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The Perceived Influence of Non-Cognitive Skills on the Student Post-Secondary Journey

2021· article· en· W7042498919 sur OpenAlexaboutno aff

Notice bibliographique

RevueScholarship at UWindsor (University of Windsor) · 2021
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueHigher Education and Employability
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPreparednessPremiseHigher educationInstitutionQualitative researchStudy skillsCommunity collegeAcademic advisingProcess (computing)Time management
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Learners typically enter higher education by meeting the academic threshold placed on them by their institution; however, their ability or inability to traverse the multi-interactional elements of post-secondary life are what underlie the premise of this research study. Over 320,000 students begin their post-secondary journey at a Canadian institution each year (Statistics Canada, 2019), and of those students, approximately 20-25% will withdraw before their second year (Grayson & Grayson, 2003). Of the students who choose to attend a community college in the Greater Toronto Area, 29-45% will never complete their program (Lopez-Rabson & McCloy, 2013). However, questions have been raised as to learner preparedness when entering higher education and whether today’s learners possess the non-cognitive skill levels needed to handle their new learning environment and to adequately engage with the resources designed to support their transition, success, and retention (Adams, 2012; Savitz-Romer & Bouffard, 2012). As a result, this study explored the current level, value, and role of non-cognitive skills in today’s college learners, along with the impact these skills have on their post-secondary journey. More specifically, the how and what stakeholders have experienced with non-cognitive skills were explored to understand its impact on student post-secondary experiences, academic and social development, engagement, and ultimately the decision-making process and ability to persist to graduation. Qualitative data were collected in the fall of 2019 at an Ontario community college located in the Greater Toronto Area. Semi-structured interviews were conducted using Interpretive Phenomenological Analysis as the research method. In total, the lived experiences of nine college stakeholders consisting of three students, two staff members, two faculty members, and two administrators were analyzed and interpreted to gain the perspectives of those who occupy the Ontario college ecosystem. Although not generalizable, results showed that staff, faculty members, and administrators perceived non-cognitive skills to be lacking among today’s college learners at a recognizable level. This, in turn, was said to contribute to student difficulties with juggling new responsibilities, coping with tragedies, forming new friendships and social circles, participating in academic and social activities, and making controlled decisions. These skill deficiencies were also found to contribute to students questioning their place within higher education and to situations where bumps along the college journey cannot be overcome. Student participants of this study held varying views regarding current skill levels. Student stories revealed perceptions of non-cognitive skill levels among the student population as lacking, good, and unknown. Nonetheless, non-cognitive skills were found to have a positive impact on a learner’s post-secondary journey and all stakeholder groups identified a need for institutions to work toward developing these skills among their student population. Three recommendations were offered to build community awareness and create skill-development opportunities. The recommendations encouraged institutions to: 1) plan, integrate, and embed non-cognitive skills development in all facets of college life from student services to the classroom; 2) raise non-cognitive skills awareness and development through exposure and education; 3) provide upfront disclosure of the essential skills needed for program and student success.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,189
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0020,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,020
Tête enseignante GPT0,302
Écart entre enseignants0,282 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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