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Predicting Learning Outcomes in Distance Learning Universities: Perspectives from an Integrated Model

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Higher Education Learning Methodologies and Technologies Online (HELMeTO 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1091))

Abstract

The progressive spread of online academic courses is a result of the flexible and customisable nature of the related learning process, while some studies on students’ achievement in distance learning universities have underlined retention as a priority issue for future research. Despite the number of studies that have investigated specific variables related to online learning, there are no systemic reference models that consider specific online environmental variables, IT competence and outcomes together. This paper offers an integrated model to test the contribution of different variables in predicting student performance in online academic courses, building on the literature on the digital learning environment and achievement. The model, based on the initial Biggs’ 3P learning model, aims to evaluate technical competency and the ability to self-manage as personal variables; furthermore, it proposes the analysis of a set of perceptions related to course design. Through the proposed model, a student’s background, personal variables, perception of the physical learning environment and perception of the course design can be utilized as predictors of student performance. Future research should investigate the applicability of the model in academic distance learning contexts.

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Author information

Authors and Affiliations

  1. Faculty of Psychology, e-Campus University, Novedrate, Italy

    Massimiliano Barattucci

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  1. Massimiliano Barattucci
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Correspondence to Massimiliano Barattucci .

Editor information

Editors and Affiliations

  1. Universidad Internacional de La Rioja, Logroño, La Rioja, Spain

    Daniel Burgos

  2. Unitelma Sapienza University, Rome, Italy

    Marta Cimitile

  3. Department of Information Engineering, University of Pisa, Pisa, Italy

    Pietro Ducange

  4. Università degli Studi eCampus, Novedrate, Como, Italy

    Riccardo Pecori

  5. SMARTEST Research Centre, Università degli Studi eCampus, Novedrate, Como, Italy

    Pietro Picerno

  6. Università degli Studi eCampus, Novedrate, Italy

    Paolo Raviolo

  7. Open University in the Netherlands, Heerlen, The Netherlands

    Christian M. Stracke

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Barattucci, M. (2019). Predicting Learning Outcomes in Distance Learning Universities: Perspectives from an Integrated Model. In: Burgos, D., et al. Higher Education Learning Methodologies and Technologies Online. HELMeTO 2019. Communications in Computer and Information Science, vol 1091. Springer, Cham. https://doi.org/10.1007/978-3-030-31284-8_3

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  • DOI: https://doi.org/10.1007/978-3-030-31284-8_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-31283-1

  • Online ISBN: 978-3-030-31284-8

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