J
Jamalludin Harun
Researcher at Universiti Teknologi Malaysia
Publications - 74
Citations - 523
Jamalludin Harun is an academic researcher from Universiti Teknologi Malaysia. The author has contributed to research in topics: Collaborative learning & Higher-order thinking. The author has an hindex of 11, co-authored 69 publications receiving 403 citations. Previous affiliations of Jamalludin Harun include Multimedia University.
Papers
More filters
Journal ArticleDOI
The effect of Mobile problem-based learning application DicScience PBL on students’ critical thinking
TL;DR: The way the Problem Based Learning environment was integrated into the design and development process of mobile apps for learning scientific terms showed that the app had a positive effect on the students’ critical thinking.
Journal Article
Exploring students' knowledge construction strategies in computer-supported collaborative learning discussions using sequential analysis
TL;DR: This research found that groups those being able to construct high-level knowledge tend to negotiate on shared information and arguments are found to contribute for successful knowledge construction at higher-level.
Journal ArticleDOI
Problem Based Learning to Enhance Students Critical Thinking Skill via Online Tools
TL;DR: In this paper, a review of the use of online tools in Problem Based Learning (PBL) to enhance critical thinking skills is presented, which is defined as the intellectual thinking skills like analyzing, reasoning, problem solving, creative thinking, making judgement and good decision maker.
Journal Article
Relationship between teachers' ICT competency, confidence level, and satisfaction toward ICT training programmes : a case study among postgraduate students
TL;DR: In this article, the authors investigated the relationship among ICT competency, confidence level in using ICT, and satisfaction towards ICT training programs. But, they found that teachers had a high level of ICT competence (mean = 3.95).
Journal ArticleDOI
A predictive model to evaluate students' cognitive engagement in online learning
TL;DR: This study proposes the use of two types of data: students’ participation, and written messages that were collected and analyzed using the data mining technique to produce a predictive model that illustratesStudents’ pathways while engaging in online learning cognitively.