A computational framework for academic accreditation and assessment in higher education (A3-HE): part 2 technologies

  • Authors:

  • Aboubekeur Hamdi-Cherif

  • Affiliations:

  • Computer College, Computer Science Department, Qassim University, Buraydah, Saudi Arabia and Computer Science Department, Faculty of Engineering, Université Ferhat Abbas Setif, Setif, Algeria

  • Venue:
  • AIKED'11 Proceedings of the 10th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
  • Year:
  • 2011

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Abstract

In Part 1 of this paper, we described the main processes involved in academic accreditation and assessment in Higher Education (A3-HE). We have stressed the issue of heavy and tedious paperwork that characterize actual academic processes. On the other hand, both the internal self-examination undergone by institutions / programs and the external reviewing processes made by accrediting bodies are prone to errors, biases and subjective judgments because they are largely based on rules of thumb human judgments - despite the use of standards. In this second part of the paper, we propose a set of computational technologies for the enhancement of A3-HE. Emphasis is put on technologies spanning (crude) data, information, refined information including decision support, ultimately leading to the most refined and expensive piece of information, i.e., knowledge and its discovery in large and diversified databases over the Web. A human-machine interactive knowledge-based learning control system for A3-HE is our far-reaching goal. Because the A3-HE processes are too complex to be addressed by computerized systems alone, scaling up to real-life applications still require much time to reach maturation.