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Record W4384130686 · doi:10.47814/ijssrr.v6i7.1261

Metu Students’ College Life Satisfaction

2023· article· en· W4384130686 on OpenAlexaff
Furkan Berk Danisman, Sıla Ilyurek Kilic, Niyousha Amini, Osman Orcun Ada, Sena Gulizar Aktas, Gizem Sarul

Bibliographic record

VenueInternational Journal of Social Science Research and Review · 2023
Typearticle
Languageen
FieldNursing
TopicHealthcare Education and Workforce Issues
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyLife satisfactionSocial psychologyMedical educationMedicine

Abstract

fetched live from OpenAlex

The research was conducted to identify the factors that influence college students' satisfaction with their college experience. Firstly, the study was focused on the literature review to determine relevant factors that have been previously studied in the literature. Then, the survey analysis examined three main independent factors that have been found to be related to college students' satisfaction: Major Satisfaction, Social Self-Efficacy, and Academic Performance. The findings of the study suggested that the most important factor affecting students' satisfaction with their college experience is their satisfaction with their chosen major. This means that students who are satisfied with the major they have chosen are more likely to be overall satisfied with their college experience. It's worth noting that, while the study found that major satisfaction is the most crucial factor, it doesn't mean that other factors such as Social Self-Efficacy, Academic Performance, and Campus Life Satisfaction are not important. Based on these findings, it is recommend that students prioritize their major satisfaction when making college choices in order to maximize their overall satisfaction with their college experience.

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)0.007
metaresearch head score (Gemma)0.002
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 score0.690
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
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 science0.0000.000
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 head0.171
GPT teacher head0.578
Teacher spread0.407 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations1
Published2023
Admission routes1
Has abstractyes

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