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Hyeseong Lee; Jake Cho; Anne Walsh – Journal of Advanced Academics, 2025
This study explores machine learning (ML) approaches for identifying gifted students by integrating academic and socioemotional characteristics from the data collected with the Having Opportunities Promotes Excellence teacher rating scale. By using the Gaussian Mixture Model (GMM) and ML approaches, including support vector machine (SVM) and…
Descriptors: Gifted Education, Talent Identification, Academically Gifted, Electronic Learning
Lauder, Hugh – Journal of Education and Work, 2011
There are many aims that have been articulated with respect to national qualifications frameworks (NQFs). Among them are those concerned with transparency, which is to say, that it is assumed that once employers understand the competencies of employees, as defined by their education credentials, then the mismatch between what employers are looking…
Descriptors: Employment Qualifications, Employees, Credentials, Classification
Hicheri, Ida Gennari-El; Caroff, Xavier; Paroche, Pauline; Chemolle, Elise; Lubart, Todd – Gifted and Talented International, 2013
In a time of economic turmoil, finding executive managers with high potential is increasingly important in the business world. Structural constraints (such as flexibility and reactivity linked to constant environmental change), and demographic trends (such as replacement of leaders who retire) are two challenges, among others, that companies have…
Descriptors: Foreign Countries, Talent Development, Talent, Talent Identification

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