Understanding the Progression of Educational Topics via Semantic Matching
<|reference_start|>Understanding the Progression of Educational Topics via Semantic Matching: Education systems are dynamically changing to accommodate technological advances, industrial and societal needs, and to enhance students' learning journeys. Curriculum specialists and educators constantly revise taught subjects across educational grades to identify gaps, introduce new learning topics, and enhance the learning outcomes. This process is usually done within the same subjects (e.g. math) or across related subjects (e.g. math and physics) considering the same and different educational levels, leading to massive multi-layer comparisons. Having nuanced data about subjects, topics, and learning outcomes structured within a dataset, empowers us to leverage data science to better understand the progression of various learning topics. In this paper, Bidirectional Encoder Representations from Transformers (BERT) topic modeling was used to extract topics from the curriculum, which were then used to identify relationships between subjects, track their progression, and identify conceptual gaps. We found that grouping learning outcomes by common topics helped specialists reduce redundancy and introduce new concepts in the curriculum. We built a dashboard to avail the methodology to curriculum specials. Finally, we tested the validity of the approach with subject matter experts.<|reference_end|>
@article{alkhidir2024understanding,
    title={Understanding the Progression of Educational Topics via Semantic
  Matching},
    author={Tamador Alkhidir (1), Edmond Awad (2), Aamena Alshamsi (3) ((1)
  Curriculum Department, Ministry of Education, United Arab Emirates, (2)
  Department of Economics and Institute for Data Science and AI, University of
  Exeter, United Kingdom,(3) Heuristic World, Dubai, United Arab Emirates)},
    journal={arXiv preprint arXiv:2403.05553},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.05553},
    primaryClass={cs.CY cs.CL cs.LG}
}