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International Conference on Interactive Collaborative Learning

ICL 2019: The Impact of the 4th Industrial Revolution on Engineering Education pp 569–579Cite as

Solving Exercise Generation Problems Using the Improved EGAL Metaheuristic Algorithm with Precedence Constraints

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1135))

Abstract

Exercise generation is a well-known problem worth investigating. In our former paper, we argue on that diversity should be a primary objective as well, and we propose a novel approach called EGAL to solve a well-known problem: to generate very different exercises to test students’ knowledge in a specific range of topics. We showed that focusing on diversity and fitness at the same time result in a better quality of solutions in the resulting population. In this publication presents how the previously developed diversity oriented harmony search metaheuristic algorithm (EGAL) can be applied for some problems if there are precedence relations between some tasks of the exercise. An example is presented where we would like to generate good quality and diverse exercises to test students’ knowledge about their basic programming skills. The behaviors of the problems for which the improved EGAL algorithm can be applied effectively are summarized.

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Author information

Authors and Affiliations

  1. Corvinus University of Budapest, 8 Fővám tér, Budapest, 1093, Hungary

    Blanka Láng

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  1. Blanka Láng
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Correspondence to Blanka Láng .

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Editors and Affiliations

  1. Carinthia University of Applied Sciences, Villach, Austria

    Michael E. Auer

  2. Technische Universität Dresden, Dresden, Germany

    Hanno Hortsch

  3. King Mongkut's University of Technology North Bangkok, Bangkok, Thailand

    Panarit Sethakul

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Láng, B. (2020). Solving Exercise Generation Problems Using the Improved EGAL Metaheuristic Algorithm with Precedence Constraints. In: Auer, M., Hortsch, H., Sethakul, P. (eds) The Impact of the 4th Industrial Revolution on Engineering Education. ICL 2019. Advances in Intelligent Systems and Computing, vol 1135. Springer, Cham. https://doi.org/10.1007/978-3-030-40271-6_56

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