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. Preprints2022, 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
Bhattacharyya, S.; De, S.; Mrsic, L.; Pan, I.; Muhammad, K.; Mukherjee, A.; Konar, D. A Quantitative Assessment of Rubrics Using a Soft Computing Approach. Preprints2022, 2022100197. https://doi.org/10.20944/preprints202210.0197.v1
APA Style
Bhattacharyya, S., De, S., Mrsic, L., Pan, I., Muhammad, K., Mukherjee, A., & Konar, D. (2022). A Quantitative Assessment of Rubrics Using a Soft Computing Approach. Preprints. https://doi.org/10.20944/preprints202210.0197.v1
Chicago/Turabian Style
Bhattacharyya, S., Anirban Mukherjee and Debanjan Konar. 2022 "A Quantitative Assessment of Rubrics Using a Soft Computing Approach" Preprints. 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.
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.