Objective and subjective variables in two university classes
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 importance of the motivational components in the learning of foreign languages has attracted the interest of teachers, linguists and psychologists in recent decades, giving way to a number of acclaimed studies led by the Canadian psychologist Gardner and his associates. His theories, stressing the role of integrative motivation as a key element in successful language learning, aroused the interest of education researchers, who stressed the need to extend the field of research and include educational factors as well as socio-psychological ones. Oxford & Ehrman in the United States and Dörnyei in Europe have introduced new elements for consideration, and the latter has backed his theories with data emerging from Hungarian classrooms. In the present article we aim to underline the need to consider, on the one hand, the connections between objective variables, associated with the formal learning situation, such as class attendance and participation as well as results in language and other related subjects, and, on the other, affective variables in order to assess the importance of motivation in the language classroom.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 it