Please use this identifier to cite or link to this item: http://hdl.handle.net/11328/3862
Title: Clustering Algorithm to Measure Student Assessment Accuracy: A Double Study
Authors: Sobral, Sónia Rolland
Oliveira, Catarina Félix de
Keywords: Self-assessment
Self-evaluation
Higher education
Clustering
Accuracy
Issue Date: 18-Dec-2021
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Citation: Sobral, S. R., & Oliveira, C. F. (2021). Clustering Algorithm to Measure Student Assessment Accuracy: A Double Study. Big Data and Cognitive Computing, 5(4), 81. doi: https://doi.org/10.3390/bdcc5040081. Disponível no Repositório UPT, http://hdl.handle.net/11328/3862
Series/Report no.: ;4
Abstract: Self-assessment is one of the strategies used in active teaching to engage students in the entire learning process, in the form of self-regulated academic learning. This study aims to assess the possibility of including self-evaluation in the student’s final grade, not just as a self-assessment that allows students to predict the grade obtained but also as something to weigh on the final grade. Two different curricular units are used, both from the first year of graduation, one from the international relations course (N = 29) and the other from the computer science and computer engineering courses (N = 50). Students were asked to self-assess at each of the two evaluation moments of each unit, after submitting their work/test and after knowing the correct answers. This study uses statistical analysis as well as a clustering algorithm (K-means) on the data to try to gain deeper knowledge and visual insights into the data and the patterns among them. It was verified that there are no differences between the obtained grade and the thought grade by gender and age variables, but a direct correlation was found between the thought grade averages and the grade level. The difference is less accentuated at the second moment of evaluation—which suggests that an improvement in the self-assessment skill occurs from the first to the second evaluation moment
URI: http://hdl.handle.net/11328/3862
ISSN: 2504-2289
Appears in Collections:REMIT – Artigos em Revistas Internacionais / Papers in International Journals

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