Baltimore , Maryland
June 25, 2023
June 25, 2023
June 28, 2023
Computers in Education Division (COED)
14
10.18260/1-2--43286
https://peer.asee.org/43286
507
Safia Malallah is a postdoc in the computer science department at Kansas State University working with Vision and Data science projects. She has ten years of experience as a computer analyst and graphic designer. Besides, she's passionate about developing curriculums for teaching coding, data science, AI, and engineering to young children by modeling playground environments. She tries to expand her experience by facilitating and volunteering for many STEM workshops.
Associate professor of computer science at Kansas State University.
William H. Hsu is an associate professor of Computing and Information Sciences at Kansas State University. He received a B.S. in Mathematical Sciences and Computer Science and an M.S.Eng. in Computer Science from Johns Hopkins University in 1993, and a Ph
Dr. Josh Weese is a Teaching Assistant Professor at Kansas State University in the department of Computer Science. Dr. Weese joined K-State as faculty in the Fall of 2017. He has expertise in data science, software engineering, web technologies, computer science education research, and primary and secondary outreach programs. Dr. Weese has been a highly active member in advocating for computer science education in Kansas including PK-12 model standards in 2019 with an implementation guide the following year. Work on CS teacher endorsement standards are also being developed. Dr. Weese has developed, organized and led activities for several outreach programs for K-12 impacting well more than 4,000 students.
Salah Alfailakawi is a PhD student in Educational Technology (ET) Graduate Programs at Kansas State University's College of Education. His areas of interest include social/cultural issues in ET, the impact of ET on learners and teachers, as well as pract
Pedagogy provides a solid foundation for educators to design effective teaching and learning experiences. However, limited resources are available on computational thinking (CT) pedagogical experiences that prepare students to become problem solvers in the computer science and engineering domains, which are necessary to meet future industry requirements. To address this gap, this paper proposes a framework and models to assist educators in identifying the available CT experiences and incorporating them into their lessons. The framework includes nine pedagogical experiences, namely (1) Unplugged, (2) Tinkering, (3) Making, (4) Remixing, (5) Robotics+, (6) Engineering, (7) Coding, (8) Data Wrangling, and (9) AI. In addition, three supplementary models have been developed to help educators use the pedagogical experiences effectively.
Malallah, S., & Shamir, L., & Hsu, W. H., & Weese, J. L., & Alfailakawi, S. (2023, June), Computational Thinking Pedagogical + Framework for Early Childhood Education Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43286
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