Abstract
In this paper is presented a modeling of assessment systems of taxonomies using fuzzy logic. Specifically the taxonomies system solo is studied, which can be applied in a wide range of fields of diagnostic science. In what concerns education, the test correction is extremely hard and demands experts that are not always available. The intelligent system offers the opportunity to evaluate and classify students’ performance according to the structure of the observed learning outcome, concerning the cognitive development of the students in the field of mathematics. The system was tested on high school and university students.
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References
Biggs, J.B., Collis, K.F.: Evaluating the Quality of Learning: the SOLO Taxonomy. Academic Press, New York (1982)
Biggs, J.B., Collis, K.F.: Multimodal learning and the quality of intelligent behavior. In: Rowe, H.H. (ed.) Intelligence: Reconceptualization and Measurement Vic.: ACER, pp. 57–76. Lawrence Erb. freemanm Associates and Hawthorn, Hillsdale (1991)
Drigas, A., Kouremenos, S., Vrettos, S., Vrettaros, J., Kouremenos, D.: An ex- pert system for job matching of the unemployed. Pergamon-Elsevier Science LTD., Oxford, IDS (2004)
Cox, E.: The Fuzzy Systems Handbook: A Practitioner’s Guide to Building, Using, & Maintaining Fuzzy Systems (1999)
Gogus, O., Boucher, T.O.: A Consistency Test for Rational Weights in Multi- Criterion Decision Analysis with Fuzzy Pairwise Comparisons. Fuzzy Sets and Systems 86, 129–138 (1997)
Imrie, B.W.: Assessment for Learning: Quality and Taxonomies. Assessment and Evaluation in Higher Education 20(2), 175–189 (1995)
Koleza, E., Barkatsas, A.: The SOLO Taxonomy as a tool for evaluation in Mathe- matics. In: 2nd Mediterranean Conference on Mathematics Education, Nicosia, Cyprus (2000)
Maeda, S., Murakami, S.: The Use of a Fuzzy Decision-Making Method in a Large- Scale Computer System Choice Problem. Fuzzy Sets and Systems 54, 235–249 (1993)
Nastoulis, C., Leros, A., Bardis, N.: Banknote: Recognition Based on Probabilistic Neural Network Models. WSEAS Transactions on Systems 5(10), 2363–2367 (2006)
Vrettaros, J., Grigoriadou, M.: Design of hybrid architecture for fuzzy connectionist expert system and its application to approximate student model. In: CATE 1996. The first international conference on computers and advanced technologies in education, Cairo (1996)
Zadeh, L.F.: Toward a Theory of Fuzzy Information Granulation and its Centrality in Human Reasoning and Fuzzy Logic. Fuzzy Sets and Systems 90, 111–127 (1997)
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Vrettaros, J., Vouros, G., Drigas, A. (2007). Development of an Intelligent Assessment System for Solo Taxonomies Using Fuzzy Logic. In: Mellouli, K. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2007. Lecture Notes in Computer Science(), vol 4724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75256-1_78
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DOI: https://doi.org/10.1007/978-3-540-75256-1_78
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