certified teachers interested in pursuing a master's degree program or postbaccalaureate coursework to achieve content expertise in science and mathematics.
Beyond the Transcript: Factors Influencing the Pursuit of Science and Mathematics Coursework Susan Haag
Colleen Megowan
Arizona State University, Center for Research on Education in Science, Mathematics, Engineering, and Technology
Arizona State University, School of Arts, Media and Engineering
The nation’s middle schools suffer from a shortage of qualified science and mathematics teachers. To address this need, one university in the southwest has developed the Modeling Institute, a master’s degree program for in-service elementary educators interested in teaching science and mathematics at the middle school level. Identifying the profile of teachers interested in pursuing additional coursework in science and mathematics is necessary to more effectively attract candidates and to better facilitate the program. Thus, we administered an online survey to in-service teachers to uncover needs and influencing factors. Data revealed that the majority (60%) of 324 in-service teachers are interested in pursuing additional education, beyond that reflected on their current transcript, as a route to becoming more competent in teaching and integrating science and mathematics. The present study provides a plausible profile of K-8 certified teachers interested in pursuing a master’s degree program or postbaccalaureate coursework to achieve content expertise in science and mathematics. Such a profile can assist universities in designing math- and science-related programs that meet the needs of in-service teachers and districts they serve by increasing the number of teachers who are qualified (by transcript and test scores) and competent in their content.
In the United States, there is a shortage of qualified science and mathematics teachers (Clewell & Forcier, 2001; Clewell & Villegas, 2001). Grave deficiencies in American K-12 mathematics and science education have been brought to light in many prominent reports, such as “A Nation at Risk” (U.S. Department of Education, The National Commission on Excellence in Education, 1983), Trends in International Mathematics and Science Study (U.S. Department of Education, 2004), the Glenn Commission (U.S. Department of Education, 2000), and Program for International Student Assessment (Lemke et al., 2004). It is worth noting that these reports span over 25 years, but the issues they address remain unresolved. The consensus of these reports indicates that a large proportion of those teaching science and mathematics are underqualified, as many do not have a college major in either science or mathematics (Ingersoll, 1999, 2001, 2003). Thus, many experience out-of-field teaching (Ingersoll, 2002). Nationally, 61% of high schools and 48% of middle schools experienced difficulty locating qualified science teachers to fill vacancies, and this is expected to worsen, as 30% of teachers report considering leaving the profession (Ingersoll, 2003). There are urgent needs for teachers in physics, chemistry, earth and physical science, and biology (U.S. Department of Education, 2010), and the problem is so critical that many needy districts across the nation have recruited thousands of international K-12 science and mathematics instructors (Brulliard, 2004). School Science and Mathematics
Consequences of Shortage The current shortage of qualified middle school science and mathematics teachers not only impacts achievement, but inadequate teacher preparation discourages students from pursuing careers in the science, technology, engineering, and mathematics (STEM) or STEM education disciplines (Gafney & Weiner, 1995). Between 1966 and 1988, the United States experienced a decline in freshmen planning to pursue science, engineering, and mathematics majors, with math (4.6–.6%) and the physical sciences (3.3–1.5%) being the most dramatically affected. Additional consequences of teacher shortages include negative attitudes toward science, declining scientific literacy (Moin, Dorfield, & Schunn, 2005; Shugart & Hounshell, 1995), and lower student performance internationally in mathematics and science (National Research Council [NRC], 2002; Lemke et al., 2004; U.S. Department of Education, 2004). To illustrate, the U.S. Department of Education (2004) revealed that U.S. eighth graders ranked behind 17 of 38 other nations and that 12th graders scored below the international average. Another outcome of the shortage of qualified K-12 science and mathematics teachers is the reported decline in content knowledge preparation (Moin et al., 2005). Nearly 32% of science and mathematics teachers report majoring in neither math nor science (U.S. Department of Education, 2010). These numbers are more extreme in schools in high poverty areas, in terms of math and physical science instruction (National Science Foundation, 455
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2004). These findings are of great concern due to the correlation between teacher subject matter preparation and improved student performance (Darling-Hammond, 2000; Fuchs & Woessmann, 2004; Goldhaber & Brewer, 1997; Wobmann, 2003). Most research on science and mathematics content-preparation in preservice elementary teacher education targets pedagogical content knowledge (Shulman, 1986, 1987) or mathematical knowledge (Ball, Hill, & Bass, 2005; Hill, Rowan, & Ball, 2005; Hill, Schilling, & Ball, 2004). In addition to teacher education, sufficient grounding in the science and mathematics content is critical (Shulman, 1987). The Arizona Context Teacher shortages have hit the state of Arizona especially hard. There have been statewide shortages in middle school general science, mathematics, language arts/ reading, and socials studies; and deficits were recorded as recently as 2009–2010 in many counties, such as Apache, Gila, Graham, Greenlee, Mohave, Navajo, Pinal, and Yuma (U.S. Department of Education, 2010). In many Arizona schools, particularly those in poor urban neighborhoods or extremely rural communities, as many as 80% of mathematics and science teachers are uncertified in their content areas and hence ill prepared to teach these subjects. Moreover, too few mathematics and science teachers graduate from Arizona’s university preservice programs (Gau, Palmer, Melnick, & Heffernon, 2003) to meet the needs of Arizona’s schools. Secondary science and mathematics teachers are leaving or retiring, and new K-12 students are arriving in the state faster than our universities’ preservice teacher education programs can keep up (Middleton, 2008). Local school districts have identified elementary school-certified teachers as a potential source for new science and mathematics middle school teachers (Romero, 2008). Education funding in Arizona has always been low when compared with the national average (Public Education Finances, 2010), but the recent recession has exacerbated this problem. Hundreds of teaching positions have been eliminated and teachers have experienced pay freezes and furloughs with the bulk of cuts affecting K-8 teachers, while class sizes have been increased and special programs have been eliminated to balance budgets (Javier, 2010). Modeling Instruction The seriousness of the situation has not gone unanswered. In response to these widespread shortages, the largest university in the state (Arizona State University 456
[ASU]) recently secured National Science Foundation funding to create the Modeling Institute, devoted to deepening teachers’ content knowledge in STEM disciplines, and assisting them with the development and adaptation of curriculum so that they can focus student learning on the fundamental conceptual models that are central to science and mathematics. The choice of focus on middle-level education is deliberate. Studies have shown the detrimental effects of middle school instruction on students’ mathematical and scientific achievement (Eccles & Wigfield, 1995; Middleton & Spanias, 1999). Just as importantly, middle school students’ interest in science and mathematics and their intent to continue to pursue STEM-related careers decline during the transition from elementary to departmentalized middle schools (Middleton & Spanias, 1999). To increase students’ interest, engagement, and performance in science and mathematics, the Modeling Institute provides training in modeling instruction and in science and mathematics integration. The institute’s approach is based on modeling instruction (Hestenes, 1987, 1997, 2006), a guided inquiry approach to science teaching that was developed in the mid-1980s by a physics teacher (Wells, Hestenes, & Swackhamer, 1995) and has spread to chemistry, biology, earth science, physical science, and mathematics classrooms and is currently in use by over 2,000 high school teachers (Hestenes, 2009). Its success in improving student achievement (Hake, 1998) has led to a demand for its extension into middle school teacher education. The integration of science and mathematics, as a complement to modeling, has emerged as a key strategy in teacher education methods courses and in middle and high school classrooms (Berlin & Lee, 2005). It enriches the learning context (Frykholm & Glasson, 2005; Koirala & Bowman, 2003), increases motivation (Friend, 1985; Wolfe, 1990), and improves student achievement (McBride & Silverman, 1991; Utley, Moseley & Bryant, 2005). This strategy is used by organizations such as School Science & Mathematics Association, the American Association for the Advancement of Science, the NRC, and the National Council of Teachers of Mathematics (NCTM). Science-math integration is reflected in the national standards documents such as the National Science Education Standards (NRC, 1996) and the NCTM Standards (NCTM, 2000). National Programs The Math Science Partnership program is unique among national programs as it targets in-service teachers who are Volume 112 (8)
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interested in: (1) improving their content expertise in the STEM disciplines, (2) taking science or mathematics leadership roles in middle school, and (3) integrating science and mathematics at the course level. Despite the number of other programs emerging across the nation, few offer this comprehensive and novel approach. Other programs fall into categories that include: discipline-specific masters programs that allow teachers to pursue a master’s degree in a specific subject (e.g., mathematics, physics, chemistry, biology, or earth and space science) or master’s and certification programs for career changers who majored in one of the STEM disciplines and are now returning to school to become certified to teach. Many universities offer discipline-specific master’s degree programs but only a few (e.g., University of Houston, ASU, University of Pennsylvania) integrate the disciplines at the course level. The University of Arizona’s College of Education offers a Math & Science Teacher Education/Retention Industry Partnerships (MASTER-IP) program (http://coe.arizona. edu/tls/master-ip) that offers summer internships with science, mathematics, and engineering professionals and courses that connect mathematics and science content. MASTER-IP teachers will have a concentration in either science or mathematics. Another example is Northern Illinois University’s Master of Science in Teaching with Specialization in Middle School Mathematics Education (http://catalog.niu.edu/preview_program.php?catoid=11& poid=1861). This program offers a specialization in middle school mathematics education. Applicants admitted to the program are expected to be certified to teach secondary school mathematics (6–12) or certified to teach in the elementary school (K-9). Successful completion of this specialization leads to an endorsement to teach mathematics in the middle school and to a teacher-leader endorsement. Oregon State’s Extended Campus offers an online Master of Science in Science and Mathematics Education with options (http://ecampus.oregonstate.edu/onlinedegrees/graduate/science-math-education/). One option may appeal to a K-12 science or mathematics teacher interested in pursuing advanced knowledge, while another option may appeal to a secondary-level teacher interested in becoming a professional development specialist or a researcher. Other institutions offer online formats (e.g., Western Governor’s University, Walden University, University of Massachusetts Amherst, University of Cincinnati), and the curriculum consists primarily of methods, assessment, and other education topics in the context of science or mathematics classrooms. School Science and Mathematics
Study Overview The Modeling Institute has developed a five-semester Master of Natural Science (MNS) degree program for in-service elementary educators interested in teaching STEM subjects at the middle school level. Individuals who successfully complete the program will meet the requirements to be considered highly qualified in these subjects by the Arizona Department of Education. The present study, then, attempted to identify the characteristics of potential candidates who would be interested in pursuing additional science and mathematics courses. Initially, four focus groups with three local districts were conducted to determine K-8 in-service teacher interest in the Institute’s MNS program and to inform survey development and content. One interesting finding was made during the focus groups. Responses indicated that, rather than holding self-perceptions of being “generalists” (teaching all subjects), these teachers identified themselves as being mathematics or science “specialists.” Overall findings from focus groups and interviews thus facilitated the development of an initial survey. The survey instrument was first pilot tested with random probes on item understanding and after refinement was administered in fall of 2009, primarily to focus group attendees. The survey assessed interest in and pursuit of continued mathematics and science coursework, factors influencing that interest, and interest in applying to the Modeling Institute. Data from 33 responses revealed that teachers had internal factors and external pressures driving their pursuit of additional science and math coursework, namely, an interest in integrating science and mathematics into the curriculum and designing and delivering meaningful science and mathematics activities, a desire for increased competence in science and mathematics, and a quest to become more marketable. Findings from the pilot study sample suggested that years of postsecondary coursework in science and age were significant predictors, while years of high school science and number of years teaching showed a trend toward significance and years of postsecondary and high school mathematics did not. The pilot study instrument served as the foundation for the larger online survey developed for administration in 2010. The research questions that guided the study included: 1. Are in-service K-8 teachers interested in pursuing additional coursework in science and mathematics to become more competent in teaching science and mathematics content? 2. What external factors influence teachers to pursue additional coursework in science and mathematics (e.g., district influences and job security)? 457
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3. What internal factors influence teachers to pursue additional coursework in science and mathematics? (e.g., increased competence, perceptions of specialization, and confidence) We gathered information on factors such as district and school influences, job security, and personal goals. Sociodemographic characteristics like age, years of teaching, subjects taught, grade level taught, and years of science and mathematics taken in high school and in college were also included. Based on pilot study findings, it was hypothesized that: (1) years of teaching, prior coursework in science, types of courses taught, and grade level would predict interest in more coursework; (2) external factors such as job security and marketability would be influences; and (3) internal factors such as perceptions of teaching competence and mathematics-science content specialization would account for teacher interest. Method Participants In-service teachers in three primary local districts were targeted for the assessment. These individuals were currently employed by the districts and represented a pool of potential applicants to a science and mathematics master’s program. Quantitative Methods Based on the instrument that was pilot tested in 2009, the authors designed a survey instrument with items to answer the research questions. To answer the first research question (Are in-service teachers interested in pursuing additional coursework in science and mathematics?), respondents were asked specifically if they would pursue additional coursework, with options of “Yes” or “No” responses. We conducted a discriminant analysis to determine group membership (Agresti, 1996) and to determine which variables were the best predictors of teachers’ educational choice. Discriminant analysis was developed as a statistical procedure for using a set of predictors to account for group membership; the procedure is able to classify individuals into groups by using the scores on the predictors in a way that best match their actual classification (Cohen, Cohen, West, & Aiken, 2003). In the present study, the researchers examined which variables discriminate between in-service teachers who would (1) choose to take additional science and mathematics coursework, and those who would (2) seek no further coursework in science and mathematics. Discriminant analysis predicts group membership based on a linear combination of the interval variables. The procedure begins with a set of observations where both group 458
membership and the values of the interval variables are known. The end result is a model that allows prediction of group membership when only the interval variables are known (Cohen et al., 2003). A second purpose of discriminant function analysis is an understanding of the data set, as the prediction model that results from the procedure may give insight into the relationship between group membership and the variables used to predict group membership. The second question (What external factors would influence teachers to pursue additional coursework in science and mathematics?) required asking items associated with administrator and peer influence. A five-point Likert scale (strongly disagree = 1, disagree = 2, uncertain = 3, agree = 4, strongly agree = 5) was provided. Items probed the extent to which administration impacted decisions, and two probed for peer influences. Several items elicited perceptions of job security and marketability. Questions also probed for teachers’ perceptions of their own competence in science and mathematics to address internal factors. Qualitative Methods Personal interviews were conducted with 20 teachers (including teachers initially interested and those who ultimately enrolled in the program). Over the course of the interviews, we raised questions that would reveal participants’ perceptions concerning factors that influenced their decision to apply to the program, as well as their perceptions of their current content knowledge and teaching ability for math and science content. The interviews aimed at understanding the wide range of factors influencing their choice to enroll in math and science coursework beyond their current degree. Interviews were audiorecorded, transcribed, and coded. Codes derived from interview questions were created to reduce large amounts of information into manageable pieces for analysis. Although we did not set out to test math anxiety and self-efficacy, we saw evidence of these factors. Results The survey was administered online in primarily three local districts from March 22, 2010 until April 22, 2010. Overall, demographic data for the 324 teachers who responded revealed that participants had been teaching an average of 12 years and that the mean age was 41; about one-third held a bachelor’s degree (31%), 54% had a master’s degree, 12% were working on a master’s degree, and 1% had a doctorate degree (2% did not disclose). For the first research question (Are in-service teachers interested in pursuing additional coursework in science and mathematics?), respondents were provided with either Volume 112 (8)
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Table 1 Teacher Interest
Interest Years of science high school Years of science college Grade level taught Years of teaching Subjects currently taught Non-interest Years of science high school Years of science college Grade level taught Years of teaching Subjects currently taught Total Years of science high school Years of science college Grade level taught Years of teaching Subjects currently taught
Mean
Standard Deviation
Unweighted
Weighted
3.20 3.06 5.36 11.06 4.01
.89 1.57 2.35 8.30 2.04
193 193 193 193 193
193 193 193 193 193
2.84 2.05 3.37 14.53 2.18
.95 1.0 2.3 8.12 1.33
131 131 131 131 131
131 131 131 131 131
3.06 2.65 4.56 12.46 3.27
.935 1.45 2.53 8.39 2.00
324 324 324 324 324
324 324 324 324 324
Table 2 Test of Equality of Group Means
Wilks’ Lambda
F
df1
df2
Significance
.965 .885 .851 .959 .799
11.67 41.95 56.483 13.90 80.84
1 1 1 1 1
322 322 322 322 322
.001 .000 .000 .000 .000
Years of science high school Years of science college Grade level taught Years of teaching Subjects currently taught p ⱕ .001.
a “Yes” or “No” survey option. Participants were able to opt out of any survey item, and subsequently, of the 324 responding to this survey item, 193 (or 60%) selected “Yes” while 40% selected “No.” Those who are interested in pursuing additional coursework in science and mathematics are denoted the “interested” group and those not interested in pursuing courses are called the “notinterested” group. Again, the dependent variable for this study was interest in pursuing science and mathematics courses. We used discriminant analysis to predict teachers’ interest in pursuing further coursework in mathematics and science. Predictors were subjects currently taught, grade levels taught, years of science coursework taken beyond high school (in college), years of teaching, and years of science coursework taken during high school. We observed significant mean differences for all predictors on the dependent variable (see Tables 1 and 2). The discriminant function revealed a significant association between groups and all predictors, accounting for School Science and Mathematics
Table 3 Structure Matrix Table
Interest Subjects currently taught Grade level taught Years of science in college Years of teaching Years of science in high school
Function 1 .857 .716 .617 -.355 .326
The previous numbers are pooled within-group correlations between discriminating variables and standardized canonical discriminant functions. Variables are ordered by absolute size of correlation within function.
26% of between-group variability. The structure matrix (see Table 3) showed high loadings for subjects currently taught (.86), grade levels taught (.72), years of science coursework beyond high school (.62), years of teaching (-.36), and years of science coursework during high school (.33). This suggests a label of “experience with science and upper-level content” as the function that 459
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discriminates between those who are interested in pursuing additional coursework in mathematics and science at the graduate level and those who are not. Finally, the cross-validated classification matrix showed that 78.3% of overall cases were correctly classified. The interested group took more science classes in high school (M = 3.2 years, SD = .89) and in college (M = 3.0, SD = 1.5), had been teaching for a fewer number of years (M = 11 years, SD = 8.3), taught in higher grades (M = 5.36, SD 2.3), and taught more mathematics and science subjects (M = 4.01, SD = 2.04). In contrast, the “not interested” group who took fewer science classes in high school (M = 2.8 years, SD = .95) and college (M = 2.0, SD = 1.0) had been teaching longer (M = 14.53, SD = 8.12) and were teaching in lower grades (M = 3.3, SD 2.3) focusing on “general” subject matter (M = 2.1, SD = 1.33). Those who were interested were, on average, 39 years of age, and those who were not interested were, on average, 43 years of age. Those who were interested were primarily teaching in grades six, seven, and eight (51.2%). Those who were not interested in pursuing additional coursework in mathematics and science were primarily teaching in grades K-3 (55.7%). Group differences included coursework being taught and how teachers identified what subjects they were teaching. Teachers were asked which subject they teach and were given a comment box to fill in. Without being prompted, 61.8% of the not-interested group filled in the word “all” or “general,” while only 29% of the interested group selected those descriptors. The interested group also selected key words such as “math-science,” “math,” and “science” more frequently (44.6%) than did the notinterested group (11%). Consistent with focus group and pilot study findings, survey responses indicated that, rather than holding self-perceptions of being “generalists” (teaching all subjects), the interested group held perceptions of being mathematics or science “specialists,” indicating a “specialist” category rating. There was no significant difference in education level between the groups. That is, in both groups, more teachers held master’s degrees than bachelor’s degrees. In the interested group, 50% held a masters’ degree, 15% were working toward a master’s (currently), and 35% held a bachelor’s degree. This finding is noteworthy. Although the majority of teachers in the interested group had a graduate degree or were working toward one, they indicated a need to pursue additional coursework in science and mathematics. In the not-interested group, 62% held master’s degrees and 4.6% were working toward a master’s, while 33% held bachelor’s degrees. 460
Influence of Institutional Factors Our second research question (What external factors would influence teachers to pursue additional coursework in science and mathematics?) required asking items associated with administrator and peer influence. We used the Mann–Whitney U-test to characterize differences in career paths between the interested and not-interested groups. This resulted in significant differences between the groups in terms of external factors that included peer and administrative influence, high stakes testing, and job security and marketability (described further). However, there was no difference between the groups concerning influence from programs like “No Child Left Behind.” For those interested in pursuing additional math and science coursework, peer and administrative influence had significantly greater impact on this group than on teachers who were not interested in pursuing additional coursework or an advanced degree in science and mathematics. Interested teachers were more influenced by high-stakes testing, which contributed to their interest in pursuing more education in science and mathematics. One instructor, educated in another state, indicated that there was a lot of focus on test scores and tracking of students in Arizona: “In Arizona, there is a big push to keep scores of students—tracking all that. There is always the pressure of test scores.” See Table 4 for institutional influences. Several other items resulted in differences in terms of job security, marketability, and salary motivation (Table 5). Although in interviews teachers acknowledged that their immediate salary gains as a result of completing a science and mathematics content-focused master’s degree program would be modest (on the order of $1,000
Table 4 Institutional Influences
Interest Mean SD Interested because peers have advanced degrees. My peers would influence my desire to pursue additional coursework in science and math. My principal or school administrator influences my desire to gain more education in science and math. I am interested in getting an advanced degree in science and math due to pressure from high stakes testing. * p < .01. Volume 112 (8)
Non-Interest Mean SD
2.42 1.13 1.96*
.85
2.29 1.04 2.00*
.87
2.42 1.13 2.03*
.87
2.7
.71
1.1
1.98*
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Table 5 Influences of Job Security, Marketability, and Salary
Interest Mean SD Teachers who are highly qualified in math content knowledge are marketable. Being highly qualified in science content knowledge is a marketable skill. Being highly qualified in math provides job security. Being highly qualified in science provides job security. My current salary motivates me to gain this advanced degree.
4.00 3.95
Non-Interest Mean SD
.75 3.57* .80 3.5*
Interest Mean SD
.95 .97
3.67
1.00 3.11* 1.10
3.62
1.01 3.08* 1.12
3.35
1.2
2.57* 1.4
* p < .01.
per year salary increase), they indicated that the trade-off for increased job security made such an investment worthwhile. Others commented about job security, as one teacher stated that she was at risk of losing her job: “The investment is worth it because I want to be more marketable to other school districts or keep my own job in my district.” Another teacher stated, “Being highly qualified in math and science provides job security.” Another concurred, “If you’ll teach middle school mathematics and science, there is job security.” Another teacher further commented, “If I want a pay raise, I have to get more education. We have not had a pay raise in three years.” Influences of Competence and Content Specialization K-8 in-service teachers interested in pursuing additional science and mathematics courses were more influenced by constructs such as “teaching competence” and being “highly qualified” in science (Table 6). They had perceptions of becoming “specialists” and indicated they “would like to be considered math and science content specialists by peers.” Although mean scores were high for the interested group (M = 4.34, SD = .73) and the not-interested group (M = 4.16, SD = .90), there was no significant difference for “It is important for me to feel competent in teaching math.” These findings suggest that there is a large pool of teachers who are interested in pursuing additional courses in science and mathematics content as a route to become more competent in teaching and integrating science and mathematics content. In an interview, one instructor addressed the importance of math-science integration: “I believe that integrating math and science is extremely important because one supports the other. Students need to be comfortable with mathematics to understand the relationships in science. School Science and Mathematics
Table 6 Influences of Perceived Teaching Competence and Science or Mathematics Content Specialization
It is important for me to feel competent in teaching science. I would like to be considered a science content specialist by peers. I am interested in being highly qualified in science. I am interested in learning how to integrate science into other subjects in my curriculum. It is important for me to feel competent in teaching math. I would like to be considered a math content specialist by peers. I am interested in being highly qualified in math. I am interested in learning how to integrate math throughout my curriculum.
4.54
Non-Interest Mean SD
.64 3.98*
.98
3.97
1.01 2.91* 1.06
4.08
.96 2.95* 1.08
4.12
.87 3.60* 1.07
4.34
.73 4.16
.90
3.60
1.12 2.81* 1.10
3.71
1.14 2.96* 1.15
4.25
.62 3.63* 1.06
* p < .01.
Thus, students will go beyond the experimental part of science and really comprehend it when they can understand the math.” Another teacher added, “I think integrating mathematics and science is important because the students see more real-world applications to the subject matter.” Recurring in the interviews was the theme of going beyond the test, which is reflected in the statement, “I have taken AEPA tests and I am highly qualified already; it proves I can pass a test, but I wanted this for myself. This is my own definition of being highly qualified, beyond taking the test. According to the administration, I have a master’s degree and all the paperwork so I have all the qualifications, but it is more about becoming a specialist.” Participants remarked that they had a special interest in the modeling method of instruction, were intrigued by the program’s emphasis on science and mathematics, and all mentioned a desire to improve their teaching methods to meet students’ needs rather than resorting to worksheets. The majority of responses were aligned with becoming highly qualified and content specialists. One teacher noted, “Yes, I am interested in being highly qualified in science. The kids come through the door and they are excited about science. If you can’t meet their expectations, you turn them off to science. It’s my burden. So I want to become competent so they think like scientists.” 461
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Table 7 In-Service Teachers’ Perceptions of Self-Efficacy
Interest Non-Interest Mean SD Mean SD I generally teach science effectively. I know what to do to turn students on to science. I am confident in my ability to teach science concepts. I am typically able to answer students’ mathematics questions. I understand mathematics concepts well enough to be effective in teaching K-8 mathematics.
4.27
.95
3.9*
.82
4.08
.86
3.85*
.80
4.10
.89
3.80*
.88
4.31
.63
4.30
.70
4.06
.91
3.85
.91
* p < .01.
Significantly, when teachers were asked about their current abilities, more were positive about teaching science than for teaching mathematics; many mentioned they were uncomfortable with teaching sixth through eighth grade mathematics, and one indicated that it “got tricky” at that level. Several noted that the new (ASU) master’s program would provide relevant, integrated activities for students so they “can apply math and science to real-world problems.” To summarize, in-service teachers in the interested group were more willing to pursue innovative science content, were more eager to learn how to integrate science and mathematics into their curriculum, and had higher levels of science self-efficacy than those in the non-interested group (Table 7). Consistent with research on self-efficacy (Bandura, 1997; Enochs, Smith, & Huinker, 2000; Riggs & Enochs, 1990; Woolfolk & Hoy, 1990), behaviors such as risk taking and the use of innovation in the classroom are related to high levels of selfefficacy (Ashton, 1985; Ashton & Webb, 1986). Those with high science and math self-efficacy are more likely to use student-centered approaches and math-science integration (Berlin & Lee, 2005; Czerniak, 1990; Offer & Vasquez-Mireles, 2009), a finding also evident in this study. Learning how to employ innovative ways to deliver content was a common theme in the data transcripts, reflected in this excerpt: I want to learn a new technique to enhance student learning and to help students think outside the box. I am familiar with modeling, but this is a challenge for me. I am both nervous and excited about modeling and inquiry in the classroom as my goal is to include students in the learning process. 462
Discussion Are in-service teachers interested in pursuing additional coursework in science and mathematics? The majority (60%) of 324 Arizona K-8 in-service teachers responded to this question in the affirmative, revealing a large pool of teachers interested in becoming more competent in teaching and integrating science and mathematics content. These teachers are experienced (so unlikely to leave the field voluntarily) but younger than the average K-8 teacher in their community. They are somewhat concerned about high-stakes testing and are more concerned about their relative job security or marketability and about learning innovative, challenging new classroom techniques (e.g., modeling). The results of this survey revealed differences between the two teacher groups in terms of science education taken in high school and college, grade level and subjects taught, and years of teaching. Peer and administrative influences were moderate for those interested in pursuing additional mathematics and science coursework, but these had significantly more impact on this group than on those teachers who were not interested in pursuing additional coursework. Responses further indicated that multiple academic factors influenced teachers’ interests in pursuing science and coursework beyond their current degree, and these factors can inform the design of advanced degree programs for K-8 teachers. The architects of new master’s degree programs should consider incorporating designs that attract in-service teachers such as the modeling method of instruction, emphasis on science and mathematics content, and curriculum integration at the course level. Strategies for promoting these programs should include an emphasis on becoming highly competent and marketable in middle school science and mathematics. Pressure is increasing on the educational community to do a better job of professional and workforce development and teachers are mindful of their role in motivating student interest in the STEM disciplines. In addition to the master’s programs typically available for K-8 teachers (e.g., curriculum studies, educational leadership), universities should carefully consider creating content-focused programs for teachers in the middle grades. This study identified almost 200 teachers in just three school districts with an interest in taking graduate level science and mathematics courses. Moreover, a surprising number of teachers who had already completed a master’s degree expressed interest in pursuing a second master’s degree in middle school STEM. Volume 112 (8)
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Middle school teachers also value curriculum integration—in this instance the integration of science and mathematics. With mathematics and language arts consuming most of the school day now in this era of highstakes testing, teachers are looking for ways to weave other subjects, such as science, into the mix in order to make the content they must teach relevant. Our results indicate that teachers like the idea of a program that models curriculum integration. This program design appealed to educators who were not typically in the first three to five years of their teaching careers. The interested group had embraced the teaching profession and had examined strategies to become more competitive to meet the demands of the twenty-first century. A growing number of school districts in Arizona and across the country now require teachers to obtain a master’s degree in order to advance beyond some point on the pay scale. For teachers who prefer to direct their studies toward gaining subject matter expertise, a program such as the one described previously is an attractive alternative. The results of this study clearly identify an in-service teacher profile that such a program might serve. The profile of a teacher interested in pursuing addition coursework includes a 10-year veteran teacher in grades five through eight who completed over three years of science coursework in high school and in college, and who is influenced by external pressures such as high-stakes testing, marketability, and job security. Programs can also attract in-service teachers by promoting specific content areas for those who want to be viewed as a mathematicsscience specialist by peers. Other Factors The present study indicates that those with less interest teach primarily in elementary grades K-3. Why did we find so few K-3 teachers interested in pursuing additional math-science coursework? Prior studies reveal a profile of elementary teachers who are less interested in mathematics coursework (Beilock, Gunderson, Ramirez, & Levine, 2010; Hembree, 1990; Perry & Bussey, 1979). Students with “math anxiety” tend to avoid math courses and mathrelated career paths (Ashcraft & Kirk, 2001; Chipman, Krantz, & Silver, 1992; Richardson & Suinn, 1972). Although this was not a main focus of the present study, as a possible interpretation of the results, lingering “math anxiety” may factor into future course-taking for some K-3 teachers. After offering the MNS program for one year, preliminary findings indicate that in-service teachers, currently enrolled in the program, are coping with the mathematical School Science and Mathematics
demands. To attract and appeal to elementary teachers who have math anxiety, master’s programs may consider adding a mathematics refresher course or “boot camp” into the curriculum. Summary The present study provides a plausible profile of the K-8 certified teacher interested in pursuing a STEM contentintensive master’s degree program or postbaccalaureate coursework to achieve content expertise in science and/or mathematics. Such a profile can assist universities in designing STEM-related programs that are useful and appealing to teachers and helpful to the districts they serve by increasing the number of teachers who are both qualified (by transcript and test scores) and confident in their content expertise. References Agresti, A. (1996). An Introduction to categorical data analysis. New York: John Wiley & Sons. Ashcraft, M. H., & Kirk, E. P. (2001). The relationship among working memory, math anxiety, and performance. Journal of Experimental Psychology, 130, 224–237. Ashton, P. T. (1985). Motivation and the teachers’ sense of efficacy. In C. Ames & R. Ames (Eds.), Research on motivation in education: The classroom milieu (pp. 141–174). Orlando, FL: Academic Press. Ashton, P. T., & Webb, P. B. (1986). Making a difference. Teachers’ sense of efficacy and student achievement. New York: Longman. Ball, D. L., Hill, H. C., & Bass, H. (2005). Knowing mathematics for teaching: Who knows mathematics well enough to teach 3rd grade, and how can we decide? American Educator, 29(1), 14–17. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman. Beilock, S. L., Gunderson, E. A., Ramirez, G., & Levine, S. C. (2010). Female teachers’ math anxiety affects girls’ math achievement. Proceedings of the National Academy of Sciences of the United States of America, 107, 1860– 1863. Berlin, D., & Lee, H. (2005). Integrating science and mathematics: Historical analysis. School Science and Mathematics, 105(1), 15–24. Brulliard, K. (2004, March 8). New visa ceiling called threat to teacher recruitment. The Washington Post, p. A3. Chipman, S. F., Krantz, D. H., & Silver, R. (1992). Mathematics anxiety and science careers among able college women. Psychological Science, 3, 292–295. Clewell, B. C., & Forcier, L. B. (2001). Absence unexcused: Ending leader shortages in high-need areas. Washington, DC: Urban Institute. Clewell, B. C., & Villegas, A. M. (2001). Increasing the number of math and science teachers: A review of teacher recruitment programs. Teaching and Change, 8, 331–361. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences. Mahwah, NJ: Lawrence Erlbaum Associates. Czerniak, C. M. (1990). A study of self-efficacy, anxiety and science knowledge in preservice elementary teachers. Paper presented at the annual meeting of the National Association for Research in Science Teaching, Atlanta, GA. Darling-Hammond, L. (2000). Teacher quality and student achievement: A review of state policy evidence. Education Policy Analysis Archives, 8(1). Retrieved from http://olam.ed.asu.edu/epaa/v8n1 463
Beyond the Transcript
Eccles, J., & Wigfield, A. (1995). Achievement task values and expectancyrelated beliefs. Personality and Social Psychology Bulletin, 2, 215–225. Enochs, L. G., Smith, P. L., & Huinker, D. (2000). Establishing factorial validity of the mathematics teaching efficacy beliefs instrument. School Science & Mathematics, 100, 194–202. Friend, H. (1985). The effect of science and math integration on selected seventh grade student attitudes toward and achievement in science. School Science and Mathematics, 85, 453–461. Frykholm, J., & Glasson, G. (2005). Connecting science and mathematics instruction: Pedagogical context knowledge for teachers. School Science and Mathematics, 105, 127–141. Fuchs, T., & Woessmann, L. (2004). What accounts for international differences on student performance? A re-examination using PISA data. CESIFO Working Paper 1235, Category 4: Labor Markets. Gafney, L., & Weiner, M. (1995). Finding future teachers from undergraduate science and mathematics majors. Phi Delta Kappan, 76, 637–641. Gau, L. B., Palmer, R., Melnick, R., & Heffernon, R. (2003). Is there a teacher shortage? Demand and supply in Arizona. Tempe, AZ: Morrison Institute for Public Policy, ASU. Goldhaber, D. D., & Brewer, D. J. (1997). Evaluating the effects of teacher degree level on education performance. In W. Fowler (Ed.), Developments in school finance. 1996 (NCES 97-535) (pp. 197–210). Washington, DC: U.S. Government, U.S. Department of Education, NCES. Hake, R. R. (1998). Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. American Journal of Physics, 66, 64–74. Hembree, R. (1990). The nature, effects, and relief of math anxiety. Journal for Research in Mathematics Education, 21(1), 33–46. Hestenes, D. (1987). Toward a modeling theory of physics instruction. American Journal of Physics, 55, 440–454. Hestenes, D. (1997). Modeling methodology for physics teachers. In E. Redish & J. Rigden (Eds.), The changing role of the physics department in modern universities (Vol. II, pp. 935–957). New York: Springer-Verlag. Hestenes, D. (2006). Notes for a Modeling Theory of Science, Cognition and Instruction. Paper presented at the GIREP Conference, Modeling in Physics and Physics Education, Amsterdam, Netherlands. Hestenes, D. (2009). Modeling instruction for STEM education reform. Tempe, AZ: Arizona State University. Hill, H. C., Rowan, B., & Ball, D. L. (2005). Effects of teachers’ mathematical knowledge for teaching on student achievement. American Educational Research Journal, 42, 371–406. Hill, H. C., Schilling, S. G., & Ball, D. L. (2004). Developing knowledge of teachers’ mathematics knowledge of teaching. The Elementary School Journal, 105, 11–30. Ingersoll, R. (2003). Is there a shortage among mathematics and science teachers? Science Educator, 12, 1–9. Ingersoll, R. M. (1999). The problem of underqualified teachers in American secondary schools. Educational Researcher, 28, 26–37. Ingersoll, R. M. (2001). Teacher turnover, teacher shortages and the organization of schools. Seattle, WA: University of Washington, Center for the Study of Teaching and Policy. Ingersoll, R. M. (2002). Out-of-field teaching, educational inequality and the organization of schools: An exploratory analysis. Seattle, WA: University of Washington, Center for the Study of Teaching and Policy. Javier, J. (2010). Teachers in Phoenix area having to take 2nd jobs. Arizona Republic. Retrieved from http://www.azcentral.com/community/gilbert/ articles/2010/03/31/20100331teachers-taking-second-jobs-ev-CP.html Koirala, H. P., & Bowman, J. K. (2003). Preparing middle level preservice teachers to integrate mathematics and science: Problems and possibilities. School Science and Mathematics, 103, 145–154. Lemke, M., Sen, A., Pahlke, E., Partelow, L., Miller, D., Williams, T., . . . Jocelyn, L. (2004). International outcomes of learning in mathematics literacy and problem solving: PISA 2003 results from the U.S. perspective. 464
(NCES 2005–003). Washington, DC: U.S. Department of Education, National Center for Education Statistics. McBride, J. W., & Silverman, J. L. (1991). Integrating elementary/middle school science and mathematics. School Science and Mathematics, 91, 18–25. Middleton, J. A. (2008). The preparation and support of mathematics and science teachers in Arizona. In W. Doyle (Ed.), Who will teach our children? (pp. 133–152). Phoenix, AZ: 92nd Arizona Town Hall. Retrieved from http://www.aztownhall.org/pdf/92nd_Workbook_complete.pdf Middleton, J. A., & Spanias, P. A. (1999). Motivation for achievement in mathematics: Findings, generalizations, and criticisms of the research. Journal for Research in Mathematics Education, 30, 65–88. Moin, L. J., Dorfield, J. K., & Schunn, C. D. (2005). Where can we find future K-12 science and mathematics teachers? A search by academic year, discipline, and academic performance level. Science Education, 89, 980– 1006. National Council of Teachers of Mathematics (NCTM). (2000). Principles and standards for school mathematics. Reston, VA. National Research Council (NRC). (1996). National science education standards. Washington, DC: National Academy of Press. National Research Council (NRC). (2002). Attracting science and mathematics PhDs to secondary school education. Committee on Attracting Science and Mathematics PhDs. Office of Scientific and Engineering Personnel. Washington, DC: National Academy of Press. National Science Foundation. (2004). Science and engineering indicators 2004. Elementary and secondary education. Washington, DC: Author. Offer, J., & Vasquez-Mireles, S. (2009). Mix it up: Teachers’ beliefs on mixing mathematics and science. School Science and Mathematics, 109, 146–152. Perry, D. G., & Bussey, K. (1979). The social learning theory of sex differences: Imitation is alive and well. Journal of Personality and Social Psychology, 37, 1699–1712. Public Education Finances. (2010). US Census Bureau. Richardson, F. C., & Suinn, R. M. (1972). Mathematics anxiety rating scale: Psychometric data. Journal of Counseling Psychology, 19, 551–554. Riggs, I. M., & Enochs, L. G. (1990). Toward the development of an elementary teachers science teaching efficacy belief instrument. Science Education, 74, 625–637. Romero, M. (2008). Title II funding survey. Chandler, AZ: Chandler Unified School District. Shugart, S., & Hounshell, P. (1995). Subject matter competence and the recruitment and retention of secondary science teachers. Journal of Research in Science Teaching, 32, 63–70. Shulman, L. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14. Shulman, L. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57(1), 1–22. U.S. Department of Education. (2000). Before It’s Too Late: A Report to the Nation from the National Commission on Mathematics and Science Teaching for the 21st Century [On-line]. Available from http://www.ed.gov.inits/ Math/glenn U.S. Department of Education. (2004). Highlights from the trends in international mathematics and science study (TIMSS) 2003. (NCES 2005-005). Washington, DC: National Center for Education Statistics. U.S. Department of Education. (2010). Teacher shortage areas nationwide listing, 1990–91 through 2010–2011. Washington, DC: Office of Postsecondary Education. U.S. Department of Education, The National Commission on Excellence in Education. (1983). A nation at risk: The imperative for educational reform. A report to the Nation and the Secretary of Education. Washington, DC: Author. Utley, J., Moseley, C., & Bryant, R. (2005). Relationship between science and mathematics teaching efficacy of preservice elementary teachers. School Science and Mathematics, 105, 82–88. Volume 112 (8)
Beyond the Transcript
Wells, M., Hestenes, D., & Swackhamer, G. (1995). A modeling method for high school physics instruction. American Journal of Physics, 63, 606– 619. Wobmann, L. (2003). Schooling resources, educational institutions, and student performance: The International evidence. Oxford Bulletin of Economics and Statistics, 65(2), 117–170. Wolfe, L. F. (1990). Teaching science to gifted underachievers: A conflict of goals. Journal of Education, 6, 88–97. Woolfolk, A. E., & Hoy, W. K. (1990). Prospective teachers’ sense of efficacy beliefs about control. Journal of Educational Psychology, 82, 81–91.
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