Optimising Lifelong Learning for Adults: A Chatbot-Assisted Samvada Framework for Self-Directed Learning

Samvāda, a concept from the Upanishads and traditional Indian educational practices, represents a dialogic method for exploring complex ideas. In a rapidly changing world, where learners must continually develop new skills, self-directed learning has become a vital skill. This paper reinterprets Samvāda as a tool for self-learning in the digital era through AI chatbots. To harness this potential, the study presents a chatbot-based Samvāda framework with six elements: questioning, cross- questioning, cross-referencing, summarising, validation, and self-assessment. These components aim to transform chatbot interactions from simple exchanges into structured, learner-centred dialogues. This approach also aligns with Knowles’ principles of Self-Directed Learning (SDL), where learners identify their needs, set goals, locate resources, and evaluate outcomes as active participants in their own learning journey. The study employed a pre-test–post-test control group design. This design enabled an evaluation of whether a guided conversational model could provide more meaningful learning experiences than unstructured approaches. By bridging ancient methods of inquiry with modern technologies, the study highlights the potential of Samvāda to promote the self-directed learning abilities of students in higher education.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-30
DOI
https://doi.org/10.5281/zenodo.17231539
Primary Topic
Bacterial Genetics and Biotechnology
Type
article
Field-Weighted Citation Impact
0.00
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article

Optimising Lifelong Learning for Adults: A Chatbot-Assisted Samvada Framework for Self-Directed Learning

Zenodo (CERN European Organization for Nuclear Research)
Bacterial Genetics and Biotechnology
article

Optimising Lifelong Learning for Adults: A Chatbot-Assisted Samvada Framework for Self-Directed Learning

article en

Abstract

Samvāda, a concept from the Upanishads and traditional Indian educational practices, represents a dialogic method for exploring complex ideas. In a rapidly changing world, where learners must continually develop new skills, self-directed learning has become a vital skill. This paper reinterprets Samvāda as a tool for self-learning in the digital era through AI chatbots. To harness this potential, the study presents a chatbot-based Samvāda framework with six elements: questioning, cross- questioning, cross-referencing, summarising, validation, and self-assessment. These components aim to transform chatbot interactions from simple exchanges into structured, learner-centred dialogues. This approach also aligns with Knowles’ principles of Self-Directed Learning (SDL), where learners identify their needs, set goals, locate resources, and evaluate outcomes as active participants in their own learning journey. The study employed a pre-test–post-test control group design. This design enabled an evaluation of whether a guided conversational model could provide more meaningful learning experiences than unstructured approaches. By bridging ancient methods of inquiry with modern technologies, the study highlights the potential of Samvāda to promote the self-directed learning abilities of students in higher education.

Zenodo (CERN European Organization for Nuclear Research)
Karnatak University (IN)
Quality Education
Openalex Percentile: Top 37%
Bacterial Genetics and Biotechnology
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