Predicting Academic Self-Efficacy Based on Self-Directed Learning and Future Time Perspective
dc.contributor.author | Karatas, Kasim | |
dc.contributor.author | Arpaci, Ibrahim | |
dc.contributor.author | Suer, Sedef | |
dc.date.accessioned | 2024-04-24T17:14:33Z | |
dc.date.available | 2024-04-24T17:14:33Z | |
dc.date.issued | 2023 | |
dc.department | Dicle Üniversitesi | en_US |
dc.description.abstract | The purpose of this study was to investigate the relationship between teacher candidates' academic self-efficacy, self-directed learning, and future time perspective. A dual-stage analytical approach, utilizing both traditional structural equation modeling (SEM) and Machine Learning Classification Algorithms, was employed to test the proposed hypotheses. The study included a sample of 879 teacher candidates. The SEM analysis revealed that self-directed learning had a significant positive effect on academic self-efficacy. Furthermore, future time perspective was found to significantly predict academic self-efficacy. The combined endogenous constructs accounted for a substantial portion of the explained variance. Additionally, the study employed LMT and Multiclass classifiers from Machine Learning algorithms to predict academic self-efficacy. In summary, the findings of this study suggest that self-directed learning and future time perspective are significant factors in predicting teacher candidates' academic self-efficacy. The study utilized both traditional SEM and Machine Learning algorithms to provide a comprehensive analysis of the relationships between these variables. | en_US |
dc.identifier.doi | 10.1177/00332941231191721 | |
dc.identifier.issn | 0033-2941 | |
dc.identifier.issn | 1558-691X | |
dc.identifier.pmid | 37503547 | |
dc.identifier.scopus | 2-s2.0-85165953671 | |
dc.identifier.scopusquality | Q1 | |
dc.identifier.uri | https://doi.org/10.1177/00332941231191721 | |
dc.identifier.uri | https://hdl.handle.net/11468/18048 | |
dc.identifier.wos | WOS:001038720800001 | |
dc.identifier.wosquality | N/A | |
dc.indekslendigikaynak | Web of Science | |
dc.indekslendigikaynak | Scopus | |
dc.indekslendigikaynak | PubMed | |
dc.language.iso | en | en_US |
dc.publisher | Sage Publications Inc | en_US |
dc.relation.ispartof | Psychological Reports | |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Academic Self-Efficacy | en_US |
dc.subject | Future Time Perspective | en_US |
dc.subject | Self-Directed Learning | en_US |
dc.subject | Machine Learning | en_US |
dc.title | Predicting Academic Self-Efficacy Based on Self-Directed Learning and Future Time Perspective | en_US |
dc.title | Predicting Academic Self-Efficacy Based on Self-Directed Learning and Future Time Perspective | |
dc.type | Article | en_US |