 11% Latino, ~1% Native American, 12% multiracial, and 44% White), and whether parents went to college or not (37% neither parent went to college). Brandeis researchers (Melchior, Cohen, Cutter, & Leavitt, 2005) garnered and shared many conclusions in their report; summarized below are a few relevant to this study: 1.

86% had an increased interest in technology and science.

2.

69% were more interested in careers in technology and science.

3.

Regarding the value of teamwork, 95% had a higher understanding of it.

4.

A desire to help others, specifically 65% “wanted to help younger students learn

about math and science” (p. 4). 5.

More than the national average (65%) went to college: 89% for FRC alumni.

6.

Female FRC alumni did take engineering classes: 40%

7.

For those in college, 41% were studying engineering versus a national average of

6% and FRC alumni were “twice as likely” (p. 6) to study computer science (pp.5-6).


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Application Summary In 2007, Bolin asserted a crisis does exist for the U.S. economy; it needs “to resurrect [itself] and demonstrate the entrepreneurial characteristics that made the United States great!” (para. 2). As has been shown in the earlier Breadth section, “It was Americans who invented and commercialized the semiconductor, the personal computer, and the Internet; other countries merely followed the U.S. lead” (Segal, 2004, para. 1). Only three years earlier, in 2004, Segal, a senior fellow for the Council on Foreign Relations, claimed that: At the moment, it would be premature to declare a crisis [emphasis added] in the United States' scientific or technological competitiveness. The United States is still the envy of the world for reasons ranging from its ability to fund basic scientific research to the speed with which its companies commercialize new breakthroughs. (para. 4). Considering the data presented in prior sections on United States R&D spending (see Figure 11, Figure 12, & Figure 13), patent trends (see Figure 4 & Figure 5), and other innovation metrics (see Figure 14), Segal’s assertion might be incorrect today and Bolin’s statement appears to be more apt: a crisis exists, the United States premier position in innovation appears to be in decline. Why? The globalization of R&D is well underway. Since 2004, many of the largest and smallest high tech firms have established R&D centers outside the United States, in China and India. Software testing, commonly 30-50% of a software product’s development costs, is being accomplished in Romania, Vietnam and other nations, countries with lower labor costs and sufficient technology infrastructure to provide both facilities and a trained workforce. However, the lower labor cost factor is a red herring for the most part. Dr. Lazowska, from the University of Washington, spoke to the New York Times (Dean, 2007, ¶10) stating “‘Cheap labor is not high on the list…It is access to talent.’[emphasis added].” Other researchers would agree: Finding qualified engineers and scientists can be difficult. “One of the paradoxical outcomes of


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globalization: geography has become both less and more important to innovation” (Segal, 2004, “Engineering Ecosystems”, para. 7). Will the United States vaunted innovative capital remain the envy of the world for much longer? Programs such as For Inspiration and Recognition of Science and Technology (FIRST) are making a difference. For many teams, FIRST is a shining light. Cynthia Botello, aged 19 from Phoenix, Arizona, spoke to Oprah Winfrey and beamed: I'm a sophomore at Arizona State University, studying to become a project engineer. I don't think I would have gone to college at all if not for FIRST. My high school was 96 percent Hispanic. Girls in our community aren't going to school, especially not for science and engineering. But once you get into FIRST, you see that it's fun. Before FIRST, I didn't even have any idea what an engineer was, but now I feel I can be successful in a male-dominated field—and I can inspire my younger sisters to stay in school. (Sugerman, 2009, final para.). With programs like these, engineering and computer science careers become interesting and more viable for today’s Gen Y teens and for future young people.

Application Project Embedded

ccraigkam1societalinfl uencesaffectingteense


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