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Record W2279275920 · doi:10.1177/0735633115603989

Achievement Goal Orientations and Self-Reported Study Strategies as Predictors of Online Studying Activities

2015· article· en· W2279275920 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

VenueJournal of Educational Computing Research · 2015
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGoal orientationPsychologyTask (project management)Applied psychologySelf-regulated learningStructural equation modelingConfirmatory factor analysisValue (mathematics)Mathematics educationSocial psychologyComputer scienceMachine learning

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate whether achievement motivations influence the adoption of learning strategies and learning strategies influence studying behavior in an online learning environment. The Goal Orientation Questionnaire was used to measure achievement motives, and the Motivated Strategies for Learning Questionnaire was used to assess learning strategies. In addition, data on how learners tagged and annotated the learning materials were collected using software designed to aid studying and to examine studying behavior. Confirmatory factor analyses were conducted on Goal Orientation Questionnaire data from 170 university students who used the learning software to study a chapter from a textbook. Results showed that task value and effort regulation subscales from the Motivated Strategies for Learning Questionnaire positively predicted the number of notes created. In addition, mastery and performance goals positively predicted task value, and work-avoidance goals negatively predicted effort regulation and task value.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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)0.0000.000

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 head0.143
GPT teacher head0.479
Teacher spread0.335 · 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