Promotion of the transition from instructed to independent problem solving in physics by learning resources automatically adapted to learning progress
The application of knowledge in complex situations is difficult for many students, as the large-scale assessment studies TIMSS and PISA for Germany have shown. An already intensively researched and effective method of learning to apply knowledge is the use of worked-out examples in class (e.g. Chi et al., 1989, Renkl, 2011). An example task consists of a problem definition, an elaboration of the solution steps and the solution itself. With example task sequences, in which the type (scope, quality) of the elaboration of the solution steps is adapted to the learning level of the learners, a transition from guided to independent problem solving can be achieved. It is conducive to learning if the learners “explain” the solution steps to themselves.
In the doctoral project it will be investigated which types of feedback best support this largely self-directed learning process and how the example tasks can be adapted to the individual conditions of the learner. The aim is to avoid effects such as the “illusion of understanding” in beginners and to promote successful approaches such as “anticipating solution steps” in more efficient learners (experts). Learning Analytics methods will be investigated and, if necessary, adapted for their use in individualising example tasks (sequences) and feedback and their application will be tested in an intervention study in physics.
Chi; M.I.T., Bassok, M., Lewis, M., Reimann, P. & Glaser, R. (1989). Self-explanations. How students study and use examples in learning to solve problems. Cognitive Sciene, 13, 2, 145 – 182.
Renkl, A. (2011). Instruction based on Examples. In: Mayer, R.E. & Alexander, P.A.(Hrsg.). Handbook of research in learning and instruction. New York: Routledge.