Non-Cognitive Factors Influencing Science Achievement in Malaysia and Japan: An Analysis of TIMSS 2015

Abstract

Japan's continual excellent achievement in TIMSS has led to many research and discussions of the Japanese school system as a way of understanding the factors and system that underlie Japan's success in TIMSS. However, comparative studies have focused more on cognitive skills and less on non-cognitive skills as plausible factors for the continual success. Thus, this study aimed to examine the non-cognitive factors related to students' science achievement in TIMSS. This study adopted secondary data analysis where the analysis was carried out on TIMSS 2015 data for respondents from Malaysia and Japan. This study proposed two models for each country which contained five constructs, namely four independent variables which are science teaching practices, victims of bullying, attitude towards science, school climate, and one independent variable i.e. science achievement. From the structural model of multiple group comparison analysis, almost all non-cognitive factors in the model showed significant difference between the two countries except for the relationship between attitude towards science and science achievement in TIMSS.

Investigating Latent Interactions between Students’ Affective Cognition and Learning Performance: Meta-Analysis of Affective and Cognitive Factors

“…Many factors affect students' academic performance, including internal and external motivation, self-efficacy, and self-initiative, among others [58][59][60][61][62][63]. Scholars have also explored the effects of cognitive and emotional components on these factors.…”

International Comparative Assessment of Science and Mathematics Achievement in TIMSS

“…Japan's continual excellent achievement in TIMSS has led to many researches and discussions of the Japanese school system as a way of understanding the factors and system that underlie Japan's success in TIMSS. In this article, Mohtar, Halim, Samsudin, and Ismail (2019) examined the non-cognitive factors as plausible factors to students' TIMSS science achievement in Malaysia and Japan. The study adopted secondary data analysis in which the analysis was carried out on TIMSS 2015 data for respondents from Malaysia and Japan.…”

Determination of the Characteristics Predicting Science Achievement through the Classification and Regression Tree (CART) Method: The Case of TIMSS 2015 Turkey

“…Bu bağlamda, bu araştırmadan elde edilecek sonuçların fen eğitimi ve gelişimine ayrıca fen eğitiminin değerlendirilmesi ve karşılaştırılmasına katkı sağlayacağı düşünülmektedir. Literatürde, araştırmanın problem durumu ve veri yapısına benzer problem durumu ve veri özellikleri üzerinden, farklı yıllarda gerçekleştirilmiş olan PISA (Programme for International Student Assessment) ve TIMSS uygulamalarının verilerinden yararlanılarak yürütülmüş çalışmalar (Anıl, 2009;Atar ve Atar, 2012;Beese ve Liang, 2010;Chen, Lin, Wang, Lin ve Kao, 2012;Forbes, Neumann ve Schiepe-Tiska, 2020;Gee ve Wong, 2012;Kaya ve Doğan, 2017;Mohtar, Halim, Samsudin ve Ismail, 2019;Wiberg ve Rolfsman, 2019) mevcuttur. Bu çalışmalarda literatüre paralel olarak; hiyerarşik doğrusal (lineer) model (HLM), yapısal eşitlik modeli (YEM), çoklu regresyon, lojistik regresyon, ANOVA, t testi gibi analiz teknikleri kullanılarak öğrencilerin fen başarılarını yordayan ya da fen başarıları ile ilişkili olan özelliklerin belirlenmesi amaçlanmıştır.…”