Evaluation of suitability, acceptance and use of personalised learning scenarios
Julija Kurilova
Vilniaus universitetas
Eugenijus Kurilovas
Vilniaus Gedimino technikos universitetas
Saulius Minkevičius
Vilniaus universitetas
Published 2017-12-20


personalised learning scenarios
probabilistic suitability indexes
acceptance and use
UTAUT model
learning components

How to Cite

Kurilova J., Kurilovas E. and Minkevičius S. (2017) “Evaluation of suitability, acceptance and use of personalised learning scenarios”, Lietuvos matematikos rinkinys, 58(B), pp. 45–50. doi: 10.15388/LMR.B.2017.08.


The paper aims to present a methodology (i.e. model and method) to evaluate suitability, acceptance and use of personalised learning scenarios. High-quality learning scenarios should consist of the learning components (i.e. learning objects, learning activities, and learning environment) 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 scenarios evaluation methodology presented in the paper is based on (1) probabilistic suitability indexes to identify learning components suitability to particular students needs according to their learning styles, and (2) Educational Technology Acceptance & Satisfaction Model (ETAS-M) based on well-known Unified Theory on Acceptance and Use of Technology (UTAUT) model.

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