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Evaluating Computer Science Professional Development for Teachers in the United States

Published: 18 November 2021 Publication History

Abstract

Teacher professional development (PD) is a key factor in enabling teachers to develop mindsets and skills that positively impact students. It is also a key step in building capacity for computer science (CS) education in K-12 schools. Successful CS PD meets primary learning goals and enable teachers to grow their self-efficacy, asset and equity mindset, and interest in teaching CS. As part of a larger study, we conducted a secondary analysis of CS PD evaluation instruments (). We found that instruments across providers were highly dissimilar with limited data collected for measures related to teacher learning, which has implications for future K-12 CS education. Likewise, the instruments were limited in being connected to student learning and academic growth. As a way to enable PD providers to construct measures that align with known impacting factors, we offer recommendations for collecting demographic data and measuring program satisfaction, content knowledge, pedagogical content knowledge, growth and equity mindset, and self-efficacy. We also highlight questions for PD providers to consider when constructing their evaluation, including reflecting community values, the goals of the PD, and how the data collected will be used to continually improve CS programs.

References

[1]
Ahmet Oguz Akturk and Handan Saka Ozturk. 2019. Teachers’ TPACK levels and students’ self-efficacy as predictors of students’ academic achievement. International Journal of Research in Education and Science 5 (2019). Issue 1.
[2]
Alicia C Alonzo. 2007. Challenges of simultaneously defining and measuring knowledge for teaching. (2007).
[3]
Daniel Alston, Jeff. Marshall, and Andrew Tyminski. 2017. Convincing Science Teachers for Inquiry-Based Instruction: Guskey’s Staff Development Model Revisited.Science Educator 25(2017). Issue 2.
[4]
Judy Anderson and Deborah Tully. 2020. Designing and Evaluating an Integrated STEM Professional Development Program for Secondary and Primary School Teachers in Australia. https://doi.org/10.1007/978-3-030-52229-2_22
[5]
Nalline Baliram and Arthur K. Ellis. 2019. The impact of metacognitive practice and teacher feedback on academic achievement in mathematics. School Science and Mathematics 119 (2019). Issue 2. https://doi.org/10.1111/ssm.12317
[6]
A. Bandura. 1997. Self-efficacy: The exercise of control.W H Freeman/Times Books/ Henry Holt & Co.
[7]
Eric R Banilower, P Sean Smith, Kristen A Malzahn, Courtney L Plumley, Evelyn M Gordon, and Meredith L Hayes. 2018. Report of the 2018 NSSME+.Horizon Research, Inc.(2018).
[8]
Jürgen Baumert and Mareike Kunter. 2013. The effect of content knowledge and pedagogical content knowledge on instructional quality and student achievement. In Cognitive activation in the mathematics classroom and professional competence of teachers. Springer, 175–205.
[9]
Patricia Benner. 1982. From novice to expert. American Journal of nursing 82, 3 (1982), 402–407.
[10]
Edward M Bettencourt, Maxwell H Gillett, Meredith Damien Gall, and Ray E Hull. 1983. Effects of teacher enthusiasm training on student on-task behavior and achievement. American educational research journal 20, 3 (1983), 435–450.
[11]
Moiz Bhai and Irina Horoi. 2019. Teacher characteristics and academic achievement. Applied Economics 51(2019). Issue 44. https://doi.org/10.1080/00036846.2019.1597963
[12]
David Blazar. 2016. Teacher and teaching effects on students’ academic performance, attitudes, and behaviors. Ph.D. Dissertation.
[13]
Rosemary Callingham, Colin Carmichael, and Jane M Watson. 2016. Explaining student achievement: The influence of teachers’ pedagogical content knowledge in statistics. International Journal of Science and Mathematics Education 14, 7(2016), 1339–1357.
[14]
Computer Science Teachers Association. 2021. Quality PD Indicators. https://www.csteachers.org/Page/quality-pd-review-process
[15]
National Research Council 2001. Classroom assessment and the national science education standards. National Academies Press.
[16]
Linda Darling-Hammond, Maria E Hyler, and Madelyn Gardner. 2017. Effective Teacher Professional Development. Research Brief.Learning Policy Institute(2017).
[17]
Sloan Davis, Jason Ravitz, and Juliane Blazevski. 2018. Evaluating Computer Science Professional Development Models and Educator Outcomes to Ensure Equity. 2018 Research on Equity and Sustained Participation in Engineering, Computing, and Technology, RESPECT 2018 - Conference Proceedings. https://doi.org/10.1109/RESPECT.2018.8491716
[18]
Yaron Doppelt, Christian D. Schunn, Eli M. Silk, Matthew M. Mehalik, Birdy Reynolds, and Erin Ward. 2009. Evaluating the impact of a facilitated learning community approach to professional development on teacher practice and student achievement. Research in Science and Technological Education 27 (2009). Issue 3. https://doi.org/10.1080/02635140903166026
[19]
Stuart E Dreyfus. 2004. The five-stage model of adult skill acquisition. Bulletin of science, technology & society 24, 3 (2004), 177–181.
[20]
David Dunning. 2011. The Dunning–Kruger effect: On being ignorant of one’s own ignorance. In Advances in experimental social psychology. Vol. 44. Elsevier, 247–296.
[21]
Anna J Egalite and Brian Kisida. 2018. The effects of teacher match on students’ academic perceptions and attitudes. Educational Evaluation and Policy Analysis 40, 1 (2018), 59–81.
[22]
Roger D Goddard, Laura LoGerfo, and Wayne K Hoy. 2004. High school accountability: The role of perceived collective efficacy. Educational Policy 18, 3 (2004), 403–425.
[23]
Thomas R Guskey. 2003. What makes professional development effective?Phi delta kappan 84, 10 (2003), 748–750.
[24]
Karla Hamlen, Nigamanth Sridhar, Lisa Bievenue, Debbie K. Jackson, and Anil Lalwani. 2018. Effects of teacher training in a computer science principles curriculum on teacher and student skills, confidence, and beliefs. SIGCSE 2018 - Proceedings of the 49th ACM Technical Symposium on Computer Science Education 2018-January. https://doi.org/10.1145/3159450.3159496
[25]
Ronald H Heck, Terry J Larsen, and George A Marcoulides. 1990. Instructional leadership and school achievement: Validation of a causal model. Educational Administration Quarterly 26, 2 (1990), 94–125.
[26]
Wayne K Hoy and John W Hannum. 1997. Middle school climate: An empirical assessment of organizational health and student achievement. Educational Administration Quarterly 33, 3 (1997), 290–311.
[27]
Helen H Hu, Cecily Heiner, Thomas Gagne, and Carl Lyman. 2017. Building a statewide computer science teacher pipeline. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education. 291–296.
[28]
Thomas J Kane, Daniel F McCaffrey, Trey Miller, and Douglas O Staiger. 2013. Have We Identified Effective Teachers? Validating Measures of Effective Teaching Using Random Assignment. Research Paper. MET Project.Bill & Melinda Gates Foundation(2013).
[29]
Erdogan Kaya, Ezgi Yesilyurt, Anna Newley, and Hasan Deniz. 2019. Examining the impact of a computational thinking intervention on pre-service elementary science teachers’ computational thinking teaching efficacy beliefs, interest and confidence. Journal of Computers in Mathematics and Science Teaching 38, 4(2019), 385–392.
[30]
Melanie M Keller, Knut Neumann, and Hans E Fischer. 2017. The impact of physics teachers’ pedagogical content knowledge and motivation on students’ achievement and interest. Journal of Research in Science Teaching 54, 5 (2017), 586–614.
[31]
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. Journal of Science Teacher Education 15, 3 (2004), 175–195.
[32]
Lisa E Kim, Ilan Dar-Nimrod, and Carolyn MacCann. 2018. Teacher personality and teacher effectiveness in secondary school: Personality predicts teacher support and student self-efficacy but not academic achievement.Journal of Educational Psychology 110, 3 (2018), 309.
[33]
Robert M Klassen and Ming Ming Chiu. 2010. Effects on teachers’ self-efficacy and job satisfaction: Teacher gender, years of experience, and job stress.Journal of educational Psychology 102, 3 (2010), 741.
[34]
Kim Lange, Thilo Kleickmann, and Kornelia Möller. 2011. Elementary teachers’ pedagogical content knowledge and student achievement in science education. In ESERA-Conference, Lyon, France. 5–9.
[35]
Jihyun Lee and Valerie J Shute. 2010. Personal and social-contextual factors in K–12 academic performance: An integrative perspective on student learning. Educational psychologist 45, 3 (2010), 185–202.
[36]
Monica M McGill, Leigh Ann DeLyser, Karen Brennan, Baker Franke, Errol Kaylor, Eric Mayhew, Kelly Mills, and Aman Yadav. 2020. Evaluation and assessment for improving CS teacher effectiveness. ACM Inroads 11, 4 (2020), 35–41.
[37]
Muhsin Menekse. 2015. Computer science teacher professional development in the United States: a review of studies published between 2004 and 2014. Computer Science Education 25, 4 (2015), 325–350.
[38]
Bismark Mensah and Eric Koomson. 2020. Linking Teacher-Student Relationship to Academic Achievement of Senior High School Students. Social Education Research(2020). https://doi.org/10.37256/ser.122020140
[39]
Emmelien Merchie, Melissa Tuytens, Geert Devos, and Ruben Vanderlinde. 2018. Evaluating teachers’ professional development initiatives: towards an extended evaluative framework. Research Papers in Education 33 (2018). Issue 2. https://doi.org/10.1080/02671522.2016.1271003
[40]
Ahmad Mojavezi and Marzieh Poodineh Tamiz. 2012. The Impact of Teacher Self-efficacy on the Students’ Motivation and Achievement.Theory & Practice in Language Studies 2, 3 (2012).
[41]
National Center for Education Statistics. 2019. Digest of Education Statistics. https://nces.ed.gov/programs/digest/d20/tables/dt20_214.10.asp
[42]
Isaac M. Opper. 2019. Teachers Matter: Understanding Teachers’ Impact on Student Achievement. RAND Corporation, Santa Monica, CA. https://doi.org/10.7249/RR4312
[43]
Shivaun O’Brien, Gerry McNamara, Joe O’Hara, and Martin Brown. 2020. Learning by doing: evaluating the key features of a professional development intervention for teachers in data-use, as part of whole school self-evaluation process. Professional Development in Education(2020). https://doi.org/10.1080/19415257.2020.1720778
[44]
Ursula Pieper and Jan Vahrenhold. 2020. Critical Incidents in K-12 Computer Science Classrooms-Towards Vignettes for Computer Science Teacher Training. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education. 978–984.
[45]
Jason Ravitz, Chris Stephenson, Karen Parker, and Juliane Blazevski. 2017. Early lessons from evaluation of computer science teacher professional development in Google’s CS4HS program. ACM Transactions on Computing Education (TOCE) 17, 4 (2017), 1–16.
[46]
Susan J Rosenholtz. 1989. Workplace conditions that affect teacher quality and commitment: Implications for teacher induction programs. The Elementary School Journal 89, 4 (1989), 421–439.
[47]
Ronny Scherer and Fazilat Siddiq. 2015. Revisiting teachers’ computer self-efficacy: A differentiated view on gender differences. Computers in Human Behavior 53 (2015), 48–57.
[48]
Alan H Schoenfeld. 2007. The complexities of assessing teacher knowledge. (2007).
[49]
Khurram Shahzad and Sajida Naureen. 2017. Impact of Teacher Self-Efficacy on Secondary School Students’ Academic Achievement.Journal of Education and Educational Development 4, 1(2017), 48–72.
[50]
Roger C Shouse. 1998. Restructuring’s impact on student achievement: Contrasts by school urbanicity. Educational Administration Quarterly 34, 1_suppl (1998), 677–699.
[51]
Lee Shulman. 1987. Knowledge and teaching: Foundations of the new reform. Harvard educational review 57, 1 (1987), 1–23.
[52]
Scott R Sweetland and Wayne K Hoy. 2000. School characteristics and educational outcomes: Toward an organizational model of student achievement in middle schools. Educational Administration Quarterly 36, 5 (2000), 703–729.
[53]
Seçil Bal Taştan, Seyed Mehdi Mousavi Davoudi, Alfiya R. Masalimova, Alexandr S. Bersanov, Rashad A. Kurbanov, Anna V. Boiarchuk, and Andrey A. Pavlushin. 2018. The impacts of teacher’s efficacy and motivation on student’s academic achievement in science education among secondary and high school students. Eurasia Journal of Mathematics, Science and Technology Education 14 (2018). Issue 6. https://doi.org/10.29333/ejmste/89579
[54]
Bruce W Tuckman and Thomas L Sexton. 1991. The effect of teacher encouragement on student self-efficacy and motivation for self-regulated performance. Journal of Social Behavior and Personality 6, 1 (1991), 137.
[55]
Cynthia L Uline, Daniel M Miller, and Megan Tschannen-Moran. 1998. School effectiveness: The underlying dimensions. Educational Administration Quarterly 34, 4 (1998), 462–483.
[56]
Mucella Ulug, Melis Seray Ozden, and Ahu Eryilmaz. 2011. The Effects of Teachers’ Attitudes on Students’ Personality and Performance. Procedia - Social and Behavioral Sciences 30 (2011), 738–742. https://doi.org/10.1016/j.sbspro.2011.10.144 2nd World Conference on Psychology, Counselling and Guidance - 2011.
[57]
University of Southern California - Center for Urban Education. 2021. Equity Mindset. https://cue.usc.edu/about/equity/equity-mindedness/
[58]
U.S. Census Bureau. 2019. Census Bureau Reports Nearly 77 Million Students Enrolled in U.S. Schools. https://www.census.gov/newsroom/press-releases/2019/school-enrollment.html
[59]
Beverly Vaillancourt and Emmanuel Schanzer. 2018. In Search of Quality Professional Development. https://drive.google.com/file/d/1ztko8ePIVo7I-QQzPuUrCIB4-qItPc88/view
[60]
Rebecca Vivian and Katrina Falkner. 2018. A survey of Australian teachers’ self-efficacy and assessment approaches for the K-12 digital technologies curriculum. Proceedings of the 13th Workshop in Primary and Secondary Computing Education (2018).
[61]
Herbert Ware and Anastasia Kitsantas. 2007. Teacher and collective efficacy beliefs as predictors of professional commitment. The journal of educational research 100, 5 (2007), 303–310.
[62]
Aman Yadav and Marc Berges. 2019. Computer science pedagogical content knowledge: Characterizing teacher performance. ACM Transactions on Computing Education (TOCE) 19, 3 (2019), 1–24.
[63]
Aman Yadav, Marc Berges, Phil Sands, and Jon Good. 2016. Measuring computer science pedagogical content knowledge: An exploratory analysis of teaching vignettes to measure teacher knowledge. In Proceedings of the 11th Workshop in Primary and Secondary Computing Education. 92–95.
[64]
Aman Yadav, Alex Lishinski, and Phil Sands. 2021. Self-efficacy Profiles for Computer Science Teachers. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education. 302–308.
[65]
Marjolein Zee and Helma MY 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. Review of Educational research 86, 4 (2016), 981–1015.
[66]
Albert Zeggelaar, Marjan Vermeulen, and Wim Jochems. 2020. Evaluating effective professional development. Professional Development in Education(2020). https://doi.org/10.1080/19415257.2020.1744686
[67]
Ninger Zhou, Ha Nguyen, Christian Fischer, Debra Richardson, and Mark Warschauer. 2020. High School Teachers’ Self-efficacy in Teaching Computer Science. ACM Transactions on Computing Education (TOCE) 20, 3 (2020), 1–18.

Cited By

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  • (2024)Piloting a Revised Diagnostic Tool for CSTA Standards for CS TeachersProceedings of the 2024 on ACM Virtual Global Computing Education Conference V. 110.1145/3649165.3690122(207-213)Online publication date: 5-Dec-2024
  • (2023)Classifying the Characteristics of Effective Continuing Professional Development (CPD) for Computer Science Teachers in the 16-18 SectorACM Transactions on Computing Education10.1145/358227523:2(1-30)Online publication date: 8-Jun-2023
  • (2022)Digital Learning Environment Values of Pre-Service Teachers as a Basis for Successful Professional Self-Realisation: A Case StudyEducation Sciences10.3390/educsci1202012012:2(120)Online publication date: 10-Feb-2022

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Koli Calling '21: Proceedings of the 21st Koli Calling International Conference on Computing Education Research
November 2021
287 pages
ISBN:9781450384889
DOI:10.1145/3488042
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 18 November 2021

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Author Tags

  1. K-12
  2. PCK
  3. Professional development
  4. content knowledge
  5. evaluation
  6. mindset
  7. pedagogical content knowledge
  8. primary
  9. recommendations
  10. secondary
  11. self-efficacy
  12. teacher

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View all
  • (2024)Piloting a Revised Diagnostic Tool for CSTA Standards for CS TeachersProceedings of the 2024 on ACM Virtual Global Computing Education Conference V. 110.1145/3649165.3690122(207-213)Online publication date: 5-Dec-2024
  • (2023)Classifying the Characteristics of Effective Continuing Professional Development (CPD) for Computer Science Teachers in the 16-18 SectorACM Transactions on Computing Education10.1145/358227523:2(1-30)Online publication date: 8-Jun-2023
  • (2022)Digital Learning Environment Values of Pre-Service Teachers as a Basis for Successful Professional Self-Realisation: A Case StudyEducation Sciences10.3390/educsci1202012012:2(120)Online publication date: 10-Feb-2022

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