Investigating the feasibility of using assessment and explanatory feedback in desktop virtual reality simulations

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Guido Makransky, Richard Mayer, Anne Nøremølle, Ainara Lopez Cordoba, Jakob Wandall, Mads Bonde

There is great potential in making assessment and learning complementary. In this study, we investigated the feasibility of developing a desktop virtual reality (VR) laboratory simulation on the topic of genetics, with integrated assessment using multiple choice questions based on item response theory (IRT) and feedback based on the cognitive theory of multimedia learning. A pre-test post-test design was used to investigate three research questions related to: (1) students’ perceptions of assessment in the form of MC questions within the VR genetics simulation; (2) the fit of the MC questions to the assumptions of the partial credit model (PCM) within the framework of IRT; and (3) if there was a significant increase in intrinsic motivation, self-efficacy, and transfer from pre- to post-test after using the VR genetics simulation as a classroom learning activity. The sample consisted of 208 undergraduate students taking a medical genetics course. The results showed that assessment items in the form of gamified multiple-choice questions were perceived by 97% of the students to lead to higher levels of understanding, and only 8% thought that they made the simulation more boring. Items within a simulation were found to fit the PCM and the results showed that the sample had a small significant increase in intrinsic motivation and self-efficacy, and a large significant increase in transfer following the genetics simulation. It was possible to develop assessments for online educational material and retain the relevance and connectedness of informal assessment while simultaneously serving the communicative and credibility-based functions of formal assessment, which is a great challenge facing education today.

Original languageEnglish
JournalEducational Technology Research and Development
ISSN1042-1629
DOIs
Publication statusE-pub ahead of print - 2019

    Research areas

  • Assessment, Cognitive theory of multimedia learning, Desktop virtual reality, Explanatory feedback, Item response theory, Retrieval practice, Simulations

ID: 226871974