![](https://journals.bilpubgroup.com/public/site/images/shuangyu/alpsp.jpg)
Innovating Pedagogical Practices through Professional Development in Computer Science Education
DOI:
https://doi.org/10.30564/jcsr.v5i3.5757Abstract
Recent advancements in technology have opened up new avenues for educators to facilitate teaching and leverage more learning access in the digital age. As the demand for computational skills continues to grow in preparation for future careers, both teachers and students face the challenge of developing problem-solving, critical thinking, communication, and collaboration skills within an emerging digital landscape. Technology adoption, big data, cloud computing and artificial intelligence pose ongoing challenges for both teachers and students in adapting to the changing workforce development landscape. To tackle these challenges, the paper highlights the importance of exploring the implications of learning sciences in classroom teaching, developing a holistic vision for professional development in education, and understanding the complexities of teacher change. To effectively implement these components, it is crucial to adopt design approaches that prioritize student ownership in education and embrace the principles of inclusive education to reconceptualize the teaching practices in education and technology.
Keywords:
Education; Computational thinking; Teacher education; Professional development; Design; EquityReferences
[1] Breazeal, C., 2022. AI Literacy for All with Prof. Cynthia Breazeal [Internet]. Available from: https://openlearning.mit.edu/news/ai-literacy-all-prof-cynthia-breazeal
[2] Darling-Hamond, L., Oakes, J., 2019. Preparing teachers for deeper learning. Harvard Education Press: Cambridge, MA.
[3] Podolsky, A., Kini, T., Darling-Hammond, L., 2019. Does teaching experience increase teacher effectiveness? A review of US research. Journal of Professional Capital and Community. 4(4), 286-308.
[4] Sutcher, L., Darling-Hammond, L., Carver-Thomas, D., 2019. Understanding teacher shortages: An analysis of teacher supply and demand in the United States. Education Policy Analysis Archives. 27(35).
[5] National Academies of Sciences, Engineering, and Medicine, 2018. How people learn II: Learners, contexts, and cultures. National Academies Press: Washington, D.C.
[6] Papadopoulos, I., Lazzarino, R., Miah, S., et al., 2020. A systematic review of the literature regarding socially assistive robots in pre-tertiary education. Computers & Education. 155, 103924.
[7] Rosenberg-Kima, R.B., Koren, Y., Gordon, G., 2020. Robot-supported collaborative learning (RSCL): Social robots as teaching assistants for higher education small group facilitation. Frontiers in Robotics and AI. 6, 148.
[8] Grover, S., Pea, R., Cooper, S., 2015. Designing for deeper learning in a blended computer science course for middle school students. Computer Science Education. 25(2), 199-237.
[9] Hsu, T.C., Chang, S.C., Hung, Y.T., 2018. How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education. 126, 296-310.
[10] Fullan, M., 2016. The new meaning of educational change. Teachers College Press: New York.
[11] Grover, S., Pea, R., 2013. Computational thinking in K-12: A review of the state of the field. Educational Researcher. 42(1), 38-43.
[12] Webb, M., Bell, T., Davis, N., et al. (editors), 2017. Computer science in the school curriculum: Issues and challenges. Tomorrow's Learning: Involving Everyone. Learning with and about Technologies and Computing: 11th IFIP TC 3 World Conference on Computers in Education, WCCE 2017; 2017 Jul 3-6; Dublin, Ireland. p. 421-431.
[13] Du, X., Parks, R., Tezel, S., et al. (editors), 2023. Designing a computational action program to tackle global challenges. SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Education; 2023 Mar 15-18; Toronto ON, Canada. New York: Association for Computing Machinery. p. 1320-1320.
[14] Meier, E.B., Mineo, C., 2021. Pedagogical challenges during COVID: Opportunities for transformative shifts. Handbook of research on transforming teachers' online pedagogical reasoning for engaging K-12 students in virtual learning. IGI Global: Hershey. pp. 86-108.
[15] Meier, E.B., 2021. Designing and using digital platforms for 21st century learning. Educational Technology Research and Development. 69(1), 217-220.
[16] Darling-Hammond, L., Flook, L., Cook-Harvey, C., et al., 2020. Implications for educational practice of the science of learning and development. Applied Developmental Science. 24(2), 97-140.
[17] Scardamalia, M.B., 2014. Knowledge building and knowledge creation. Cambridge handbook of the learning sciences. Cambridge University Press: Cambridge. pp. 297-417.
[18] Harju, V., Niemi, H., 202). Newly qualified teachers' support needs in developing professional competences: The principal's viewpoint. Teacher Development. 24(1), 52-70.
[19] Ng, D.T.K., Lee, M., Tan, R.J.Y., et al., 2022. A review of AI teaching and learning from 2000 to 2020. Education and Information Technologies. 1-57.
[20] Dash, B.B., 2022. Digital tools for teaching and learning English language in 21 st century. International Journal Of English and Studies. 4(2), 8-13.
[21] Biswas, S., Benabentos, R., Brewe, E., et al., 2022. Institutionalizing evidence-based STEM reform through faculty professional development and support structures. International Journal of STEM Education. 9(1), 1-23.
[22] McGill, M.M., Reinking, A., 2022. Early findings on the impacts of developing evidence-based practice briefs on middle school computer science teachers. ACM Transactions on Computing Education. 22(4), 1-29.
[23] Apiola, M., Sutinen, E., 2021. Design science research for learning software engineering and computational thinking: Four cases. Computer Applications in Engineering Education. 29(1), 83-101.
[24] Casey, E., Jocz, J., Peterson, K.A., et al., 2023. Motivating youth to learn STEM through a gender inclusive digital forensic science program. Smart Learning Environments. 10(1), 2.
[25] Tissenbaum, M., Weintrop, D., Holbert, N., et al., 2021. The case for alternative endpoints in computing education. British Journal of Educational Technology. 52(3), 1164-1177.
[26] Schaper, M.M., Smith, R.C., Tamashiro, M.A., et al., 2022. Computational empowerment in practice: Scaffolding teenagers' learning about emerging technologies and their ethical and societal impact. International Journal of Child-Computer Interaction. 34, 100537.
[27] Tsortanidou, X., Daradoumis, T., Barberá, E., 2019. Connecting moments of creativity, computational thinking, collaboration and new media literacy skills. Information and Learning Sciences. 120(11/12), 704-722.
[28] Alfaro-Ponce, B., Patiño, A., Sanabria-Z, J., 2023. Components of computational thinking in citizen science games and its contribution to reasoning for complexity through digital game-based learning: A framework proposal. Cogent Education. 10(1), 2191751.
[29] Ketelhut, D.J., Mills, K., Hestness, E., et al., 2020. Teacher change following a professional development experience in integrating computational thinking into elementary science. Journal of Science Education and Technology. 29, 174-188.
[30] Bragg, L.A., Walsh, C., Heyeres, M., 2021. Successful design and delivery of online professional development for teachers: A systematic review of the literature. Computers & Education. 166, 104158.
[31] Mystakidis, S., Fragkaki, M., Filippousis, G., 2021. Ready teacher one: Virtual and augmented reality online professional development for K-12 school teachers. Computers. 10(10), 134.
[32] Li, M., 2020. Multimodal pedagogy in TESOL teacher education: Students' perspectives. System. 94, 102337.
[33] Kafai, Y.B., Baskin, J., Fields, D., et al. (editors), 2020. Looking ahead: Professional development needs for experienced CS teachers. SIGCSE' 20: Proceedings of the 51st ACM Technical Symposium on Computer Science Education; 2020 Mar 11-14; Portland OR, USA. New York: Association for Computing Machinery. p. 1118-1119.
[34] Tshukudu, E., Cutts, Q., Goletti, O., et al. (editors), 2021. Teachers' views and experiences on teaching second and subsequent programming languages. ICER 2021: Proceedings of the 17th ACM Conference on International Computing Education Research; 2021 Aug 16-19; Virtual Event, USA. New York: Association for Computing Machinery. p. 294-305.
[35] Rich, P.J., Larsen, R.A., Mason, S.L., 2021. Measuring teacher beliefs about coding and computational thinking. Journal of Research on Technology in Education. 53(3), 296-316.
[36] Bereczki, E.O., Kárpáti, A., 2021. Technology-enhanced creativity: A multiple case study of digital technology-integration expert teachers' beliefs and practices. Thinking Skills and Creativity. 39, 100791.
[37] Griful-Freixenet, J., Struyven, K., Vantieghem, W., 2021. Exploring pre-service teachers' beliefs and practices about two inclusive frameworks: Universal design for learning and differentiated instruction. Teaching and Teacher Education. 107, 103503.
[38] Dignath, C., Rimm-Kaufman, S., van Ewijk, R., et al., 2022. Teachers' beliefs about inclusive education and insights on what contributes to those beliefs: a meta-analytical study. Educational Psychology Review. 34(4), 2609-2660.
[39] Almazroa, H., Alotaibi, W., 2023. Teaching 21st century skills: Understanding the depth and width of the challenges to shape proactive teacher education programmes. Sustainability. 15(9), 7365.
[40] Bhutoria, A., 2022. Personalized education and artificial intelligence in the United States, China, and India: A systematic review using a human-in-the-loop model. Computers and Education: Artificial Intelligence. 3, 100068.
[41] Bozkurt, A., 2020. Educational technology research patterns in the realm of the digital knowledge age. Journal of Interactive Media in Education. (1).
[42] Çiftci, S., Bildiren, A., 2020. The effect of coding courses on the cognitive abilities and problem-solving skills of preschool children. Computer Science Education. 30(1), 3-21.
[43] Saad, A., Zainudin, S., 2022. A review of Project-Based Learning (PBL) and Computational Thinking (CT) in teaching and learning. Learning and Motivation. 78, 101802.
[44] Wang, Y., 2023. The role of computer supported project-based learning in students' computational thinking and engagement in robotics courses. Thinking Skills and Creativity. 48, 101269.
[45] Bers, M.U., Blake-West, J., Kapoor, M.G., et al., 2023. Coding as another language: Research-based curriculum for early childhood computer science. Early Childhood Research Quarterly. 64, 394-404.
[46] Huang, W., Looi, C.K., 2021. A critical review of literature on“unplugged” pedagogies in K-12 computer science and computational thinking education. Computer Science Education. 31(1), 83-111.
[47] Yildiz Durak, H., Atman Uslu, N., Canbazoğlu Bilici, S., et al., 2022. Examining the predictors of TPACK for integrated STEM: Science teaching self-efficacy, computational thinking, and design thinking. Education and Information Technologies. 1-28.
[48] Lee, S.W.Y., Liang, J.C., Hsu, C.Y., et al., 2023. Students' beliefs about computer programming predict their computational thinking and computer programming self-efficacy. Interactive Learning Environments. 1-21.
[49] Lee, S.J., Francom, G.M., Nuatomue, J., 2022. Computer science education and K-12 students' computational thinking: A systematic review. International Journal of Educational Research. 114, 102008.
[50] Ung, L.L., Labadin, J., Mohamad, F.S., 2022. Computational thinking for teachers: Development of a localised E-learning system. Computers & Education. 177, 104379.
[51] Kallia, M., van Borkulo, S.P., Drijvers, P., et al., 2021. Characterising computational thinking in mathematics education: A literature-informed Delphi study. Research in Mathematics Education. 23(2), 159-187.
[52] Ogegbo, A.A., Ramnarain, U., 2022. A systematic review of computational thinking in science classrooms. Studies in Science Education. 58(2), 203-230.
[53] Chen, C.H., Liu, T.K., Huang, K., 2023. Scaffolding vocational high school students' computational thinking with cognitive and metacognitive prompts in learning about programmable logic controllers. Journal of Research on Technology in Education. 55(3), 527-544.
[54] Gao, X., Li, P., Shen, J., et al., 2020. Reviewing assessment of student learning in interdisciplinary STEM education. International Journal of STEM Education. 7(1), 1-14.
[55] Madkins, T.C., Martin, A., Ryoo, J., et al. (editors), 2019. Culturally relevant computer science pedagogy: From theory to practice. 2019 Research on Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT); 2019 Feb 27; Minneapolis, MN, USA. New York: IEEE. p. 1-4.
[56] Guskey, T.R., 2002. Does it make a difference? Evaluating professional development. Educational Leadership. 59(6), 45-51.
[57] Li, L., Ruppar, A., 2021. Conceptualizing teacher agency for inclusive education: A systematic and international review. Teacher Education and Special Education. 44(1), 42-59.
[58] Tissenbaum, M., Sheldon, J., Abelson, H., 2019. From computational thinking to computational action. Communications of the ACM. 62(3), 34-36.
[59] Madkins, T.C., Howard, N.R., Freed, N., 2020. Engaging equity pedagogies in computer science learning environments. Journal of Computer Science Integration. 3(2).
[60] Morales-Chicas, J., Castillo, M., Bernal, I., et al., 2019. Computing with relevance and purpose: A review of culturally relevant education in computing. International Journal of Multicultural Education. 21(1), 125-155.
Downloads
How to Cite
Issue
Article Type
License
Copyright © 2023 Author(s)
![Creative Commons License](http://i.creativecommons.org/l/by-nc/4.0/88x31.png)
This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.