A Learning Analytics Approach to Address Heterogeneity in the Classroom: The Teachers’ Diagnostic Support System
Tobias Kärner, Julia Warwas, Stephan Schumann
Abstract
Abstract Addressing heterogeneity in the classroom by adapting instruction to learners’ needs challenges teachers in their daily work. To provide adaptive instruction in the most flexible way, teachers face the problem of assessing students’ individual characteristics (learning prerequisites and learning needs) and situational states (learning experiences and learning progress) along with the characteristics of the learning environment. To support teachers in gathering and processing such multidimensional diagnostic information in class, we have developed a client–server based software prototype running on mobile devices: the Teachers’ Diagnostic Support System. Following the generic educational design research process, we (1) delineate theoretical implications for system requirements drawn from a literature review, (2) describe the systems’ design and technical development and (3) report the results of a usability study. We broaden our theoretical understanding of heterogeneity within school classes and establish a basis for technological interventions to improve diagnostic accuracy in adaptive instructional strategies.