Tempognize: Fostering Deep Learning and Knowledge Consolidation with a Large Language Model-Based Learning Assistant

The swift progression of artificial intelligence (AI), especially large language models (LLMs), offers both prospects and obstacles for education. Although LLMs provide opportunities for improved knowledge acquisition and individualized learning, they may not intrinsically foster higher-order cognitive abilities. This study presents Tempognize, a novel learning assistant application utilizing LLMs to promote Socratic learning and tackle the widespread problem of "information hoarding." Tempognize seeks to enhance learning and knowledge retention by combining AI-generated questions with innovative note lifecycle management and regular evaluations. An extensive semester-long classroom intervention, evaluated via student course reviews, indicates Tempognize's efficacy in augmenting student engagement, fostering deeper learning, and strengthening critical thinking abilities. This study offers a significant example of the successful incorporation of AI in education.

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Published
2025-02-20
DOI
https://doi.org/10.1109/icctech66294.2025.00037
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
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article

Tempognize: Fostering Deep Learning and Knowledge Consolidation with a Large Language Model-Based Learning Assistant

Xin Xie, Rongyu Cui
Intelligent Tutoring Systems and Adaptive Learning
article

Tempognize: Fostering Deep Learning and Knowledge Consolidation with a Large Language Model-Based Learning Assistant

Xin Xie, Rongyu Cui
article en

Abstract

The swift progression of artificial intelligence (AI), especially large language models (LLMs), offers both prospects and obstacles for education. Although LLMs provide opportunities for improved knowledge acquisition and individualized learning, they may not intrinsically foster higher-order cognitive abilities. This study presents Tempognize, a novel learning assistant application utilizing LLMs to promote Socratic learning and tackle the widespread problem of "information hoarding." Tempognize seeks to enhance learning and knowledge retention by combining AI-generated questions with innovative note lifecycle management and regular evaluations. An extensive semester-long classroom intervention, evaluated via student course reviews, indicates Tempognize's efficacy in augmenting student engagement, fostering deeper learning, and strengthening critical thinking abilities. This study offers a significant example of the successful incorporation of AI in education.

Chengdu University (CN), Neusoft (China) (CN), Chengdu Neusoft University
Quality Education
Openalex Percentile: Top 90%
Intelligent Tutoring Systems and Adaptive Learning
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Tempognize: Fostering Deep Learning and Knowledge Consolidation with a Large Language Model-Based Learning Assistant — Xin Xie, Rongyu Cui · (2025) | TGRS Research Map | TGRS