• Gilberto Marzano Ecoistituto, Italy, Rezekne Academy of technologies, Latvia (IT)
  • Anda Abuze Rezekne Academy of technologies (LV)
  • Yeliz Nur Scaricam Public Education Center Adana (TR)



Learning Adaptivity, Learning Analytics, Learning Unit Structure, Smart Learning Environment


It has been broadly argued that, in the near future, the demand for skilled labor will increase whilst that for routine activities will decrease. In this regard, the need for making greater investments in education to re-skill workers and support continuous learning has been invoked as an essential requirement for preserving people’s employability.

Digital technology is deemed increasingly necessary to sustain the educational endeavor, for the possibilities it offers to make more accessible and low-cost educational interventions. It allows for the creation of personalized learning paths and customized digital learning solutions, for courses to be available to a large attendance of learners, and for teaching-learning activities to be offered at significantly reduced cost.

In this article, a learning unit structure designed to improve adaptive learning is proposed, and mechanisms for adaptive learning in a smart learning environment are discussed.

The implemented teaching-learning solution is also illustrated. This is a preliminary application based on an approach that combines the teacher experience with learning analytics.


Supporting Agencies
This paper has been supported by the board of Science of Latvia within the scope of the project “Implementation of Transformative Digital Learning in Doctoral Program of Pedagogical Science in Latvia” (DocTDLL) lzp-2018/2-0180 and by the ASL project co-funded by the Erasmus Programme of the European Union (Adult self-learning, supporting learning autonomy in a technology-mediated environment, reference number 2019-1-TR01-KA204-076875). The views expressed reflect those of the authors alone.


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How to Cite

G. Marzano, A. Abuze, and Y. Nur, “IMPROVING ADAPTIVE LEARNING IN A SMART LEARNING ENVIRONMENT”, ETR, vol. 2, pp. 93–99, Jun. 2021, doi: 10.17770/etr2021vol2.6509.