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Multimedia interactive exercises for online training

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Abstract

Multimedia tutorials are more and more considered for online professional training as a valuable complement to traditional in presence training. Indeed, video and pictures can offer rich detail, show relevant context, and provide concrete visualisations of key concepts. An important aspect of achieving effective learning is to create an engaging experience for the learner. This can be obtained by increasing the level of interactivity required to the students, keeping them active and interested. However, there are different categories of interactive video, and what type of interactivity works best for online training needs to be systematically investigated. Moreover, the effort in developing such multimedia tutorials by instructional designers should be sustainable to enable large scale adoption. This calls for the development of appropriate methods and tools to support authors and teachers from the conception of an exercise to its deployment and evolution. These challenges have been addressed in the context of an industrial innovation project called ELEVATE (E-LEarning with Virtual interAcTive Experience). In order to collect empirical evidence on what type of interactive multimedia exercise could be effective in training, we performed an experiment to compare online training exercises based on linear videos with ones based on interactive videos having a graph-structure. Meanwhile, prototypes of the ELEVATE tool suite were being developed and validated in an iterative approach, by adding advanced features, such as those enabling the production of customisable exercises. In this paper, we present the design of the experiment and an execution with sixteen subjects, which provided useful results. The ELEVATE tool suite and the companion methodology are also described, together with the mechanisms it provides to develop customisable multimedia exercises.

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Data Availability

The dataset generated and analysed during the controlled experiment presented in this paper is available from the corresponding author on reasonable request.

Notes

  1. The PRESTO (Plausible Representation of Emergency Scenarios for Training Operations) project, a 4-year industrial research project ended in 2016.

  2. An alternative model is proposed in [7], where correlations between quality attributes are taken into account, and appropriate weights are assigned by experts to the evaluation attributes, depending on the object and goal of the evaluation. For our experiment we preferred to consider same weight for the considered attributes

  3. A blinded version of the experiment package is available at https://figshare.com/s/c4143a098823ebe201a8

  4. General Data Protection Regulation is a regulation in EU law on data protection and privacy in the European Union and the European Economic Area

  5. https://unity.com/

  6. Science, technology, engineering, and mathematics.

  7. Called demonstration videos in [23].

  8. Demo of the multimedia exercises produced with the ELEVATE Tool Suite can be found at the following link: https://elevate.deltainformatica.eu/portfolio.html (in Italian). It is possible to get a trial access to the ELEVATE Tool Suite by requesting a demo account at the following link: https://elevate.deltainformatica.eu - clicking on ”ACCEDI A ELEVATE”

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Acknowledgements

We would like to thank the anonymous reviewers for their invaluable help to improve the presentation of this work.

Funding

Partial financial support was received from Provincia Autonoma di Trento, L.P. 6/1999, the ELEVATE industrial innovation project.

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Authors and Affiliations

  1. Fondazione Bruno Kessler, Trento, Italy

    Anna Perini, Linda Marilena Bertolli, Angelo Susi & Artem Gabbasov

  2. Leibniz Universität Hannover, Hannover, Germany

    Kurt Schneider

  3. University of Trento, Trento, Italy

    Linda Marilena Bertolli

  4. Delta Informatica SpA, Trento, Italy

    Paolo Busetta & Matteo Pedrotti

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  1. Anna Perini
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  2. Kurt Schneider
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  3. Linda Marilena Bertolli
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Correspondence to Anna Perini.

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Perini, A., Schneider, K., Bertolli, L.M. et al. Multimedia interactive exercises for online training. Multimed Tools Appl 82, 38319–38343 (2023). https://doi.org/10.1007/s11042-023-15157-8

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