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Record W4297688891 · doi:10.54691/bcpep.v5i.1578

Expectancy Effect on Academic Success of English Language Learners

2022· article· en· W4297688891 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBCP Education & Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEllExpectancy theoryPsychologyMathematics educationDemographicsConstruct (python library)PopulationAcademic achievementPedagogyTeaching methodSociologySocial psychologyComputer scienceVocabulary development

Abstract

fetched live from OpenAlex

English Language Learners (ELLs) comprise a unique student body in the demographics of the student population. However, the innate challenge of acquiring language proficiency often reveals as an additional barrier for them to succeed early enough in their schooling; therefore, pedagogical studies derived to investigate factors that limit teachers and students from achieving their goals. Among them, teachers’ expectations construct effective pedagogy that addresses both the linguistic and socio-emotional needs to succeed academically. This paper thus reviews the mechanism of expectancy effect on academic success. Specifically, this effect enacts upon intrinsic motivation, nurtured through enhanced teacher-student interaction and classroom environment, to mediate the gap of achievement due to socio-economic backgrounds. Further, professional development is implied at the end to investigate barriers of access for these students for future studies.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0210.000

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 head0.031
GPT teacher head0.443
Teacher spread0.412 · 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