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Computational Thinking: A Pedagogical Approach Developed to Prepare Students for the Era of Artificial Intelligence

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Computers in Education 7 - Modulus 2

Tagged Division

Computers in Education

Tagged Topic

Diversity

Page Count

10

DOI

10.18260/1-2--36827

Permanent URL

https://peer.asee.org/36827

Download Count

82

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Paper Authors

biography

Gulustan Dogan University of North Carolina Wilmington

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Gulustan Dogan is an assistant professor at University of North Carolina Wilmington in Computer Science department. She worked at Yildiz Technical University, Istanbul, Turkey as an Associate Professor. She worked at NetApp and Intel as a software engineer in Silicon Valley. She received her PhD degree in Computer Science from City University of New York. She received her B.Sc degree in Computer Engineering from Middle East Technical University, Turkey. She is one of the founding members of Turkish Women in Computing (TWIC), a Systers community affiliated with Anita Borg Institute. She also serves as Ambassador of Women In Data Science Stanford.

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Yang Song University of North Carolina Wilmington Orcid 16x16 orcid.org/0000-0001-5297-3072

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Damla Surek Yildiz Technical University

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Ms. Damla Surek is a Computer Education and Instructional Technology student in her third year at Yildiz Technical University in Istanbul, Turkey.

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Abstract

We propose Computational Thinking (CT) as an innovative pedagogical approach with broad application. Research and current industry trends illustrate that students should have a solid computational thinking ability in order to have the skills required for future jobs in Artificial Intelligence. Due to current social issues regarding COVID-19 and natural disasters, we are rapidly moving towards a cyberspace era where many citizens will conduct their work online. Understanding the foundations and tools of computation – e.g., abstraction, decomposition, pattern recognition – is critical for any student to be prepared for the digital AI age. Believing students should be fully prepared for future jobs that involve computation, we developed a CT module on a Learning Management System (LMS). We have collected data of students who took our CT course module. We looked into the students’ activity records and analyzed the number of students’ views on the pages and the number of participants on each quiz. We counted the total number of engagements of the ten components in the CT course module. Ultimately, we believe that our modules had a greater impact on those students who were newer to computational thinking, over those who had prior experience and were enrolled in upper-level computational courses.

Dogan, G., & Song, Y., & Surek, D. (2021, July), Computational Thinking: A Pedagogical Approach Developed to Prepare Students for the Era of Artificial Intelligence Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36827

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