Literaturnachweis - Detailanzeige
| Autor/in | Jena, Ananta Kumar |
|---|---|
| Titel | Predicting Learning Outputs and Retention through Neural Network Artificial Intelligence in Photosynthesis, Transpiration and Translocation |
| Quelle | In: Asia-Pacific Forum on Science Learning and Teaching, 19 (2018) 1, Artikel 8 (26 Seiten)
PDF als Volltext |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 1609-4913 |
| Schlagwörter | Artificial Intelligence; Pretests Posttests; Misconceptions; Experimental Groups; Control Groups; Prediction; Outcomes of Education; Science Instruction; Retention (Psychology); Science Tests; Teaching Methods; Plants (Botany); Secondary School Students; Foreign Countries; India |
| Abstract | 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. (As Provided). |
| Anmerkungen | 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 |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2020/1/01 |
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