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Record W4225472174 · doi:10.1177/23328584221083662

Instructional Supports for Motivation Trajectories in Introductory College Engineering

2022· article· en· W4225472174 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

VenueAERA Open · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsMcGill University
FundersNational Science Foundation
KeywordsPsychologyCompetence (human resources)Expectancy theoryPerceptionAutonomySelf-efficacySelf-determination theoryGoal theorySocial psychologyIntrinsic motivationMathematics education

Abstract

fetched live from OpenAlex

Students, instructors, and policy makers are in need of research-based recommendations for supporting students’ motivation to pursue STEM fields. The present study addressed this need by examining relations between perceived motivational supports, year-long trajectories of expectancy for success and three task values, and grades among students ( N = 1,021) in a large, gateway engineering course. Results indicated that students with higher motivation at the beginning of the year tended to perceive their class as more motivationally supportive. Controlling for relations between initial motivation and perceptions, perceived instructional supports for mastery goals, autonomy, and competence predicted more positive trajectories of all three task values. Conversely, higher perceived instructor performance goals negatively predicted grades and the slopes of self-efficacy and interest value. Results contribute key understanding about the interconnectedness of individual motivation and climate perceptions, while indicating the importance students place on certain motivationally supportive practices in promoting students’ STEM motivation trajectories.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.649
Threshold uncertainty score0.579

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.260
Teacher spread0.233 · 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