International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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Impact Factor: 9.24
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 8 Issue 4
July-August 2026
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Hierarchical Misconception Classification in STEM Education Using BERT-Based Text Classification
| Author(s) | Ms. Devipriya P |
|---|---|
| Country | India |
| Abstract | Misconceptions among students in Science, Technology, Engineering, and Mathematics (STEM) domains pose a major challenge to effective learning and the development of accurate conceptual knowledge. Conventional assessment approaches generally focus on evaluating final answers and often fail to reveal the specific reasoning difficulties or misunderstandings that lead to incorrect responses. This study presents a hierarchical misconception classification framework utilizing Bidirectional Encoder Representations from Transformers (BERT) to automatically analyze and classify misconceptions present in students’ textual answers. The proposed framework adopts a multi-level classification strategy, where responses are initially distinguished as correct or incorrect, followed by the identification of specific misconception categories, including conceptual misunderstandings, procedural mistakes, and calculation errors. Experimental analysis highlights the effectiveness of transformer-based language models in capturing contextual information from educational text and supporting automated misconception identification. The proposed approach provides a foundation for intelligent assessment systems that can generate personalized learning support and targeted feedback to improve students’ conceptual understanding. |
| Keywords | BERT, Misconception Identification, Hierarchical Classification, STEM Learning, Educational Data Mining, Natural Language Processing |
| Field | Computer > Artificial Intelligence / Simulation / Virtual Reality |
| Published In | Volume 8, Issue 4, July-August 2026 |
| Published On | 2026-08-10 |
| DOI | https://doi.org/10.36948/ijfmr.2026.v08i04.85531 |
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E-ISSN 2582-2160
CrossRef DOI prefix of IJFMR is 10.36948/ijfmr
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