Implementation of Gamification as an Active Methodology to Enhance Motivation and Academic Performance in EFL Learners
Bibliographic record
Abstract
Gamification is a dynamic instructional methodology that enhances motivation and learning by incorporating game elements, which actively engage students. In this context, the present research aimed to determine the impact of gamification on public school students’ motivation to learn English as a Foreign Language. The sample consisted of N=441 learners (251 female and 190 male) who attended onsite classes. Their ages ranged from 11 to 12 years old. A quasi-experimental design was used to carry out this quantitative and qualitative study, which lasted five months. The techniques used were survey, interview, pre-test and post-test. The findings revealed that gamification had a positive influence on students' motivation to learn this language because students became interested in learning it in a fun way. Furthermore, the use of gamification helped students to improve their performance, which favoured their English academic achievement. Further research might consider using this methodology to promote students´ motivation to develop English skills in other learning environments, such as virtual ones.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".