Sigma&Mu: Journal of Mathematics, Statistics and Data Science
Vol. 1 No. 2 (2023): September

Development of TPACK Based-Learning Media Oriented Towards Students' Motivation and Mathematics Outcomes

Aulia Dinda Dwi Kartika (Unknown)
Eka Kurniawan (Unknown)



Article Info

Publish Date
30 Sep 2023

Abstract

This study aims to develop Technological Pedagogical Content Knowledge (TPACK)-based learning media oriented towards motivation and mathematics learning outcomes that are valid, practical and effective. The subjects in this study are class VIII students at one of the junior high school in Mataram. This type of this study is Research and Development with the ADDIE (Analysis, Design, Development, Implementation and Evaluation) model. Data analysis in this study was carried out using descriptive quantitative and qualitative regarding the advisibility of learning media obtained from assessment or validation sheets, analysis of the practicality of learning media obtained from student response questionnaires and teacher responses to learning media, and analysis of the effectiveness of learning media obtained from posttest results. The study results obtained that:  TPACK-based learning media has been developed is suitable for use as learning media with high validity; TPACK-based learning media is practically used as learning media with a practicality score of 79.67%;  The N-gain value for increasing students matemathics learning motivation is 43.34% in the medium category, while for increasing students matemathics learning outcomes it is 56.74% in the medium category. Based on the results, TPACK-based learning media is suitable for use, practically applied for learning, less effective for increasing learning motivation, and quite effective in improving learning outcomes

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Journal Info

Abbrev

sigmamu

Publisher

Subject

Education Mathematics

Description

Sigma&Mu: Journal of Mathematics, Statistics and Data Science is an international peer-reviewed journal that publishes original and high-quality research papers in all areas of mathematics, statistics, and data sciences. As an important academic exchange platform, scientists and researchers can know ...