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Record W1993098458 · doi:10.1177/0098628311401591

The Role of Statistics and Research Methods in the Academic Success of Psychology Majors

2011· article· en· W1993098458 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

VenueTeaching of Psychology · 2011
Typearticle
Languageen
FieldMathematics
TopicStatistics Education and Methodologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyComprehensionTest anxietyMathematics educationPsychological researchExperimental psychologyPositive psychologyAnxietyApplied psychologySocial psychologyCognition

Abstract

fetched live from OpenAlex

Comprehension of statistics and research methods is crucial to understanding psychology as a science ( APA, 2007 ). However, psychology majors sometimes approach methodology courses with derision or anxiety ( Onwuegbuzie & Wilson, 2003 ; Rajecki, Appleby, Williams, Johnson, & Jeschke, 2005 ); consequently, students may postpone enrollment ( Onwuegbuzie, 2004 ). We examined the importance of methodology course performance (i.e., grade) and timing of enrollment in these courses for the academic success of psychology majors. After controlling for number of courses taken, relevant American College Test (ACT) scores, and prior Grade Point Average (GPA), we found that methodology course grade and timing of enrollment predicted upper-division psychology GPA. In addition, methodology course grade predicted performance on an assessment of knowledge in psychology. We discuss implications of these results for teaching and advising.

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)0.018
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.285
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.552
GPT teacher head0.662
Teacher spread0.110 · 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