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Enhancing Self-Directed Learning and Python Mastery through Integration of a Large Language Model and Learning Analytics Dashboard

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Title: Enhancing Self-Directed Learning and Python Mastery through Integration of a Large Language Model and Learning Analytics Dashboard
Language: English
Authors: Ming Liu (ORCID 0000-0003-4256-6531), Zhongming Wu, Haimin Dai (ORCID 0000-0002-0015-8727), Yifei Su, Laiba Malik, Jian Liao (ORCID 0000-0001-6290-3326), Wei Zhang, Shuo Guo, Li Liu (ORCID 0000-0002-4776-5292), Junqiang Zhao
Source: British Journal of Educational Technology. 2026 57(4):1009-1035.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 27
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Descriptors: Independent Study, Mastery Learning, Programming Languages, Natural Language Processing, Learning Analytics, Educational Technology, Artificial Intelligence, Online Courses, Computer Science Education, Self Evaluation (Individuals), Interpersonal Competence, Electronic Learning
DOI: 10.1111/bjet.70005
ISSN: 0007-1013
1467-8535
Abstract: Self-directed learning (SDL) is a critical skill in the 21st century, particularly in online Python learning environments. Learning analytics (LA) can track and analyse learning processes, which can be leveraged to prompt students to reflect on their learning strategies and progress through learning analytics dashboards (LADs). However, LADs lack pedagogical domain knowledge and fail to provide effective personalised feedback and guidance. This study designs and presents a Generative AI-powered SDL tool, SDLChat. It integrates a large language model (ERNIE-3.5) with retrieval-augmented generation (RAG) technology to generate contextualised, actionable feedback for learners across the entire SDL cycle: planning, self-monitoring and self-reflection. To evaluate the impact of SDLChat on learners' SDL skills and Python knowledge, a randomised experimental study was conducted over a six-week Python online course. The study compared the changes in SDL skills and Python knowledge of students using both SDLChat and LAD group (n = 39) and LAD-only group (n = 35). The results indicate that: (1) students using SDLChat and LAD significantly outperformed those using LAD alone in Python knowledge mastery, self-monitoring and interpersonal skills and (2) the LAD-only group showed significant improvement only in Python knowledge mastery; however, (3) no significant differences were found in posttask motivation between these two groups. This study highlights the potential of integrating LLM with learning analytics to enhance SDL skills and learning performance in online learning contexts. It also establishes a theory-informed operational framework for understanding the LLM-empowered SDL process.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1508528
Database: ERIC
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  Data: Enhancing Self-Directed Learning and Python Mastery through Integration of a Large Language Model and Learning Analytics Dashboard
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  Data: <searchLink fieldCode="AR" term="%22Ming+Liu%22">Ming Liu</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-4256-6531">0000-0003-4256-6531</externalLink>)<br /><searchLink fieldCode="AR" term="%22Zhongming+Wu%22">Zhongming Wu</searchLink><br /><searchLink fieldCode="AR" term="%22Haimin+Dai%22">Haimin Dai</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-0015-8727">0000-0002-0015-8727</externalLink>)<br /><searchLink fieldCode="AR" term="%22Yifei+Su%22">Yifei Su</searchLink><br /><searchLink fieldCode="AR" term="%22Laiba+Malik%22">Laiba Malik</searchLink><br /><searchLink fieldCode="AR" term="%22Jian+Liao%22">Jian Liao</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6290-3326">0000-0001-6290-3326</externalLink>)<br /><searchLink fieldCode="AR" term="%22Wei+Zhang%22">Wei Zhang</searchLink><br /><searchLink fieldCode="AR" term="%22Shuo+Guo%22">Shuo Guo</searchLink><br /><searchLink fieldCode="AR" term="%22Li+Liu%22">Li Liu</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-4776-5292">0000-0002-4776-5292</externalLink>)<br /><searchLink fieldCode="AR" term="%22Junqiang+Zhao%22">Junqiang Zhao</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22British+Journal+of+Educational+Technology%22"><i>British Journal of Educational Technology</i></searchLink>. 2026 57(4):1009-1035.
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: 27
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  Data: <searchLink fieldCode="DE" term="%22Independent+Study%22">Independent Study</searchLink><br /><searchLink fieldCode="DE" term="%22Mastery+Learning%22">Mastery Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Programming+Languages%22">Programming Languages</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+Language+Processing%22">Natural Language Processing</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Analytics%22">Learning Analytics</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Technology%22">Educational Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Online+Courses%22">Online Courses</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Science+Education%22">Computer Science Education</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Evaluation+%28Individuals%29%22">Self Evaluation (Individuals)</searchLink><br /><searchLink fieldCode="DE" term="%22Interpersonal+Competence%22">Interpersonal Competence</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+Learning%22">Electronic Learning</searchLink>
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  Data: 10.1111/bjet.70005
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  Data: 0007-1013<br />1467-8535
– Name: Abstract
  Label: Abstract
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  Data: Self-directed learning (SDL) is a critical skill in the 21st century, particularly in online Python learning environments. Learning analytics (LA) can track and analyse learning processes, which can be leveraged to prompt students to reflect on their learning strategies and progress through learning analytics dashboards (LADs). However, LADs lack pedagogical domain knowledge and fail to provide effective personalised feedback and guidance. This study designs and presents a Generative AI-powered SDL tool, SDLChat. It integrates a large language model (ERNIE-3.5) with retrieval-augmented generation (RAG) technology to generate contextualised, actionable feedback for learners across the entire SDL cycle: planning, self-monitoring and self-reflection. To evaluate the impact of SDLChat on learners' SDL skills and Python knowledge, a randomised experimental study was conducted over a six-week Python online course. The study compared the changes in SDL skills and Python knowledge of students using both SDLChat and LAD group (n = 39) and LAD-only group (n = 35). The results indicate that: (1) students using SDLChat and LAD significantly outperformed those using LAD alone in Python knowledge mastery, self-monitoring and interpersonal skills and (2) the LAD-only group showed significant improvement only in Python knowledge mastery; however, (3) no significant differences were found in posttask motivation between these two groups. This study highlights the potential of integrating LLM with learning analytics to enhance SDL skills and learning performance in online learning contexts. It also establishes a theory-informed operational framework for understanding the LLM-empowered SDL process.
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      – SubjectFull: Programming Languages
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