Monday, April 11
11:30-11:50 AM

Characteristics of High and Low Performing Students’ Computational Thinking Facets Based on Structural Topic Modeling

Brief Paper (F2F) ID: 61041
  1. aaa
    Eunsung Park
    Texas Tech University
  2. aaa
    Jongpil Cheon
    Texas Tech University

Abstract: Computational thinking in computer science education requires a range of competencies to complete various projects. To improve computational thinking skills, students need to not only possess computational thinking concepts, but apply systematic approaches to solve problems. This study aims to identify differences between high- and low-performing students by analyzing students’ coding journals describing process of programing and testing their projects. We analyzed a total of 152 journals of 73 students using the structural topic modeling methodological approach. Finding shows differences in prevalent CT facets in high- and low-performing groups. We suggest more frequent debugging activities and more segmented, and multiple levels of CT activities to improve computational thinking skills.

No presider for this session.


Conference attendees are able to comment on papers, view the full text and slides, and attend live presentations. If you are an attendee, please login to get full access.