Capturing Competence: The Design, Evaluation, and Implementation of a Video‐Based Instrument for Assessing Verbal Aggression Management Competence.

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Title: Capturing Competence: The Design, Evaluation, and Implementation of a Video‐Based Instrument for Assessing Verbal Aggression Management Competence.
Authors: Franco, Delphine1 (AUTHOR) delphine.franco@ugent.be, Vanderlinde, Ruben1 (AUTHOR), Valcke, Martin1 (AUTHOR)
Source: European Journal of Education. Mar2025, Vol. 60 Issue 1, p1-16. 16p.
Subject Terms: *Student teachers, *Teacher education, *Teacher training, *Assessment of education, Invective
Abstract: Complex competences, such as managing students' aggressive behaviour, are challenging to develop during teacher training. Recently, video‐based simulations have been considered promising, yet suitable assessment instruments are limitedly available. This paper reports on the design and evaluation of a video‐based assessment tool tailored to measure preservice teachers' verbal aggression management competence (V‐AMC) development. Design considerations for video‐based activities served as a framework, resulting in an assessment instrument consisting of video vignettes mirroring classroom situations concerning verbal aggressive behaviour, questions prompting situation‐specific skills development, and a coding scheme to analyse preservice teachers' answers. Furthermore, this paper discusses the results of the instrument's implementation on preservice teachers' (n = 182) V‐AMC. Findings support the appropriateness of the instrument in assessing V‐AMC levels and mapping the impact of a simulation‐based intervention. The data partially confirm the intervention's contribution to V‐AMC development. Implications for future interventions targeting competence development are discussed. [ABSTRACT FROM AUTHOR]
Copyright of European Journal of Education is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Capturing Competence: The Design, Evaluation, and Implementation of a Video‐Based Instrument for Assessing Verbal Aggression Management Competence.
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  Data: <searchLink fieldCode="JN" term="%22European+Journal+of+Education%22">European Journal of Education</searchLink>. Mar2025, Vol. 60 Issue 1, p1-16. 16p.
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  Data: Complex competences, such as managing students' aggressive behaviour, are challenging to develop during teacher training. Recently, video‐based simulations have been considered promising, yet suitable assessment instruments are limitedly available. This paper reports on the design and evaluation of a video‐based assessment tool tailored to measure preservice teachers' verbal aggression management competence (V‐AMC) development. Design considerations for video‐based activities served as a framework, resulting in an assessment instrument consisting of video vignettes mirroring classroom situations concerning verbal aggressive behaviour, questions prompting situation‐specific skills development, and a coding scheme to analyse preservice teachers' answers. Furthermore, this paper discusses the results of the instrument's implementation on preservice teachers' (n = 182) V‐AMC. Findings support the appropriateness of the instrument in assessing V‐AMC levels and mapping the impact of a simulation‐based intervention. The data partially confirm the intervention's contribution to V‐AMC development. Implications for future interventions targeting competence development are discussed. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of European Journal of Education is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/ejed.12834
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        Text: English
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              Text: Mar2025
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