Unraveling the Research on Deeper Learning: A Review of the Literature

  • Stylianos Sergis
  • Demetrios Sampson


Deeper learning (DL) has emerged at the spotlight of educational policies around the world and has gained significant attention from various stakeholders in education (teachers, school leaders, curricula designers, policy makers). This is the result of DL being associated to core competences of the current and future workplaces such as problem-solving, critical thinking, self-regulated learning, and effective collaboration, which are considered as essential for building innovative solutions to wicked global challenges. However, despite this well-acknowledged trend research related to modeling, cultivating and assessing Deeper Learning competences is still at a shaping stage. This is also reflected in the rather limited advancements in the use of digital educational technologies to support the assessment and measurement of DL. In this context, the contribution of this chapter is to perform a systematic literature review of the current state on existing works for modeling DL competences, teaching approaches applied to cultivate them as well as, methods and instruments proposed for assessing and measuring DL.


Deeper learning Modeling deeper learning Deeper learning competences Assessment of deeper learning Measuring deeper learning Teaching strategies for deeper learning 



The work presented in this paper has been partially funded by (a) the European Commission in the context of the “STORIES—Stories of Tomorrow: Students Visions on the Future of Space Exploration” project (Grant Agreement no. 731872) under Horizon 2020 Program, H2020-ICT-22-2016-2017 “Information and Communication Technologies: Technologies for Learning and Skills” and (b) the Greek General Secretariat for Research and Technology, under the Matching Funds 2014–2016 for the EU project “Inspiring Science: Large Scale Experimentation Scenarios to Mainstream eLearning in Science, Mathematics and Technology in Primary and Secondary Schools” (Project Number: 325123). This document does not represent the opinion of neither the European Commission nor the Greek General Secretariat for Research and Technology, and the European Commission and the Greek General Secretariat for Research and Technology are not responsible for any use that might be made of its content.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Stylianos Sergis
    • 1
  • Demetrios Sampson
    • 1
    • 2
  1. 1.Department of Digital SystemsUniversity of PiraeusPiraeusGreece
  2. 2.School of EducationCurtin UniversityPerthAustralia

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