The Measurement of Change: Learning-Dependent Progression of Mental Models
Dirk Ifenthaler and Norbert M. Seel
The assessment of the learning-dependent progression of mental models is a problem which is yet unsolved. However, if we want to influence mental model progression through instruction, we first need to focus on the trajectory of the learners’ mental models. Measuring a person’s mental model only before and after instruction is not enough. Additionally, each learner’s model should be measured with a longitudinal perspective. We therefore developed a computer-based multimedia learning environment in which learners solve problems actively through the construction and revision of mental models. In addition, we developed a stochastic model based on the calculation of transition probabilities to assess similarities between models. In this article we report on the results of two conducted studies. The center of interest is the stochastic model of the measurement of change, which enables us to calculate the probability of a learning-dependent progression of externalized models constructed during the learning process. The results show (1) that the instrument we developed is highly reliable and (2) that there is a very high probability of change from the learner’s preconceptions (the “a priori”-model) to the subsequent learning-day model. Other findings indicate (3) a decrease in the probability of change in the following learning days. However, the theory of mental models and our initial results require that we modify and develop the instrument further.