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Self-Determination Theory and Language Learning

2023· book-chapter· en· W4321607886 on OpenAlexaff
Kimberly A. Noels

Bibliographic record

VenueOxford University Press eBooks · 2023
Typebook-chapter
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSociocultural perspectiveSociocultural evolutionPerspective (graphical)PsychologyLanguage acquisitionContext (archaeology)Learning theorySelf-determination theoryPedagogySociologyMathematics educationComputer science

Abstract

fetched live from OpenAlex

Abstract This chapter reviews the burgeoning research conducted from a self-determination theory (SDT) perspective concerning people’s motivation for learning new languages. To guide the review, a conceptual model of motivational processes, grounded in SDT principles, is presented. The model highlights the central role of basic psychological needs in motivational dynamics, including behavioral regulation (or orientations) and engagement, and ultimately the diverse outcomes that follow from language learning. These resultant resources include not only linguistic proficiency but also sociocultural (e.g., relationships with members of the target ethnolinguistic community, a broader cultural perspective) and psychological (e.g., well-being, personal growth) capital. The model emphasizes that language learning takes place across diverse sociopolitical and sociocultural milieu and that, depending on the context, teachers, family members, members of the target-language community, and many others could support (or not) learners’ motivation. The chapter ends with directions for future interdisciplinary research on language learning and teaching from a SDT perspective.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.994
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.206
Teacher spread0.183 · 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 teacher head, not a consensus.

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

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

Citations23
Published2023
Admission routes1
Has abstractyes

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