Dechawut WanichsanPatcharin Panjabureeพัชรินทร์ ปัญจบุรีParames Laosinchaiปรเมศวร์ เหล่าสินชัยWannapong TriampoSasithorn ChookaewMahidol University. Institute for Innovative LearningMahidol University. Faculty of Science2015-11-272018-01-262015-11-272018-01-262012-07Expert Systems with Applications. Vol.39, (2012), 8380-83880957-4174https://repository.li.mahidol.ac.th/handle/20.500.14594/3386In the recent years, diagnosing students’ learning problems after testing and providing learning sugges- tions for them are an important research issue. Many studies have been conducted to develop a method for analyzing learning barriers of students such that helpful learning suggestions or guidance can be provided based on the analysis results. In this paper, we present a new procedure for integrating test item–concept relationship opinions based on majority density of multiple experts in order to enhance a concept–effect relationship model used for generating personalized feedback. It provides a useful and practical way to decrease inconsistencies in the weighting criteria of multiple experts and to enhance the entire learning-diagnosis procedure for developing testing and diagnostic systems.engMahidol UniversityConcept–effect relationship modelComputer-based testingComputer-assisted learningDiagnostic learning systemMulti-expert systemA majority-density approach to developing testing and diagnostic systems with the cooperation of multiple experts based on an enhanced concept-effect relationship modelArticleElsevier Ltd.10.1016/j.eswa.2012.01.182