Development of a Practical System for Computerized Evaluation of Descriptive Answers of Middle School Level Students

Autor/inn/en	Saha, Sujan Kumar; Rao C. H., Dhawaleswar
Titel	Development of a Practical System for Computerized Evaluation of Descriptive Answers of Middle School Level Students
Quelle	In: Interactive Learning Environments, 30 (2022) 2, S.215-228 (14 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Saha, Sujan Kumar) ORCID (Rao C. H., Dhawaleswar)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1049-4820
DOI	10.1080/10494820.2019.1651743
Schlagwörter	Middle School Students; Grading; Artificial Intelligence; Automation; Social Studies; Student Evaluation; Foreign Countries; India + Suchen Sie Ihr Suchwort? Middle school; Middle schools; Student; Students; Mittelschule; Mittelstufenschule; Schüler; Schülerin; Notengebung; Schulnote; Künstliche Intelligenz; Gemeinschaftskunde; Studentische Bewertung; Ausland; Indien
Abstract	Assessment plays an important role in education. Recently proposed machine learning-based systems for answer grading demand a large training data which is not available in many application areas. Creation of sufficient training data is costly and time-consuming. As a result, automatic long answer grading is still a challenge. In this paper, we propose a practical system for long or descriptive answer grading that can assess in a small class scenario. The system uses an expert-written reference answer and computes the similarity of a student answer with it. For the similarity computation, it uses several word level and sentence level similarity measures including TFIDF, Latent Semantic Indexing, Latent Dirichlet Analysis, TextRank summarizer, and neural sentence embedding-based InferSent. The student answer might contain certain facts that do not occur in the model answer. The system identifies such sentences, examine their relevance and correctness, and assigns extra marks accordingly. In the final phase, the system uses a clustering-based confidence analysis. The system is tested on an assessment of school-level social science answer books. The experimental results demonstrate that the system evaluates the answer books with high accuracy, the best root mean square error value is 0.59 on a 0-5 scoring scale. (As Provided).
Anmerkungen	Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01