Material Development for Peer-Assisted Learning Program (PALP) in Higher Education
Bibliographic record
Abstract
Teaching English as a foreign language in higher education becomes more challenging from year to year. Based on the learner and learning needs, nowadays, English should be taught in relation to the other fields of the study. The phenomena require a certain ‘scenario’ to support the students’ English mastery. In accordance to the condition, English Education Department of Universitas Ahmad Dahlan has a program to help the students improving their English skills called Peer-Assisted Learning Program PALP. As an official program in the department, PALP is managed professionally by the boards. However, developing the appropriate materials for the program still becomes one big question to everyone dealing with the program, especially the boards. It is a really challenging work to develop such informative and practical materials for the students joining the program. Thus, in this paper, the writer will discuss several theories as the basis in developing the materials for PALP. It will cover the information about PALP, learner needs, learning needs, criteria of good materials, material development, and materials evaluation/assessment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| 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".