Litcius/Paper detail

Blended learning in the engineering field: A systematic literature review

Roberto Sala, Antonio Maffei, Fabiana Pirola, Fredrik Enoksson, Sandi Ljubić, Arian Skoki, Joseph Paul Zammit, Amberlynn Bonello, Primož Podržaj, Tena Žužek, Paolo C. Priarone, Dario Antonelli, Giuditta Pezzotta

2024Computer Applications in Engineering Education15 citationsDOIOpen Access PDF

Abstract

Abstract Blended Learning (BL) is defined as a combination of face‐to‐face and digital activities that, in recent years, has been adopted more and more frequently by Higher Educational Institutions (HEIs). In the engineering field, the adoption of BL allows creating challenging situations for students with industry‐like problems to foster the acquisition of advanced problem‐solving skills. Thus, it can be used to enhance traditional learning by enriching it with new aspects, allowing to update the Intended Learning Outcomes traditionally defined by teachers. Although prior coronavirus disease 2019 (COVID‐19) teachers had the time to prepare and programme the transition to BL, during the pandemic they had to abruptly move to the full digital delivery of the content, requiring technological and organizational adaptation, as well as change in the content teaching and assessment methods. Through a systematic literature review, this paper aims to understand how BL has been implemented in the engineering field by HEIs, discussing if and how the learning expectations of teachers (evaluated through Bloom's Taxonomy) change when using different mixes of face‐to‐face and digital activities and when the target audience changes. More specifically, the investigation addresses how content and learning expectations are split and set in face‐to‐face and digital settings. Additionally, the interest is towards understanding how COVID‐19 impacted the adoption of BL, not only during the pandemic but also after.

Topics & Concepts

Blended learningComputer scienceAdaptation (eye)Field (mathematics)Face (sociological concept)Set (abstract data type)Knowledge managementMathematics educationPsychologyEducational technologySociologySocial scienceMathematicsNeuroscienceProgramming languagePure mathematicsExperimental Learning in EngineeringInnovative Teaching MethodsOnline and Blended Learning