Computing Education: From Content, Pedagogies, and Technologies, to Cognitive, Psychological and Philosophical Aspects

Dear colleagues:

Recently, the entire educational system has faced numerous challenges. On the one hand, recent crises such as the COVID-19 pandemic have significantly undermined the United Nations’ efforts towards achieving quality education for all. Moreover, the persistence of ongoing wars worldwide, including in Europe, has hindered many from accessing their basic necessities, education included, according to Maslow's hierarchy of needs.

On the other hand, disruptive technological advancements such as large language models, machine learning and artificial intelligence are both challenging and revolutionizing the current educational approaches.

Given these considerations, it is evident that education must adopt a comprehensive approach  that encompasses  a wide range of  competencies with a spectrum as broad as possible, ranging from domain-specific skills  to pedagogical, technological, psychological, and philosophical aspects.

With these premises in mind, this Special Issue welcomes quantitative, qualitative, and mixed-method research papers. We also encourage extended reviews of substantive research studies and/or technical reports that have been previously published. Furthermore, Education Sciences invites commentaries and original opinion pieces and/or analyses of issues related to the following topics:

1. Computer Science Pedagogy (Fincher, 2019), (The Big Book, 2019)
   1. Peer Instruction and peerinstruction4CS.
   2. Parson problems.
   3. Process-oriented guided inquiry learning .
2. Disci, multi, inter and transdisciplinary computing Curricula Development (Maiorana, 2021), (Maiorana, 2019), (Taylor, 2018)
   1. Artificial Intelligence and data science (Müller, 2024), (Ozmen, 2023), (Decker, 2019).
   2. Computer security.
   3.  
   4. Digital and green transformations through the lenses of computing education.
   5. Civic education (Naval, 2022), (Cristaldi, 2022).
3. Character and holistic development
   1. Holistic student development (Datnow, Park, Peurach, & Spillane 2022).
   2. Character education (Watts & Kristjánsson, 2022; Vaccarezza, 2023).
   3. Applied behavioral science with a special emphasis on behavior change frameworks such as the mindspace framework (Dolan, 2012).
4. Special and gifted education needs with a special emphasis on Computer Science education
   1. Universal design for learning.
   2. AccessCSforAll (Ladner, 2017).
   3. Universal Design Learning for Computer Science (UDL4CS) (Twarek, 2021).
   4. Supporting metacognition (Mitsea, 2023).
5. From learning science to Science of Learning (Saleh, 2023)
   1. Cognitive aspects of reasoning and problem solving (Fedorenko,2019).
   2. Cognitive psychology.
   3. Cognitive neuroscience (Scherer, 2019).
   4. Learning theories in relation to computing education (Ko, 2023), (Mcgill, 2022).

References

• Cristaldi, G., Quille, K., Csizmadia, A. P., Riedesel, C., Richards, G. M., & Maiorana, F. (2022, March). The intervention, intersection and impact of social sciences theories upon computing education. In 2022 IEEE Global Engineering Education Conference (EDUCON) (pp. 1561-1570). IEEE.
• Dolan, P., Hallsworth, M., Halpern, D., King, D., Metcalfe, R., & Vlaev, I. (2012). Influencing behavior: The mindspace way. Journal of economic psychology, 33(1), 264-277.
• Datnow, A., Park, V., Peurach, D. J., & Spillane, J. P. (2022). Research foundation Transforming Education for Holistic Student Development: Learning from Education System (Re) Building around the World.
• Decker, A., & McGill, M. M. (2019). A systematic review exploring the differences in reported data for pre-college educational activities for computer science, engineering, and other STEM disciplines. Education Sciences, 9(2), 69.
• Fedorenko, E., Ivanova, A., Dhamala, R., & Bers, M. U. (2019). The language of programming: a cognitive perspective. Trends in cognitive sciences, 23(7), 525-528.
• Fincher, S. A., & Robins, A. V. (Eds.). (2019). The Cambridge handbook of computing education research. Cambridge University Press.
• Ko, A. J., Draper, S., Maguire, J., Pajunen, J., Tedre, M., Sinclair, J., & Szabo, C. (2023). A dialog about the special issues on theory. ACM Transactions on Computing Education, 23(1), 1-5.
• Ladner, R. E., & Stefik, A. (2017). AccessCSforall: making computer science accessible to K-12 students in the United States. ACM SIGACCESS Accessibility and Computing, (118), 3-8.
• Maiorana, F. (2021). From High School to Higher Education: Learning Trajectory for an Inclusive and Accessible Curriculum for Teachers and Their Students. International Journal of Smart Education and Urban Society (IJSEUS), 12(4), 36-51.
• Maiorana, F. (2019). Interdisciplinary Computing for STE (A) M: a low Floor high ceiling curriculum. Innovations, Technologies and Research in Education, 37.
• McGill, M. M., Snow, E., & Camping, A. (2022). A Theory of Impacts Model for Assessing Computer Science Interventions through an Equity Lens: Identifying Systemic Impacts Using the CAPE Framework. Education Sciences, 12(9), 578.
• Mitsea, E., Drigas, A., & Skianis, C. (2023). VR Gaming for Meta-Skills Training in Special Education: The Role of Metacognition, Motivations, and Emotional Intelligence. Education Sciences, 13(7), 639.
• Müller, V. C. Philosophy of AI: A structured overview. Forthcoming in Smüha, Nathalie (ed.) (2024):  Cambridge Handbook on the Law,  Ethics and Policy of Artificial Intelligence,  Cambridge: Cambridge University Press.
• Naval, C., Villacís, J. L., & Ibarrola-García, S. (2022). The transversality of civic learning as the basis for development in the university. Education Sciences, 12(4), 240.
• Ozmen Garibay, O., Winslow, B., Andolina, S., Antona, M., Bodenschatz, A., Coursaris, C., ... & Xu, W. (2023). Six human-centered artificial intelligence grand challenges. International Journal of Human–Computer Interaction, 39(3), 391-437.
• Saleh, I. M., & Khine, M. S. (2023). New Science of Learning: Exploration in Mind, Brain, and Education (Vol. 14). Brill.
• Scherer, R., Siddiq, F., & Sánchez Viveros, B. (2019). The cognitive benefits of learning computer programming: A meta-analysis of transfer effects. Journal of Educational Psychology, 111(5), 764.
• Taylor, C., Spacco, J., Bunde, D. P., Butler, Z., Bort, H., Hovey, C. L., ... & Zeume, T. (2018, July). Propagating the adoption of CS educational innovations. In Proceedings companion of the 23rd annual ACM conference on Innovation and Technology in Computer Science Education (pp. 217-235).
• The Big Book of Computing Pedagogy: Hello World’s
• Twarek, B., Freeman, C., Friend, M., Israel, M., Mora, L., & Ray, M. (2021, May). Infusing Equity and Inclusion in K-12 Computer Science Teacher Development. In 2021 Conference on Research in Equitable and Sustained Participation in Engineering, Computing, and Technology (RESPECT) (pp. 1-2). IEEE.
• Vaccarezza, M. S., Kristjánsson, K., & Croce, M. (2023). Phronesis (Practical Wisdom) as a Key to Moral Decision-Making: Comparing Two Models. The Jubilee Centre for Character & Virtues Insight Series.

Watts, P., & Kristjánsson, K. (2022). Character education. In Handbook of Philosophy of Education (pp. 172-184). Routledge.

Guest Editors

Dr. Francesco Maiorana

Prof. Dr. Elena Commodari

Dr. Valentina Lucia La Rosa

Guest Editor Assistants

Giusy Cristaldi

Andrew Csizmadia

Dr. Francesco Maiorana
Prof. Elena Commodari
Dr. Valentina Lucia La Rosa
Dr. Giusy Cristaldi
Dr. Andrew Csizmadia
Guest Editors

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• Computer Science Education
• Character development
• holistic learner development
• cognitive process in learning