Effects of Business Reading Model on Thai Learners’ Reading and Creative Thinking Abilities
Bibliographic record
Abstract
In second language research, reading has attracted the attention of numerous researchers. However, little has been carried out to investigate effects of a reading instructional model on Thai learners’ business reading and creative thinking abilities. Thus, this study investigates whether a business reading model designed based on Concept-Oriented Reading Instruction (CORI) and Project-Based Learning (PBL) enhances Thai undergraduates’ reading and creative thinking abilities. The study also investigates what reading strategies the students use frequently to improve their reading abilities. Based on pretest-posttest design, this study measured 35 undergraduates’ reading abilities and strategies through a reading comprehension test. Additionally, a mini project was assigned to gauge the students’ creative thinking abilities following the treatment. The findings demonstrate that the business reading model significantly increased the participants’ reading abilities and helped promote their creative thinking abilities. It is also discovered that the top three reading strategies these students used frequently to increase their reading abilities include finding the main idea, taking notes, and mapping the concept and integrating information. The study concludes by providing useful insights for researchers or educators who are interested in business English reading instruction. Pedagogical recommendations for further studies are also offered in this study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".