Causalitic-learning model to improve reasoning-ability in learning physics in terms of student creativity during the covid-19 pandemic
Author(s) -
Nurjamilah Nurjamilah,
Joni Rokhmat,
Haerunisyah Sahidu,
Ahmad Harjono,
Hikmawati Hikmawati
Publication year - 2021
Publication title -
journal of physics conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1816/1/012039
Subject(s) - creativity , mathematics education , class (philosophy) , population , psychology , critical thinking , computer science , social psychology , artificial intelligence , sociology , demography
This study aims to examining the effect of 1) the causalitic-learning model (CLM) on reasoning-ability (RA), 2) creativity on RA, and 3) the interaction between the CLM and creativity on RA. This research is quasi-experimental with a 2x2 factorial design. The population is all students of class X-IPA. Sampling uses purposive-technique with consideration of the ability and support of parents in facilitating students and obtained students of class X-IPA-3 (31-students) as an experimental class and class X-IPA-4 (30-students) as a control class. The data of RA and creativity were gathered by using four description-tests. The results show that the data is normally distributed and homogeneous as indicated by chi-square counted (10.87) < chi-square table (11.07), F count (1.57) < F count (1.85) (for RA) and F count (1.50) < F count (1.85) (for creativity). The hypothesis was tested using two-way ANOVA with the help of the SPSS 18 application. The conclusion is that in learning physics during the Covid-19 pandemic: 1) there is an influence of the CLM on RA, 2) there is an influence of creativity on RA, and 3) there is no interaction effect between the CLM and creativity on RA. Recommendation: In implementing a CLM to improve RA, it is better to use creativity-related phenomena in the form of pictures to facilitate students to do causality-thinking and argument formulation.
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