Automated Test-Item Generation System for Retrieval Practice in Radiology Education.

Objective: To develop and disseminate an automated item generation (AIG) system for retrieval practice (self-testing) in radiology and to obtain trainee feedback on its educational utility.Materials and Methods: An AIG software program (Radmatic) that is capable of generating large numbers of distin...

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Publicado en:Academic Radiology Vol. 26; no. 6; pp. 851 - 860
Autores principales: Gunabushanam, Gowthaman, Taylor, Caroline R., Mathur, Mahan, Bokhari, Jamal, Scoutt, Leslie M.
Formato: research tables/charts Journal Article
Publicado: Elsevier B.V. Jun2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2019
      vid: 26
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      pub: Elsevier B.V.
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        10.1016/j.acra.2018.09.017
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        atl: Automated Test-Item Generation System for Retrieval Practice in Radiology Education.
      aug:
        au:
          Gunabushanam, Gowthaman
          Taylor, Caroline R.
          Mathur, Mahan
          Bokhari, Jamal
          Scoutt, Leslie M.
        affil: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St, P O Box 208042, New Haven, Connecticut 06520-8042
      sug:
        subj:
          Internship and Residency
          Computer-Assisted Instruction
          Specialties, Medical Education
          Educational Measurement
          Test Taking
          Scales
      ab: Objective: To develop and disseminate an automated item generation (AIG) system for retrieval practice (self-testing) in radiology and to obtain trainee feedback on its educational utility.Materials and Methods: An AIG software program (Radmatic) that is capable of generating large numbers of distinct multiple-choice self-testing items from a given "item-model" was created. Instead of writing multiple individual self-testing items, an educator creates an "item-model" for one of two distinct item styles: true/false knowledge based items and image-based items. The software program then uses the item model to generate self-testing items upon trainee request. This internet-based system was made available to all radiology residents at our institution in conjunction with our didactic conferences. After obtaining institutional review board approval and informed consent, a written survey was conducted to obtain trainee feedback.Results: Two faculty members with no computer programming experience were able to create item-models using a standard template. Twenty five of 54 (46%) radiology residents at our institution participated in the study. Twelve of these 25 (48%) study participants reported using the self-testing items regularly, which correlated well with the anonymous website usage statistics. The residents' overall impression and satisfaction with the self-testing items was quite positive, with a score of 7.89 ± 1.91 (mean ± SD) out of 10. Lack of time and email overload were the main reasons provided by residents for not using self-testing items.Conclusion: AIG enabled self-testing is technically feasible, and is perceived positively by radiology residents as useful to their education.
      pubtype: Academic Journal
      doctype:
        research
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      ougenre: Article
    language: English
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