Project P

Project P

Project P focuses on mixture modelling as an approach to modelling characteristics of learners and their learning processes to identify their needs and personalise simulation-based learning accordingly.

Summary

Project P develops and provides an overarching methodological basis for mixture modelling as a means to modelling learner characteristics and learning processes and personalise learning environments by identifying and implementing interventions that best meet learners` needs. The newly created methodological insights should serve the goals of the Collaborative Research Centre (CRC) across subprojects that use the person-centred methodological approach of mixture modeling. To this end, Project P conducts a literature review to identify research contexts, modelling approaches, and empirical findings that characterise mixture modelling in simulation-based learning. In addition, Project P conducts methodological research such as simulation studies to provide insights into the most promising analytic approaches for mixture modelling in this context. Furthermore, Project P consolidates the results both within the CRC and develops corresponding systematic frameworks to contribute to overarching theory-building through person-centred integrative data analyses, it provides statistical training, and consults for subprojects.

Participants

Principal Investigators

Collaboration partners

Goal

The aim of project P is to systematically develop and provide the methodological basis using mixture modelling as a means to modelling learner characteristics and personalizing learning in, with and from simulations based on identified learners’ needs. In addition, project P contributes to the integration of research findings from other SHARP subprojects and to consult for projects that use mixture modelling or share interest in using this methodological approach. To achieve this, the project conducts a literature review, simulation studies, theoretical methodological work, and it develops new modelling frameworks. Based on the work in Project P, we contribute person-centred evidence for an overarching theoretical model of personalised simulation-based learning in higher education.

Research Questions

  • What are the characteristics of studies on simulation-based learning employing mixture modelling to identify profiles of learning prerequisites, processes, our outcomes?

  • Which fit statistics and modelling approaches work best to identify learner profiles and to relate these to learner characteristics, process measures, and variation in the effects of (non-)personalised interventions?

  • How can we establish the generalisability of learner profiles, their predictors, outcomes, and interactions with instructional parameters across different learning contexts and populations of learners?

  • How generalisable are results regarding learner profiles of learning prerequisites, learning process data, and learning outcomes, as well as their relations to predictor variables, outcome variables, and to the effects of scaffolding and feedback across different contexts (as represented by SHARP projects), and what predicts variation in these results?

Methodology

Project P is developing a methodology for mixture modelling across all SHARP projects and research on simulation-based learning more generally. To this end, systematic review approaches are used, and log, process, and learning-related behavioral data are analysed. This is complemented by person-centred meta-analyses, statistical simulation studies, and theoretical development of analytic frameworks. Data from SHARP projects will be analysed using approaches such as latent profile-, latent transition-, growth mixture- and hidden Markov modeling, as well as integrative and meta-analytic extensions thereof to serve the overarching purpose of integrated theory building across projects within and beyond the CRC.