Developing Eighth-Grade Students’ Computational Thinking with Critical Reflection

Abstract

As computer science has become a vital power in facilitating the rapid and sustainable development of various fields, equipping everyone with computational thinking (CT) has been recognized as one of the core pillars supporting the sustainable development of individuals and our digital world. However, it remains challenging for secondary school students to assimilate CT. Recently, critical reflection has been proposed as a useful metacognitive strategy for regulating students’ thinking to solve current and future problems. In this study, a quasi-experiment was conducted to investigate the role of critical reflection in advancing eighth-grade students’ CT. The participants were 95 eighth-grade students, comprising an experimental group (n = 49) and a control group (n = 46). The students’ CT was evaluated based on their learning performance in computational concepts, computational practices, and computational perspectives. The results showed that critical reflection, compared with traditional instruction from teachers, could significantly advance eighth-grade students’ CT. Interestingly, the two groups showed significantly different learning performance in computational practices during the learning process. Furthermore, interaction with peers and instructors played an essential role in helping students engage as active agents in critical reflection. The results of this study emphasize the need to develop students’ CT by practicing critical reflection in eighth-grade education.

Abstractive-Based Programming Approach to Computational Thinking: Discover, Extract, Create, and Assemble

“…Although Wei et al (2021) and Taylor and Baek (2019) found positive transfer outcomes, code writing and code reading were the underlying skills measured in the studies. Other studies adopted self-report instruments such as the CT-scale by Korkmaz et al (2017) in an investigation of the effects of critical reflection on middle schoolers’ CT skills (He et al, 2021). Whereas He et al (2021) found that students’ CT skills improved, the finding seems to equate CT disposition and self-beliefs to represent CT skills.…”

“…Other studies adopted self-report instruments such as the CT-scale by Korkmaz et al (2017) in an investigation of the effects of critical reflection on middle schoolers’ CT skills (He et al, 2021). Whereas He et al (2021) found that students’ CT skills improved, the finding seems to equate CT disposition and self-beliefs to represent CT skills. When CT is operationalized as programming or disposition, it may not be comparable with the result of CT as an instance of everyday problem-solving.…”

Effects of the Fundamental Concepts of Computational Thinking on Students’ Anxiety and Motivation toward K-12 English Writing

“…Incorporating the fundamental concepts of CT in English writing enables the exercise of participants' critical thinking and develops a deeper understanding of complex issues [18,51]. The ability to think critically in writing is particularly important for sustainable development [6,18]. It enables students to effectively communicate their ideas, engage in constructive criticism, and work toward a sustainable world.…”

“…Computational thinking (CT) has been extensively integrated into the K-12 educational curriculum to establish a foundation for strong student performance and global sustainability in line with the Sustainable Development Goals for quality education [5,6]. Incorporating real-world applications and more hands-on project-based learning activities into the curriculum, and increasing technology use in the classroom can help K-12 students better understand the material and how it applies to their lives.…”

Computational thinking scale: the predictive role of metacognition in the context of higher order thinking skills

“…The relationship between CT and critical thinking was examined to determine the criterion based validity of the developed CTS. Studies have reported that CT and critical thinking are interrelated (Buckley, 2012;Doleck et al, 2017;He et al, 2021). The Pearson product-moment correlation coefficient was measured to define the correlation between the scores from the CTS and MCTDS.…”