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Record W4405202807 · doi:10.5539/elt.v18n1p1

Directed Motivational Currents Under DST: A Critical Review

2024· review· en· W4405202807 on OpenAlexvenueno aff

Bibliographic record

VenueEnglish Language Teaching · 2024
Typereview
Languageen
FieldComputer Science
TopicEducational Technology and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyConstruct (python library)Cognitive psychologyGoal theoryCognitive scienceSocial psychologyComputer science

Abstract

fetched live from OpenAlex

"Directed motivational currents" (DMCs) represent a novel construct within L2 motivation theory, extensively utilized in the domain of second language acquisition research. Initially introduced by Dörnyei (2013), DMCs describe a state of complete immersion in a task, aligning with the dynamic systems theory (DST), particularly during the socio-dynamic phase of L2 motivation. At the outset, Dörnyei was inspired by the 'flow experience' introduced by Csikszentmihalyi in 1975. This review centers on the construct of 'directed motivational currents' in accordance with the complex dynamic systems theory (DST). Consequently, the four significant periods in second language (L2) motivation, the complex dynamic systems theory, as well as the characteristics and dimensions of DMCs will be expounded. Additionally, this article begins with presenting its origin and reflecting on how the research of DMCs has evolved over time. This can be categorized into its validity, its application in teaching, the triggers and mediating forces involved, and its relationship with other concepts. Critiques regarding it will also be provided.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.048
GPT teacher head0.417
Teacher spread0.369 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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