Abstract
The aim of the paper is to present a methodology (i.e. model and method) to evaluate suitability, acceptance and use of personalised learning units/scenarios. Learning units/scenarios are referred here as methodological sequences of learning components (learning objects, learning activities, and learning environment). High-quality learning units should consist of the learning components optimised to particular students according to their personal needs, e.g. learning styles. In the paper, optimised learning scenarios mean learning scenarios composed of the components having the highest probabilistic suitability indexes to particular students according to Felder-Silverman learning styles model. Personalised learning units evaluation methodology presented in the paper is based on (1) well-known principles of Multiple Criteria Decision Analysis for identifying evaluation criteria; (2) Educational Technology Acceptance & Satisfaction Model (ETAS-M) based on well-known Unified Theory on Acceptance and Use of Technology (UTAUT) model, and (3) probabilistic suitability indexes to identify learning components’ suitability to particular students’ needs according to their learning styles. The methodology to evaluate personalised learning units presented in the paper is absolutely new in scientific literature. This methodology is applicable in real life situations where teachers have to help students to create and apply learning units that are most suitable for their needs and thus to improve education quality and efficiency.
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Kurilova, J., Minkevicius, S., Kurilovas, E. (2017). On Personalised Learning Units Evaluation Methodology. In: Damaševičius, R., Mikašytė, V. (eds) Information and Software Technologies. ICIST 2017. Communications in Computer and Information Science, vol 756. Springer, Cham. https://doi.org/10.1007/978-3-319-67642-5_41
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