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                <identifier>ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:1:11593</identifier>
                <datestamp>2025-09-22T08:21:00Z</datestamp>
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                    <dim:field mdschema="dc" element="title" lang="en">Predicting Student Performance Using the Multilayer Perceptron Method Combined with Traditional Evaluation Techniques</dim:field>
                    <dim:field mdschema="dc" element="date" qualifier="issued">2025</dim:field>
                    <dim:field mdschema="dc" element="identifier" qualifier="uri">http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/1/11593</dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="orcid::0000-0003-1098-371X" confidence="-1">С. Спасић</dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="orcid::0000-0001-5187-6254" confidence="-1">V. Tomašević</dim:field>
                    <dim:field mdschema="dc" element="description" qualifier="abstract">This paper examines student performance in higher education by proposing the use of the Multilayer Perceptron (MLP) method for grade classification and performance forecasting. The main objective is to monitor students&amp;apos; knowledge and predict their performance using multiple indicators. This model supports early identification of at-risk students, enhances instructional strategies, and promotes student engagement. The results highlight the effectiveness of MLP in monitoring and predicting student progress, improving the objectivity of assessment.</dim:field>
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