Learning and Instruction is soliciting submissions for a special issue entitled Using Real-Time Process Data of Domain-Specific Learning Processes to Provide Adaptive Support for Learning and Instruction.
Abstracts are to be submitted with the guest editors Dr. Anselm Strohmaier, Prof. Fien Depaepe & Prof. Andreas Obersteiner before June 30, 2023.
There are many perspectives, conceptualizations, and aspects involved in the study and development of adaptive support for learning and instruction. Recent reviews and meta- analyses show that adaptive support is generally promising for learning and instruction, but that there are mixed findings across studies (e.g., Belland et al., 2017; Major & Francis, 2020; Major et al., 2021; Van Schoors et al., 2021; Xie et al., 2019; Zheng et al., 2022) as well as varying conceptualizations and methodologies (e.g., Bernacki et al., 2021; Van Schoors et al, 2021).
While research would benefit from unified frameworks and approaches regarding adaptive support, this goal is often limited by the unique requirements of specific domains. In this special issue, we want to focus on these domain-specific challenges and discuss commonalities and differences across domains. This includes the search for feasible unified conceptualizations of the nature of adaptive support, theoretical models and design principles for adaptive support, approaches to collecting and interpreting real-time data as a basis for adaptive support, evaluating the effectiveness of adaptive support for learning, and exploring the potential of learning technologies for implementing adaptive support - all with a clear link to domain- specific learning and instruction.