Digital Educational Escape Rooms as E-courses Using D-EER4SmL: Investigation of Motivational Affordances

Research has shown that educational escape rooms (EERs) motivate and engage learners in the learning process, mainly due to the incorporation of game elements into their educational context. As a result, various frameworks have been proposed to design and develop EERs over the past few years. However, these frameworks fail to highlight the important "D"-digital factor of technology which transforms EERs into Digital Educational Escape Rooms (DEERs), as well as the smart pedagogy (SmP), which in turn goes beyond game-based approaches and is currently essential for the design and the development of well-orchestrated and reusable smart learning solutions. Due to the fact that technology increases motivation, this study introduces the work-in-progress framework D-EER4SmL, primarily based on John Keller's theory of ARCS and the 10-step systematic design process for the development of motivational e-courses, tailored to learners' preferences. The framework was aligned with various EER design principles, along with Smart Pedagogical (SmP) approaches, which could be facilitated by web technologies in order to design and develop DEERs as e-courses. To confirm the motivational aspect of smart learning and the assumption that digital technology provides additional motivation, a DEER e-course was developed, based on this framework. The DEER e-course was delivered to ICT students - future ICT teachers/e-learning educators - who would be trained in instructional/e-learning design utilizing web technologies. A total of 108 higher education students of digital systems voluntarily participated in the workflows of the DEER e-course, played the game, and evaluated motivational affordances (MAs), after completing it. Quantitative data analysis was conducted, based on an improvised questionnaire for DEERs, aligned with Keller’s Instructional Materials Motivation Survey (IMMS). As far as motivation is concerned, the framework was proven effective in the initial research findings; however, further research is needed to confirm its effectiveness within the wider context of smart learning.