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Describing the Pre-service Teacher

Technological Pedagogical Content Knowledge (TPACK) Literature Using Confidence Intervals By Jamaal R. Young, Jemimah L. Young, Ziad Shaker, University of North Texas

Abstract

The validity and reliability of Technological Pedagogical Content Knowledge (TPACK) as a framework to measure the extent to which teachers can teach with technology hinges on the ability to aggregate results across empirical studies. The results of data collected using the survey of pre-service teacher knowledge of teaching with technology (TKTT) were synthesized using confidence intervals (CIs). Mean pre-service teacher TPACK point estimates were characterized by graphing CIs across studies from 2009 until 2011. The results present approximations of TPACK population parameters and implications for researchers and teacher educators. Keywords: TPACK, pre-service teachers, confidence intervals, literature review

T

he theoretical underpinning of the Technological Pedagogical Content Knowledge framework is well documented in the research literature (Koehler & Mishra, 2009; Mishra & Koehler, 2006; Mishra & Koehler, 2007). An entire handbook of TPACK was developed for educators in response to the influx of literature on the subject. Of the numerous TPACK research areas under investigation pre-service teacher preparation receives notable emphasis in the literature (Finger, Jamieson-Proctor, Albion, 2010; Jang & Chen, 2010; Kereluik, Casperson, & Akcaoglu, 2010; Ward & Overall, 2010). The attention placed on the theoretical and practical complexities of applying the TPACK framework as means to support pre-service

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teacher education has created a need to develop valid and reliable instruments to measure pre-service teacher knowledge of the framework. Several reviews of the current methodologies and instruments used to measure pre-service teacher TPACK exist (Abbitt, 2011). However, studies that synthesize the measurement of pre-service teacher TPACK are elusive. Meta-analytic studies of pre-service teacher TPACK are necessary because they can provide a means to examine the precision and consistency of measurements across studies. These results have implications for researchers as well as teacher educators.

Pre-service Teacher TPACK The TPACK framework merges technology with earlier work on Pedagogical Content Knowledge (PCK). Shulman (1986) explicated the interrelationship of pedagogy and content in relation to teacher effectiveness. Shulman’s work mediated the debate over the importance of content knowledge as opposed to pedagogical knowledge. This paradigm shift lead to drastic changes in pre-service teacher education and training. Mishra and Koehler (2006) then elaborated this initial model to address the need for teachers to understand how technology, pedagogy, and content afford and constrain one another. In an era of constant technological evolution this shift in thinking has the potential to have subsequent impacts on teacher education. Therefore, the accurate measurement of TPACK TechTrends • September/October 2012

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is imperative to teacher education. Seven separate components are included in the TPACK framework. The foundational components of the TPACK framework are: (a) Technology Knowledge (TK), (b) Pedagogical Knowledge (PK), and Content Knowledge (CK). Technology Knowledge refers to knowledge about different analog and digital technologies. Content knowledge is the knowledge of content and subject matter that is taught (Mishra & Koehler, 2006). Pedagogical knowledge is the methodology and processes of teaching including classroom management, assessment and lesson planning. These three types of knowledge intersect with one another to create the basic TPACK constructs: (a) Pedagogical Content Knowledge (PCK), (b) Technological Content Knowledge (TCK), and (c) Technological Pedagogical Knowledge (TPK) Technological Content Knowledge or TCK is the knowledge of how technology enhances the teaching of content. This type of knowledge is important for pre-service teachers because it supports the decisionmaking processes and skills necessary to choose appropriate technologies to support content learning. Likewise, this knowledge can help teachers avoid using inappropriate technology to teach content that is constrained or hindered by the use of that technology. Similarly, Technological Pedagogical Knowledge or TPK assists teachers in better understanding the affordances and constraints of technology on pedagogy. Teachers TPK helps them to design lessons and activities that use technology to assist in the acquisition of the content. Pedagogical activities that support learning, such as simulations, are delivered via technology, and TPK helps teacher facilitate these activities. According to Mishra and Koehler (2008) the intersection of PCK, TCK, and TPK is the quintessence of TPACK, and this type of knowledge is vitally important for teaching with technology. The different sets of knowledge and skills that TPACK encompasses require: an understanding of multiple representations of concepts using technologies; constructive pedagogical techniques that apply differentiated instructional technologies to meet the needs of all students; knowledge of nuances of particular content areas that make them difficult for students to comprehend and how technology can assist with student acquisition of the concepts; knowledge of scope and sequence of content and epistemological assumptions; and knowledge of how technologies can scaffold student content knowledge (Harris, Mishra, Koehler, 26

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2007). These skills are essential for pre-service teachers; therefore the adequate evaluation preservice teacher TPACK is vital. The context specific nature of the TPACK framework presents many challenges for the measurement and evaluation of pre-service teacher knowledge across the TPACK constructs.

Confidence Intervals as a Means to Characterize Pre-service Teacher TPACK The inability to aggregate valid and reliable results across studies hinders the development of TPACK as a framework to guide the measurement of pre-service teachers ability to teach with technology. According to Zientek, Yetkiner, and Thompson (2010) confidence intervals are one particularly useful medium for aggregating effects of prior research (p. 425). Confidence intervals provide a means to aggregate research across studies and draw conclusions about population parameter estimates and measurement precision. Cummings and Finch (2005) suggest that Confidence intervals have four major advantages. First confidence intervals give point estimates and intervals in measurement units that are comprehensible to the research context (Cummings & Finch, p.171). Confidence intervals are comprised of a point estimate of a population parameter (e.g., means, medians, effect sizes). In the context of the pre-service teacher TPACK mean pre-service teacher PCK, TCK, TPK, and TPACK point estimates are most appropriate. Secondly, there is a link between confidence intervals and p values, thus there is a translation to null hypothesis statistical significant testing (NHST) (Cummings & Finch, p. 171). Thirdly, confidence intervals support meta-analytic thinking by helping to combine evidence across studies (p. 171). Thus, confidence intervals could be used to aggregate evidence across the various studies of pre-service teacher TPACK and present a meta-analytic review of the results. Finally, confidence intervals provide information about the precision of measurements across studies (p. 171). The confidence intervals for pre-service teacher mean TPACK point estimates allow researchers to survey the results across administrations and evaluate the precision of measurement. The aggregation of pre-service mean TPACK point estimates across studies using confidence intervals would allow researchers to evaluate the quality of measurement precision between studies as well as the consistency in the Volume 56, Number 5

measurement of the constructs. These results would provide estimates of population parameters and support implications for further TPACK research and practice. However, the validity of these measurements hinges on the selection and implementation of an appropriate instrument to measure pre-service teacher TPACK.

Pre-service Teacher TPACK Survey Instruments Several survey instruments are currently available to measure teacher TPACK (Archambault, & Crippen, 2009; Jamieson-Proctor, Finger, Albion, 2010; Mishra & Koehler, 2005; Schmidt, Baran, Thompson, Koehler, Sahin & Erdogan, 2010; Shin,  & Mishra, 2009). However, some of the aforementioned instruments were designed for use with in-service teachers. Table 1 presents the descriptive information for the available pre-service teacher TPACK survey instruments and excludes instruments designed for in-service teachers. The pre-service teacher TPACK surveys presented in table 1 were designed to assess pre-service teacher TPACK in different contexts.

Mishra and Koehler (2005) designed their survey for administration in a specific faculty development course to measure participant attitudes, opinions, and learning. Because the focus of the course was learning by the design, faculty as well as graduate students participated in the course and survey. Accordingly, the questions in the survey were written specifically for this context. For example, one item read, “Our group has been considering how course pedagogy and technology influence one another” (Mishra & Koehler, 2005). The Schmidt et al. (2009) survey was designed to measure preservice early childhood education (ECE) teachers TPACK. Thus, the items address mathematics, science, literacy and social studies content, which is commonly taught in ECE. The Sahin and Erdogan (2010) survey was administered to college students to address their acquaintance with different applications of TPACK. The TPACK Confidence survey addressed specific elements of TPACK as the related to Information Communication Technology (ICT). Jamieson-Proctor, Finger, Albion (2010) administered the survey to senior pre-service teachers in association with an ICT course. The design

Table 1. TPACK Survey Descriptions

Study D

escription

Population of Interest N

umber of items

Mishra & Koehler (2005)

Survey Designed to assess preservice teachers perceptions of the classroom environment and TPACK

Pre-service teachers 3

Schmidt et al. (2009)

Survey designed to assess preservice (Early childhood) teachers TPACK

Pre-service Early Childhood teachers

47

Sahin & Erdogan (2010)

Survey designed to assess college students perceptions of TPACK

College Students

47

JamiesonProctor, Finger, Albion (2010)

TPACK Confidence Survey – combination of Learning with ICT & ICT Audit Survey

Final year Pre-service teachers

25

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of each of these surveys although very specific, is consistent with the nature of the TPACK framework. The specific nature of the available TPACK instruments may limit the broader applications to different context (Abbitt, 2011), but a universal survey instrument is not available, neither is it reflective of the TPACK framework. Although several instruments currently exist to measure teacher TPACK, studies summarizing the current pre-service teacher TPACK knowledge base are elusive. The lack of research synthesis is partly attributed to the context specific nature of the TPACK framework that limits the numbers of studies that can reasonably be compared. Despite these limitations the need for a valid and reliable measure of teacher TPACK is imperative (Mishra & Koehler, 2006; Schmidt et al., 2009). The survey developed by Schmidt et al. (2009) is the most universally used survey, and encompasses most of the aspects of TPACK associated with pre-service teacher education. This survey is not perfect, but very appropriate for the description of pre-service teacher TPACK given its support in the literature.

Purpose The purpose of this study was to summarize the current literature on pre-service teacher TPACK and provide implications for researchers and teachers. This study aggregates the research on pre-service teacher TPACK, and more specifically within the research using the survey of pre-service teacher knowledge of teaching and technology (TKTT). The TKTT is a survey instrument designed specifically to measure pre-service teacher TPACK with an internal reliability that ranges from .80 to .92 (Schmidt et al., 2009). The individual reliability for Content Knowledge, Pedagogy Knowledge, Pedagogical Content Knowledge, Technological Content Knowledge, Technological Pedagogical Knowledge, and Technological Pedagogical Content Knowledge are .85, .84, .85, .86, .80, and .92, respectively (Schmidt et al.). The survey is scored on a 5-point likert scale where a score of 1 is assigned to strongly disagree and a score of 5 is assigned to strongly agree. The scores with in each construct are then averaged and the average constitutes the score for that construct. Although the TKTT is one of many surveys available to measure teacher TPACK, the TKTT is the most suitable for the purpose of this study because of its broad applications across pre-service teaching.

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Method To locate studies that measured TPACK using the TKTT survey a four-step process was applied. First, four databases from 2009 until 2011 were searched using the key words “TPACK” “TPCK”, Technological Pedagogical Content Knowledge, and pre-service teachers. The initial year of 2009 was selected although TPACK was first proposed by in Pierson (2001) Technology integration practice as a function of pedagogical expertise because the TKTT was not available until 2009. The four databases were the Educational Resources Information Center (ERIC), Education and Information Technology Digital Library, PyschInfo Search, and ProQuest Dissertations and Thesis. Then a search of journals with a technology focused was conducted. These journals included, Journal of Computers in Mathematics and Science Teaching (JCMST), Journal of Interactive Learning Research (JILR), Journal of Technology and Teacher Education (JTATE), AACE Journal, and, Contemporary Issues in Technology & Teacher Education (CITE). Finally, other articles were selected from the references cited within the retrieved studies. These procedures yielded 139 appropriate articles, conference presentations, theses, and dissertations. The methodology and results sections were then read to establish pertinence. A study was considered pertinent if (a) the study used the TKTT survey to measure the TPACK, (b) the article provided sufficient details to categorize the sample accordingly, and (c) statistical data such as the mean, standard deviation, and sample size were present or could be obtained reasonably. After each article was reviewed the initial pool of 139 articles was reduced to 10 studies that met all of the criteria for this study. The articles with preceding superscripts denote the 10 studies used in the present study. Procedures To compare the various confidence intervals across studies, the conventional 95% confidence level was chosen because it is the most commonly found level in the literature. Fortunately, all of the studies selected provided all the information pertinent to the confidence interval calculations, thus no other information was needed. The stock option in Microsoft Excel was used to create the graphical displays of the confidence intervals for the four major constructs (PCK, TCK, TPK, and TPACK). The point and interval estimates for the individual means for each study was compared to the other studies

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on the four TPACK constructs. The purpose of this comparison was twofold. First this allows the one to assess the precision of the point and interval estimates in comparison to other studies. Secondly, the reasonableness of the mean point estimates can be assessed across studies. Both of these assessments are performed by means of visual inspection and are to a certain degree subjective, but guided by sound theory. The precision of the point estimate hinges upon the margin of error associated with the point estimate. According to Cumming and Finch (2005) the confidence interval will be a range centered on M, and extending a distance w on either side of M, where w (for width) is called the margin of error (p. 170). Therefore, confidence intervals with a smaller margin of error or width are more precise. The margin of error is based on the standard error and is a function of the SD and n, as seen in the formula for standard error SE = SD/√n (Cumming & Finch). The confidence intervals that have narrowed bands or widths are more precise and tend to have a large sample sizes or smaller SDs. This logic holds true with the studies presented in this analysis. Because the sample sizes in some of the studies were relatively small comparing the point and interval estimates across studies allows one to better ascertain the relative precision of the estimates across studies.

Results The ten studies included eight journal articles, one dissertation, and one conference presentation. The study sample sizes ranged from 12 to 1664, with a median sample size of 146.

The larger sample sizes yielded smaller confidence intervals; likewise the smaller sample sizes yielded larger confidence intervals. The ten samples in this study are comprised of five samples of Early Childhood Education majors (ECE), and five secondary content specialist groups. The studies were organized by participate characteristics for ease of comparison, thus the five ECE studies were clustered together, and likewise the five secondary content specialist studies were clustered together. The study years of publication ranged from 2009 to 2011, with two studies published in 2009, three studies published in 2010, and five studies published in 2011. The references for all studies included in this analysis are located in Appendix. Each reference is preceded by a superscript that corresponds to the order of representation in each figure. For example a superscript of 1-1 indicates that the referenced article was located in figure one and was the first study in the figure. Pre-service Teacher Pedagogical Content Knowledge The 95 % CI for the mean scores of pre-service teachers in these studies are presented in figure 1. A subjective comparison of the overlaps in figure one suggested that the mean PCK of pre-service teachers ranges from 3.4 to 3.8. Studies five and eight from the secondary content specific cluster fall way outside the ranges presented here. These studies were therefore considered outliers and not included in the range for the population approximation. Furthermore, studies five and eight were among the studies with the smallest samples sizes 12

Figure 1. Confidence intervals for mean Pedagogical Content Knowledge (PCK) of pre-service teachers

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and 24 respectively. The relatively large widths of these confidence intervals are indicative of the smaller sample sizes that constitute larger amounts of sampling error. Pre-service Teacher Technological Pedagogical Knowledge Confidence intervals for mean pre-service teacher TPK are presented in figure 2. The approximate mean TPK score for the pre-service teacher population is between 3.6 and 4.0. Studies six and nine represent outliers in this analysis and thus are not representative of the remaining mean scores. Although the study numbers are

different for figure 2, studies six and nine are the same studies from the secondary content specific cluster that were outliers in the previous analysis. The confidence intervals for studies six and nine are much smaller than the confidence intervals for the mean PCK scores, this suggest that the SD for these scores is much smaller, because the sample size did not change. Pre-service Teacher Technological Content Knowledge Mean confidence intervals for TCK are presented in figure 3. As shown in the figure the spread of scores for TCK are less concentrated in

Figure 2. Confidence intervals for mean Technological Pedagogical Knowledge (TPK) of pre-service teachers

Figure 3. Confidence intervals for mean Technological Content Knowledge (TCK) of pre-service teachers

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Figure 4. Confidence intervals for mean Technological Pedagogical Content Knowledge (TPACK) of pre-service teachers

a specific range and appear to have more variation between mean confidence intervals. Thus, the approximate population range of mean TCK scores is slightly larger, 3.2 to 3.6. The same two studies from the secondary content specific cluster continue to fall outside the range of the other studies, and studies six and eight fall slightly below and above the range respectively. Furthermore, two additional studies fall outside the range. First study two from the ECE cluster falls just outside the range, and study seven from the secondary content specific cluster falls well outside the range. These variations suggest that pre-service teacher TCK is less consistent across the studies presented here. Pre-service Teacher TPACK Figure 4 shows the mean pre-service teacher confidence intervals for TPACK. The approximate range for pre-service teacher TPACK is between 3.4 and 3.8. Studies six, eight, and nine from the secondary content specific cluster fall well outside this range and should thus be considered as outliers. The widest confidence interval shown in figure four is for study number two which has the third smallest sample size. The remaining confidence intervals are relatively small, which indicates high levels of precision present in the measurements.

Discussion The purpose of this study was to summarize the current literature on pre-service teacher TPACK and provide implications for researchers and teachers. The TKTT mean Confidence intervals for the TPK, TCK, PCK, and TPACK Volume 56, Number 5

constructs were used as a means of metaanalytically summarizing the TPACK literature. The results of this study present implications for teacher educators and researchers, and provide approximations of the population means for the four TPACK constructs analyzed. The approximate mean score population for PCK, TPK, TCK, and TPACK respectively are 3.4-3.8, 3.6-4.0, 3.2-3.8, and 3.4-3.8. Thus, pre-service teachers report to have and above average knowledge of PCK, TPK, TCK, and TPACK. Ideally, one would like for the mean scores to fall between the 4.0-5.0 score range, however these results are representative of only three years of data collection. Although these results suggest that pre-service teachers have room to improve, the results are an evaluation of pre-service teacher TPACK in its infancy. Of the three constructs analyzed in this study TCK mean confidence intervals were the least consistently measured. The spread of the mean confidence intervals for TCK were less concentrated in terms of overlap between confidence intervals. Furthermore, the widths of the confidence bands were wider than the bands for the same studies mean scores on the other constructs. This suggests that the level of precision in the measurement of this construct is not as precise as the measurement of the other constructs. Sampling error may account for a significant amount of the lack of consistency and overlap in the TCK construct mean CIs. This initial characterization of pre-service teacher mean TPACK suggest that pre-service teachers have a stable foundation upon which TechTrends • September/October 2012

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teacher educators can build new knowledge and skills for teaching with technology. According to Hughes (2005) teacher knowledge affects teachers’ actions in the classroom. Therefore, if pre-service teachers possess the appropriate knowledge to teach with technology then the translation of this knowledge to the classroom is reasonable. Since the results indicate that preservice teachers exhibit above average knowledge of TPACK more classroom resources can be allocated to transition TPACK knowledge into practice. Transitioning pre-service teachers beyond their knowledge of TPACK to formal implementation of their knowledge is difficult (McDougall, 2008; Law, Pelgrum & Anderson, 2008; Lock & Redmond, 2010). Likewise, practices to increase pre-service teacher implementation of TPACK are currently scarce. The development of these practices is essential to the development of pre-service teachers that are equipped to maximize the technology at their disposal. This study also provides several research implications. Although TPACK is a fairly new framework more research is needed to ascertain better approximations of the mean levels of TPACK possessed by pre-service teachers. The TKTT is one of several survey instruments available to measure pre-service teacher TPACK, but it is specially designed for early childhood teachers, which limits its use in other areas. The results of this study indicate that the current measurements of mean PCK, TPK, and overall TPACK are relatively consistent, however the mean confidence intervals for TCK are less consistent and precise. The lack of overlap shown in the TCK scores is indicative of the difficulty in applying this survey across content specific context. Because the TCK construct is the most content specific TPACK construct it is plausible that some of the variation in mean scores is due to the various groups of pre-service teachers represented in this study. Thus, the development of content specific measures of TPACK is essential to the refinement of the TPACK framework. Several content specific instruments and standards are currently available for science and mathematics, (Graham, Burgoyne, Cantrell, Smith, St. Clair, & Harris, 2009; Niess, et al., 2009). More work is needed to development instruments and standards for other content areas such as social studies, literacy, and the arts. One difficulty in aggregating the TPACK literature is the nature of the framework, which is context specific, but as more instruments and standards are developed researchers can begin to draw better conclusion about teach32

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ing with technology across content areas. These conclusions can then help to better inform teaching and learning with technology across all content areas, which is one of the major goals of the TPACK framework. Jamaal Young, Ph.D. is an Assistant Professor at the University of North Texas. His research interest revolves around the use of technology to develop teacher’s knowledge of mathematics. Other emphases in his work are culturally responsive STEM education and mathematics achievement of children of color. Jemimah Young focuses her attention on preparing preservice teachers to meet the needs of all their students. Her research interest is in the investigation of alternative cultures in education. Other emphases in her work are culturally responsive education and achievement of children of color. Ziad Shaker is currently a doctoral candidate at the University of North Texas specializing in curriculum and instruction studies in the field of science education. His doctoral research is in the use of concept maps to assess elementary pre-service teachers’ understanding of science concepts and misconceptions using Vygotsky’s theory of concept development.

References Abbitt, J. T. (2011). Measuring technological pedagogical content knowledge in preservice teacher education: A review of current methods and instruments. Journal of Research on Technology in Education, 43(4), 281300. Archambault, L., & Crippen, K. (2009). Examining TPACK among K-12 online distance educators in the United States. Contemporary Issues in Technology and Teacher Education, 9(1), 71-88. Baran, E., Chuang, H., Thompson, A. (2011). TPACK: An emerging research and development took for teacher educators. The Turkish Online Journal of Educational Technology, 10(4), 370-377. Cummings, G., & Finch, S. (2005). Inference by eye: Confidence intervals and how to read pictures of data. American Psychologist, 60(2), 170-180. Finger, G., Jamieson-Proctor, R., Albion, P. (2010). Beyond Pedagogical Content Knowledge: The importance of TPACK for informing preservice teacher education in Australia. In M.Turcanyis-Szabo & N. Reynolds (Eds.), Key competencies in the knowledge society (pp. 114-125). Berlin, Heidelberg: Springer. Graham, C. R., Burgoyne, N., Cantrell, P., Smith, L., St. Clair, L., & Harris, R. (2009). TPACK development in science teaching: Measuring the TPACK confidence of inservice science teachers. Tech Trends, 53(5), 7079. Harris, J. B., Mirsha, P., & Koehler, M. J. (2007, April). Teachers’ technological pedagogical content knowledge: Curriculum-based technology integration reframed. Paper presented at American Educational Research Association conference, Chicago, IL.

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Hughes, J. (2005). The role of teacher knowledge and learning experience in forming technology-integrated pedagogy. Journal of Technology and Teacher Education, 13, 277-302 Jamieson-Proctor, R., Finger, G., & Albion, P., (2010). Auditing the TK and TPACK confidence of pre-service teachers: Are they ready for the profession? Australian Educational Computing, 25(1), 8-17. Jang, S., & Chen, K. (2010). From PCK to TPACK: Developing a transformative model for pre-service science teachers. Journal of Science Education and Technology 19(6), 533-564. Kereluik, K., Casperson, G. & Akcaoglu, M. (2010). Coding Pre-Service Teacher Lesson Plans for TPACK. In D. Gibson & B. Dodge (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference 2010 (pp. 3889-3891). Chesapeake, VA: AACE. Koehler, M., & Mishra, P. (2009). What is technological pedagogical content knowledge? Contemporary Issues in Technology and Teacher Education, 9(1), 60-70. Law, N., Pelgrum, W. J. & Plomp, T. (2008). Pedagogy and ICT use in schools around the world. Findings from the IEA SITES 2006 study. CERC Studies in comparative education. Hong Kong: Comparative Education Research Centre, The University of Hong Kong, and: Springer. Lock, J. V., & Redmond, P. (2010, December) Transforming pre-service teacher curriculum: observation through a TPACK lens. In: ASCILITE 2010: Curriculum, Technology and Transformation for an Unknown Future, 5-8, Sydney, Australia. McDougall, A. (2008). Models and practices in teacher education programs for teaching with and about ICT. In J. Voogt & G. Knezek (Eds.), International handbook of information technology in primary and secondary education (pp. 461 - 474). NewYork: Springer. Mishra, P., & Koehler, M. (2005). What happens when teachers design educational technology? The development of technological pedagogical content knowledge. Journal of educational Computing Research, 32(2), 131-152. Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for integrating technology in teachers’ knowledge. Teachers College Record, 108(6), 1017–1054. Mishra, P., & Koehler, M., J. (2007). Technological pedagogical content knowledge (TPCK): Confronting the wicked prob-

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lems of teaching with technology. In R. Carlsen, K. McFerrin, J. Price, R. Weber & D. A. Willis (Eds.), Proceedings of the Society for InformationTechnology & Teacher Education International Conference 2007 (pp.2214-2226). Chesapeake, VA:AACE. Mishra, P., & Koehler, M. (2008, March). Introducing technological pedagogical content knowledge. Paper presented at the annual meeting of the American Educational Research Association, New York. Niess, M. L., Ronau, R. N., Shafer, K. G., Driskell, S. O., Harper S. R., Johnston, C., Browning, C.,Ozgün-Koca, S. A., & Kersaint, G. (2009). Mathematics teacher TPACK standards and development model. Contemporary Issues in Technology and Teacher Education, 9(1), 4-24. Pierson, M. E. (2001). Technology integration practice as a function of pedagogical expertise. Journal of Research on Computing in Education, 33(3), 413-429. Sahin, I., & Erdogan, A. (2010). Relationship between math teacher candidates’ technological pedagogical and content knowledge (TPACK) and achievement levels. Procedia Social and Behavioral Sciences, 2, 2707-2711. Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Journal of Research on Technology in Education, 42(2), 123-149. Ward, G. & Overall, T. (2010). Pre-Service Teacher Technology Integration: The Team-Taught Cohort Model and TPACK. In D. Gibson & B. Dodge (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference 2010 (pp. 3944-3951). Chesapeake, VA: AACE. Zientek, L. R., Yetkiner, Z. E., & Thompson, B. (2010). Characterizing the mathematics anxiety literature using confidence intervals as a literature review mecha-

nism. The Journal of Educational Research, 103, 424-438.

Appendix: References for Studies Included in the Analysis Abitt, J. T. (2011). An Investigation of the Relationship between Self-Efficacy Beliefs about Technology Integration and Technological Pedagogical Content Knowledge (TPACK) among Preservice Teachers. Journal of Digital Learning in Teacher Education, 27(4), 134-143

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Agyei, D. & Voogt, J. (2011). Determining Teachers’ TPACK through observations and self-report data. In M. Koehler & P. Mishra (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference 2011 (pp. 2314-2319). Chesapeake, VA: AACE. 1-1,2-1,3-1,4-1 Baran, E., Chuang, H., Thompson, A. (2011). TPACK: An emerging research and development took for teacher educators. The Turkish Online Journal of Educational Technology, 10(4), 370-377. 4-4 Chai, C. S., Koh, J. H. L., & Tsai, C.-C. (2010). Facilitating Preservice Teachers’ Development of Technological, Pedagogical, and Content Knowledge (TPACK). Educational Technology & Society, 13 (4), 63–73. 2-3,4-3 Chai, C. S., Ling Koh, J. H., Tsai, C., Wee Tan, L. L. (2011). Modeling primary school pre-service teachers’ technological pedagogical content knowledge (TPACK) for meaningful learning with information and communication technology (ICT), Computers & Education, 57, 1184-1193. 1-6,2-8,3-5 Koh, J.H.L., Chai, C. S., & Tsai, C. C. (2010). Examining the technological pedagogical content knowledge of Singapore pre-service teachers with large-scale survey. Journal of Computer Assisted Learning, 26, 563-573. 1-3,2-4,3-3,4-3 Nathan, E. J. (2009). An examination of the relationship between pre-service teachers’ level of technology integration self-efficacy (TISE) and level of technological pedagogical content knowledge (TPACK) (Unpublished Dissertation). University of Houston, Houston, Tx. 1-7,2-7,3-6,4-7 Nordin, H., Morrow, D., & Davis, N. (2011). Pre-service teachers’ experience with ICT in secondary schools: A case study of one New Zealand context. Unpublished manuscript, College of education, University of Canterbury, New Zealand. 1-7,2-8,3-4,4-5 Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Journal of Research on Technology in Education, 42(2), 123-149. 1-8,2-9,3-8,4-9 Yang, H. H., & Chen, P., (2010). Building teachers’ TPACK through webquest development and blended learning process. Lecture Notes in Compute Science, 6248, 71-81. 1-5,2-6,3-7,4-6

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