Effects of a Mobile Cloud-Based Learning System Using a P2P Reverse Engineering Approach on Enhancing Computational Thinking

Effects of a Mobile Cloud-Based Learning System Using a P2P Reverse Engineering Approach on Enhancing Computational Thinking

Cloud Based Learning

Reverse Engineering

Computational Thinking

Peer Learning.

In each country, skills development in the 21st century plays a crucial role in education at all levels. One of these skills is computational thinking (CT), which is the ability to systematically think and solve problems in daily life. This research aims to ascertain the benefits of using a mobile cloud-based learning system with a peer-to-peer reverse engineering approach in enhancing CT skill. In this study, a cloud-based learning system and learning management plans were employed as research instruments, and a CT test was used as a data gathering instrument. The data were analyzed using the mean and standard deviation, repeated-measures analysis of variance (ANOVA), and t-test. The findings suggested that the students’ scores were higher after using the cloud-based learning system, at a 0.05 level of significance. After performing the repeated-measures ANOVA, the students’ scores were significantly higher at a 0.05 level in each round of the CT test. At the same time, peer learning increased the positive attitude of the learners toward the system and promoted the effectiveness of working in a team. This study provides a better understanding of the current research trends in the field of CT education, the perception of students, and the learning strategies and technology involved in CT education.

Supaluk, Sutiwat

Khlaisang, Jintavee

Songkram, Noawanit

International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 21 (2021); pp. 67-87

1865-7923

International Association of Online Engineering (IAOE), Vienna, Austria

2021-11-09

Copyright (c) 2021 Sutiwat Supaluk, Jintavee Khlaisang, Noawanit Songkram

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eng

info:eu-repo/semantics/article

info:eu-repo/semantics/publishedVersion

Peer-reviewed Article