Rasch Measurement of Collaborative Problem Solving in an Online Environment.

This paper describes an approach to the assessment of human to human collaborative problem solving using a set of online interactive tasks completed by student dyads. Within the dyad, roles were nominated as either A or B and students selected their own roles. The question as to whether role selection affected individual student performance measures is addressed. Process stream data was captured from 3402 students in six countries who explored the problem space by clicking, dragging the mouse, moving the cursor and collaborating with their partner through a chat box window. Process stream data were explored to identify behavioural indicators that represented elements of a conceptual framework. These indicative behaviours were coded into a series of dichotomous items. These items represented actions and chats performed by students. The frequency of occurrence was used as a proxy measure of item difficulty. Then given a measure of item difficulty, student ability could be estimated using the difficulty estimates of the range of items demonstrated by the student. The Rasch simple logistic model was used to review the indicators to identify those that were consistent with the assumptions of the model and were invariant across national samples, language, curriculum and age of the student. The data were analysed using a one and two dimension, one parameter model. Rasch separation reliability, fit to the model, distribution of students and items on the underpinning construct, estimates for each country and the effect of role differences are reported. This study provides evidence that collaborative problem solving can be assessed in an online environment involving human to human interaction using behavioural indicators shown to have a consistent relationship between the estimate of student ability, and the probability of demonstrating the behaviour.