engleski

Towards Automated Assessment Generation in e- Learning Systems Using Combinatorial Testing and Formal Concept Analysis

In this paper, we research the usage of software combinatorial testing techniques and Formal Concept Analysis method for preparing sets of questions for student assessment in e- learning systems. Utilizing these techniques and methods, we ensure that the selected questions optimally cover the course material and that each question combines multiple topics. Therefore, in this paper we introduce our method for preparing student assessments that performs automated combinatorial testing and selection of questions, as well as automated generation of appropriate sequences of questions. The input for our method is a set of questions, labelled with attributes or features. This set of questions is pre- processed using Formal Concept Analysis method, and then the combinatorial testing of questions’ features is performed that generates a concise list of test-cases that cover all pairs or triples of question features. Correspondingly, our method helps to identify and select a subset of questions that covers all the generated test-cases. Afterwards, Formal Concept Analysis automatically generates suitable sequences of selected questions for formative student assessments in e-learning systems. In this paper we implemented proposed combinatorial testing method, and furthermore, we demonstrated the feasibility of the proposed method on a use-case from an actual e- learning system.

combinatorial testing ; pairwise testing ; formal concept analysis ; e-learning systems ; automated test generation ; process mining

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