Special Issue on Teacher Preparation and Computing Education

Journal of Technology in Teacher Education
Special Issue: Teacher Preparation and Professional Development in Computing Education
Guest Editors: Chrystalla Mouza, Aman Yadav and Anne Ottenbreit-Leftwich

Recent policy efforts such as Computer Science for All, emphasize the importance of helping all students acquire a deeper understanding of how to recognize aspects of computation in the world around us, solve real-world problems, design systems, and understand human behavior by drawing on computer science concepts (Royal Academy of Engineering, 2012; Wing, 2006). One way to achieve this goal is under the broader umbrella of computational thinking (CT) (Wing, 2006). Wing (2006) suggested that CT is a fundamental skill for everyone and in addition “to reading, writing, and arithmetic, we should add computational thinking to every child’s analytical ability” (p. 33). Although definitions of CT vary in the literature, in this issue we recognize CT as a problem-solving process that utilizes abstraction, problem decomposition, algorithmic thinking (i.e., developing precise instructions or a series of sequenced steps), data collection and analysis, and automation (i.e., programming). Nonetheless, we are receptive to different interpretations of CT, particularly in relation to teacher education.

Promoting computing education in K-12 settings, however, is challenging because few teachers have the knowledge and skills to embed CT in school curricula (Barr & Stephenson, 2011). In fact, most teachers are unaware of the term CT and falsely describe CT as the basic use of computers or technology (Bowers & Falkner, 2015; Mouza, Yang, Pan, Yilmaz Ozden, & Pollock, in press; Yadav, Mayfield, Zhou, Hambrusch, & Korb, 2014). Thus, an important step for successfully integrating CT into K-12 education is to help teachers develop an understanding of CT and its connection to their curricular context (Yadav, Hong, & Stephenson, 2016). In this special issue we seek to identify promising pathways and pedagogical strategies that help pre- service and in-service teachers infusing CT in their curricula. In all instances, we expect clear connections between the proposed approaches and teacher education. In particular, we invite contributions including, but not limited to the following issues.

• Conceptual papers that articulate the specific knowledge and skills needed by pre-service and in-service teachers to infuse CT into K-12 curricula.
• Professional development approaches for helping in-service teachers infuse CT into K-12 curricula.
• Discipline-specific approaches for infusing CT into methods courses for pre-service teachers.
• Design of stand-alone educational technology courses that help pre-service acquire knowledge of CT concepts and pedagogical practices for teaching CT.
• Methods courses for teaching CT or computer science principles.
• Design of innovative programs, such as certificates or graduate degrees that help teachers (pre-service/in-service) earn licensure or certification in computing, drawing on computer science principles.

Timeline

• July 17: Open Call for Manuscripts
• November 15: Full paper deadline
• January 31: Reviews due back to Authors
• March 15: Revised paper deadlines
• April 30: Submission of final paper after revisions
• Summer 2018: Expected publication date

References

Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community? ACM Inroads, 2(1), 48-54. https://doi.org/10.1145/1929887.1929905Bower, M., & Falkner, K. (2015). Computational thinking, the notional machine, pre-service teachers, and research opportunities. Proceedings of the 17th Australasian Computer Education Conference (ACE2015) (pp.37-46), Sydney, Australia.

Mouza, C., Yang, H., Pan, Y.-C., Yilmaz Ozden, S., & Pollock, L. (in press). Resetting educational technology coursework for pre-service teachers: A computational thinking approach to the development of technological pedagogical content knowledge (TPACK). Australasian Journal of Educational Technology. https://doi.org/10.14742/ajet.3521

Royal Society of Engineering (2012). Shut down or restart: The way forward for computing in UK schools. Retrieved from http://royalsociety.org/education/policy/computing-in- schools/report/

Wing, J.M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215

Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: Pedagogical approaches to embedding a 21st century problem solving in K-12 classrooms. TechTrends, 60(6), 565-568. https://doi.org/10.1007/s11528-016-0087-7

Yadav, A., Mayfield, C., Zhou, N., Hambrusch, S., & Korb, J. T. (2014). Computational thinking in elementary and secondary teacher education. ACM Transactions on Computing Education, 14(1), Article 5. https://doi.org/10.1145/2576872