# Contextualization, Procedural Logic, and Active Construction: A Cognitive Scaffolding Model for Topic Sentiment Analysis in Game-Based Learning

## TL;DR

This study explores how game-based learning can boost motivation and knowledge construction by analyzing user comments and developing a cognitive scaffolding model.

## Contribution

The study introduces a novel integration of LDA topic modeling and sentiment analysis to measure learner attitudes in gamified education.

## Key findings

- Four core cognitive themes were identified in gamified learning: contextual strategies, active participation, logical thinking, and teaching innovation.
- A cognitive scaffolding model combining contextualization, procedural logic, and active construction was developed.
- The study provides empirical insights for optimizing educational platforms and personalized learning support.

## Abstract

Following the significant disruption of traditional teaching by the COVID-19 pandemic, gamified education—an approach integrating technology and cognitive strategies—has gained widespread attention and use among educators and learners. This study explores how game-based learning, supported by situated learning theory and game design elements, can boost learner motivation and knowledge construction. Using 20,293 user comments from the Chinese video platform Bilibili, the study applies sentiment analysis and LDA to uncover users’ sentimental tendencies and cognitive themes. The analysis identifies four core themes: (1) The application of contextual strategies in language learning, (2) Autonomous exploration and active participation in gamified learning, (3) Progressive enhancement of logical thinking in gamified environments, and (4) Teaching innovation in promoting knowledge construction and deepening. Building on these findings, the study further develops a cognitive scaffolding model integrating “contextualization–procedural logic–active construction” to explain the mechanisms of motivation–cognition interaction in gamified learning. Methodologically, this study innovatively combines LDA topic modeling with sentiment analysis, offering a new approach for multidimensional measurement of learner attitudes in gamified education. Theoretically, it extends the application of situated learning theory to digital education, providing systematic support for instructional design and meaning-making. Findings enrich empirical research on gamified learning and offer practical insights for optimizing educational platforms and personalized learning support.