Evaluation of Online Learners’ Learning Performance Based on Fuzzy Borda Method
DOI:
https://doi.org/10.3991/ijet.v18i14.40397Keywords:
fuzzy Borda method, online learners, learning performance, performance evaluationAbstract
Since the traditional evaluation system of learning focuses only on the summative evaluation of learners’ test scores, ignoring the process evaluation of learners in learning process, the evaluation system should not only consider the content of the online learning process but also that of face-to-face classroom teaching process to evaluate learners’ learning performance in multiple dimensions and levels. This approach evaluates online learning more reasonably, operably and feasibly. To overcome limitation of using more than one method in the evaluation of learning performance, the learning performance of online learners was first evaluated using the principal component analysis method, entropy method, comprehensive indicator method, and TOPSIS method. Based on these four evaluation results, a combination evaluation model of online learners’ learning performance was constructed. The Fuzzy Borda method was used to evaluate nine administrative classes of accounting majors in three colleges and universities in Hainan. The results show that simply using a single evaluation method to evaluate the learning performance of online learners has defects, and the evaluation results are too biased. By using the Fuzzy Borda method, multiple evaluation methods can be combined, allowing a single evaluation method to realize complementary advantages and obtain more comprehensive and credible evaluation results. Using the Fuzzy Borda method to systematically evaluate the learning performance of online learners improves the scientificity of evaluation results and provides a new idea and method for the evaluation of online learning performance. The results of this study have significant reference value for using scientific evaluation methods and objective data to evaluate online learning performance, rank online learners scientifically, and summarize teaching experience to improve online learning performance.
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Copyright (c) 2023 Hongbing Lin, Dongdong Lin
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