Context-based problem-posing and solving instructional approach and students’ engagement in learning data handling
Abstract
The poor level of engagement in learning mathematics is primarily caused by ineffective methods of instruction. Therefore, the purpose of this study was to investigate how context-based problem-posing and solving instructional approaches influence students’ engagement in learning data handling using a concurrent embedded quasi-experimental non-equivalent pre-test-post-test control group mixed method design. A total of 138 fifth-grade students participated in the study. The data were collected using the Students’ Engagement in Learning Data Handling Scale, interviews, and lesson observation. Quantitative data were analyzed using mean, standard deviation, percentage, paired sample t-test, and ANCOVA. Qualitative data were analyzed thematically. The study found that context-based problem-posing and solving instructional approaches have brought a significant increment in students overall engagement and its entire component’s in learning data handling. Besides, it has been observed that there is a large effect size on overall engagement and cognitive, behavioral, and medium treatment effects on emotional engagement when the context-based problem-posing and solving instructional approaches group is compared to the comparison group. Context-based problem-posing and solving instructional approaches also encouraged students to pay attention, to think in different ways, to create and solve problems, to ask, share, reflect, and work through problems more diligently than before. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Author(s)
Tesfaw, Bimerew Kerie, Ayele, Mulugeta Atnafu, Wondimuneh, Tadele Ejigu
Year
2024
Countries
Ethiopia
Language
English
Research Method
Mixed Methods
Article Type
Peer-Reviewed Articles
Keywords
Higher education | health education | Mathematics education | Teaching methods | Problem-based learning | Excel Import
Full Citation Style
Research Team
Tesfaw, Bimerew Kerie
Ayele, Mulugeta Atnafu
Wondimuneh, Tadele Ejigu
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