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Scalise, K., Bernbaum, D.J., Timms, M., Harrell, S.V., Burmester, K., Kennedy, C.A. and Wilson, M. (2007) Adaptive Technology for E-Learning: Principles and Case Studies of an Emerging Field. Journal of the American Society for Information Science and Technology, 58, 2295-2309.
http://dx.doi.org/10.1002/asi.20701

has been cited by the following article:

• TITLE: Towards Designing an Intelligent Educational Assessment Tool

  AUTHORS: Thair Hamtini, Shahd Albasha, Marwa Varoca

  KEYWORDS: Artificial Intelligent, Evaluation, Knowledge Space Theory, Precedence Relation, Competences

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.8 No.2, February 10, 2015

  ABSTRACT: Assessment is an important part of learning process. It can be defined as the process of gathering information for the purpose of making judgments about a current state of affairs presumably for the purpose of enhancing future outcomes [1]. It determines whether or not the goals of education are being met. Typically, most assessment tools give a numerical score as the result of the assessment. This may not be enough to improve the student’s progress. In this paper we defined main problems in current assessment tools and proposed a new assessment model that uses notions in knowledge space theory to overcome the shortage of the current assessment models. The experiment result showed that this new prototype made the assessment process easier and more effective. However, assessment affects decisions about grades, instructional needs and curriculum. This is an important phase of the learning process being showed in this paper in knowledge states framework. Future research will focus on making the tool behave intelligently to improve students’ learning momentum.