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Contextualization, Procedural Logic, and Active Construction: A Cognitive Scaffolding Model for Topic Sentiment

Liwei Ding1, Hongfeng Zhang1, Jinqiao Zhou1

  • 1Faculty of Humanities and Social Sciences, Macao Polytechnic University, Macao, China.

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Summary

Gamified education enhances learner motivation and knowledge construction by integrating contextual strategies and active participation. This study reveals key themes and develops a cognitive scaffolding model for effective digital learning.

Keywords:
LDA topic modelingcognitive scaffoldinggame-based learningsentiment analysissituated learning theory

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Area of Science:

  • Educational Technology
  • Cognitive Science
  • Digital Learning

Background:

  • COVID-19 pandemic disrupted traditional teaching methods.
  • Gamified education emerged as a popular alternative, integrating technology and cognitive strategies.
  • Situated learning theory and game design elements are key to understanding gamified learning's impact.

Purpose of the Study:

  • To explore how game-based learning boosts learner motivation and knowledge construction.
  • To analyze user comments for sentimental tendencies and cognitive themes in gamified learning.
  • To develop a cognitive scaffolding model for motivation-cognition interaction in gamified environments.

Main Methods:

  • Analysis of 20,293 user comments from the Bilibili platform.
  • Application of Latent Dirichlet Allocation (LDA) topic modeling.
  • Integration of sentiment analysis with LDA for multidimensional attitude measurement.

Main Results:

  • Identified four core themes: contextual strategies in language learning, autonomous exploration, enhanced logical thinking, and teaching innovation.
  • Developed a cognitive scaffolding model: contextualization-procedural logic-active construction.
  • Uncovered users' sentimental tendencies and cognitive themes related to gamified learning.

Conclusions:

  • Gamified learning effectively promotes knowledge construction and deepens understanding.
  • The study provides a novel methodological approach for analyzing learner attitudes in digital education.
  • Findings offer practical insights for optimizing educational platforms and personalized learning support.