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ERIC Number: EJ1192370
Record Type: Journal
Publication Date: 2018-Jun
Pages: 26
Abstractor: As Provided
ISBN: N/A
ISSN: EISSN-1609-4913
Predicting Learning Outputs and Retention through Neural Network Artificial Intelligence in Photosynthesis, Transpiration and Translocation
Jena, Ananta Kumar
Asia-Pacific Forum on Science Learning and Teaching, v19 n1 Article 8 Jun 2018
Artificial Intelligence is a branch of computer science connects, classifies, differentiates, and elaborates the domains of learning in neural network, a paradigm shift is using in the construction of knowledge. In this pretest-posttest single group experimental design, neural network artificial intelligence used to investigate the existing misconception status of the participants, and predicted the learning outcomes, and retention of learning. The study aimed to assess the effects of neural network artificial intelligence approach on the achievement and retention in science learning. Forty students of a class were participated in this study, and out of them five students found having 60% to 80% of misconceptions assessed in the misconception test before exposed to the neural network artificial intelligence approach. It resulted that the mean of posttest score was statistically significant in different from the mean of the pretest score. It was resulted that input layer and first hidden layer were related with the output of the artificial intelligence.
Hong Kong Institute of Education. 10 Lo Ping Road, Tai Po, New Territories, Hong Kong. Tel: +011-852-2948-7650; Fax: +011-852-2948-7726; e-mail: apfslt@sci.ied.edu.hk; Web site: http://www.ied.edu.hk/apfslt
Publication Type: Journal Articles; Reports - Research; Tests/Questionnaires
Education Level: Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: India