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All Journal Dinamika Jurnal Pendidikan Dasar Al-Jabar : Jurnal Pendidikan Matematika
Lam, Toh Tin
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Decision Sciences, Operations Research & Management Education Mathematics

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Use of Real-World Contexts in Instructional Materials Designed by Pre-University Mathematics Teachers Tan, Zheng Han, Hans; Lam, Toh Tin; Fah, Lay Yoon
Dinamika Jurnal Ilmiah Pendidikan Dasar Vol. 15 No. 2 (2023): Dinamika Jurnal Ilmiah Pendidikan Dasar
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/dinamika.v15i2.18973

Abstract

Pre-university education in Singapore serves as a bridge between secondary and university education. Despite its importance and the popularity of mathematics as a subject, few studies have been conducted on Singapore pre-university mathematics. We also notice that problems in real-world contexts have been increasingly emphasised in the Singapore mathematics curriculum. In this paper, we study the infusion of real-world contexts in the instructional materials of a typical pre-university institution, with a focus on the topic of vectors. The word problems used in the instructional materials involving real-world contexts are categorised into neutral contexts and basic real-life experiences, and the benefits of utilising these problems are discussed. The benefits include the potential to raise students’ awareness that mathematics can be used as a resource to solve real-world problems or explain real-world phenomena. The alignment of these word problems to the Singapore mathematics curriculum and 21st Century Competencies is also discussed.
On Some Guiding Principles of Enacting Mathematical Problem Solving for Classroom Instruction Ng, Yu Xin; Lam, Toh Tin
Dinamika Jurnal Ilmiah Pendidikan Dasar Vol. 16 No. 1 (2024): Dinamika Jurnal Ilmiah Pendidikan Dasar
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/dinamika.v16i1.20441

Abstract

In addressing the key role that problem solving has been playing in mathematics instruction for K-12, this paper aims to assist mathematics teachers and educators to consider a set of guiding principles for designing problem solving tasks for classroom instructions. The set of guiding principles was synthesized and proposed through the researchers’ systematic review of existing education literature on problem solving.
Generation Z Prefers Teacher-Assisted over Artificial Intelligence-Assisted Mathematics Learning: A Self-Determination Theory Analysis Arwadi, Fajar; Lam, Toh Tin; Qalbi, Nurfitri
Al-Jabar: Jurnal Pendidikan Matematika Vol 17 No 3 (2026): Al-Jabar : Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/

Abstract

Purposes:  The rapid integration of artificial intelligence (AI) in education has reinforced techno-optimistic assumptions that algorithmic efficiency can support increasingly autonomous learning. This study examined Generation Z students’ preferences for AI-assisted and teacher-assisted mathematics learning through the lens of Self-Determination Theory (SDT). Method: A quantitative within-subject comparative design was employed to collect data from 481 students in South Sulawesi, Indonesia. Participants evaluated both learning conditions using a 4-point Likert-scale questionnaire covering six dimensions: Concept Clarity, Feedback, Motivation, Learning Mode, Trust, and Comfort in Asking Questions. Paired-sample t-tests were used to compare students’ evaluations across the two conditions. Findings: Students rated teacher-assisted learning significantly higher than AI-assisted learning across all six dimensions (p < .001). The largest mean differences were observed in Concept Clarity and Trust, while the smallest occurred in Comfort in Asking Questions. Teacher-assisted learning was also rated more favorably in Learning Mode, despite the flexibility commonly associated with AI-based learning. Although AI-assisted learning received moderately positive evaluations, the overall pattern suggests that students placed greater value on the conceptual and relational support associated with teacher assistance. Significance: The findings suggest that technological flexibility alone may not be associated with stronger student preference for mathematics learning. Within this context, AI may be better positioned as a complementary instructional resource rather than a replacement for teacher assistance. Because the study relied on self-reported perceptions, the findings should not be interpreted as evidence of comparative instructional effectiveness.
Co-Authors Fah, Lay Yoon Fajar Arwadi NG, Yu Xin Qalbi, Nurfitri Tan, Zheng Han, Hans