A study on the design of constructivist learning environment model based on metacognitive regulation enhancement

Metacognition, as a fundamental ability for learners to adapt to complex environments, is equally adapted to constructivist teaching and learning activities. In this paper, we propose a model of learning environment characteristics for metacognitive regulation under constructivist learning theory, and utilize Item2Vec algorithm, Self-Attention mechanism, and BiGRU model to construct a model of metacognitive ability. The model presents a kind of multi-channel network characteristic composed of Self-Attention mechanism and BiGRU model. Design a theoretical model of the learning environment oriented to improving students’ metacognitive ability, and analyze the functional modules of the overall system of the learning environment. Propose a learning activity aiming at the improvement of metacognitive ability and incorporating constructivist theory as the guiding concept to allocate the various aspects of the whole constructivist teaching activity. Analyze the implementation effect of constructivist teaching activities based on metacognitive strategies and organize the influencing factors of metacognitive strategies. The bivariate correlation analysis of students’ total test scores and usual grades are closely related to planning strategies, monitoring strategies, and regulating strategies, and the significance (two-tailed) is less than 0.01. This indicates that the higher the students’ scores, the higher the corresponding level of metacognitive strategies.

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Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-03-19
DOI
https://doi.org/10.61091/jcmcc124-44
Primary Topic
Education and Learning Interventions
Type
article
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article

A study on the design of constructivist learning environment model based on metacognitive regulation enhancement

Xi Qu, Sumalee Chaijaroen
1 links
Journal of Combinatorial Mathematics and Combinatorial Computing
Education and Learning Interventions
article

A study on the design of constructivist learning environment model based on metacognitive regulation enhancement

Xi Qu, Sumalee Chaijaroen
article en

Abstract

Metacognition, as a fundamental ability for learners to adapt to complex environments, is equally adapted to constructivist teaching and learning activities. In this paper, we propose a model of learning environment characteristics for metacognitive regulation under constructivist learning theory, and utilize Item2Vec algorithm, Self-Attention mechanism, and BiGRU model to construct a model of metacognitive ability. The model presents a kind of multi-channel network characteristic composed of Self-Attention mechanism and BiGRU model. Design a theoretical model of the learning environment oriented to improving students’ metacognitive ability, and analyze the functional modules of the overall system of the learning environment. Propose a learning activity aiming at the improvement of metacognitive ability and incorporating constructivist theory as the guiding concept to allocate the various aspects of the whole constructivist teaching activity. Analyze the implementation effect of constructivist teaching activities based on metacognitive strategies and organize the influencing factors of metacognitive strategies. The bivariate correlation analysis of students’ total test scores and usual grades are closely related to planning strategies, monitoring strategies, and regulating strategies, and the significance (two-tailed) is less than 0.01. This indicates that the higher the students’ scores, the higher the corresponding level of metacognitive strategies.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 124
Openalex Percentile: Top 94%
Education and Learning Interventions
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A study on the design of constructivist learning environment model based on metacognitive regulation enhancement — Xi Qu, Sumalee Chaijaroen · Journal of Combinatorial Mathematics and Combinatorial Computing (2025) | TGRS Research Map | TGRS