A Rule-based Approach toward Automating the Assessments of Academic Curriculum Mapping

Curriculum mapping is the blueprint of a successful academic program. It is progressively utilised in higher education as a monitoring tool in the current age of standard-based regu-lations and empowers program leaders and course instructors to align their curricula for the offered courses and the corresponding learning outcomes. It is often depicted by a two-dimensional matrix expressing the relationship between the students learning outcomes (i.e., SOs) and the courses. However, its mapping remains a challenging exercise, even for experienced program leaders. The complexity stems from the fact that mistakes are prone to happen during the mapping, and program leaders need to be aware of the rules and the acceptable practices of curriculum-effective mapping. Besides, it is not straightforward to spot contradictions in the SO-course mappings. Consequently, this paper aims to tackle these challenges by investigating effective-mapping rules from existing curriculum mappings, which allows one to inspect the SO-course mappings, discover inefficiencies, and provide suggestions for improving the curriculum mapping. We identify the main mapping criteria and propose a rule-based algorithm for curriculum matrix assessments. This algorithm is implemented in an online application and evaluated using a user-based experiment, relying on curriculum mapping experts. The findings have shedded light on the promise of our approach.

@article{Alshanqiti2020,
  title     = {A Rule-based Approach toward Automating the Assessments of Academic Curriculum Mapping},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {12},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Abdullah Alshanqiti and Tanweer Alam and Mohamed Benaida and Abdallah Namoun and Ahmad Taleb},
  doi       = {10.14569/IJACSA.2020.0111285},
  url       = {https://doi.org/10.14569/IJACSA.2020.0111285}
}