Eko Pardiyanto, - and Winarti, - (2021) Generative Learning Strategy Assisted by Flash Animation to Remediate Students’ Misconceptions on Newton’s Law of Gravity. Jurnal Pendidikan Sains Indonesia, 9 (2). pp. 201-216. ISSN e-ISSN: 2615-840X p-ISSN: 2338-4379
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Abstract
The generative learning strategy assisted by flash animation had not been applied to overcome learners’ misconceptions. This research aims to find out the effectiveness of generative learning strategy assisted by flash animation to remediate learners’ misconceptions toward the Newton’s law about gravity and to determine the way to decrease learners’ misconceptions after the intervention. This research applied the quasi-experimental method with pretest-posttest control group design. This research was conducted at Public Senior High School 5 Yogyakarta. The population consisted all ten graders, 216 participants. The sample was taken with purposive sampling from X-science-mathematics-2 learners as the control group and X-science-mathematics-4 learners as the experimental group. There were seventy-two learners. The applied instruments were two-tier multiple choice items and the learner-interview sheet, as the non-test instrument. From the research, the obtained N-Gain was 0.476. The hypothesis test showed that the t-test obtained the asymp.sig 2(tailed)of 0.000 and the probability score was 0.05. The asymp.sig (2-tailed) was lesser than the probability score and its effectiveness was 0.988. The decreased misconception after the intervention found in experimental group was 20% while the control group was 2.30%. It meant generative learning strategy assisted with flash animation was effective to remediate the tenth-graders’ misconceptions of Public Senior High School 5 Yogyakarta on Newton’s law about gravity
Item Type: | Article |
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Uncontrolled Keywords: | Flash Animation, Generative Learning, Newton’s Law of Gravity, Remediate Misconceptions |
Subjects: | Fisika |
Divisions: | Artikel (Terbitan Luar UIN) |
Depositing User: | Dra. Khusnul Khotimah, SS, M.IP - |
Date Deposited: | 13 Jul 2022 13:44 |
Last Modified: | 13 Jul 2022 13:44 |
URI: | http://digilib.uin-suka.ac.id/id/eprint/51942 |
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