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Gabriele Morganti; Alexandra Lascu; Gennaro Apollaro; Laura Pantanella; Mario Esposito; Alberto Grossi; Bruno Ruscello – Sport, Education and Society, 2024
Talent identification and development systems (TIDS) adopt a deterministic perspective (i.e. athletes' future state/performances can be predicted by observations of their initial state/performance), which encourages early identification and specialisation in sport. In this framework, the main aim of sport systems is to enhance predictability and…
Descriptors: Talent Identification, Talent Development, Athletics, Athletes
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Dayana Amala Jothi Antony; Savarimuthu Arulandu; Satyanarayana Parayitam – Learning Organization, 2024
Purpose: This study aims to investigate the relationship between talent management, organizational commitment and turnover intention. The moderating role of gender and experience in relationships was explored. Design/methodology/approach: A conceptual model was developed, and relationships were studied by collecting data from 392 faculty members…
Descriptors: Foreign Countries, Gender Differences, Experience, Talent Development
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Dante D. Dixson; Leah Jansen; Ersie-Anastasia Gentzis; Frank C. Worrell – High Ability Studies, 2024
In this study, the relationship between clusters of hope and a psychosocial profile of academic talent development is examined in a sample of 466 academically gifted adolescents. First, cluster analysis is leveraged to examine whether interpretable three- and four-cluster hope solutions can be found in the sample. Second, differences among a group…
Descriptors: Academically Gifted, Adolescents, Predictor Variables, Student Characteristics
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Linda J. Sax; Kaitlyn N. Stormes; Maxx F. Pereyra – ACM Transactions on Computing Education, 2025
To cultivate more computing talent (including more diverse talent), it is important to understand how college students experience their computing courses and if such experiences vary based on students' gender and racial/ethnic identities. In this paper, we focus on course modality to understand whether taking courses in-person, online, or a hybrid…
Descriptors: Computer Science Education, Electronic Learning, Online Courses, Delivery Systems