Developing Themes of Guiding Principles to Foster Higher Order Thinking Skills in Teaching and Learning of Mathematics
Bibliographic record
Abstract
The trend results of TIMSS and PISA shows that students' achievement is low in the field of mathematics, especially in answering questions that require Higher Order Thinking Skills (HOTS).Thus Malaysian Education Blueprint 2013-2025 suggested transitions in mathematics education from focusing on cognitive algorithm skills to the implementation of HOTS in teaching and learning of mathematics.A holistic framework in the form of comprehensive processes of fostering HOTS in mathematics teaching and learning is needed to guide teachers in implementation suitable activities in the classroom.Therefore, this research is intended to develop a Guiding Principles of Fostering Higher Order Thinking Skills (GP-HOTS) in teaching and learning of mathematics for secondary school students.Specifically, this article discusses the analysis of HOTS inculcation development in teaching and learning in general and in mathematics education to generate items and themes for GP-HOTS.This qualitative analysis document involves two strategies.Firstly, the electronic databases and journals used to find related articles.In addition, the journals related to HOTS are analyzed to identify more relevant journals.Keywords used for search is HOTS, creative thinking, critical thinking, methods/strategies/techniques for teaching in the 21st century, and the methods/strategies/techniques for effective teaching.At the second stage, the method of snowballing is used to identify the items and themes for GP-HOTS.The themes and items for GP-HOTS were then tested for the content validity and reliability by determing the content validity and the alpha Cronbach indices.The results showed that there are seven main themes of how teachers can foster HOTS in teaching and learning of mathematics namely determining the learning outcomes, planning questioning strategies, practicing active learning, developing habits of mind, practicing reflective thinking, implementing optimally assessment for learning and integrating information, communication and technology.The themes and its items have satisfied level of content validity indices for the face and content validities as well as revealed excellent
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".