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., ion, 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. © American Society for Engineering Education, 2021
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., ion, 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. © American Society for Engineering Education, 2021