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

  • Blanka LángEmail author
Conference paper
  • 16 Downloads
Part of the Advances in Intelligent Systems and Computing book series (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.

Keywords

Exercise generation problem Harmony search metaheuristic algorithm Precedence constraints 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Corvinus University of BudapestBudapestHungary

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