Integrating Student-Centered Learning in Finance Courses: The Case of a Malaysian Research University
Bibliographic record
Abstract
The student-centered learning (SCL) approach is an approach to education that focuses on learners and their needs, rather than relying upon the input of the teacher's. The present paper examines how the SCL approach is integrated as a learner-centered paradigm into finance courses offered at a business school in a research university in Malaysia. Specifically, this paper identifies how a learner-centered environment is integrated into teaching methods, learning activities and evaluation tools. Since the adoption of the SCL approach is partly to cater for the needs of the research university, the analysis of the courses is supported with responses from the respective lecturers. This study finds that the lecturers of the five courses examined have used active/interactive learning and group project approaches as standard teaching methods under the SCL approach which includes projects, class discussion and presentation. Alongside these standard methods, some of the courses use additional methods under the SCL approach, including real life experiential learning and case studies. For example, students of the Investment and Portfolio Analysis course are exposed to the real world investment decision making by investing funds in selected stocks listed on Bursa Malaysia. In terms of course evaluations, the courses place greater weight on continuous assessment based on group projects and presentations, while reduce the emphasis on examinations. Overall, implementing the SCL approach requires a careful design of the learning process, which includes the classroom setting; flexibility of the curriculum; teaching methods; evaluation policies; and course content. In general, the study demonstrates that SCL has great potential to function as an effective learning tool in an environment where the labor market demands generically skilled job candidates and in which universities are demanding further resources to be devoted to efforts relating to research and publications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".