Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Quantitative Assessment of Rubrics Using a Soft Computing Approach

Version 1 : Received: 10 October 2022 / Approved: 14 October 2022 / Online: 14 October 2022 (02:18:02 CEST)

How to cite: Bhattacharyya, S.; De, S.; Mrsic, L.; Pan, I.; Muhammad, K.; Mukherjee, A.; Konar, D. A Quantitative Assessment of Rubrics Using a Soft Computing Approach. Preprints 2022, 2022100197. https://doi.org/10.20944/preprints202210.0197.v1 Bhattacharyya, S.; De, S.; Mrsic, L.; Pan, I.; Muhammad, K.; Mukherjee, A.; Konar, D. A Quantitative Assessment of Rubrics Using a Soft Computing Approach. Preprints 2022, 2022100197. https://doi.org/10.20944/preprints202210.0197.v1

Abstract

This study aims to elucidate a soft computing approach for quantitative assessment of the scoring grade or rubrics for students in an outcome based education system. The intended approach resorts to a fuzzy membership based assessment of the different parameters of the scoring system, thereby yielding a novel and humanly assessment technique. The selection of the membership functions is based on the human behavior so as to make a realistic representation of the scoring strategy. The novelty of the proposed strategy lies in assigning fuzzy membership based weighted scores instead of simply assigning score bands to rubric categories, as is performed in normal rubrics based assessment. Comparative results demonstrated on a case study of Indian education scenario reveal the effectiveness of the proposed strategy over other fuzzy membership and normal rubrics based assessment procedures.

Keywords

OBE; OBTE; graduate attributes; rubrics; fuzzy sets.

Subject

Computer Science and Mathematics, Computer Science

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