ORA (Round 5) - Facilitating Self-Regulated Learning with Personalized Scaffolds on Student's own Regulation Activities

The focus of education is increasingly set on students' ability to regulate their own learning within technology-enhanced learning environments (TELs). Prior research has shown that self-regulated learning (SRL) leads to better learning performance but students often experience difficulties to adequately self-regulate their learning. Instructional scaffolds are a successful method to help learners and consequently improve learning outcomes. However, scaffolds are often standardized and do not adapt to the individual learning process. Learning analytics and machine learning offer an approach to better understand SRL-processes during learning. Yet, current approaches lack validity or require extensive analysis after the learning process. This research collaboration will research how to advance support given to students by i) improving unobtrusive data collection and machine learning techniques to gain better measurement and understanding of SRL-processes and ii) using these new insights to facilitate student's SRL by providing personalized scaffolds. We will reach this goal by investigating and improving trace data in exploratory studies (exploratory study1 and study 2) and using the insight gained from these studies to develop and test personalized scaffolds based on individual learning processes in laboratory (experimental study 3 and study 4) and a subsequent field study (field study 5). Our joint expertise in the fields of self-regulated learning and learning analytics provide superior opportunities to develop and test more powerful adaptive educational technologies.

The results will be disseminated in both academic and non-academic avenues. The academic avenues will primarily include publications in major journals (e.g., Learning and Instruction, Journal of Educational Psychology, and Computers & Education) and conferences (EARLI, AREA, LAK). The impact for non-research beneficiaries will be made with the following stakeholders: teaching staff in the partner institutions, industry and practice-based communities, educational policy makers, and general public. The project team has an excellent track record in working non-academic stakeholders such policy makers (SURF, QAA, and Jisc), educational technology industry (Blackboard, Moodle, and Desire2Learn), and professional organizations (e.g., SoLAR and EARLI). The collaboration will ensure that impact is initiated from the outset through increased awareness of opportunities from the start of the research life-cycle, rather than waiting until the end of project when models have been developed. The project team will remain flexible in terms of approach and incorporate insights from stakeholders and end-users throughout the project phases. Specifically, direct impacts are expected in the following directions: i) Informing teaching practice in higher education and ii) Impact on learning analytics and online learning platforms. We shall organize a series of engagement events - one right after the project kickoff in the first month with key stakeholders, and after 12 months an education-wide and industry event will be organised to bring the various stakeholders together to share and co-construct initial research findings. Two follow-up knowledge exchange events will be held together in parallel with the partner meetings. The project will also have a website which will host the project results, policy briefs, relevant podcasts, and videos demonstrating how the project results be translated to practice and policy. All the resources will be available in English, Dutch, and German.