Towards Hybrid Human-System Regulation

Abstract

This paper proposes a new approach to translate learner data into self-regulated learning support. Learning phases in blended classrooms place unique requirements on students' self-regulated learning (SRL). Learning path graphs merge moment-by-moment learning curves and learning phase data to understand student' SRL support needs. Results indicate 4 groups with different SRL support needs. Students in the self-regulated learning group are capable of learning without external regulation. In the teacher regulation group students need initial teacher regulation but rely on SRL thereafter. Students in the system regulation group require teacher and system regulation to learn. Finally, the advanced system support group is in need of support beyond the current level of system regulation. Based on these insights, the application of personalized dashboards and hybrid human-system regulation is further specified.

Towards hybrid human‐AI learning technologies

“…Research indicates that more task‐related feedback is given to students, and that teachers change the allocation of feedback due to the additional information (Knoop‐van Campen & Molenaar, 2020), and students who need assistance receive more help (Holstein et al, 2020). In a similar vein, student‐faced dashboards have been shown to help students improve their practice behaviour in maths classes (Molenaar et al, 2019). Student maths practice became more effective and efficient when they had dashboards that showed their progress and insights into their learning development (Molenaar et al, 2021).…”

“…In addition, there is growing awareness that current learning technologies are taking over regulation from learners (Molenaar et al, 2021). This off‐loading of self‐regulated learning may harm the development of cognitive and meta‐cognitive skills that drive the application of SRL during learning (Molenaar et al, 2019). Researchers have called for caution in how adaptivity is developed and the need to be alert to the consequences of AI taking over critical tasks from students (Bodily et al, 2018).…”

“…Although offloading control is widely practised, there is currently little understanding of where this is justified (Molenaar et al, 2019). Depending on the roles of learner, teacher and AI, educational use cases can be positioned somewhere on the six‐levels‐of‐automation model.…”

Hybrid model in accounting education: The experience of management simulation course

“…Students considered the technologies used (ERP, communication platforms -ZOOM and equivalents, assessment platform -Moodle Avalia -and VPN viewer) the most appropriate. However, some point out that there was no remote access to the ERP, which did not facilitate the execution of the requested activities during class, which means, the group colleagues in face-to-face class would only be able to finish the activities requested if the ones at home had remote access to the system (Molenaar, Horvers & Baker, 2019). Remote access would have avoided an overload of work for the group in certain classes.…”

“…The Association of Chartered Certified Accountants (ACCA, 2020) states that there is a great need to improve teaching methods to convey accounting subjects due to the accelerated development of accounting. Following, personalized learning is the key to an adaptive learning set (Molenaar, Horvers, & Baker, 2019). This learning process is based on several levels for the automation of personalized learning, to promote students' engagement with and in digital learning methodologies at the same time, it is required a hybrid human system regulation (D'Mello, 2021).…”