Profiling self-regulation behaviors in STEM learning of engineering design

Zheng, Juan; Xing, Wanli; Zhu, Gaoxia; Chen, Guanhua; Zhao, H.; Xie, Charles

doi:10.1016/j.compedu.2019.103669

Cited by 72 publications

(42 citation statements)

References 39 publications

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“…Our study adds to the understanding of HE students' self-regulation of their learning and corroborates previous research emphasizing the importance of self-regulation, which rests on accurate metacognition and evaluative judgments, for students in HE (e.g. Boud & Soler 2016;Negretti 2017;Tai et al 2018;Zheng et al 2020). However, a study with engineering students has shown that only self-regulation of cognition does not lead to the greatest gains in achievement (Zheng et al 2020), with potential consequences for lifelong learning (see Hadgraft & Kolmos 2020, on the complexity of lifelong learning in engineering).…”

Section: Implications For Theory and Practicesupporting

confidence: 88%

“…Furthermore, studies have emphasised differential achievement gains for students depending on type of program and institution (Dalmon et al 2019), posing that across HE context, students' ability to take control of their learning is crucial. The importance of developing effective SRL strategies is particularly evident for engineering students, who face a fast-changing work life with increasingly complex challenges (Hadgraft & Kolmos 2020;Wallin & Adawi 2018;Zheng et al 2020). Unfortunately, such learning strategies are seldom explicitly taught in HE (Bjork et al 2013).…”

Section: Introductionmentioning

confidence: 99%

“…We broaden the picture and test this hypothesis in an authentic HE setting, taking into account how not only cognition but also motivation, behaviour and context may explain student's selfreported choice of strategies. In this regard, a recent study with engineering students has shown that competent self-regulated learners had the greatest ability to accurately assess their knowledge and adopt relevant learning strategies, with greater achievement gain when compared with cognitive-oriented self-regulation (Zheng et al 2020). To take learning context into account, we consider the different programs and types of courses students are enrolled in.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Metacognitive illusion or self-regulated learning? Assessing engineering students’ learning strategies against the backdrop of recent advances in cognitive science

et al. 2020

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Knowing how students approach learning in higher education contexts is key to promote learning strategies that are effective in the long run. Previous research has concluded that students often use ineffective learning strategies but believe them to be effective—a phenomenon known as metacognitive illusion. In a bid to broaden the perspective on students’ use of learning strategies, this study draws on the notion of self-regulated learning as a theoretical lens. A questionnaire, comprising both open-ended and closed-ended questions, was developed to gather data from 416 engineering students. The questionnaire was geared towards (1) mapping what learning strategies students use in a real-world setting, in real courses, (2) probing their metacognitive awareness of the effectiveness of various learning strategies and (3) investigating why students choose certain learning strategies. We also compared which learning strategies the engineering students chose across programs and types of courses. The findings reveal a complex picture of why students sometimes use seemingly ineffective learning strategies, and we conclude that this is not always due to metacognitive illusion. It is instead often linked to attempts to regulate behaviour, motivation and/or learning context, sometimes in response to the context. This study adds to the current HE research investigating students’ abilities to reflect on, assess and take control of their learning in an effective way, confirming that students need explicit guidance.

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Section: Implications For Theory and Practicesupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Metacognitive illusion or self-regulated learning? Assessing engineering students’ learning strategies against the backdrop of recent advances in cognitive science

et al. 2020

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“…The processes of teaching and learning through the STEM teaching method require an adequate development of teaching professionals [39][40][41], where years of experience, level of education and subject matter expertise have a direct influence on whether the teaching method is applied with assurance, as well as increased involvement of families who support STEM learning at home [42,43].…”

Section: Introductionmentioning

confidence: 99%

Scientific Performance and Mapping of the Term STEM in Education on the Web of Science

Lucena

Dúo-Terrón²,

Navas-Parejo

et al. 2020

Sustainability

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Technological progress is causing terms such as "STEM", an acronym for Science, Technology, Engineering and Mathematics, to burst into the educational arena, marking a new era in the application of innovative and motivating teaching and learning processes. The objective of this research is to analyze the trajectory and the transcendence of the "STEM" concept in the educational field, having as reference the reported literature of Web of Science. The methodology applied in this research is based on bibliometrics, analyzing both the performance and the structural and dynamic development of the concept through a co-word analysis. The total number of documents analyzed is 4390. The results show that the scientific community mainly uses English and research papers to present their results. From 2015 onwards, the main lines of research are beginning to be established, which focus on "women" and "science". It can be concluded that the term "STEM" in education is beginning to have a greater incidence and impact on the processes of teaching and learning, especially in the field of science, although there are currently discrepancies between men and women in its use.

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“…collaborative learning, computational thinking, educational psychology, and learning analytics presented contributions to self-regulated learning with the goal of stimulating crossborder discussion in the field (Noroozi et al, 2019). Self-regulation behaviours offer new insights into STEM education and selfregulated learning with emerging learning analytics (Zheng et al, 2020). Self-regulated learners manage their learning, engage in more metacognitive monitoring and control, are more intrinsically motivated (Muis, 2008).…”

Section: Introductionmentioning

confidence: 99%

Exploring Students Computational Thinking based on Self-Regulated Learning in the Solution of Linear Program Problem

Nuraisa

Azizah

Nopitasari

et al. 2019

JIPM

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This study aims to analyze the students computational thinking in the solution of the linear program problem based on self-regulated learning. The data were collected by self-regulated learning questionnaire, computational thinking test, and depth interviews. This study was conducted in SMAN 10 Tangerang. Computational thinking in students with high and medium levels of self-regulated learning has no difference. Students still make a solution that is fixated with linear program problem-solving procedures in general, that is using examples, substitution, and elimination. In solving problems, students can reach the stages of decomposition and pattern recognition only. Students still do not evaluate the results of their work. Algorithmic performed is less coherent because the abstraction has not been done. The recommendation for further research is the need for research that can develop student abstraction in solving problems. Besides, there is also a need for research that analyzes the reflective of students in computational thinking when solving problems.

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Profiling self-regulation behaviors in STEM learning of engineering design

Cited by 72 publications

References 39 publications

Metacognitive illusion or self-regulated learning? Assessing engineering students’ learning strategies against the backdrop of recent advances in cognitive science

Metacognitive illusion or self-regulated learning? Assessing engineering students’ learning strategies against the backdrop of recent advances in cognitive science

Scientific Performance and Mapping of the Term STEM in Education on the Web of Science

Exploring Students Computational Thinking based on Self-Regulated Learning in the Solution of Linear Program Problem

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