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Record W4213045762 · doi:10.5539/jedp.v12n1p43

Change in Students’ Educational Expectations – A Meta-Analysis

2022· article· en· W4213045762 on OpenAlexvenueaboutno aff
Martin Pinquart, Martin C. Pietzsch

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsnot available
FundersDeutsche Forschungsgemeinschaft
KeywordsPsycINFOModerationMeta-analysisEducational attainmentPsychologyDegree (music)DemographyDevelopmental psychologySocial psychologyMEDLINEMedicinePolitical scienceEconomicsSociologyEconomic growth

Abstract

fetched live from OpenAlex

Data from the U.S. and Canada indicate that students’ educational expectations are often unrealistically high. Thus, the present meta-analysis tested whether students tend to decrease, on average, their educational expectations from childhood to emerging adulthood. A systematic search in the electronic databases ERIC, PsycInfo, PSYNDEX, and Web of Science identified 91 longitudinal studies the results of which were integrated with multi-level meta-analysis. While expectations about the highest future educational degree showed very small declines per year (of g = -.02 standard deviation units), the mean yearly decline of expectations about future grades was estimated to be g = -.73. Moderator analysis found a decline in expectations about the final degree only in studies from the U.S. and Canada—countries with the highest gap between expectation and future educational attainment. In addition, change in expectations about the final degree varied by age, with the strongest decline being observed around the age of 20 years. We conclude that positive expectations about the final educational attainment often tend to persist over longer intervals probably due to lacking strong counter-evidence and because of indicating a desirable outcome.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0700.000

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 head0.185
GPT teacher head0.455
Teacher spread0.269 · 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.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2022
Admission routes2
Has abstractyes

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