Analysis of Collaborative Learning in a Computational Thinking Class

Chowdhury, Bushra; Bart, Austin Cory; Kafura, Dennis

doi:10.1145/3159450.3159470

Cited by 16 publications

(2 citation statements)

References 5 publications

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“…Despite the reported instances of computational thinking courses being taught to non-CS majors (e.g., [15,16]), there is little available empirical research evaluating these courses. In one of the few cases where the course was evaluated, Chowdhury et al [19] found that students had mostly positive experiences in the course and found the use of a collaborative cohort model to be beneficial. However, their evaluation focused on students' perceptions of and experiences with the course, it and did not include an analysis of students' learning of computational thinking.…”

Section: Computational Thinking Coursesmentioning

confidence: 99%

Building Computational Creativity in an Online Course for Non-Majors

Peteranetz

Soh

Ingraham

2019

Proceedings of the 50th ACM Technical Symposium on Computer Science Education

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In recent years, a growing number of universities have begun to offer specialized courses as a way to make computer science (CS) more accessible to students with little or no prior CS or programming experience, especially non-CS majors. One of the ways courses have been modified for these students is by supplementing the core problem solving and coding aspects of the curriculum with explicit instruction on computational thinking principles. These "computational thinking" courses are promising in that they ground computational thinking in discipline-specific contexts and emphasize application of computational principles. However, there is little empirical research evaluating the extent to which students learn computational thinking from these courses. The purpose of this study was to evaluate the impact of an online Computational Creativity course on students' computational thinking skills, creative competencies, and self-efficacy. Students in the Computational Creativity course were predominantly non-CS majors, and they completed four Computational Creativity Exercises (CCEs) that have previously been shown to improve learning and achievement. Results indicate that the Computational Creativity course was effective in increasing students' computational thinking knowledge and self-efficacy for applying computational thinking in their fields, but it did not have an impact on students' creative competencies. Additionally, students' reactions to the course and the CCEs were mostly positive. Thus, this study provides initial evidence that non-CS majors can learn computational thinking through the online Computational Creativity course.

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Section: Computational Thinking Coursesmentioning

confidence: 99%

Building Computational Creativity in an Online Course for Non-Majors

Peteranetz

Soh

Ingraham

2019

Proceedings of the 50th ACM Technical Symposium on Computer Science Education

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“…Collaborative learning is an approach to teaching and learning where students work together in groups to complete tasks and promotes a positive learning atmosphere where interaction and negotiation trigger learning (Chowdhury et al, 2018). The use of computers to promote collaborative learning has been extensively researched, with a recent focus on using game environments as a learning framework.…”

Section: Introductionmentioning

confidence: 99%

Multiplayer Serious Games Supporting Programming Learning

Wynn,

Wang,

Han

et al. 2023

ECGBL

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Computational thinking (CT) is crucial in education for providing a multifaceted approach to problem-solving. However, challenges exist such as supporting teachers' knowledge of CT and students' desire to learn it, particularly for non-technical students. To combat these challenges, Computer Supported Collaborative Learning (CSCL) has been introduced in classrooms and implemented using a variety of technologies, including serious games, which have been adopted across several domains aiming to appeal to various demographics and skill levels. This research focuses on a Collaborative Multiplayer Serious Game (MSG) for CT skill training. The architecture is aimed at young students and is designed to aid in the learning of programming and the development of CT skills. The purpose of this research is to conduct an empirical study to assess the multiplayer game gameplay mechanics for collaborative CT learning. The proposed game leverages a card game structure and contains complex multi-team multi-player processes, allowing students to communicate and absorb sequential and conditional logics as well as graph routing in a 2D environment. A preliminary experiment was conducted with four fourth-graders and eight sixth-graders from a French school in Morocco who have varying levels of understanding of CT. Participants were split into three groups each with two teams and were required to complete a 16-question multiple-choice quiz before and after playing the same game to assess their initial structural programming logics and the effectiveness of the MSG. Questionnaires were collected along with an interview to gather feedback on their gaming experiences and the game’s role in teaching and learning. The results demonstrate that the proposed MSG had a favourable effect on the participants’ test scores as the scores of 4 of the teams increased and 1 remained the same. All students performed well on the sequential and conditional logics, which was significantly better than the achievement of the Bebras test of the graph routing. Furthermore, according to the participants, the game provides an appealing environment that allows players to immerse themselves in the game and the competitive aspect of the game adds to its appeal and helps develop teamwork, coordination, and communication skills.

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