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Authors: Kazuma Mihara ; Takahito Tamai and Yukie Majima

Affiliation: Graduate School of Humanities and Sustainable System Sciences, Osaka Prefecture University and Japan

Keyword(s): Class Evaluation, Active Learning, Text Mining, Correspondence Analysis, Health Care Related Subjects.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Active learning is defined as "a general term for professors and learning methods that incorporate participation in active learning of the students, unlike teachers' unilateral lecture style education." Universities that improve classes from the viewpoint of active learning are increasing in recent years. A class evaluation questionnaire has been established to improve the understanding and satisfaction of students' classes. In many cases, the Likert scale is used for the class evaluation questionnaire. There are also aspects for which statistical processing is easy to do. However, it is difficult to ascertain the students ' specific opinions and ideas alone. Therefore, we attempted to evaluate health-care-related subjects from the two viewpoints of ‘free description’ and ‘degree of accomplishment of class goal’ for active learning classes aimed at students' subjective learning.

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Paper citation in several formats:
Mihara, K.; Tamai, T. and Majima, Y. (2019). Evaluating Health-care-related Active Learning Class Lectures using Class Achievement and Text Mining of Free Descriptions. In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - HEALTHINF; ISBN 978-989-758-353-7; ISSN 2184-4305, SciTePress, pages 456-461. DOI: 10.5220/0007572704560461

@conference{healthinf19,
author={Kazuma Mihara. and Takahito Tamai. and Yukie Majima.},
title={Evaluating Health-care-related Active Learning Class Lectures using Class Achievement and Text Mining of Free Descriptions},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - HEALTHINF},
year={2019},
pages={456-461},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007572704560461},
isbn={978-989-758-353-7},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - HEALTHINF
TI - Evaluating Health-care-related Active Learning Class Lectures using Class Achievement and Text Mining of Free Descriptions
SN - 978-989-758-353-7
IS - 2184-4305
AU - Mihara, K.
AU - Tamai, T.
AU - Majima, Y.
PY - 2019
SP - 456
EP - 461
DO - 10.5220/0007572704560461
PB - SciTePress

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