Integration of Intrinsic and Extrinsic Motivation in Second Language Acquisition: Magnetism as a Proposed Theory
Bibliographic record
Abstract
Language learning motivation is significantly shaped by both external and internal factors, influencing the learning process in either a positive or negative manner. These factors span educational and environmental domains, particularly in a demotivated learning society. Thus, this paper introduces a theory that combines intrinsic and extrinsic motivation components, aiming to attract learners to language learning, given its relevance to knowledge across diverse domains and global understanding. This theoretical paper not only offers an overview of previously proposed theories, assessing their merits and limitations but also delves into the conceptualized components of the new theory, Magnetism, along with its foundational principles. Magnetism comprises two intricately linked major components elucidating intrinsic and extrinsic motivation, detailing their interaction, mutual influence, and their role in fostering a positive attitude toward language learning. Additionally, the paper delineates three types of relationships that connect the components and their constructs to each other and to the overall framework.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".