Analysis of motivational strategies in 11th grade students of English class at Amistad Quebec School in Teustepe, Boaco
Bibliographic record
Abstract
This research was focused in the motivational strategies that influence 11th grade students of English language class at Amistad Quebec School. Three main factors were identified in the teaching -learning process of this grade. \n \nThe factors are the following: intrinsic and extrinsic motivation, traditional motivation and language anxiety. \n \nExtrinsic motivation, which leads to negative motive, attitude, and discouragement in participants, teacher and students, extrinsic motivation overrides intrinsic motivation in that some students are expected to finish the scholastic year to find a job. Traditionally, students do not use English outside of the classroom because classes usually focus on repetitive strategies. \n \nAlso, old tendencies contribute to low student achievement in general. Language anxiety, in which students feel afraid to use what they have learned in the classroom, contributes to low achievement of the target language. \n \nIn this investigation, interviews and focal groups will be used to understand how strategies used by teachers affect student motivation. \n \nIn general, this research considers the relationship between traditional and modern methods in the engagement of students in English class, the attitude of the teacher toward English, and the ways in which the teacher motivates his students
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".