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High School Teachers’ Self-efficacy in Teaching Computer Science

Authors:

Christian Fischer,

Debra Richardson,

Mark WarschauerAuthors Info & Claims

ACM Transactions on Computing Education (TOCE), Volume 20, Issue 3

Article No.: 23, Pages 1 - 18

https://doi.org/10.1145/3410631

Published: 01 September 2020 Publication History

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Abstract

Self-efficacy is an important construct for CS teachers’ professional development, because it can predict both teaching behaviors as well as student outcomes. Research has shown that teachers’ self-efficacy can be as influential as their actual level of knowledge and abilities. However, there has been very limited research on CS teachers’ self-efficacy. This study describes the development and implementation of an instrument that measures secondary school teachers’ self-efficacy in teaching computer science. Teachers attended a nine-week hybrid professional development program and completed the computer science teaching self-efficacy instrument. Confirmatory factor analysis validated the self-efficacy instrument, which can be potentially used in other CS education settings. The results also indicated that teachers’ self-efficacy in the content knowledge and pedagogical content knowledge dimensions of teaching computer science significantly increased from participating in the professional development program.

References

[1]

2016. K-12 Computer Science Framework steering committee. Technical Report. Retrieved from http://www.k12cs.org.

[2]

William Aspray. 2016. Recent efforts to broaden informal computer science education. In Participation in Computing. Springer, Cham, 147--163.

[3]

Richard P. Bagozzi, Youjae Yi, and Lynn W. Phillips. 1991. Assessing construct validity in organizational research. Admin. Sci. Quart. 36, 3 (1991), 421.

[4]

Deborah Loewenberg Ball, Mark Hoover Thames, and Geoffrey Phelps. 2008. Content knowledge for teaching: What makes it special? Journal of Teacher Education 59, 5 (2008), 389--407.

[5]

Albert Bandura. 1986. The explanatory and predictive scope of self-efficacy theory. J. Soc. Clin. Psychol. 4, 3 (1986), 359--373.

[6]

Albert Bandura. 1993. Perceived self-efficacy in cognitive development and functioning. Educ. Psychol. 28, 2 (1993), 117--148.

[7]

A. Bandura. 1994. Self-efficacy. In Encyclopedia of Human Behavior, Vol. 4, V. S. Ramachaudran (Ed.). Academic Press, New York, 71--81.

[8]

Albert Bandura. 2006. Guide for constructing self-efficacy scales. In Self-efficacy Beliefs of Adolescents, Tim Urdan and Frank Pajares (Eds.). IAP, 307--337.

[9]

Albert Bandura. 2011. Social cognitive theory. In Handbook of Social Psychological Theories, Paul A. M. Van Lange, Arie W. Kruglanski, and E. Tory Higgins (Eds.). Sage, 349--373.

[10]

Albert Bandura, C. Barbaranelli, G. V. Caprara, and C. Pastorelli. 2001. Self-efficacy beliefs as shapers of children’s aspirations and career trajectories.Child Dev. 72, 1 (2001), 187--206.

[11]

N. Bean, J. Weese, R. Feldhausen, and R. S. Bell. 2015. Starting from scratch: Developing a pre-service teacher training program in computational thinking. In Proceedings of the IEEE Frontiers in Education Conference (FIE’15). 1--8.

[12]

Robert E. Bleicher. 2004. Revisiting the STEBI-B: Measuring self-efficacy in preservice elementary teachers. School Sci. Math. 104, 8 (2004), 383--391.

[13]

H. Borko. 2004. Professional development and teacher learning: Mapping the terrain. Educ. Res. 33, 8 (2004), 3--15.

[14]

Hilda Borko, J. Jacobs, and K. Koellner. 2010. Contemporary approaches to teacher professional development. In International Encyclopedia of Education, Penelope Peterson, Eva Baker, and Barry McGaw (Eds.). Elsevier, Oxford, UK, 548--556.

[15]

Quincy Brown and Amy Briggs. 2015. The CS10K initiative. ACM Inroads 6, 3 (2015), 52--53.

Digital Library

[16]

Luis M. Carrascal, Ismael Galván, and Oscar Gordo. 2009. Partial least squares regression as an alternative to current regression methods used in ecology. Oikos 118, 5 (2009), 681--690.

[17]

Computer Science Teachers Association. 2017. CSTA K-12 Computer Science Standards. Retrieved from http://www.csteachers.org/standards.

[18]

Linda Darling-Hammond, Maria E. Hyler, and Madelyn Gardner. 2017. Effective Teacher Professional Development. Technical Report. Learning Policy Institute, Palo Alto, CA. Retrieved from https://learningpolicyinstitute.org/product/teacher-prof-dev.

[19]

C. Dede. 2006. Scaling up: Evolving innovations beyond ideal settings to challenge contexts of practice. In The Cambridge Handbook of Learning Sciences, R. K. Sawyer (Ed.). Cambridge University Press, New York, NY, 551--556.

[20]

Chris Dede, Diana Jass Ketelhut, P. Whitehouse, L. Breit, and E. M. McCloskey. 2008. A research agenda for online teacher professional development. J. Teach. Educ. 60, 1 (2008), 8--19.

[21]

Chris Dede, Diane Jass Ketelhut, Pamela Whitehouse, Lisa Breit, and Erin M. McCloskey. 2009. A research agenda for online teacher professional development. J. Teach. Educ. 60, 1 (2009), 8--19.

[22]

Laura Desimone. 2009. Improving impact studies of teachers’ professional development: Toward better conceptualizations and measures. Educ. Res. 38, 3 (2009), 181--199.

[23]

Laura Desimone and Michael S. Garet. 2015. Best practices in teachers’ professional development in the United States. Psychol. Soc. Educ. 7, 3 (2015), 252--263.

[24]

Carsten F. Dormann, Jane Elith, Sven Bacher, Carsten Buchmann, Gudrun Carl, Gabriel Carré, Jaime R. García Marquéz, Bernd Gruber, Bruno Lafourcade, Pedro J. Leitão, Tamara Münkemüller, Colin McClean, Patrick E. Osborne, Björn Reineking, Boris Schröder, Andrew K. Skidmore, Damaris Zurell, and Sven Lautenbach. 2013. Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 1 (2013), 27--46.

[25]

Jonathan Drennan and Abbey Hyde. 2008. Controlling response shift bias: The use of the retrospective pre-test design in the evaluation of a master’s programme. Assess. Eval. High. Educ. 33, 6 (2008), 699--709.

[26]

Educational Testing Service. 2015. The Praxis Computer Science test: Test at a glance. Retrieved from https://www.ets.org/c/praxis/30167/pdf/Praxis-computer-science-test-at-glance-advance-copy.pdf.

[27]

Christian Fischer, Arthur Eisenkraft, Barry Fishman, Nicolas Hübner, and Frances Lawrenz. 2018. Adapting to the large-scale advanced placement chemistry reform: An examination of teachers’ challenges and instructional practices. J. Chem. Educ. 95, 10 (2018), 1701--1710.

[28]

Barry Fishman, Spyros Konstantopoulos, Beth W. Kubitskey, Richard Vath, Gina Park, Heather Johnson, and Daniel C. Edelson. 2013. Comparing the impact of online and face-to-face professional development in the context of curriculum implementation. J. Teach. Educ. 64, 5 (2013), 426--438.

[29]

Barry Fishman, Ronald W. Marx, Stephen Best, and Revital T. Tal. 2003. Linking teacher and student learning to improve professional development in systemic reform. Teach. Teach. Educ. 19, 6 (2003), 643--658.

[30]

Kim Frumin, Chris Dede, Christian Fischer, Brandon Foster, Frances Lawrenz, Arthur Eisenkraft, Barry Fishman, Abigail Jurist Levy, and Ayana McCoy. 2018. Adapting to large-scale changes in advanced placement biology, chemistry, and physics: The impact of online teacher communities. Int. J. Sci. Educ. 40, 4 (2018), 397--420.

[31]

Joanna Goode, Gail Chapman, and Jane Margolis. 2012. Beyond curriculum: The exploring computer science program. ACM Inroads 3, 2 (2012), 47--53.

Digital Library

[32]

Joanna Goode, Jane Margolis, and Gail Chapman. 2014. Curriculum is not enough: The educational theory and research foundation of the exploring computer science professional development model. In Proceedings of the 45th Annual ACM SIGCSE Conference. 493--498.

Digital Library

[33]

John W. Graham. 2009. Missing data analysis: Making it work in the real world. Annual Rev. Psychol. 60, 1 (2009), 549--576.

[34]

P. Grossman. 1990. The Making of a Teacher: Teacher Knowledge and Teacher Education. Teachers College Press, New York.

[35]

Suchi Grover and Roy Pea. 2013. Computational thinking in K-12: A review of the state of the field. Educ. Res. 42, 1 (2013), 38--43.

[36]

Mark Guzdial and Briana Morrison. 2016. Growing computer science education into a STEM education discipline. Commun. ACM 59, 11 (2016), 31--33.

Digital Library

[37]

Joe F. Hair, Marko Sarstedt, Christian M. Ringle, and Jeannette A. Mena. 2012. An assessment of the use of partial least squares structural equation modeling in marketing research. J. Acad. Market. Sci. 40, 3 (2012), 414--433.

[38]

Joseph F. Hair Jr., G. Tomas M. Hult, Christian Ringle, and Marko Sarstedt. 2016. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications.

[39]

Jörg Henseler, Geoffrey Hubona, and Pauline Ash Ray. 2016. Using Please path modeling in new technology research: Updated guidelines. Industr. Manag. Data Syst. 116, 1 (2016), 2--20.

[40]

Jörg Henseler, Christian M. Ringle, and Marko Sarstedt. 2015. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Market. Sci. 43, 1 (2015), 115--135.

[41]

Robin K. Henson. 2002. From adolescent angst to adulthood: Substantive implications and measurement dilemmas in the development of teacher efficacy research. Educ. Psychol. 37, 3 (2002), 137--150.

[42]

George S. Howard. 1980. Response-shift bias: A problem in evaluating interventions with pre/post self-reports. Eval. Rev. 4, 1 (1980), 93--106.

[43]

Peter Hubwieser, Michal Armoni, Michail N. Giannakos, and Roland T. Mittermeir. 2014. Perspectives and visions of computer science education in primary and secondary (K-12) schools. ACM Trans. Comput. Educ. 14, 2 (2014).

Digital Library

[44]

Jessica Ivy, Shelly Hollis, Dana Franz, Sarah Lee, and Donna Reese. 2017. Exploring pathways to developing self-efficacy in new computer science teachers. In Proceedings of the ASEE Zone II Conference. Retrieved from http://zone2.asee.org/sessions/program/3/37.pdf.

[45]

Michael J. Kennedy, Wendy J. Rodgers, John Elwood Romig, John Wills Lloyd, and Mary T. Brownell. 2017. Effects of a multimedia professional development package on inclusive science teachers’ vocabulary instruction. J. Teach. Educ. 68, 2 (2017), 213--230.

[46]

Mary M. Kennedy. 2016. How does professional development improve teaching? Rev. Educ. Res. 86, 4 (2016), 945--980.

[47]

Claudia Khourey-Bowers and Doris G. Simonis. 2004. Longitudinal study of middle grades chemistry professional development: Enhancement of personal science teaching self-efficacy and outcome expectancy. J. Sci. Teach. Educ. 15, 3 (2004), 175--195.

[48]

Robert M. Klassen, Virginia M. C. Tze, Shea M. Betts, and Kelly A. Gordon. 2011. Teacher efficacy research 1998-2009: Signs of progress or unfulfilled promise? Educ. Psychol. Rev. 23, 1 (2011), 21--43.

[49]

Paul Kline. 2014. An Easy Guide to Factor Analysis. Routledge, London.

[50]

Richard Ladner and Tammy VanDeGrift. 2011. Introduction to special issue (Part 1). ACM Trans. Comput. Educ. 11, 2 (2011).

Digital Library

[51]

Min Hsien Lee and Chin Chung Tsai. 2010. Exploring teachers’ perceived self efficacy and technological pedagogical content knowledge with respect to educational use of the world wide Web. Instruct. Sci. 38, 1 (2010), 1--21.

[52]

Jiangjiang Liu, Ethan Philip Hasson, Zebulun David Barnett, and Peng Zhang. 2011. A survey on computer science K-12 outreach: Teacher training programs. In Proceedings of the Frontiers in Education Conference (FIE’11). IEEE, T4F–1–T4F–6.

Digital Library

[53]

L. Llosa, O. Lee, F. Jiang, A. Haas, C. O’Connor, C. D. Van Booven, and M. J. Kieffer. 2016. Impact of a large-scale science intervention focused on English language learners. Amer. Educ. Res. J. 53, 2 (2016), 395--424.

[54]

Jane Margolis, Joanna Goode, and Gail Chapman. 2015. An equity lens for scaling. ACM Inroads 6, 3 (2015), 58--66.

Digital Library

[55]

Jane Margolis, Jean J. Ryoo, Cueponcaxochitl Dianna Moreno Sandoval, Clifford Lee, Joanna Goode, and Gail Chapman. 2012. Beyond access: Broadening participation in high school computer science. ACM Inroads 3, 4 (2012), 72--78.

Digital Library

[56]

Rick Marks. 1990. Pedagogical content knowledge: From a mathematical case to a modified conception. J. Teach. Educ. 41, 3 (1990), 3--11.

[57]

Gregoria Mateos-Aparicio. 2011. Partial least squares (PLS) methods: Origins, evolution, and application to social sciences. Commun. Stat. Theor. Meth. 40, 13 (2011), 2305--2317.

[58]

Michael McCracken, Tadeusz Wilusz, Vicki Almstrum, Danny Diaz, Mark Guzdial, Dianne Hagan, Yifat Ben-David Kolikant, Cary Laxer, Lynda Thomas, and Ian Utting. 2001. A multi-national, multi-institutional study of assessment of programming skills of first-year CS students. ACM SIGCSE Bull. 33, 4 (2001), 125.

Digital Library

[59]

Muhsin Menekse. 2015. Computer science teacher professional development in the United States: A review of studies published between 2004 and 2014. Comput. Sci. Educ. 25, 4 (2015), 325--350.

[60]

L. Nordén, L. Mannila, and A. Pears. 2017. Development of a self-efficacy scale for digital competences in schools. In Proceedings of the IEEE Frontiers in Education Conference (FIE’17). 1--7.

[61]

M. F. Pajares. 1992. Teachers’ beliefs and educational research: Cleaning up a messy construct. Rev. Educ. Res. 62, 3 (1992), 307--332.

[62]

C. Price and A. Chiu. 2018. An experimental study of a museum-based, science PD programme’s impact on teachers and their students. Int. J. Sci. Educ. 40, 9 (2018), 941--960.

[63]

Nicole F. Richter, Gabriel Cepeda, José L. Roldán, and Christian M. Ringle. 2016. European management research using partial least squares structural equation modeling (PLS-SEM). Europ. Manag. J. 34, 6 (2016), 589--597.

[64]

John Ross. 1992. Teacher efficacy and the effects of coaching on student achievement. Canad. J. Educ. 17, 1977 (1992), 51--65.

[65]

John Ross and Catherine Bruce. 2007. Professional development effects on teacher efficacy: Results of randomized field trial. J. Educ. Res. 101, 1 (2007), 50--60.

[66]

Guoyuan Sang, Jo Tondeur, Ching Sing Chai, and Yan Dong. 2016. Validation and profile of Chinese pre-service teachers’ technological pedagogical content knowledge scale. Asia-Pacific J. Teach. Educ. 44, 1 (2016), 49--65.

[67]

Ronny Scherer, Jo Tondeur, and Fazilat Siddiq. 2017. On the quest for validity: Testing the factor structure and measurement invariance of the technology-dimensions in the technological, pedagogical, and content knowledge (TPACK) model. Comput. Educ. 112 (2017), 1--17.

[68]

Anita M. Schuchardt, Miray Tekkumru-Kisa, Christian D. Schunn, Mary Kay Stein, and Birdy Reynolds. 2017. How much professional development is needed with educative curriculum materials? It depends upon the intended student learning outcomes. Sci. Educ. 101, 6 (2017), 1015--1033.

[69]

Dale H. Schunk and Ellen L. Usher. 2012. Social cognitive theory. In The Oxford Handbook of Human Motivation, Richard M. Ryan (Ed.). Vol. 1. Oxford University Press.

[70]

L. S. Shulman. 1986. Those who understand: Knowledge growth in teaching. Educ. Res. 15, 2 (1986), 4--14.

[71]

Einar M. Skaalvik and Sidsel Skaalvik. 2007. Dimensions of teacher self-efficacy and relations with strain factors, perceived collective teacher efficacy, and teacher burnout. J. Educ. Psychol. 99, 3 (2007), 611--625. 611

[72]

Einar M. Skaalvik and Sidsel Skaalvik. 2016. Teacher stress and teacher self-efficacy as predictors of engagement, emotional exhaustion, and motivation to leave the teaching profession. Creat. Educ. 7, 13 (2016), 1785--1799.

[73]

Kelley M. Skeff, Georgetite A. Stratos, and Merlynn R. Bergen. 1992. Evaluation of a medical faculty development program: A comparison of traditional pre/post and retrospective pre/post self-assessment ratings. Eval. Health Prof. 15, 3 (1992), 350--366.

[74]

Megan Tschannen-Moran and Anita Woolfolk Hoy. 2007. The differential antecedents of self-efficacy beliefs of novice and experienced teachers. Teach. Teach. Educ. 23, 6 (2007), 944--956.

[75]

Megan Tschannen-Moran and Denise Johnson. 2011. Exploring literacy teachers’ self-efficacy beliefs: Potential sources at play. Teach. Teach. Educ. 27, 4 (2011), 751--761.

[76]

J. H. Van Driel and A. Berry. 2012. Teacher professional development focusing on pedagogical content knowledge. Educ. Res. 41, 1 (2012), 26--28.

[77]

Ruth Chung Wei, Linda Darling-Hammond, Alethea Andree, Nikole Richardson, and Stelios Orphanos. 2009. Professional Learning in the Learning Profession: A Status Report on Teacher Development in the U.S. and Abroad. Technical Report. National Staff Development Council, Washington, DC.

[78]

Jason Williams and David P. MacKinnon. 2008. Resampling and distribution of the product methods for testing indirect effects in complex models. Struct. Equat. Model. 15, 1 (2008), 23--51.

[79]

Jeannette M. Wing. 2005. Computational thinking. Commun. ACM 49, 3 (2005), 33--35.

Digital Library

[80]

R. F. Woolson. 2008. Wilcoxon signed-rank test. In Wiley Encyclopedia of Clinical Trials.

[81]

Aman Yadav, Susanne Hambrusch, John T. Korb, and Sarah Gretter. 2014. Professional development for CS teachers: A framework and its implementation. In Proceedings of the Future of CS Education Summit. 2--5.

[82]

Marjolein Zee and Helma M. Y. Koomen. 2016. Teacher self-efficacy and its effects on classroom processes, student academic adjustment, and teacher well-being: A synthesis of 40 years of research. Rev. Educ. Res. 86, 4 (2016), 981--1015.

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Index Terms

High School Teachers’ Self-efficacy in Teaching Computer Science
1. Social and professional topics
  1. Professional topics
    1. Computing education

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cover image ACM Transactions on Computing Education

ACM Transactions on Computing Education Volume 20, Issue 3

September 2020

200 pages

EISSN:1946-6226

DOI:10.1145/3406963

Editor:
Chris Hundhausen
Washington State University, USA

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Published: 01 September 2020

Accepted: 01 June 2020

Revised: 01 June 2020

Received: 01 August 2019

Published in TOCE Volume 20, Issue 3

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