A Model of the Test Technology of Teaching: Theoretical and Applied Aspects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The aim of this article is to reveal the results of studying the theoretical and applied aspects of the test technology of teaching: to structure the technological cycle, develop a model of the test technology of teaching, reveal the ways of optimisation of the educational process using the test technology. The conducted research shows that using test technologies of teaching significantly increases the qualitative indicators of mastering the material because of the motivational component, objectivity of evaluation, psychological comfort and elements of gamification. It has been determined that the efficiency of its implementation is affected by such aspects as compliance with the technological cycle, balancing the level of difficulty of test tasks by the difficulty index (Is), selection of the strategy for task placement, correctness of distractor creation, establishment of optimal quantitative and temporal characteristics of the test, the evaluation system, synchronous or asynchronous interaction between a teacher and students.
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.
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 | 0.002 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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 it