Infornation Overload in Computer-Mediated Communication and ...

Infornation Overload in Computer-Mediated Communication and Education: 1s there really too much information? Implications for distance education.

Helena Felicity Paulo

A thesis subrnitted in confomiity with the rcquirements

for the degne of Master of Arts Department of Cumculum, Teaching and Leaming

Ontario Institute for Studics in Education of the University of Toronto

0 Copyright by Helena Fclicity Paulo (1999)

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Infocmation Overload in Computer-Mediated Communication and Education: 1s there really too much infornation? Implications for distance education Master of Arts 1999 Helena Felicity Paulo Department of Curriculum, Teaching and Leaming Ontario Institute for Studies in Education of the University of Toronto

Abstract The development of computer technology and the rapid growth of the Intemet have led to a plethora of on-line information resources. For some domains it seems obvious that information overload is an inevitable result of technological advancements and a subsequent characteristic of the current information revolution. However, it is not clear that this is the case for computer-mediated communication (CMC) in education. Twenty-five adult students in a CMC course with supplemental face-to-face meetings, were observed and mesures of the amount of information pnsented in both media were obtained. In spite of the students'

perceptions, it was discovered that the CMC component contained less information than the face-to-face component. Variables that confound students' perceptions are discussed and it is hypothesized that students in CMC courses experience 'stimulus' overload and not 'information' overload per se.

Acknowledgments Many of my ideas here developed in conversations (both face-to-face and on-line) with my fnends and colleagues. 1 thank Geoffrey Kushnir and John Stathakos for their helpful feedback on some of my earlier work, and especially for our fun and enlightening discussions about CMC issues. Also, 1would like to particularly thank my thesis cornmittee, Professor

Lynn Davie (my Supentisor) and Professor Jim Hewitt, for their support and guidance. Their input was truly insightful. My fiiends here have made this endeavor a thoroughly enjoyable expenence.

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Table of Contents Abstract

................................................................ ii

Acknowledgments

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

ListofTables

.............................................................vi

List of Figures

............................................................ vi

1. Introduction

..........................................................

1

1.1 What is information overload? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3 1.2 Where does information overload occur?

1.3 Why does information overload occur? 1.3.1 Human Factors

. . . . . . . . . . . . . . . . . . . . . . . . . . . .7

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

...........................................9

1.3.2 Computer Factors ........................................10 1.4 How cm one manage information overload?

. . . . . . . . . . . . . . . . . . . . . . . .12

1.4.1 Cornputer Factors ........................................ 13 1.4.2 Human Factors

..........................................15

1.5 How does on know when infomation overload is occumng

and how does one respond to it?

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

1.6 What do CMC classes look like and what are the benefits of such classes?

.................................................18

1.6.1 Class Elements

1.6.2 Benefits

II.

..........................................

18

.............................................. -20

Problem under investigation

.............................................23

2.1 Purpose ......................................................24

2.2 Hypotheses ...................................................25

III. Method

.............................................................28

3.1 Participants ................................................... 28 3.2 Procedure and Materiais .........................................28

3.3 Analysis 3.3.1

.....................................................30

Wordcountdata ......................................... 30

3.3.2 Questionnaire data

.......................................31

IV. Results ..............................................................32 V.

Discussion ...........................................................42

VI . Future Considerations

..................................................53

VIL References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .54 .

wI. Appendices

..........................................................62

8.1 Appendix A: Face-to-face Group Discussion Assignment

.................. 62

8.2 Appendix B: Questionnaire: Measuring information in face-to-face

settings versus CMC settings

........................................64

8.3 Appendix C: Participant Consent Fom 8.4 Appendix D: Ethical Review Fom

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70

....................................72

8.5 Appendix E: Debriefing Form ........................................78

8.6 Appendix F: Frequency Tables for Questionnaire Items 4 to 23 8.7 Appendix G: One-Sample Kolmogorov-Smimov Tests

............. 81

. . . . . . . . . . . . . . . . . . . .87

List of Tables Table 1 : Word counts of face-to-face recordings and on-line database Table 2: Response freguencies for categories derived fiom open-ended questionnaire items Table 3: Correlations among dependent variables: Questionnaire items

List of Figures Figure 1: Participants' report of tirne spent on the on-line component compared to the face-to-

face ( f l f ) component.

Information Overload

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1. Introduction As the saying goes, 'informatioa is power', and as Gifford (1992)rerninds us, this is

especially so in today's world. We are shifting into higher gear and speeding into an infornation revolution, leaving the industrial revolution behind. With this comes an explosion of data and information for which we may (or may not) have any use or need. Stratulat (1998) explains that we are experiencing a social and economic change that has us moving boom an indushial focus at a national level, to an information focus at a global level. The information age and knowledge society that we currendy live in has the 'haves' doing well and the 'have nots' floundering. There is so much information out there; when is too much information detrimental and no longer powerful? 1s there some optimal level of infonnation that people c m manage before rendering themselves powerless and unable to manage or process that information? According to many researchers, the current influx of infocmation is pnmarily due to the continued development of computer technology, applications and the Internet (Forester, 1992; Noyes and Thomas, 1995; Stanley and Clipsham, 1997; Wishard, 1996; Wurman, 1989) and as a direct result, people are overwhelmed (Etzel, 1995) and some are seriously afYected, psychologically and physiologically, by what many cal1 'information overload' (Forester, 1992; Foumier, 1996; Stanley and Clipsham, 1997; Wishard, 1996).

The tenn 'information overload' is particularly vague. It cm refer to different conditions, such as the quantity of information, the processing of information, or the retrieval

of information. Also, information overload is defhed in a variety of ways, suggesting that it

means differmt things to different people (Burge, 1994; Fournier, 1996; Rudd and Rudd, 1986; Wilson, 1995) and mearchers h m various disciplines report it in the literature: areas


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such as cornputer and information science; human-factors engineering; the social sciences (Hiltz and Turoff, 1985); management science (Butcher, 1995; Etzel, 1995; Hiltz and Turoff, 1985); electrical engineering (Butcher, 1995); psychology (Reeves, 1996); consumer research

(Cole et. al., 1997); and the recreation literature (Keller and Staelin, 1987). Not only is information overload written about by people with very different interests, it is also written about in various areas of publications (Eisenberg and Small, 1993) such as refereed joumals, books (e.g., see Reeves, 1996 and Wunnan, 1989), newspapers, magazines, and most recently, the Intemet (e.g., see Fournier, 1996). This project represents an effort to clari fy what information overload is and what the issues surrounding it are. The primary focus of this paper is information overload in computer-mediated communication (CMC) and education. CMC refers to the use of computea to facilitate interactions arnongst spatially separated individuals who otherwise may not have the opportunity to meet in a face-to-face setting (Everetts, 1998; Hightower and Sayeed 1995; Hiltz, 1986; Hiltz and Wellman, 1997; Jonassen et. al., 1995). Leaniing environments in which teachers and students are geographically separated nom one another are relying more often on the use of CMC

technologies for the delivery of instruction. Unfortunately, one of the most serious cornplaints often reported by CMC students is that they are overloaded with vast amounts of information presented in courses using such technologies (Harasim, 1987; Hiltz and Turoff, 1985; Hiltz et. al., 1986; Hiltz and Wellman, 1997; Wilson and Whitelock, 1995). There is very linle research about the effects of the information explosion on education (Eisenberg and Small 1993). but hdings about the effects of technological developments and information overload kom other mas and disciplines are relevant to CMC and education.

With a focus on information overload in CMC and education, the following issues are


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considered: What is information overload? (i.e., how has it been defined in the literature?); Where does it occur? (Le., does it occur at the instance of sensation and perception, or during processing, storage or retrieval?); Why does it occur? (Le., what is the cause of infomation overload?); How c m one manage it?; How does one b o w when infomation overload is occurring and how does one nspond to it? (i.e., what are the characteristics of someone who is overloaded?); and finally, What do CMC classes look like and what are the benefits of such classes? A review of these issues should bring clarity to a body of research that connects several disciplines. Also, a study addressing issues of information overload in

CMC and education is presented, followed by a discussion of the findings and the implications for education and for friture research.

1.1 What is information overload?

Information overload has a variety of defhitions. Some authors have defmed it as a condition resulting fiorn one being taxed beyond one's capacity (Fournier, 1996). For others, it is the stress caused because the 'overload' exceeds one's ability to benefit fiom the infonnation (Eisenberg and Small, 1993) or, it is simply the overwheiming feeling created by too much information for one ta deal with, too much information for the brain to digest (Stanley and Clipsharn, 1997). Others have defined it as one having more information than one cm take in. or knowingly having a large supply of relevant information that goes unused because one simply lacks the t h e or motivation to process it and later use it (Wilson, 1995). These defïnitions, along with many others not included here, are evidence of the wide scope of this topic (for more examples, see Allen and Griffeth, 1997; Biggs, 1989; Burge, 1994; Hiltz and Turoff.1985; and Noyes and Thomas, 1995). Rudd and Rudd (1986) have noted


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noted the need for some consensual definition, but with so many different contexts under which information overload is currently investigated, and with so many different contexts in which it affects people, arriving at any interdisciplinaryconsensus may be very difficult. Hiltz and Turoff (1985) present a definition of information overload for a CMC context. These authors suggest that the technologies may offer usen more communications

than they can respond to, and that some CMC technologies possibly offer these in such an unorganized manner that users are unable to decipher the relevance of given topics. Burge (1994) also proposes a CMC specific definition of information overload, or what this author

calls 'cognitive load'. Consistent with Hiltz and Turoff (l985), Burge (1994, p. 37) suggests that "the quantity and fiagrnentation of incoming information to process within time limits and the feelings of pressure to produce gramrnatically correct and substantive messages" need

to be considered. Though one rnay not uncover a single comrnon definition of information overload in the literature, one readily discovers a common theme, that is, generaily, information overload means that there is too much information, it has negative connotations, and it is a widespread problem with which much angst is associated. Some authors give readers a bird's eye view of the amount of information that is available nowadays. It is no wonder that there is much anxiety associated with this phenornenon. For example, Wurman (1989, p. 32) tells readers that "a weekday edition of The New York Times contains more information than the average person was likely to corne across in a lifetime in seventeenth-century England.", and that information doubles about every 4.5 years, and every day, 1,000 books are published. Forester (1992) tells readea that about 40,000 scientific journals are publishing more than

one million papers per year; that works out to almost 3000 per day. Also, with the increased


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use of computen, and thus increase in flow of infomation, the United States used about 4 trillion pages of paper in 1991 compared with 2.5 trillion in 1986. Meanwhile, Birkerts (1996) speaks of this trernendous proliferation with regards to a shift fiom vertical reading to

horizontal reading, that is, a shift fiom depth to breadth, or intensive to extensive reading. In a CMC and education context, Everetts (1998) describes a CMC course that she reviewed in which the instructor presented the equivalent of a 42-page class syllabus, compared with the average 6-page class syllabi of classes that meet face-to-face. Harasirn (1987)describes that

CMC students in her study reported spending significantly more time on their on-line courses compared with their face-to-face courses. It seems that this increase of information is prevailing in many domains. Burge's use of the term 'cognitive load' (1994, as noted above) suggests that not only is a more narrow definition of 'information overload' required, but the meaning of 'information' also needs clarification. When reading this body of literature, one is often uncertain of whether authors are refemng to data, infomation, or knowledge. Terms such as information overload, and cognitive load can mean very different things. Other analogous tems found in the literature include infomation explosion, data overload, cognitive burden, message overload, and infobog. Each of these tems will have different implications for the meaning of overload, and perhaps, more importantly, for one's understanding of the information. 1s it a problem if individuah are overloaded with too much information, but their knowledge and understanding of whatever information they do process remain

unaffected? 1s this even possible? In discussing information overload, one needs to consider what it is that is overloaded. There must be a distinction between tenns such as 'data', 'information', and laiowledge'. As Wuman (1989, p. 37) suggests, "the word 'information'


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has always been an ambiguous term, wantonly applied to define a variety of concepts." Some authon have contemplated definitions of such terms; again, as in other areas of

this literature, readers find variations (see Birkerts, 1996; Heindl, 1998; Reeves, 1996; and

Wurrnan, 1989). It is not the goal here to delve into an analysis of epistemological terms, but for the purposes of this discussion, the following distinctions between the terms data', 'infonnation', and 'knowledge' are adopted: 'Data' are the individual pieces of information that can stand alone (e.g., words). Although each data piece is meaningful, they do not communicate any particular message on their own as disjointed or Eagrnented units. 'Information' is a collection of data that communicates a message or tells a story, but not a personal story (e.g., an arrangement of words, phrases or sentences). 'Information' is 'data' with context and rneaning derived fiom the juxtaposition of 'data'. 'Knowledge' is a collection of 'data' and 'information' items. It is also one's understanding of 'data' and 'infomation', such that one can tell a story in one's own terrns, using expenence and familiarity with data and infomation, and adding this to one's current knowledge base. It is not accurate to assume that 'infomation' is simply the summation of 'data', or that 'knowledge' is simply the summation of 'data', 'infonnation', experience and understanding. The issues here are much more complicated han this; entire fields of study are dedicated to understanding these tems much more thoroughly than is possible in this discussion. However, it is ceasonable for our purposes here to assume that a 'data' count (or a word count) is a good indicator or estimate of 'infonnation', since one would expect that, generally, more text probably contains more infonnation. One can imagine that measuring absolute quantities of context ami meaning is difficult, and without getting into issues of the reliability

and validity of testing, it would be even more difficult to measure an absolute quantity of


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'know ledge'. Given the variety of contexts and meanings of information overload, understanding at what point there is overload is important. In clarifjmg such (informational) t e n s as those presented above, and making clear what it is that is overloaded, one inherently clarifies a definition of idonnation overload. For example, the issue of information overload could be one of too much 'data' such that one cannot synthesis and process the 'information' and then assimilate it into one's knowledge base, to consmict some meaning, understanding or new 'knowledge'. Lucky (1997) suggests that a 'right' amount of information exists, but certainly the issue is much more complicated than simply considering the absolute amount of information with which one is presented. Exposure to information does not necessarily guarantee that one will attend to it or process it; simply ignoring ii is possible. It seems that what is equally important, if not more important, is what happens to the information afier it is presented, that is, once it is attended to and processed and presumably progressing from 'information' to 'knowledge'. With such analyses, one may reveal important findings regarding the effects of information overload. This leads to the next question: Where does information overload occur?

1.2 Where does information overload occur? Current technology clearly provides the means for acquiring greater arnounts of information with more efficiency than ever before. Whether the information is coming From the Intemet, CMC environments or other technologies, the consensus is that information is more readily available and more quickiy accessible (Hiltz, 1986). Given this, usen still need to process that information and are likely unable to process it any quicker. Technologies are


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advancing in this respect, not humans. How do students of CMC courses assimilate on-line information? They must acquire and structure information, and mentally process material while physically engaghg in the creation of their own leaming (Jib and Reeves 1992). Students in CMC courses must try to process what they read on-line (Le., both classrnates' posted messages and course readings); they must also think up their own ideas and post messages in response to others' messages. When one considers the capacity of the human mental processing system, CMC students have a rather great assignment on their hands (or better yet, their minds!). The previous discussion regarding the various levels of informational ternis illustrates that there are a number of places in Our infonnation processing system where overload can have an effect. This c m be at the point of input where 'data' are presented and when sensation and perception occur. This could also take place during processing and storage where 'information' is spthesized and possibly assimilated into existing or new 'knowledge'. Altematively, the effects of information overload can occur during retrieval, that is, at the point of information output, where presumably 'knowledge' cornes into play. The initial stages ofmemory are very limited in capacity. For exarnple, Miller (1956) found that working memory has a capacity ofseven 'chunks' of infonnation, plus or minus two khunks'. Our long term memory seems limitless, but as memory retrieval theorists suggest, if retrieval is to be successful, the retrieval cues must have a good match to cues used during the early stages of memory when encoding of information takes place (Tulving

and Osler, 1968; Tulving and Thomson, 1973). Thus, with limited working rnemory capacity, CMC students may have difficulty assimilating the various elements of information concurrently available to them (Sweller and Chandler, 1994). It may also be that if the


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information is not well encoded and put into context initially, then retrieval at a later time may be very difficult. As Shenk (1997, p. 20) states, "Memory is stored according to specific cues -contexts within which the infonnation is experienced. When the contexts begin to vanish in a sea of data, it becomes more difficult to remember any single piece of it. The more we know, the less we know." As Fournier (1996) suggests, it seems that the effects of information overload can occur anywhere along the infomation processing system, that is, at input, encoding, or retrieval.

1.3 Why does information overload occur? The discussion above not only suggests where information overload occurs but it also suggests that it occurs because one's capacity to process information is limited and that taxing the system beyond its limits will lead to overload. Given this, what other factors erist that might affect one's ability to process information, and thus cause one to feel overloaded? When considering the use of CMC technologies in education, there are two types of factors one must consider: human factors and computer factors. Both will affect one's ability to

manage information either as mutually exclusive influences, or as cornbined, interactive influences.

1.3.1 Human Factors: The incidence of information overload can be influenced by (a lack of) certain individual charactenstics and behavioun. Individuals who lack the technical skills required to participate in on-line environments may be more susceptible to experiencing infonnation overload than those who possess such skills (Althaus, 1997; Hiltz and Turoff, 1985; Latting, 1994; Stratulat, 1998). Anxiety and feelings associated with 'computer phobias' have also


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been atûibuted to the experience of information overload (Ahhaus, 1997; Fournier, 1996; Latting, 1994). CMC users that are uncornfortable working in such environrnents are certainly at a greater disadvantage unless they overcome such feelings.

In addition to how usen of CMC technologies feel about working in such environments, their level of expenence will affect their ability to manage information. It is more Iikely that novice users expenence information overload more often than experienced users because novices have to l e m simultaneously how to use the technology and the course material that is delivered through this medium (Burge, 1994; Hiltz, 1986). The experienced user needs to focus only on the to-be-Iearned material. Finally, poor instmctor facilitation is bound to cause people to experience information overload (Kimball, 1995; Hiltz and Turoff, 1985). Students need to understand the purpose of a particular course and the expectations for participation in the course. Through periodic feedback, lcnowing whether the quality of their participation is meeting the goals of the coune and the expectations of the instructor is helpful for users (Kimball, 1995). If this online facilitation is unavailable, then students are likely to become confused and mistrated (Althaus, 1997). 1.3.2 Com~uterFactors:

Only a few computer factors that may contribute to one's experience of information overload are considered here, since the following section discusses which factors can help with the management of infonnation overload, thus suggesting sorne of its causes. There is a wide body of literature investigating the issue of reading electronic text and comparing the differences of reading from paper venus screens. As with the infonnation overload literature, there are many discrepancies here. Some investigaton suggest that reading from a


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computer screen is more difficult and time consuming than reading from paper, while others report that there are few differences, for example, in speed, and that reading fiom a computer screen may be more efficient and preferred to paper. Most researchers agree that reading fiom a screen is very different to reading from paper and there are a number of factors one needs consider in such cornparisons (e.g., type of reading: skimming or deep-processing, screen size, resolution, font size, distance of matenal fiom eyes, lighting conditions, etc.,). (See Dillion, 1992; Muter and Maunino, 1991, and O'Hara and Sellen, 1997 and works ci ted in these for a comprehensive review of this literature.) Much of the literature companng face-to-face discussions with CMC discussions makes the point that because CMC discourse occurs over a computer, it lacks certain nonverbal cues that are inherent in face-to-face discourse (e.g., cues such as body ianguage, voice inflection and social presence). Some authors would argue that a lack of such cues is a positive feature of computer discourse, since participants can concentrate on the task rather than being distracted by possibly irrelevant cues (Hiltz and Wellman, 1997; Tracz, 1980). Other authon argue that these missing cues are necessary and that the discourse lacks pertinent information when such cues are lacking (Feenberg, 1989; Harasim, 1987; Walker and Hackrnan, 1992). Since students oflen cornplain of infornation overload in CMC courses, the lack of such cues may play a significant role in one's perception of information overload. It seems reasonable that cues are not meant to detract one from a particular task; rather, they are meant to provide useful information so that the status of a conversation can be interpreted (e.g., agreement or disagreement by nodding or shaking one's head; approvai or disapproval by smilhg or fiowning; perplexed facial expressions versus ones that communicate comprehension). Usea of CMC technologies may have to exert extra


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cognitive effort to fill-in the missing infonnation that they do not see. This extra effort due to less information might translate to more (cognitive) overload because more processing is required as one tries to determine the status of the communication without any cues. Face-to-face discourse is clearly very different from CMC discourse. That CMC discourse takes place on a computer makes this a computer factor. One's communication is limited (or enhanced) by the medium. Spoken discourse is spontaneous and transient, where

CMC discourse is planned and recorded to a database (Thimbleby 1996). People usually think about what they are going to write before writing it; this is not necessarily so in speech. One cm imagine exarnples of blurting something before thinking about it and later wishing one had exercised more thought before speaking. Most people might agree that saying something is often easier than writing it and that it often takes longer to write something than it would to Say it. It is possible that because of this, working in a text-based environment leaves one with the illusion that there is more infonnation recorded in a CMC meeting than there is information spoken in a face-to-face meeting. Feenberg (1989) makes the opposite point and staies that writing something is ofien easier than saying it, especially for a speech or presentation where one must organize and plan a strategy. There are many possibilities for why information overload OCCLUS. Why and how it affects people depends on individual needs, characteristics, abilities and preferences of how information is received and processed. The following section considers what one can do to manage information overload.

1.4 How can one manage information overload? When focusing on the management of information, one needs to consider various


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factors. First, one needs to consider that there are issues of 'sifting' through information or 'filtering' of information ('data', 'knowledge', etc., ). Second, as in the section above, one must consider the involvement of both computer factors and human factors when discussing issues of si&g or filtering of information. Much of the literature tends to focus on one or the other; of these, most concentrate on the computer side of the issue, while few concentrate on both factors.

1Al C o m ~ter u factors: Considering previously mentioned differences in the literature of information overload, one should not be surpnsed to leam that while some researchers maintain that the technology is the main cause of information management problems (e.g., Noyes and Thomas, 1995, claim that the Intemet is poorly organized and simply adds to the user's burden), others

suggest that the technology is the solution to the problem (e.g., Etzel, 1995). Many researches have investigated how novel features of CMC environments and Other technologies can assist usea with organizing information so that later use of information is optimized. Historically, these technologies have been primarily text-based, but recently, sorne investigators have found, for example, that the use of non-speech sounds provides extra auditory feedback, providing the user with information regarding place and direction of the information, thus reducing one's workload (Brewster, 1997; Faber, 1994). Others have investigated the use of intelligent agents and have found that this development provides users with a sort of (computerized) persona1 assistant whose main task is to search for relevant information amongst huge amounts ùf imlevant information. This style of human-cornputer interaction is drarnatically changed from usual interactions, and agents Save users hours of


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wasted filtering time, thus reducing infonnation overload (Maes. 1994). Navigational features are also considered, specifically the use of hypertext to reduce one's processing load by organizing material for the user. Haavind (1990) reminds us that hypertext relies on the most basic human act, that is, pointing to what one wants. This is indeed a very good point! (Pm intended!) Though, as Stanton and Baber (1992) caution, hypertext done badly or poor navigation design could disorient users, causing them to feel lost and fmstrated, thus increasing their cognitive burden instead of decreasing it. The efficacy of hypertext as a tool to help reduce information overload is yet unclear. McEneaney (1998) provides empirical evidence that readers in this study found hypertext environments more cognitively demanding. Oostendorp and Nimwegen (1998)argue that how information is structured in a hypertext environment (e.g., whether links are visible on a

single screen or whether users must scroll to find links) influences the speed with which users find information and also influences users' recognition of the information. These authors argue that scrolling to find infonnation in hypertext environments takes extra time and extra cognitive resources, which in hm,leads to lower recognition of the information. Hiltz (1986) suggests the development of graphical functions that would enable CMC environments functions for reducing information overload in educational settings that are analogous to using a blackboard. Lohse (1997) also argues for the use of graphs and coloun to reduce one's cognitive load. This author comments that the use of graphs and colours helps users in forming perceptual groups of infonnation that facilitate 'chunking'. This is consistent with Miller's (1956) idea that chunks may consist of many bits of related information, thus increasing the capacity of working mernory. A cornmon denominator in alî of the above suggestions is that a reduction in a user's


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effon results fiom shifting some cognitive demands to other perceptual systems that more traditional. text-based systems did not tax. Basically, these provide organizational strategies for the user, thus fieeing up the user's resources for other tasks.

1.4.2 Human Factors: As discussed earlier, user resources are a critical piece of the information overload

puzzle. Some authors have addressed the importance of understanding human cognition to understand information overload. For example, Sweller and Chandler (1994) discuss how schema (Le., mental representations of categories of information) reduce cognitive loads. This is analogous to the concept of perceptual grouping discussed above, and this is also consistent with Miller's (1956) idca of chunks of information. Schema also facilitate 'chunking' such that one can organize many bits of related information into meaningful categories, thus increasing one's capacity of working memory. Where perceptual grouping facilitates at a physical stimulus (or 'data') level, schema facilitate at a mental processing (or 'knowledge') level. Harasim (1987) discusses strategies that CMC users l e m as they become more expenenced with the technology. This author found that participants in the study developed coping strategies such as reading selectively by scanning posted messages, and cornmenthg more selectively to other students' messages. The issue of participant experience is an important one for understanding information overload, at least in a CMC and education setting. Hiltz and Turoff (1985) found that novice CMC students reported trying to read everything for fear of missing something important. As mentioned previously, experience or familiarity is helpful in managing information overload. Wilson and Whitelock (1995) have c o n f h e d this in their study. One other strategy presented by Wilson (1996) is to divide user

information Overload

16

resources, not individual resources, but team or group resowces. As this author states: "a group of worken c m easily do what a single individual would find impossible." (p. 194). Although much of the research concentrates on information filtenng features of cornputers, considering the cognitive f i l t e ~ systems g of humans is very important. Generally, human needs and capacities are what guide the design of technology, and the goal should be to develop cornputer designs that adapt to human needs. Unfortunately, there are many examples of how designers have failed in this respect, where their focus shified fiom 'cm people use the system' to 'can the systern to the job'(Spectrum Staff, 1987; Thimbleby, 1996). Such products tend to have design features that do not suit our needs and to which we

eventually have to adapt (Thirnbleby, 1996). Histoncally, this approach has not succeeded and tums out to be a very expensive one (Spectrum Staff, 1987). Also, in Hiltz and Turoffs

(1985) summary of how CMC environrnents should be sinictured to avoid information overload, such design features clearly need to be flexible for individual needs and preferences, if successful and valuable communications are to take place. If the discipline's goal is genuinely to configure technology features that facilitate usen' processing of information (rather than forcing the user to fit the system), then it seems that hurnan filtering processes are a focal area for more research.

1.5 How does one know when information overload is occurring and how does one respond to it?

Unlike an electrical box that short circuits when overloaded, there are no observable, ovect, indicators of when a human is overloaded. Many investigaton have cited characteristic feelings and cornplaints of CMC usen when they feel overloaded, for example,


17

feeling ovewhelmed (Etzel, 1995), stressed (Hiltz and Turoff, 1W),Iost (Stanton and Baber, 1992) anxious, depressed, confùsed, and unable to be attentive (Fournier, 1996). None of these authors reported how respondents understood these terms, but in one study, the author predicted that participants were not weighting these ternis in any clinical sense (Fournier, 1996). Stanley and Clipsham (1997) cite an intemationai survey that characterizes the occurrence of information overload quite well. The report suggested that overloaded employees have emotional and physical problems both at work and at home, report greater loss of job satisfaction, increased tension with work colleagues, and a poorer persona1 and social life outside work. Also, many of their respondents reported a slowing down of the decision making process because of information overload. Although these authors are refemng to the work place, there are obvious implications for the education place. The literature is discouraging at times; apparently information overload is constantly affecting many users of CMC technologies. As mentioned previously, one of the most senous cornplaints often reported by students enrolled in CMC courses is that they feel overloaded by the endtess amount of information that seems to be associated with such courses. This, coupled with al1 of the negative connotations associated with infoxmation overload and CMC should have some readers wondenng why instructors, software developers, and technology experts bother using such technologies in education. As the old adage goes: "if it aidt broke, don't fix it!". Nevertheless, there must be some positive prospects to CMC in education, such that students can reap benefits of the wealth of information avaiIable to them. The next section describes.what CMC classes 'look' like or what factors one aeeds to evaluate for their design, and considers the benefits of such classes.


18

1.6 What do CMC classes look like and what are the benefits o f such classes?

CMC technologies have been available for more than thirty years but it has only been since the late 70's that such technologies were used in classrooms (Althaus, 1997). There is a hodgepodge of possibilities for CMC classes. The nature of any particular CMC class and the direction it takes depends on a number of factors, such as, how the class is designed; what the class requirements and expectations are; who participates and how many people participate in the course. There are necessary, key elements that define these factors: elements such as effective instnictors or facilitators; keen students; dynamic communication; efficient technology; and pedagogical objectives. Ultimately, for a successfûl CMC class, a culture must be developed much Iike one finds in the traditional face-to-face class. How this development proceeds hinges on the successful implementation of these key elements. 1.6.1 Class Elements:

Basically, CMC in education represents electronic (on-line) interactivity between teachers and students (Leonard, 1996). These interactions can be one-to-one, one-to-many,

or many-to-many (Harasim, 1987). CMC interactions do not require that students and instmctors be physically in one place; however, on-line communication rnay be either synchronous (which is dependent on students and instnictors being available to communicate at the sarne tirne) or, more comrnonly, on-line communication may be asynchronous (which does not require that discussions occur at the same tirne). Also, CMC courses may be held entirely on-line, (e.g., see Everetts, 1998, and Harasim, 1987), or alternatively, CMC courses may be supplemented with face-to-face communications (e.g., see Althaus, 1997, and

Leonard, 1996). Although it was mentioned earlier that CMC connects spatially separated individuals who othexwise may not have the oppomuiity to meet in a face-to-face setting,


19

CMC courses often have both an on-line component and a face-to-face component. CMC allows students to engage in new forms of communication that are unlike any face-to- face conversations, and as Feenberg (1989), Leonard (1 996), Scardamalia and Bereiter (1 996), and Scardamalia et. al. (1989) suggest, a successful CMC class is not one in which students work independently or in isolation; it is one in which students are active participants and collaborators, sharing in each others' knowledge. There are a variety of technologies that one can use for a CMC class. Some use conferencing software (e.g., see Feenberg, 1989; Scardamalia and Bereiter, 1996), while others use bulletin boards, electronic mail, group electronic mail (Le., LISTSERV),and course home pages (Althaus, 1997; Everetts, 1998; Harasim, 1987; Leonard, 1996). The technology is the backbone of a CMC course; it is what binds the class culture. It must be carefully selected as there are a number of circumstances that can affect users' applications of the technology, (e.g., how easy it is to use). If the technology is too complicated and difficult to use, then users may become mistrated to the point where it is not worth participating. Accessibility is another concem (Althaus, 1997; Hiltz, 1986; and Tracz, 1980). If users have difficulty accessing the technology, then this will most definitely fnistrate users and cause unnecessary anxiety. As in face-to-face classes, and as one mi@ expect, CMC classes Vary with respect to

the philosophies of education. The pedagogical objectives set out at the begiming of a

course will help define the characteristics of the classes. Some course designers may opt for pure exploratory leaming, while others will go the more traditional route and merely disseminate knowledge by giving students information (Leonard, 1996). Course requirements differ depending on the objectives of a particular course. Some courses may


20

require students to post assignmmts on-line for peer review, others may require that students post a minimum number of posts per week, etc., (for some exarnples see Althaus, 1997; Burge, 1994; Hiltz and Wellman, 1997; Latting, 1994; Leonard, 1996; and Wiesenberg and Hutton, 1996). Each element described above cari blend in a variety of ways to create exciting and challenging CMC classes. The combinations and possibilities are great. Readers rnay consult Everetts (1998) and Harasim (1987) for examples and detailed descriptions of classes conducted entirely on-line, or consult Althaus (1997) and Leonard (1996) for examples and detailed descriptions of courses held on-line and supplemented with face-to-face meetings. For fiirther discussion regarding the key elements of CMC classes, readers rnay consult Feenberg (1989).

1.6.2 Benefits: One of the most obvious benefits of the use of CMC in education is convenience. Snidents do not have to leave their offices or homes to get an education from accredited universities or institutions. Its use grants individuals who live in geographically remote areas the opportunity to study from just about any location; their basic requirement is the

technology to be c o ~ e c t e dto leaming comrnunities. Without gettins into issues of cost, often a phone line and personal cornputer with appropnate Internet browser software are the minimum requirements. The least obvious benefit, but perhaps the most important, is the type of training, critical thinking and problem solving skilis that such environments nurture. Constructivist learning theorists argue that CMC systems advance knowledge construction and learning in a manner consistent with that of the 'real world' and 'expert cornrnunities', where the focus is on


21

collaboration, intentional leaming and progressive inquiry (Jonassen et. al., 1995; Perkins, 1992; Scardamaiia & Bereiter, 1993). Since the on-line communication is preserved on a computer database, students are encouraged to engage in academic activities such as revisiting ideas, reworking and editing their contributions to the database, and reviewing their peenl contributions (activities that are not as readily available or encouraged in face-to-face discourse). These theorists also argue that such CMC environments facilitate 'knowledge building' rather than 'knowledge reproduction' or 'transmission' (Scardamalia & Bereiter, 1993); the focus is shifted From teaching to leaming, and from instructional goals to facilitative environments (Collins, 1996). Bnefly, as McLean (1997, p. 1) explains: "The 'knowledge building1philosophy holds that leaming is an intentional and collaborative activity that mimics the way in which knowledge is developed in cornmunities of expert learners. It is charactenzed by a progressive construction and refinement of explicit expressions of current understanding. The refinement of understanding is a group activity and responsibility, and ideas are openly expressed, elaborated, cntiqued, modified and refined by ail. There is an explicit, intentional focus on the probiem that is to be understood."

It is of utmost importance to determine what variables might negatively impact students' leaming when using CMC technologies and then correct these whenever possible. As King (1995) reminds us, the positive effects of the advances in technology far out weigh the negative ones, and CMC researchers show that such technologies advance learning and performance of students using CMC in education (Aithaus, 1997; Everetts, 1998; Hiltz, 1986; Hiltz and Wellman, 1997; Scardamalia et. al., 1992).

During a time in which there is national concern about the effectiveness of our

Tnfonnation Overload

22

schools and the failure of students developing competent problem-solving and critical thinking skills, considering refocusing our insûuctional strategies is important (Cognition

and Technology Group, 1992; Scardamalia and Bereiter, 1996). CMC environments may lay the foundation for this necessary rethinking of schooling, but the discussion of educational reform will be reserved for another venue, and we will continue with the problem at hand: infornation overload in CMC and education.


23

II. Problem under investigation Students ngistered in CMC courses often cornplain about information overload, and

as reviewed above, many researchers believe (and report) that it does exist. Across disciplines there exists a plethora of information created, or at least made readily available, by the continued development of computer technology, applications and the Intemet. This

seems obvious for some domains but it does not seem so obvious for others. For example, there is no doubt that there is more information presented in newspapen today than there was 60 years ago. It is also obvious that the rapid growth and expansion of the Intemet translate

to more information. Yet it is not so clear that CMC classes in education present more information to students than do traditional face-to-face classes. To date, there is no research that the author knows of where investigators have empirically measured whether students in CMC courses are really presented with more information compared with students in face-to-face courses, or whether students in CMC courses merely perceive more infonnation compared with students in face-to-face courses. It may be that, in reality, students in CMC courses do not encounter more information than students in face-to-face courses. Perhaps other variables are present in CMC environrnents that leave students with the impression that they are presented with too much information to process (or that they are simply presented with more information than in traditional face-toface classes). Hiltz et. al., (1986) compared communication processes and outcornes in face-to-face classes and CMC classes. They compared these two modes of class communication on a number of variables including amount of information, quality of group decisions, and the likelihood of reaching agreement before task-time expired. Briefly, among other


24

expectations, they predicted that there would be less communication in the CMC groups and that typing would decrease the amount of communication. Although the authors state that they took absolute measures of information, they held task-time constant across both modes of communication (Le., CMC and face-to-face). This confounds their 'absolute' measure of information. The inherent problem with this design is that if it takes three-times longer to wn'te something than it does to Say it, then it is understandable that there will be less communication in the typewritten environment. Observing the environment in this manner seems unnatural. To measure the amount of information in a CMC environment, one would have to allow a reasonable amount of time for completion of the task, comparable to the amount of time required for completion of the task. One unique characteristic of on-line discussions is that it is fiee of time limits and is self-paced (Althaus, 1997). Hiltz et. al., (1986) were comparing the arnount of communication that transpires within the same arnount

of time in face-to-face and CMC communications. This is not the goal of the present study; this study will focus on the amount of information students receive in an entire course. This

is the context in which instructors hear students' complaints of overload. Students do not complain of an instance of overload, they ofien argue that CMC courses, in generai, have more information, require more effort and work, and cause them to feel overloaded. In this study, a CMC course supplemented with face-to-face meetings is considered.

2.1 Purpose:

The purpose of this study is to investigate the problem of real versus perceived infbrmation overload. The first question to be addressed empirically is: Do students enrolled in CMC courses receive more information (measured in words) than students enrolled in


25

face-to-face courses, or do students enrolled in CMC courses merely perceive more infonnation?' Second, if studmts of CMC courses are not presented with significantly more information, then what other variables exist that might confound students' perceptions of the amount of information received in various modes of presentation (i.e., CMC versus face-toface)? Since information overload has a variety of definitions, no precise definition is offered at this tirne. Rather, the conventional assurnption that 'information overload' is caused by an excess of information will guide this discussion. The findings presented later and the issues considered should advance a clearer notion of what is infonnation overload.

2.2 Hypotheses:

Hypothesis 1: It is hypothesized that students in CMC classes do not receive more information than students in face-to-face classes, and that students in face-to-face classes probably receive more information.' It is M e r hypothesized (Hypotheses 2 to 1 1 below) that there exist other variables that result in the misconception of the actual amount of information presented in CMC courses. The author suspects that such variables demand

'

Given the distinction between 'data' and 'information' discussed earlier, a count of individual words corresponds to a measure of data and perhaps not information per se. A quantitative measure of idormation is difficult since, as discussed previously, it is difficult to measure absolute quantities of context and meaning. It is assumed for the purposes of this research that a data count roughly corresponds to an information count since one can expect that more text probably contains more infonnation. This is excluding reading assignments above and beyond class discussions, whether online or face-to-face, that is, information related either only to the on-line or only the face-to-face component of the course is considered, but not information that would be present in both (e.g., both groups would be exposed to extra handouts or readings that might be discussed in class or on-line). The focus is on the face-to-face tasks venus the on-line tasks that students encounter in courses.


26

more effort on the student's part, than variables evident ih face-to-face environments. This increase in effort rnay be misconceived as an increase in the absolute amount of information presented, which in hün, may lead to the perception and feeling of information overload.

The following are a priori hypotheses about the variables that the author predicts will have significant associations with the perception of information overload:

Hypothesis 2: Participants who typically read everything in the CMC environment will estirnate that they spend more time on the on-line component of the course than thefaceto-face component, that the on-line component of the course requires more effort than the face-to-face, and that they find they have too much infonnation to work with on-line.

Hypothesis 3: Participants who report spending more time on the on-line component of the course compared to the face-to-face component will also report that they typically edit the work they do on-line, and find that they have too much information to work with on-line.

Hypothesis 4: Participants who report that reading from a computer monitor is difficult will also report that reading other students' contributions to the database requires more effort than submitting contributions themselves, and that they typically pnnt on-line documents to read them in paper format.

Hypothesis 5: Participants who report that the CMC cornponent requires more effort than the face-to-face component will also report that they participate very often, for many hours, typically edit the work they do on-line, find that they have too much information to work with on-line, and find that it involves a lot more work than the face-to-face component.

Hypothesis 6: Participants who report balancing their participation throughout the week (instead of concentrating their participation to one or two sessions) will report that the on-line component of the course requires the same or less effort than the face-to-face


27

component. Hypothesis 7: Participants who report easy access to computea will report that the on-line component of the course requires the sarne or less effort than the face-to-face component, and they will find that they have too much information to work with on-line. Hypothesis 8: Participants who report that they typically edit the work they do online will find that they have too much information to work with on-line and that it involves a lot more work than the face-to-face component. Hypothesis 9: Participants for whom English is not their first Ianguage will report that reading other students' contributions to the database requires more effort than submitting contributions themselves. It might be that they find it more difficult to read English text than

if they read text presented in their first language, or that they read more slowly and find it more difficult to keep up with a steady stream of text-based discussion than participants for whom English is their fint language. Hypothesis 10: Participants who have not had keyboard training will report that submitting contributions to the database requires more effort than reading other student's contributions. Altematively, participants who have had keyboard training will report the opposite. Hypothesis 1 1 : Participants who report that they have good or great typing skills will

also report that the on-line component does not require more effort, that they participate oRen but for relatively fewer hours than othen, and that they do not find that they have too much information to work with on-line.

Monnation Overload

28

m. Method 3.1 Participants Twenty-five masters and doctoral degree candidates at the Ontario Institute for Studies in Education of the University of Toronto (OISEAJT), who were enrolled in an introductory computer applications in education course, were invited to participate in this study. Participation simply required students to complete a questionnaire and students' consent to allow the author to observe their participation in the course activities. For example, this particular course had both an on-line component and face-to-face component which students were required to actively participate in for course credit. The on-line component consisted of a computer conferencing database where students were required to engage in group discussions about various coune topics by contributing notes to the database. The face-to-face component consisted of traditional classes with group discussions and some lecturing. Participants varied in their experience with CMC technologies and on

the b a i s of the course instnictor's ranking, participants were ranked as either novice (n=19) or expert ( n a ) .

3.2 Procedure and Materials

The study consisted of three basic components. First, six face-to-face group discussions, ranging fiom hventy-five to forty minutes, were tape recorded to measure an average word count of 'an average' face-to-face class meeting. The taped recordings were taken during a class in which students were asked to discuss a problem assigned by the course instructor. Students were given a list of tasks that they were required to first work on

in small groups of four to five students, and then they were required to report on theu


29

discussions to the whole class. (See Appendix A for a detailed description of the face-toface, group discussion assignment$ Second, the on-line component of the course (Le., the class database where the on-line discussions were recorded electronically) was analyzed to measure how many words were in the database. The course requirements for these students are shilar to the requirements of other courses cited in the literature (e.g., see Burge, 1994; Althaus, 1997; Leonard, 1996;

Everetts, 1998; Harasim, 1987), therefore it is assumed that the database of the on-line discussion for this sample presurnably presents 'average' or 'typical' on-Iine discoune. Third, at the end of the terni, the author administered a twenty-three-item questionnaire regarding students' perceptions of their activities in the course and their perceptions of the effort required to participate in the course. For example, students were asked if they typically read al1 of the readings in the database in any given week; how many hours they typically spent on-line in any given week; and if they believed that the on-line or the face-to-face component of the course required more effort. There were also questions exploring students on-line behaviours (e.g., if they typically pnnted on-line documents so as to read them in paper fomat), and a couple of demographic and skill type questions, such as,

if English was their fini language and how they would rate their typing skills. (See Appendix B for the complete questionnaire.) Throughout this study, participants were not entirely aware of exactly what the author

' The course instructor ofien administered this sort of assignment to students, but he usually divided the class into srnaller groups within the classroom. Since the author required a rather quite environment so that each tape recording would be ffee of background noise, the instructor facilitated the experimental episode and sent students to separate classroorns. Thus, this was a typical event for this particular c l w , just that for this assignent, the class discussions were held in six different classrooms. It was not the case that the taped recordings represented an unusual face-to-face meeting, rather they represented a valid condition.


30

was investigating. The author attended one of the face-to-face class meetings to invite students to participate in the study and required infonned consent fkom each participant. Participation in this study was voiuntary and students were assured of their anonymity and of the confidentiality of the results. Students were initially told that the purpose of the study was simply to measure the amount of information conveyed in different media of instruction

(i.e., CMC versus face-to-face). (See Appendix C for a copy of the Participant Consent

Form.) They were not told that the author was also exploring variables that might influence the way in which the participants perceived the course information. Nor were they told that the study was about information overload in CMC and education until the study was completed, at which point participants were debriefed about the exact nature of the study. (See Appendix D for the Ethical Review Form and see Appendix E for the Debriefing Form.)

3.3 Analysis 3.3.1 Word count data:

The taped recordings of the face-to-face discussions were transcribed to a word processing computer software package and a total word count was obtained nom the resulting text file. The total word counts were then averaged to words per minute and the averaged word count per minute was extrapolated to derive an average, total word count for the entire face-to-face component of the course. One tape cassette was entirely defective and was not included in the analysis. Another tape cassette was also defective but seven minutes

of the discussion were transcribed and included in the analysis. Since the on-line database discussions were in text format, a total word count for the entire on-line component was obtained by simply importing the database into a word processing computer software package.


31

3.3.2 Questionnaire data:

The first three questions of the questionnaire were open-ended. The first asked participants what they found most hstrating about using the on-line conferencing s o h a r e used in the course. The second asked participants what they found most effortless about using the on-line conferencing software. The third question asked what they found took the most time when they were engaged in on-line interactions. Responses were grouped into 1 1 categories that ernerged fiom participants' responses and the fiequencies of these responses

are reported. A one-sarnple Kolmogorov-Smirnov test was conducted to determine normality of the

variables. The test revealed that only three of the questionnaire items were normally distributed, thus, nonpararnetric tests of association were conducted to evaluate the degree to which the questionnaire data were related. Kendall's tau-b test was conducted since it allows for directional, one-tailed tests of the a priori hypotheses. Also, this test of association calculates concordances and discordances, and corrects for any ties in the data. Linear transformations were performed on variables with negative value response scales, but this was found to have no difference on the Kendall's tau-b tests of association. Because of the sarnple size, chi-square analyses were not conducted on the nominal data with binary categories since no more than 20% of the cells can have an expected frequency of less than 5 (see Appendix B, questions with 'yes'Pnot response scales and twopoint scales, that is, questions 4,6,7,9, 17, 19, and 21). Given the relatively small sarnple size (n = 17). and given that these are 2 x 2 analyses, one ce11 with an expected frequency of less than 5 is above the minium 20% (Le., 1 of 4 cells, or 25%). Rather, Fisher's exact test was conducted on these data, therefore reducing Type4 errors.


32

IV. Results The average word counts are presented in Table 1. There is no variance in the faceto-face word count data since the total average word count is an extrapolatecl estimate, therefore, no empirical tests were conducted on these data. It is adequate to Say, qualitatively, that there is more information presented in the face-to-face component of this course compared with the on-line component (Hypothesis 1: that is, 176,386words presented in the face-to-face component versus l24,62 1 words presented in on-line component, with a difference of 5 1,765 words). Eighteen participants completed the questionnaire regarding students' perceptions of their activities in the course and their perceptions of the effort required to participate in the course. One participant's record had too many missing data (52% of the questionnaire was incomplete) and therefore this participant's data were dropped fiom the analyses. Table 2 presents the 11 emergent categories derived fkom the fint 3 open-ended questions and the respective fiequencies. Bnefly, the most kequently reported hstration related to 'waiting for the computer system'. Fi@-three percent of the sample expressed their lack of patience and resulting hstration with the long connection and loading time of the database, especially when the server was down or during peak traffic times in the day when c o ~ e c t i o a to s the server were slow. Participants were l e s t fiustrated by the unavailability of resources such as gaining access to a computer. It seemed that for this sample, resources were generally available; only 6% reported that access was a problem. They were also least fiustrated by the lack of certain

CMC software features that they thought would be usehil (e.g., spell-checker). Again, only 6% reported this problem. hterestingly, 18% of the sample reported fnistration with CMC


33

Table 1. Word counts of face-to-face recordines and on-line database

Face-to-face

Total words

Time

Average words per minute

Tape 1

6505

40 minutes

162.63

Tape 2

5888

36 minutes

163.56

Tape 4

6509

40 minutes

162.73

Tape 5

4060

25 minutes

162.40

Tape 6

1157

7 minutes

165.29

(Total average words per minute) 163.32

(Total words for entire face-to-face componentt)

176,385.6

(Total words for entire online component$)

l24,621

@ifference between total face-to-face component and total on-line component)

5 1,765

as calculated fkom the face-to-face recordings $ as calculated from the online database


34

Table 2. R ~ S D O Dfreauencies S~ (%)i for catenories derived from o~en-endedauestionnaire items

Item 1: What was most hstrating about using CMC?

Item 2: What was most effortless about using CMC?

Item 3: What took the most time in using CMC?

positive software features

0%

0%

negative software features

18%

OO/o

lack of software features

6%

0%

waiting for system to connect and load

53%

47%

waiting for others to respond

18%

6%

CMC tasks

18%

47%

0%

18%

revisiting or finding something

18%

6%

logging ont0 system

0%

0%

unavailability of resources

6%

0%

availability of resources

0%

0%


35

type tasks, such as, reading, writing, and responding to others' contributions, and 47% of the sample reported that such CMC tasks took the most arnount of time when interacting on-line. Almost half the sarnple (47%) reported that the existing CMC software features were easy to use and thus made using the software quite effortless, but only 18% reported that getting ont0 the system was effortless. Six percent of the sarnple reported that persona1 skills such as one's ability to type, share ideas on-line, and engage in on-line social behavioun such as giving fellow classrnates reinforcement and encouragement were effortless, and only 18% of the sample reported that such persona1 skills took the most amount of time when they interacted on-line. Consistent with what participants found most mistrating about using the

CMC software (Le., waiting for the computer system), 47% of the sarnple reported that waiting for the system to connect and load took the most arnount of time when they were online. Appendix F presents frequency distributions for the remainder of the questionnaire data, however, some of the most interesting findings are presented here. Fifty-eight percent of the sample reported to have, typically, in any given week, read al1 of the notes in the entire database; though an analysis of the database revealed that the average percentage of notes read by each student was only 24%.4 Surprisingly, 100% of the sample reported that they spent more time (i.e., slightly more, two times more, or three times more tirne) in the on-line component of the course than

This figure is confounded by the course instructor's expectation of student participation in the database. The instmctor divided the class into groups and students were required to participate in their own group's conferences and the general class conferences. They were encouraged, but not required, to participate in other group discussions. Given this, the author is uncertain when participants respond that they "read al1 of the notes in the database", whether they are refemng to the entire database (including the other group discussions) or whether they are refemng only to the parts of the database in which they were required to participate.


36

they did in the face-to-face component of the course (e.g., see Figure 1). An analysis of the raw data of this item (Le., item 5 : "Compared to the face-to-face component of the course, how much time would you estimate that you spent on the on-line component of the course?") contrasted with the raw data of item 12 (Le., "Typically, during any given week, how many hours did you spend on the on-line component of the course, either reading and or posting?") revealed that 65% of the sample did not report consistently on these two items. Eighteen percent of this portion of the sample underestimated the houn spent on-line in item 12 when compared with their reports of the time spent on-line in item 5; while 47% of these participants overestimated the hours spent on-line in item 12 when compared with their reports of the time spent on-line in item 5 .

Participantst r e ~ o rot f time s ~ e n on t the on-line comaonent c o m ~ a r e dto the face-toface (EZfl com~onent.

information Overload

37

Consistent with the fïnding that participants believeâ they spent more time on the online component than the face-to-face component, 59% of the sample reported that they

believed that the on-line component of the course required more effort on their part, and 65% reported that they believed that the on-line component involved a lot more work than the face-to-face component; 35% reported that it involved about the same amount, and thus, no one reported that it involved a lot less work than the face-to-face component. n i e sample

was almost evenly split on what they believed required more effort in on-line interactions: either reading others' contributions or making one's own contributions to the database (i.e., 47% and 53%, respectively).

No participants reported 'always' feeling like there was too much information to work with in the on-line component of the course, but 47% reported that they 'often' felt this way and 4 1% reported that they 'sometimes' felt this way. Only 6% reported that they 'never' felt

like there was too much information to work with in the on-line component of the coune and only 6% reported that they 'rarely' felt this way. Interestingly, about two-thirds of the sample reports that they have had keyboard training and most of the participants rated their typing skills as 'good' (47%) or 'great' (29%);

as expected, very few reported any great improvements in their typing skills as a result of participating in a CMC course (13%). The results of the one-sample Kolmogorov-Smirnov tests are available in Appendix

G, illustrating which of the questionnaire items were nomally distributed. An alpha level of .O5 was used for each test. As one can readily identifjr, only three items were not statistically

significant, and thus have normal distributions (i.e., item 5: time spent on CMC component ccmpami with face-to-face component,p = .210; item 12: during any given week, nurnber of


38

hours spent on CMC component, p = .336; and item 14: how o h one felt like there was too

much information to work with in the CMC component, p = .l75). Two other items were rnarginally insignificant and were not treated as nomally disûibuted variables (i .e., item 13: average number of weekly posts, p = .095; and item 20: number of languages in which participants are fluent, p = ,088). Al1 other measuns were statistically significant, indicating that they are not normally disûibuted variables. As represented by the correlation matrix in Table 3, Kendall's tau-b tests of

association indicate many significant relations and many interesting non-significant relations between various items of the questionnaire. Some of the most interesting correlations are presented here. Surprisingly, students who reported participating fiequently on-line, also expressed that this component of the course required about the sarne effort on their part as the ~ 9.429, p = .030),or altematively, those who face-to-face component required @ = 1 7 , =

reported working infkequently on-line believed that the CMC component required more effort (Hypothesis 5). Those who reported that the CMC component required more effort indicated that they often felt like there was tao much information to work with on-line (Hypothesis 5; though this was marginally significant, but not significant: n=17,1= ,345, p = .066),and as expected, (Hypothesis 5) that they felt that the CMC component involved a lot more work than the face-to-face component (n = 17, g = .438, p = .034). Also marginally significant and

along the same theme (Hypothesis 8). is the finding that if students reported editing their contributions to the CMC system often, then they also tended to believe that the on-line portion of the course involved about the sarne amount of work that the face-to-face portion required (n = 1 6 , = ~ œ.377, p = .059).

Table 3. Correlations Amone De~endentVariables: Ouestionnaire Items

5:the on-line?

8: on-line more effort?

10: when participated pedwk? 1 I : how onen participatcd per/wk? 12: number of hours on-linc per/wk? 13: nu&r o f posts pedwk 14: too much information? 15: on-line more work? 16: participatcd from whcre? 18: edited on-line work? 20: fluent in how many languages? 22: typing skills

23: typing better after online? Correlation is significant at the -05 level (1-tailed).


40

Another interesting h d i n g was those participants who described themselves as fiequent on-line participants also indicated that they posted many notes (II= 16,r = .38 1, g = .049), that they ofien went back to edit theu contributions in the database (n = 16,1= .426, g = .032), felt that the CMC component involved about the same amount of work as the face-

to-face component involved

= 17,1= 0.449, Q = .030), and that they felt that there was too

much information to work with in the on-line component less ofien than other participants ( t ~ = 17,r= 9.379, p = ,048). Students participating h

m home maintained that they participated

(I = 16, g = .468, p = .028), posted many notes @ = 1 5 , = ~ .5 12, g = .O19),and regularly J

found that the on-line portion of the coune involved about the sarne amount of work that the face-to-face portion required (n = 1 6 , =~ 0.595, p = .O1 1). Surprisingly, several variables did not predict, significantly, participants' reports of the CMC component requiring more effort than the face-to-face component. For example, the correlation between CMC effort and the following variables were not significant: (Hypothesis 6) regular participation throughout the week (Q = 15, r = -.296, g = .122); number of hours spent on-line (n = 17, g = ,147, p = .257); number of contributions made per week (n = 16,i = 0.118, g = ,304); whether participants worked fiom home or school @ = 16, g = 4 0 3 , p = ,339); and whether participants edited their contributions (n = 16, _r = 0.039, Q =

.433). Furthemore, time spent on-line did not pndict, significantly, participants' reports of

feeling like there was too much information to work with in the on-line component of the course (Hypothesis 3). For instance, reporting how much longer one spent on-Iine compared with the face-to-face component

= 17,1= .022, p = .461) or reporting the number of hours

spent on-line per week & = 1 7 , =~ ,098, a = .33 1) was not significant. Although marginally significant was the hding that participants who reported that the CMC component involved


41

a lot more work than the face-to-face component also reported that they felt like there was too much information to work with in the on-line component of the course @ = 17, = .383, g = ,055). Additionally, those who reported that their typing skills did not improve with their

use of CMC also reported that they felt like there was too much information to work with in the on-line component of the course @ = 1 5 , = ~ -.459, p = .030). Along this same theme, the data reveal that typing ski11 does not predict any of the variables measured in the questionnaire, each correlation was not significant (Hypothesis I l ) . (Please see Table 3 for more particulars.) Fisher's exact test deterrnined a significant finding in the nominal data with binary categories. There was a general bias in the sarnple where having had training in keyboarding was related to whether English was the participant's first language @ = .006). There was also a marginally significant finding with a trend that suggests that printing on-line documents to

read in paper format rather than fiom a monitor is related to cornpetition for computer access

(E= ,082).


42

V. Discussion This study was very preliminary and exploratory in nature. It more accurately represents a case study of one graduate CMC course at OISENT than it does a comprehensive study about CMC and education h m which results can be generalized to other populations. Without replication of these data using multiple CMC courses and randomly selected samples, these data are not representative of larger populations. Nonetheless, one can infer important information from the results presented above which may guide m e r research in this discipline and indicate factors that one should consider when designing CMC courses.

The data of this sample support the first hypothesis, that is, students in CMC classes do not receive more information than students in face-to-face classes. As described earliei, this particular sample was enrolled in a course that had both a CMC component and a faceto-face component. Many of the graduate courses at OISUUT, in the area of computer applications in education, are designed to include both media. Typical of CMC courses, these students also cornplain of information overload resulting fiom the on-line components. This sample received approximately 52,000 more words in the face-to-face component than in the CMC component. Applying the same method used to extrapolate the word count data, this difference translates to approximately 5.3 hours of extra face-to-face meetings, or oneand-the-quarten more face-to-face classes, or this cm also translate to aimost 15% more face-to-face classes than CMC classes. It is interesting to note that the data from the five tape-recorded samples of face-toface group discussions were very stable across the samples (See Table 1). The average word counts ber minute) were within three words across the five samples. It is possible that these


43

data represent not only an average of the amount of information conveyed in the face-to-face group discussions of this particular course, but an average of the arnount of information in

any (normally paced) conversation. It seems likely that one can only speak so quickly before others have difficulty understanding the communication, or that one can only speak so slowly before others become bored and would rather not understand the communication. It would be interesting to conceive of an 'only-so-much-oneîan-take'sort of meter for CMC environments. One could argue that the extrapolated average word count of the face-to-face meetings is not accurate since some students are likely to be absent at each class, and thus, the absolute amount of information that the average student receives is less than the estimated amount. Even after correcting the data for absenteeism, there was still more information presented in the face-to-face component (Le., about 29,000 more words).' One could also argue that the estimate of the total amount of face-toœface information is not vaIid since students cm (and probably do) tune out or daydream in class, and consequently, they are not really attending to (or receiving) al1 of the information being presented. One could make an argument for a comparable scenario in CMC settings. Iust because someone opens a note, there is no guarantee that they have read it. Similarly, just because someone hears something, does not mean that they have listened to it. The CMC software used for this course has a feature that allows users to view who in the class has read whose notes. It is possible that students open notes but do not read al1 of them. For instance, some students may not want their classrnates

'

Such a correction was deemed unnecessary since, as indicated in footnote 4, students were divided into groups for the CMC component of the coune. The expectation was that students participate in their own group's conterences and the general class conferences, but there was no expectation that students engage in al1 of the other group discussions. This 'other-groupconference' absenteeism could be analogous to 'face-to-face class' absenteeisrn.


44

to think that they are reading certain notes and ignoring others. One can imagine that group members might be offended if nobody reads their notes, so some notes may be clicked on just

to register those as 'read'. Altematively, students rnay be concemed that the instructor of the course may review the database and record who is keeping up with the group discussions and who is not. This sort of on-line policing might encourage students to click on a feature that has the iunction to register ALL notes as 'read'. One could consider this type of CMC behaviour as 'tuning out' on-line. Some analyses revealed problems with the design of the questionnaire and thus Hypothesis 2 and Hypothesis 7 were untestable. A number of the variables had binary categories, and thus were not included in the tests of associations since participants could only score either 'high' or 'low' on these variables. Such cornparisons would violate the assumptions of bivariate analyses. Replicating these results while replacing the binary category items with items having Likert-type scales would be both necessary and interesting. As an example @ut unreasonable to report here), it is tempting to claim that the data support Hypothesis 7, that is, participants who do not report easy access to cornputers find that they have too much information to work with on-line (a = 17, !:= -.615, = ,005). 'Cornputer access' was a binary category variable and 'feeling like there was too much information to work with on-line' was a 5-point scale category item. If significant results are replicated with the 'computer access' item measured on, for example, a 5-point scale, then one could interpret

that having dificulty accessing a computer to complete one's work is related to a misattribution of 'too much information', or in other words, that the effort of gaining access to a computer may be related to f e e h g like there is too much information with which to work. The results of this study do not warrant such an inference.


45

It was predicted in Hypothesis 4 that participants who reported difficulty reading fiom a computer monitor would also have reported that reading other students' contributions to the database required more effort than submitting contributions themselves, and that they typically printed on-line documents to read them in paper format. However, this was not tme. This is consistent with some literature investigating these sorts of issues (e.g., see Muter and Maurutto, 1991). As expected (Hypothesis 5 ) , if participants reported that the CMC component required more effort than the face-to-face component, then they also reported that they found that the CMC component involved a lot more work than the face-to-face component. One can assume that participants are correctly associating increased effort with increased work. Given this, it was also expected that these individuals would report participating often in any given week, but as mentioned above in the results section, the opposite was tme. Participants who reported that the CMC component required more effort than the face-to-face component also reported participating less fkequently than other participants in the sample reported. A possible explanation for this finding is that these participants spread their work out across

many visits to the database, and thus, did not feel overloaded since their work was not massed in a few sessions. Also mentioned earlier was the marginally significant finding that these individuals who reported that the CMC component required more effort than the faceto-face component also felt that there was too much information to work with on-line. Feeling like there is too much information to work with on-line had been associated with infiequent visits for this sample, so it seems that letting work pile up is a good recipe for feeling overloaded. This seems to make good sense; if you only log ont0 the system say once a week, then you will probably feel overwhelmed with everything you have to catch up on.


46

If you pace yourself, then you can divide your work into manageable 'chunks'. This is in line with Miller's (1956) work cited earlier. To be effective, one must chunk information into manageable units. This also ties in with the earlier discussion about class absenteeism. Equating missing face-to-face classes with missing CMC classes is difficult because of the transitory nature of face-to-face conversations versus the permanence of the database where CMC conversations are recorded. If students miss two weeks of face-to-face classes, then they might not have to do very much catching up. They may need to obtain another student's notes summarizing what transpired in the classes, perhaps catch up on any assignrnents that they may have missed, etc. Students who miss two weeks of CMC classes have a lot of information (or conversation) to catch up with, since the database recording is a verbatim record that lives on aAer the conversation has transpired. A marginally significant finding reported earlier, that is, if students reported editing

their contributions to the CMC system often, then they also suggested that the on-line portion of the course involved about the same amount of work that the face-to-face portion involved (IJ= 16,r= -.377, g = ,059) is

in the opposite direction than was predicted in Hypothesis 8. It

seems odd that students who are presumably doing more work (Le., editing their contributions) would report that they are doing about the same arnount of work (there is no face-to-face equivalent to editing speech). This peculiar finding could be because of a short range of valid responses by participants on the 'arnount of work' questionnaire item (Le., item 15). Although this questionnaire item had a 3-point scale, no participant reported that the online component involved a lot less work than the face-to-face component. The only valid responses for the analyses were 'Oi: "It involved about the same amount of work 2;and '1': "It involved a lot more work...". This item is now like the other binary categorical items and


47

violates the assumptions of bivariate analyses since participants are going to score either 'high' or 'low' on this item. It was hypothesized that participants for whom English was not their first language would report that reading other students' contributions to the database required more effort

than submitting contributions themselves (Hypothesis 9). The rationale being that they would find it more difficult to read English text than if they read text presented in their fint language, or that they read more slowly and find it difficult to keep up with a steady Stream of English text-based discussion. However, inconsistent with other literature (as reported in Althaus, 1997), this was not found to be true, though given the srna11 sample size, only 24% (n = 4) of the sample reported that English was not their first language. Keyboard training was not associated with the perception of effort, and thus, Hypothesis 10 was not supported. This was also true of the predictions in Hypothesis 1 1; typing skills were not related to any of the variables tested in this sample. Although this is consistent with Hiltz's 1986 findings, it is difficult to Say, fiom this sample, that typing skills are not related to other CMC variables. As reported earlier, over three-quarten of the sample ranked themselves as 'good' or 'great' typists, so there were very few 'fair' or 'poor' typists, yet

many participants reported that the CMC component required more effort than the face-toface (88%). It would be difficult to argue that 'poor' typists are not ai a greater disadvantage and find it more difficult (or more effonful) to participate in such an environment. It is encouraging to note that as reported earlier 47% of the sample complained that

CMC type tasks such as reading, writing, and responding to others' contributions are what took themost amount of time when interacting on-line. This is encouraging because at least they were not complaining about non-CMC tasks such as trying to figure out how to use the


48

software (in fact this was most often reported to be an effortless task). It seems that students are channeling their efforts to appropriate tasks. It was reported earlier that 65% of the sample was inconsistent in their responses on

the two items measuring the amount of time participants spent on-line. The time perception literature was not reviewed but it would certainly help clariS why such a large proportion of the sample provided poor estimates of the time spent on-line. One possible explanation is that the questionnaire was administered at the end of the academic terni, when students are

busy working on course assignments and projects that are typically due at the end of the tem. When the questionnaire was adrninistered, students were probably spending a greater amount of time on-line, were probably under greater stress and working harder than usual. Under such conditions, giving an unbiased estimate of their average on-line time across the whole term seems difficult. Fournier (1996) also reports this as a possible problern with his data.

In retrospect, there are a number of factors that should have been considered for this study so that the data could be interpreted more easily, though since this study was an exploratory one, anticipating al1 the variables that should have been examined was difficult. One important oversight was that participants should have been asked to rank themselves with regards to computer experience and CMC experience. As mentioned previously, the course instructor ranked participants as either 'expert' or 'novice', thus giving the proportion

of each group for this sample, but since participation in this study was anonymous, the author was unable to group participants' responses to observe whether experts and novices differed significantly on any of the variables. Another factor that was ovdooked was the speed of the computer and the type of connection to which participants typically had access. Waiting for the computer to comect


49

fiom a remote system to a host systern and waiting for required material to download emerged as the most fhquently reported hstration for this sarnple. As Shrikumar and Post (1994) suggest, it is important to consider connection issues and how to enhance the usability

of dial-up links which these authon refer to as 'thin' Intemet links. Dial-up links are likely to be around for sometime and the average 'thin' link is somewhere between 2400 bps and 33.6 kbps. It would be interesting to see if students with different connection capacities differ significantly in their reactions to CMC technologies. It is possible that participants who have quick connections and fast computers are less mistrated when using such technologies, and therefore, might perceive the effort involved differently than students who do not have quick connections and fast computen. Although participants were asked fiom where t hey participated most ofien, no questions about connection or computer specifications were asked. One cannot decipher whether students worked from where they worked because of convenience (of location) or connection and computer speed. Given the resuits reported earlier (Le., that students participating fiom home maintained that they participated regularly, posted many notes, and found that the on-line portion of the course involved about the sarne amount of work that the face-to-face portion required), it is tempting to argue that convenience (of location) is playing some role here. Since participants were not asked what type of connection they had, one cannot make such and argument. Nowadays some home computers are connected to the Intemet via fast cable lines, so speed may also be an issue here. Ideally, this snidy should be replicated incorporating the changes discussed here. It would also be optimal to repeat the study comparing one group of participants enrolled in a course offered entirely on-line with another group of participants enrolled in the same course


50

offered entirely face-to-face. Such courses exist at OISE/UT and there is one course which the same instructor teaches both sections (i.e., Eace-to-face and CMC). in the term that this study was conducted, this particular course was not offered. In the absence of such ideal conditions. it seems that the next best cornparison would be a within-subject design, such as in this study. In comparing participants enrolled in courses that have both CMC and face-COface components, one is able to partial out any effects of the instmctor and extra course readings that are not related to any particular component of the course, since al1 participants are exposed to the sarne instructor in both conditions and receive the same extra readings.

In spite of the fact that there exists a variety of definitions for information overload, the conventional assumption is that an excess of information causes information overload.

The results of this study suggest that students in CMC classes do not receive more information than students in face-to-face classes. In fact, this sarnple received less information in the CMC condition, yet they cornplained about too much information in this condition. It is argued that variables inherent in CMC environments confound one's perception of the real amount of information presented. Thinking of infomation overload in ternis of the absolute amount of infomation is too sirnplistic (and perhaps incorrect). The variables explored in this study need to be further investigated in more controlled conditions so that the effects of each variable can be better understood.

If it is not information overload that students are truly faced with, then what is it that they are experiencing? It is possible that CMC students are expenencing 'stimulus' overload, rather than 'information' overload. It may be that CMC environments offer too much stimulation for students to attend and to process at one time effectively. yet not tao much information per se. Feenberg (1989) suggests that CMC environments do not resemble


51

natural environments and this stresses users. If such environments could mimic more natual envimnments, where one could process information as natually as possible, then maybe some cornplaints will dissipate. Social psychology studies demonstrate that even in our natural environment humans do not respond well to stimulus overload. Mathews and Canon (1975) set out to study helping behaviour in noisy environments such as big, busy cities. These psychologists found that people arc less likely to help someone in need in busy urban centers, than to help someone in need in clam nual areas. Mathews and Canon claim that this is not because

urban folks ignore people in need and cannot be bothered by them. but because there is so much noise and activity in cities that people are overloaded by al1 the stimuli in the environment. Using controlled conditions, these authors found that people are likely to help 80% of the time under 'quiet' street conditions, but only 15% of the time under 'noisy' street

conditions. They concluded that noisy environments cause people to suffer 'stimulus overload'. Such overload makes it difficult for people to process everything that is happening

around them and is likely to cause information to fade into the background (Milgram, 1970). It might be that CMC environments, as they are today, give users too much 'noise', making it difficult to work in these environments. It is possible that on-line irrelevant information represents 'noise'. It seems reasonable to consider irrelevant information as distracting and it possibly clogs up valuable processing resources. This line of reasoning is consistent with Hiltz and Turoff s (1985) dennition of information overload, presented

above in the first section (Le., 1.1 What is information overload?). In their CMC definition of information overload, these authors suggest that the unorganized manner with which information is received fiom CMC systems makes it difficult for usen to decipher the


52

relevance of infonnation, and thus, users feel overloaded. If users cannot decipher relevant information, then maybe irrelevant infonnation contributes to information overload. One can imagine that if there is a lot of relevant infonnation available that a user requires to work successhilly on a task, then that information is probably not distracting and cumbersome to work through (especially if it is necessary information). Often when one finds useful and relevant information, one tends to need more supporting information. This is not so with irrelevant information which rnost likely serves to distract one from a task (Le., provide extra 'noise' and possibly stimulus overload). Mathews and Canon (1975) suggest that the solution to stimulus overload (at least in busy cities) is to ask for help when you need it. What is a CMC equivalent to this? Perhaps we need to ask CMC designers for help in creating less 'noisy' CMC environments.


53

VI. Future Considerations The possibilities for future research in this area are as diverse as the definitions of information overload presented at the beginning of this paper and as assorted as the disciplines investigating this phenornenon. Many information overload researches have demonstrated that the problem of information overload is a behavioural problem affecting humans; it is not a problem with cornputers (Heindl, 1998; Hiltz and Turofc 1985). This is hndamental. Future research in this area must remain focused on human fùnction and cognition. Also, remembering that CMC is not intended to replace face-to-face interactions is important (Everetts, 1998; Hiltz, 1986; Hiltz and Wellman, 1997; Leonard, 1996; Walker

and Hackman, 1992 -though these authors refer to telecommunications systems). As Althaus (1997) and Feenberg (1999) suggest, CMC supplements face-to-face interactions and classroom teaching; it is not meant to create 'teacherless' classrooms (Feenberg, 1999). As reported earlier, there are great benefits to CMC in education and perhaps we should concentrate on continuing to develop what is nght with CMC in education, as opposed to just fixing what is wrong with it. As a final comment, it is interesting to consider this paper's status in relation to the

rest of the information glut. It is rather ironic that papen are wntten about information overload, only to add more to what already exists (Biggs, 1989; Hiltz et. al., 1986; Shenk, 1997). If this paper adds to the 'information' fil1 about which so many cornplain, then one final comment is in order: we are confionted with the ageold problem -which came first,

the chicken or the egg? C m one impart 'knowledge' before 'information', or must 'information' precede 'knowledge'?


54

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Biggs, M. (1989). Information Overload and Information Seekers: What We Know about Them, What to Do about Them. Reference Librarian. 25-26,4 11-29, Birkerts, S. (1996). Reading in the electronic era: 1. Loeos. 7(3), 2 11-2 14. Brewster, S.A. (1997). Using non-speech sound to overcome information overload.

Disola~s,17(3-4), 179-189. Burge, E.I. (1994). Leaming in Computer Conferenced Contexts: The Learners' Perspective. Journal of Distance Education. 9(L), 19-43. Butcher, H. (1995). Information overload in Management and Business. Colloauium Digest 1223). Paper presented at: IEE Cornputhg and Control Division Colloquium on Information Overload, London, UK,November 29, 1995. Cognition and Technology Group. (1992). Technology and the Design of Generative

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IEE Colloquium Dieest (223). Paper presented at: IEE Computing and Control Division Colloquium on Information Overload, London, UK, November 29, 1995. Everetts, R.B. (1998). Expenences in Distance Leaming From a Student's Perspective. ISTAS 98. Winna the World: The Im~actof Information Technoloev on Societv. Proceedings of the 1998 International Symposium on Technology and Society,

IEEE,New York, NY, USA, vi+176 pp., p. 155-160. Faber, S. (1994). Beyond the Cocktail Party. Discover. 1S(June), p. 39. Feenberg, A. (1989). The written world: On the theory and practice of cornputer conferencing. In Mason, R., & Kaye, A. (Eds.) Mindweave: communication. commters and distance education. Oxford: Pergamon Press, pp. 22-39. Also [On-line] Available: http ://star.ucc.nau.edu/-maudmoderate/feenberg.html

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Forester, T. (1992). Megatrends or Megamistakes? What Ever Happened to the Infonnation Society? Information Societv. 8(3), 133- 146. Fournier, J.F.11. (1996). Information Overload and Technoloev Education. [On-line]. Available: h~://www.coe.uh.edu/insite/elec~~b/html1996/07coum.htm Gifford, B. (1992). Where Is the Knowledge? Knowledge Management, Research and Pedagogy in the Electronic Age. Education-Librariu. l6(3), 14-22. Haavind, R. (1990). Hypertext: the Smart Tool for information Overload. Technoloev Review. 93(Nov.-Dec.), 42-8+. Harasim, L. (1987). Teaching and Leaming On-Line: Issues in Cornputer-Mediated Graduate Courses. CJEC. l6(2), 117- 135. Heindl, D.J.(1998). A Framework for Applying Technology to Leaming. ISTAS 98. Wirine the WorId: The Impact of Infonnation Technolow on Societv. Proceedings of

the 1998 International Symposium on Technology and Society, IEEE,New York, NY, USA,

vi+176 pp., p.33-36. Hightower, R & Sayeed, L. (1995). The Impact of Cornputer-mediated Communication Systems on Biased Group Discussion. Cornouters in Human Behaviour, U(l), 33-44.

Hiltz, S.R. (1986). The "Virtual Classroom": Using Computer-Mediated Communication for University Teaching. Journal of Communication. 36(2), 95- 104. Hiltz, S.R.,& Turoff, M. (1985). Structuring Cornputer-Mediated Communication Systems to Avoid Information Overload. Çommunications of the ACM. 28(7), 680-689. Hiltz, S.R.,& Wellman, B. (1997). Asynchronous Leaming Networks as a Virtual Classroom. Communications of the ACM. 40(9), 44-49.


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Hiltz, SR.,Johnson,K., & Turoff, M. (1986). Experiments in Group decision making: Communication Process and Outcome in Face-to-face venus computenzed conferences. Human communication research. 13(2), 225-252 Jih, H.J.& Reeves, T.C. (1992). Mental Models: A Research Focus for Interactive Learning Systems. Educational TechnoloW.Research and Develo~ment.40(3), 39-53. Jonassen, D., DaGdson, M., Collins, M., Campbell, J., Bannan Haag, B. (1995). Arnerican Journal of Distance Education. 9(2), 7-26.

Keller, K.L.,& Staelin, R. (1987). Effects of quality and quantity of information on decision effectiveness. Journal of Consumer Research. 14,200-2 13. Kimball, L. (1995). Ten Ways to Make Online Learning Groups Work. Educational leaders hi^, October, 54-56.

King, W.R. (1995). Focusing IT on Society's Problems. Information Svstems Management. 12(Fall), 49-5 1. Latting, J.K.(1994). Difision of Cornputer-Mediated Communication in a Graduate Social Work Class: Lessons fiom "The Class fkom Hell". Com~utersin Human Services, 1O(3), -

2 1-45, Leonard, D.C. (1996). Using the Web for Graduate Courses in Technical

Communication with Distant Lemers. Technical Communication. Fourth Ouaner, 388-40 1. Lohse, G.L. (1997). The role of working memory on graphical information processing. Behaviour & information Technoloev. 16(6), 297-308. Lucky, R.W. (1997). Just nght! Chemtech. 27(Mar.), p.iBC. Maes, P. (1994). Agents That Reduce Work and Information Overload. Communications of the ACM. 37(7), 30-40.


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Mathews, K.E., Br Canon, L.K. (1975). Environmental noise level as a determinant of helping behaviour. Joumal of Personalitv and Social Psvcholoev. 3 5 57 1-577. McEneaney, J.E. (1998). Are less Able Readen Disadvantaged by Reading in Electronic Environments? ISTAS 98, Wirina the World: The Im~actof Information Technoloy on Society. Proceedings of the 1998 International Symposium on Technology and Society, IEEE, New York, NY,USA, vi+176 pp., p.28-32. McLean, R. (1997). What is "Knowled~e-BuildinP?"[On-line]. Available:

http://www.oise.utoronto.ca:80/-rmcleanlwl, pg 1. Miller, G A . (1956). The magical number seven, plus or minus hHo: Some lirnits on

our capacity to process information. Psycholo~icalReview. 63,8 1-97. Milgram, S. (1970). The experience of living in cities. Science. 167, 146 1- 1468.

Muter, P.,Maunitto, P. (1991). Reading and skimming from computer screens and books: the paperless office revisited? Behaviour and Information Technoloev. 10(4), 257-

266. Noyes, J.M. & Thomas, P.J. (1995). Information Overload: an Overview.

IEE

Collo~uiurnDigest (223). Paper presented at: IEE Computing and Control Division Colloquium on information Overload, London, üK.,November 29, 1995.

O'Hara, K., & Sellen, A. (1997). A cornparison of Reading Paper and On-Line Documents. ACM. CH197 [On-line]. Available: http://www. acm.org/turing!sigs/sigchi/shi97/proceedingdpaper/kohh htm

Oostendorp H. & Nimwegen, C. (1998). Locating Information in an Online Newspaper. Journal of Cornouter-Mediated Communication. 4(1), [On-line]. Available:

http://www.ascusc.org/jcmc/vol4/issue l/oostendorp.hûnl


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Perkins, D. (1992). Technology Meets Constmctivism: Do They Make a Marriage?

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Scardarnalia, M., & Bereiter, C. (1993). Technologies for Knowledge-building Discourse. Communications of the ACM. 36(5), 37-41. Scardarnalia, M., & Bereiter, C. (1996). Adaptation and Understanding: a Case for

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Shrikumar, H., & Post, R. (1994). Thintemet: life at the end of a tether. Com~uter Networks and ISDN Svstems. 27,375-385. Spectrum Staff (1987). Too much, too soon: Information overload. IEEE S~ectrurn, 24(6), 5 1-55. -

-

Stanley A.J., & Clipsharn, P.S. (1997). Information Overload Myth or Reality? Colloauiurn Dieest(340). Paper presented at: Proceedings of the 1997 IEE Colloquium on


60

Information Technology Strategies for Information Overload, London, UK,December 3. 1997.

Stanton, N., & Baber, C. (1992). An Investigation of Styles and Strategies in Self-Directed Learning. Journal of Educational Multimedia and Hwemedia 1, 147- 167.

)

Stratulat, A. (1998). T Have Nots. April. [On-line]. Available:

hnp://www.usask.ca~education/co~~~~~k~802papeds~~la~alex.htm Sweller, J., & Chandler, P. (1994). Why Some Matenal 1s Dificult to Learn. Çgenition and Instruction. 12(3), 185-233.

Tracz, G. (1980). Computerized Conferencing: an Eye-opening Expenence with

EIES. The Cariadian Journal of Information Science. 5, 11-20. Thimbleby, H. (1996). Internet. discourse and interaction wtential. Keynote at First Asia Pacific Conference on Human-Computer Interaction. Singapore. [On-line]. Available:

http://~.cs.mdx.ac.uk/harold/singaporelsingapore.h~l Tulving, E., & Thomson, D.M.(1973). Encoding specificity and reh-ieval processes in episodic memory. Psvcholoeical Review. 80,352-373. Tulving, E., & Oslet, S. (1968). Effectiveness of retrieval cues in mernory for words. Journal of Exwrimental Psvcholow. 77,593-601. Walker, K., Hackman., M. (1992). Multiple predicton of perceived leaming and satisfaction: The importance of information transfer and non-verbal immediacy in the televised course. Distance Education. 13(1), 81-92. Wiesenberg, F., & Hutton, S. (1996). Cornputer-Mediated Conferencing Software.

Journal of Distance Education. 1 1,88-99.

Infornation Overload

61

Wilson, P. (1995). Unused relevant information in research and development.

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VIII. Appendices

8.1 Appendix A

Face-to-face Group Discussion Assignment

62


Introduction to Cornputer Applications Background: In recent years, hypeaext and hypemedia have become popuiar means for organizing educational information. Hypertext is the provisions of links that when chosen transfer you to another piece of text. We c m use hypertext iinks to provide a pop up dennition of a tem, to provide altemate materials. or to devise a path through material based on interest or prior howledge. Hypermedia is the same idea. although links may be embedded in graphical images. and the destination for the link may be materials in a variety of media formats. Prgblem: Some people like hypertext because it provides options to the leamer. and a carefuiiy designed hypertext can provide opportunities to explore materiai of interest, or provide remediation for students having difficulties with certain concepts. Other people argue that hypertext is confushg and leads leamers to become "lost~~ in maîend. In addition, some topics simply require a h e u presentation.

Task: With your group discuss the issue of the advantages and disadvantages of hypertext. 1. Do you penonaiiy like hypertext? If you are viewing hypertext, do you tend to use the links? What kind of situations work best for you. 2. What do you see as the main advantages to a hypertext organization of material? 3. What do you see as the main material?

to a hypertext organization of

4. For what M d of educational situations wouid hypertext be the best

choice?

Report: Prepare a short report for the rest of the class. Retum to the classroom at

t0:00*

63


8.2 Appendix B Questionnaire: Measuring information in face-to-face settings versus CMC settings

64


65

Measuring information in face-to-face settings versus CMC settings The following is a voluntary questionnaire designed to help us identify the voiume of information that students receive in a face-to-face component of a course versus an on-line component. As indicated in the Participant Consent Fonn distributed earlier in the term, this study is being conduced by Lena Paulo, a Master of Arts student in the department of Cumculum, Teaching, and Leaming at OISE/UT under the supervision of Professor Lynn Davie. The information obtained fiom this questionnaire will be held in the stictest confidence at al1 times. Professor Davie will not view any of your cornrnents and he will not know who has participated and who has not. For any reason, and without penalty, you may discontinue you participation at any time. in completing this questionnaire, Lena Paulo and Professor Davie hope to gain a greater understanding of CMC and the effects of such an environment on information processing.

1. What did you find most fnistrating about using Knowledge Forum (i.e.. software used for your class database) ?

2. What did you find most effortless in using Knowledge Forum?

3. What do you find takes the most time when you are engaged in on-line interactions?

4. Typically, in my given week, did you do ALL the reading in the database?

Yes

No

(Plcase circle)

1

2


66

S. Compared to the face-to-face component of the course, how much time would you estimate that you spent on the on-line component of the course (excluding any course readings, i.e., the time you spent on work that you would consider related oaly to the on-line portion of the course, e.g.. reading other's contributions to the course database, creating and posting your own contributions)? (Plcasc chcck one)

+3 3 times more time than the face-to-face -

+2 2 times more time than the face-to-face +1 slightly more time than the face-to-face - 1 slightly less time than the face-to-face -2 2 times less time than the face-to-face -3 3 times less tirne than the face-to-face -

6. Generally, did you find it dificult to read nom the cornputer monitor (compared to reading from a paper document)?

Yes

No

(Plcase circlc one)

7. Typically, do you tend to prht out on-line documents so as to read them in paper format?

Yes

No

(Please circlc one)

8. In your opinion, would you Say that the on-line portion of this course required more effort on your part than the face-to-face portion? (Plcase chcck one)

+2 A lot more +1A little more

O The sarne effort -1 - A little less -2 A lot less -


67

9. Which of the following would you rate as requiring more effort on your part? (Plcase chcck one)

1 Reading others contributions to the database 2 Making contributions, younelf, to the database

10. Typically, during any given week, when did you participate in the on-line component of the coune (either reading a d o r posting and excluding class lab time)? (Plcase chcck one)

1 Usually the beginning of the week

2 Usually the middle of the week 3 Usually the end of the week 4 Usually throughout the week (e.g..every couple of days)

1 1. Typically, during any given week, how often did you participate in the on-line component of the course (either reading andtor posting)? (Pleue check one)

O

2 4

6

0-1 t h e 2-3 times 4-5 times 6 or more times

12. Typically, dunng any given week, how many hours did you spend on the on-line component of the course (either reading andor posting)? (Please check one)

O 2

0-lhour

4

2-3 hours 4-5 hours

6

more than 6 hours

13. On average, how many posts did you contribute per week? (Please chcck one)

O 2 4

6 8

0-1 post 2-3 posts 4-5 posts

6-7POS~S 8 or more posts


68

14. How often did you feel Iike there was too much information to work with in the on-line component of the course? (Please chcck one)

-2 Never

-1 Rarely

O Sometimes

1 Often

2 Always

15. Which of the following would you Say was true for you about the on-line portion of the CO une? (Pleasc chcck one)

It involved a lot more work than the face-to-face portion. It involved about the same amount of work than the face-to-face portion of the course. It involved a lot less work than the face-ta-face portion of the course.

+1 O -1

16. Where did you do most of your on-line work for this course? (Pleasc chcck one)

OISENT computer labs other OISE/UT computers Office Home Other

1 2 3 4 5

17. Did you often find that there was cornpetition to access a computer to complete you work (e.g.,many students wanting access to a lirnited number of computers, children or other family membea dominating the home computer)?

Yes

No

(Plcase circlc)

1

2

18. Typically, did you go back to edit the notes you contributed to the database? (Plcase chcck one)

2 Always

1 Ofkm

O Sometimes

-1 Rarely -2 Never


69

19. 1s English your first language?

No

Yes

(Plcasc circlc one)

2

1

20. How many languages can you speaklread fluently? (Please check ont)

-

-7

1

œ

2

1

-3 3

- >3 4

2 1. Have you ever had training in keyboarding (for eg., typing classes in high-school)

Yes

No

(Plcase circle one)

2

1

22. Please rank your typing skills: (Pleasc check ont)

-2 -1 1 2

Poor Fair Good Great

(e.g., type with two or three fingers and need to always look at keyboard)

(e.g.,type with hands appropnately positioned on keyboard and without

always looking at keyboard)

23. Do you find that your typing skills have improved with your participation in the on-line component of the course? (Please check one)

-1 O +1

Notatall Slightly Greatly

Thankyou for your participation.


8.3 Appendix C Participant Consent Form

70


71

An Investigation of Measurcs of Monnation -Participant Consent Fonn This study 4 king conducted by Lena Paulo. a Manu of Ans student in the department of Curriculum. Teaching. and tearnhg at OISUUT undcr the supervision of Profcssor Lynn Davie.

oniraio lNSTlTUTg

The purpose of rhis study is to mcasure the m u n t of information conveyed in di&rent modes of instruction. In this investigation wc will tape-record a portion of a class conversation (so that an amount oiinfomation can k calcukted) and manin the amount of Yiformation in the class database. You will also k asked to cornpkte a voluncary questionnaire at the end of tht te-

con StUOllS IIY IOUCATION

Tkre arc no physical or p~ychologicdMlcs involved by participating in ihis study. The r d 6 obtained ikom each participant wiü k k l d in the strictest çonfîdence at ali imuJ; your namc wiii not k ünlred to any re~ultsor idormation you provide. When a a m c ~do appear. thcy will k nmoved. Ail records. includhg the tape rccording. wiU be destroyed at the end of the term Professor Davie MU not vkw any of the data and he will not Laow who has partkipat~din this study and who has pot. The identity of participants is not important for our investigation as we only mwuring the amount of information rhat shidcnts rcceive in various componeats of the course. You an &aCO discontinue your participation at any the. for any reason, and without penalty. W~thyour participation m this smdy, we hope to incrcasc our understanding of CMC and the efkcts . of such envkonmcnts on information processing.

oc

tria UNlWIllSlTY

OC TORON70

1have read the above and agrre to panicipate in tbis experimcnt.

N a (pie=

print):

Date:

Signature:

1prefer NOT to participate in the foiiowing componenu: (

p

~

~

)

O : tape ncording of a clas segment O mas= of dambase information


8.4 Appendix D

Ethical Review Fonn

72

.


73

~d~ ofrasmj= Informat i o n Overload in Computec-Mediated-Conf e c e n c i n g :

1s there teally t o o much information? implications for d i s t a n c e education. J


74

Information Overload in Cornputee-Mediated-Conferencinq:

T i d e o f b j m

~mplications for distance education. Helena F. Paulo / Professor Lynn E. Davie

IS there really too much information? Principal LwatigsorCs) or

~ - ~ d- Sw w c 3 t

in

*

pjd

&akwrinkhoruod=

abjrrrwO otSw

Curriculum, Teaching and Learning: Comguter Applicat ( i ) TO investigate vhether CMC students do in f a c t

receive more information than'atudents in face-to-face classes. (ii) To investisate variables that contribute to the perception of information overload-

.

.

' ~ o r dcounts collected from: ( i ) Tape recocded segments of face-to-face classes

(ii) Knowledqe Forum database notes

( i ) Tape recoeding of face-to-face class ( i i ) Vocabulary Analyzer Tool ( t o collect data from Knowledqe

Forum database notes.

( i ) 2 or 3 one-hour segment of Profersor Lynn Davie's class EDT1602) vil1 be tape recorded and' t h e n transcribed.

e

( i i ) Uaing C.A.C.S.'s

Vocabulagy ~ n a i y z e r , Rnowledge Forum n o t e s

bc f t o m ~ r o f e a s o rDavia QI class will,,analyred-

A short questionnaire asking students about t h e i r perceptions of

information overload will be administeted at the end of the teqm.

Apptoximately 20 N a s t e r s level, OISE/UT qraduate studentfi

vil1 be asked t o voluntarily ~ a r t i c i ~ a tin e t h i s studv.

..

Volur$ry participation: .

.

s t u d e n t s in Professor Davie ' 9 E D T W l 2 a

course w i l i be invited to t a k e part in t h i s studv.


No names

76

will be attached t o any of t h e materiala: names will

be d e l e t e d and

data atored on a aecured hard disk.

Wbrr~oorillk~ofrhr~dr~rchesdolQoady?(a~mb.aPrrd~~~vu A t t h e end of t h e

term, al1 data vil1 be removed ftom the h a r d

d i s k and destroyed.

Tape recordings w i l l a l 8 0 be destroyed at

the end o f the term.

Participants vil1 be debriefed about the study: b r i e f summary of of the problem, description o f expetiment and implications for theory and/or ptactice.

So namei v i l 1 be actached ta anv

of t h e mate-.

collection: we are calculating vord counta in face-to-face and CMC classes.

Al1 participants h a v e ' t h e opportunity to vithdraw

from t h e study ant any tirne, for any reaaon and without ~ e n a l t y .


77

Participants will have the opportunkty :to :r'eview the consent form individuallv, and confidentiallv submit if investiqator.

P o the

~rincipal


8.5 Appendix E

Debriefing Fonn

78


Debriefing Sheet: "MeamringInformaiion in faceto-face settings versus CMC settings" by: Lena Paulo

(If you have any questions or commcnts, please send 111ç a message.)

Generol probiem to be investigated:

Information overload (i.e.. the presentation of too much information relative to the time one has to cognitively process the information) has always been a primary cornplaint of students registered in computer-mediated conferencing (CMC) courses. Many believe that information overload exists but it semis that, to date, no one has empincally measured this. It may be that students enrolled in CMC courses do not really encounter more information than students enrolled in courses that meet face-to-face (Qf). It may be that &ere exist "other" variables which leave students in CMC courses with the impression that they are presented with too much information to process. The purpose of this study is to investigate this problem: first, whether students enrolled in CMC courses do in fact recieve more information than students enrolled in f2f courses, or whether students enrolled in CMC courses merely perceive more idornation. Secondly, if students of CMC courses are not presented with significantly mon information than students of f2f courses, then Professor Davie and myself will try to tap into what sorts of "other" variables might confound one's perception of the amount of information received in various modes of presentation (i.e., f2f vs CMC). Brief descriptîon of our study:

The study in which you participated consists of various components: first, a f2f portion of your EDT 1602s class was tape recorded so as to obtain an average word count of 'an average' f2f meeting. Secondly, the class database will be analyzed to obtain a word count of. presurnably, 'average1CMC meetings. Since we can easily measure how many words are in the database, we will extrapolate £tom the tape recorded data to get an average word count for the f2f portion of the coune (in such a way that these two measures cari be compared). Thus, we will try to measure whether more information was adrninistered during the on-line portion of the course compared to f2f portion or whether there was about the sarne amount. Finally, many of you completed a questionnaire which will help us tap into what variables may play an important role in how one processes information and how one perceives that information. Examples of such variables might be (i) that it is difficult for some of us to read fiom a computer screen; (ii) if English is not your first language, you might find it easier or faster to read in whichever language you are most fluent; (iii) some of you may f h d it difficult or fiustrating to type out your contributions to the class

79

Tnfonnation Overload

database; or (iv) you probably often iind that it is simply easier to Say something than it is to write about it.

Our hyptheses:

Our hypotheses are that there will not be significantly more information presented in the on-line portion of the coune compared to the f2f portion, and that there exist other variables that result in the misconception of the actual amount of information presented in the on-line portion. . Out variables:

Our independent variables are the two modes of presentation of information, that is, CMC and f2f. Our dependent variables, or our outcome variables, are the various measures of participants' responses, so in our case, the number of words in the tape recordings (extrapolated data), number of words in the class database, and your responses to the questionnaire administered at the end of the tem.

Implications for theoy or for practice: The results of this study will hopefully enlighten us about unique characteristics of on-line environments and the effects of such environments on cognition, perception, and information processing. We also hope to gain a greater understanding of the factors we should consider when creating on-line courses so that students are not fnistrated by the medium or unnecessarily burden with feelings of information overload.

80


8.6 Appendix F Frequency Tables for Questionnaire Items 4 to 23

81


Frequency Tables for Questionnaire Items 4 to 23

r

Valid

1

responses

2

Frequency 10 7

Percent 58.8 41.2

Fr uen

Percent

Valid

responses

2.00 3.00 Total

41.2 100.0

17

Percent 2.00 Total

17

100.0

Valid 1.O0 ~ S P O ~ 2.00 S ~

Frequency 1O 7

Total

17

Percent 58.8 412 100.0

responses

L

I

rotai

1

100.0

1

82

Information Overioad

Valid

1.O0

Missing

System

Valid

Fmquency 7

Percent 412

17

100.0

Frequency

Percent 11.8

2.00

2

Frequency Valid responses

2.00 4.00 6.00 Total

3 5 9 17

F nquency Valid responses

2.00 4.00 6.00 Total

6 5 6 17

Percent t 7.6 29.4 52.9 100.0

Percent 35.3 29.4 35.3 106.0

.

83


Frequency Valid

tesFMn3es

2.00 4.00 6.00 8.00

3

Percent 17.6

Total Missing total

Valid responses

System

-2.00

responses 2

Percent 5.9

17

47.1 100.0

-1

Total

Valid

Frequency 1

.O0 1.00 Total

Valid

1.O0

Missing

System

Frequency 6

Percent 35.3 64.7 100.0

11 17

Frequency 7

Percent 41.2

17

100.0

84


Valid

mPonses

Frequency 7 10 17

1.O0 2.00

Total

r

,

Percent Valid responses

Missing Total

r

Percent 41.2 58.8 100.0

Valid

I

Valid

responses

Missing Total

-2.00 -1 -00 .O0 1.O0 2.00

Total System

Fmquency 13

1.O0

Total

1

1.O0 2-00

3.00 4.00 Total Systern

17

Percent 76.5

1

Frequency 5

100.0

1

Percent

29.41

85


Valid resPonses

Valid

responses

1.O0

2.00 Total

-2.00 -1.QO

2.00 Total

Valid

Missing Total

-1 .O0

Frequency If 6 17

Percent 64.7 35.3 t 00.0

Frequency 2

Percent 11.8

17

100.0

Frequency 8

Percent 47.1

17

88.2 11.8 100.0

Total System

86


8.7 Appendix G

One-Sarnple Kolmogorov-Smimov Tests

87


NonParametric Tests OnMampk KolmogorovSmimovTest

N

Normal Parametersagb

Mean

Most Extreme Differences

Std. Oeviaüon Absolute Positive Negative

Kolmogorov-Smimov Z Asyrnp. Sig. (2-tailed)

REAO AL4 17 1.41 .S 1 .380 ,380 œ.289 1.566 .O15

TlMEJ 17 2.1765 .8090 .257 ,175 0.257 1.061 .210

MONITOR6 17 1.6471 .4926 .410

.258 0.410

1.691 .O07 ,

One-Sample KolmogotovSmimov Test

PRIN77 17

N

Normal Pararnetersaeb Most Extrerne Differences

MORE EF8 17

WHAT EF9 15

Mean Std. Deviation Absolute Positive Negaîive

Kolmogorov-Smimov Z Asyrnp. Sig. (2-tailed)

OneSampk Kolmogorov-SmirnovTest

Normal Pararnetersa$b Most Extreme Oifferences

Kolmogorov-Smimov Z Asymp. Sig. (2-tailed)

Mean Std. Deviation Absolute Positive Negative

SI4

4.7059 1.5718 ,324

,352 -.5 14 1.992 .O01

,205 œ.324 1.337 .O56

3.7333 -7037

4.0000 1.7321 ,229 .229 .229 .944

-

.336

88


89

O n e m p l e Kolmogorov-Smimov Test 4

b

N Nomal Parametersab

Most Extrerne Differences



NUMPST13 16 4.6250 2.0290 .308

TOMUCH14 17 ,294 1 .8489 .268 .203 9.268

,308 9.192 1.234

t .IO4

.O95

-175

MOREWKIS 17 3471 ,4926 .410 .258 0.41O 1.691 .O07

One-Sampli, Kolmogomv-Smlrnov Test

N Normal Pararnetersagb Most Extreme Oifferences

Mean Std. Oeviation Absolute Positive Negative


WHERE16 16 2.6875 1S370 .366 .301 0.366 1.484 .O28

'

COMPET17 17 1,5882 S073 380 ,289

-.380 1.566 .O1 5

.O47

Orte-Sampk KolmogorovSrnirnov Test

Normal Par;lmeter~a+~ Mean Std. Deviation Most Extreme Absolute Positive Oifferences Negative Kolmogorov-Smimov Z Asymp. Sig. (2-biled)

1.2353 ,4372 .469 .469 -.a95 1.936 .O01

2.0000 .966 1 ,313 .313 -.188 1.250 .O88

1.3529 .4926 ,410

,410 0.258 1.691 .O07


N Normal P a r a m t m ~ b

Most Gdreme DiMnces


Kolmogomv-Smimov Z Asymp. Sig. (2-tailed) a. Test distribution is Nonnal. b. Cakulatsd h m data.

90

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