Assessing Students’ Mathematical Knowledge with Fuzzy Logic

Bibliographic Data

ID22042989
AuthorsDaniel Doz (0000-0002-6942-6937, University of Primorska, corresponding author), Darjo Felda (0000-0002-8588-0654, University of Primorska), Mara Cotič (0000-0002-4958-4858, University of Primorska)
Year2022
Volume12
Issue4
Pages266
Publication date2022-04-10
Open AccessYes
TypeARTICLE
VenueEducation Sciences (JOURNAL)
Journal identifiersISSN: 2227-7102 • E-ISSN: 2227-7102
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/educsci12040266
OpenAlexW4223640336
LanguageEN
References cited19

Assessing student mathematical knowledge is an important factor in the mathematics learning process because students obtain important feedback to improve their knowledge and learning. Despite the importance of student assessment, several researchers have shown that student grades comprise noncognitive and metacognitive factors and teachers’ prejudices and beliefs. One method to obtain a more objective view of student mathematical knowledge is through standardized assessments. In this paper, we analyze two methods of assessing student mathematical knowledge by considering their written and oral grades and achievements on the Italian National Assessment of Knowledge (INVALSI). The final grade was produced using the fuzzy logic inference system. It was tested on a sample of 2279 Grade 13 Italian high school students, who had both an oral and written grade in mathematics and who took the INVALSI assessment in the school year 2020–2021. Both tested fuzzy-logic-based assessment methods lowered the mean grades

Cognition · Fuzzy logic · Inference · Knowledge level · Mathematical logic · Mathematics education · Metacognition · Computer Science · Educational Technology and Assessment · Intelligent Tutoring Systems and Adaptive Learning · Online Learning and Analytics · Psychology · Artificial Intelligence

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