SLICES – Using the thin slices technique to analyse school lessons: A reanalysis of large-scale datasets on constructive handling of student errors
The project SLICES examines whether the thin slices technique can be used to efficiently study educational processes in very large samples, as they are common in large scale assessments. The study focuses on the "constructive handling of student errors" in the classroom, an indicator of teaching and learning that is considered to be of particular importance for adaptive interactions with heterogeneous groups of learners.
The main focus of SLICES lies on the efficient assessment of educational processes in the classroom. Previous studies in differential psychology found that the "thin slices technique“ (Ambady & Rosenthal) that relies on a person’s first impression of another person, often provides highly reliable and valid results when compared to self-descriptions and other objective measures. First applications in education research also found convincing results for the assessment of teacher characteristics. The project SLICES therefore uses this technique to re-analyse data from the TIMSS and DESI studies regarding the constructive handling of student errors in the classroom. The latter is considered a teaching method and a key criterion for teaching quality. To begin with, we explore to what extent the thin slices technique is a significantly more efficient method for video-analyses compared to conventional methods. We assume efficiency if the thin slices technique requires fewer resources than conventional video ratings but delivers equally reliable and valid data. In an additional strand of work, we assess the effect of the constructive handling of student errors as an indicator for individual support on student learning and the development of school achievement, motivation, and interest. A major focus here lies on differential results in heterogeneous groups of learners.
07/2015 – 12/2017
|Department:||Teacher and Teaching Quality|
|Contact:||Dr. Susanne Kuger, Associated Researcher|