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dc.contributor.authorDiržytė, Aistė
dc.contributor.authorVijaikis, Aivaras
dc.contributor.authorPerminas, Aidas
dc.contributor.authorRimašiūtė-Knabikienė, Romualda
dc.contributor.authorŽebrauskas, Giedrius
dc.contributor.authorKaminskis, Lukas
dc.date.accessioned2023-09-18T16:10:39Z
dc.date.available2023-09-18T16:10:39Z
dc.date.issued2021
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/112113
dc.description.abstractEducational systems around the world encourage students to engage in programming activities, but programming learning is one of the most challenging learning tasks. Thus, it was significant to explore the factors related to programming learning. This study aimed to identify computer programming e-learners’ personality traits, self-reported cognitive abilities and learning motivating factors in comparison with other e-learners. We applied a learning motivating factors questionnaire, the Big Five Inventory—2, and the SRMCA instruments. The sample consisted of 444 e-learners, including 189 computer programming e-learners, the mean age was 25.19 years. It was found that computer programming e-learners demonstrated significantly lower scores of extraversion, and significantly lower scores of motivating factors of individual attitude and expectation, reward and recognition, and punishment. No significant differences were found in the scores of selfreported cognitive abilities between the groups. In the group of computer programming e-learners, extraversion was a significant predictor of individual attitude and expectation; conscientiousness and extraversion were significant predictors of challenging goals; extraversion and agreeableness were significant predictors of clear direction; open-mindedness was a significant predictor of a diminished motivating factor of punishment; negative emotionality was a significant predictor of social pressure and competition; comprehension-knowledge was a significant predictor of individual attitude and expectation; fluid reasoning and comprehension-knowledge were significant predictors of challenging goals; comprehension-knowledge was a significant predictor of clear direction; and visual processing was a significant predictor of social pressure and competition. The SEM analysis demonstrated that personality traits (namely, extraversion, conscientiousness, and reverted negative emotionality) statistically significantly predict learning motivating factors (namely, individual attitude and expectation, and clear direction), but the impact of self-reported cognitive abilities in the model was negligible in both groups of participants and non-participants of e-learning based computer programming courses; χ2 (34) = 51.992, p = 0.025; CFI = 0.982; TLI = 0.970; NFI = 0.950; RMSEA = 0.051 [0.019–0.078]; SRMR = 0.038. However, as this study applied self-reported measures, we strongly suggest applying neurocognitive methods in future research.eng
dc.formatPDF
dc.format.extentp. 1-26
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyScopus
dc.source.urihttps://doi.org/10.3390/brainsci11091205
dc.titleComputer Programming E-Learners’ Personality Traits, Self-Reported Cognitive Abilities, and Learning Motivating Factors
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references127
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionMykolo Romerio universitetas Vilniaus Gedimino technikos universitetas
dc.contributor.institutionUAB Vadybos ir psichologijos institutas
dc.contributor.institutionVytauto Didžiojo universitetas
dc.contributor.institutionMykolo Romerio universitetas
dc.contributor.institutionTuring College
dc.contributor.facultyKūrybinių industrijų fakultetas / Faculty of Creative Industries
dc.subject.researchfieldS 006 - Psichologija / Psychology
dc.subject.researchfieldS 008 - Komunikacija ir informacija / Communication and information
dc.subject.studydirectionJ07 - Psichologija / Psychology
dc.subject.vgtuprioritizedfieldsEV04 - Komunikacijos valdymas įtraukioje ir kūrybingoje visuomenėje / Communication management in inclusive and creative society
dc.subject.ltspecializationsL103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society
dc.subject.ene-learning
dc.subject.encognitive abilities
dc.subject.enpersonality
dc.subject.enmotivation
dc.subject.encomputer programming
dcterms.sourcetitleBrain sciences
dc.description.issueiss. 9
dc.description.volumevol. 11
dc.publisher.nameMDPI AG
dc.publisher.cityBasel
dc.identifier.doi2-s2.0-85115097511
dc.identifier.doi000699385900001
dc.identifier.doi10.3390/brainsci11091205
dc.identifier.elaba111554876


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