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Taxonomy of Competence Models Based on an Integrative Literature Review
- Source :
-
Education and Information Technologies . 2024 29(13):16997-17033. - Publication Year :
- 2024
-
Abstract
- An individual competence is one of the main human resources, which enables a person to operate in everyday life. A competence profile, formally captured and described as a structured model, may enable various operations, e.g., a more precise evaluation and closure of a training gap. Such application scenarios supported by information systems are particularly compelling for the era of digitalisation, although research on adequate models capturing competence profiles is still lacking; moreover, no research was revealed synthesizing models of competence, enabling operationalisation possibilities. To fulfil this gap, current research develops a classification of competence models in the form of taxonomy, derived from operational characteristics of competence constructs. Given conceptual fuzziness of the competence term and complex, interdisciplinary scope of the study, the research method follows integrative literature review principles: results of an extensive search conducted in three iterations were critically analysed and further synthesized in the form of taxonomy. This critical analysis was performed based on an overview of twenty-four competence models with a lens of working definitions of competence framework and model concepts. As a result, all three outcomes highlight the power of competence models: (1) the overview summarises models' development methods, operationalisation, and purposes in a specific application domain, while (2) working definitions and (3) the taxonomy aim at overcoming a conceptual ambiguity of competence concepts. In addition, the presented taxonomy may serve as a knowledge base or a decision support tool on competence model selection when it comes to development of a competence management tool.
Details
- Language :
- English
- ISSN :
- 1360-2357 and 1573-7608
- Volume :
- 29
- Issue :
- 13
- Database :
- ERIC
- Journal :
- Education and Information Technologies
- Publication Type :
- Academic Journal
- Accession number :
- EJ1444070
- Document Type :
- Journal Articles<br />Information Analyses
- Full Text :
- https://doi.org/10.1007/s10639-024-12463-y