The feasibility of automatic assessment and feedback

In this study, we report on the results of studies in which two randomized groups of students are monitored while they solved exercises in a Data Structures and Algorithms (DSA) course. The first group did the exercises on the web and the second one in the classroom sessions. A web based system was employed that was able to give feedback and automatically assess the exercises. The research question was to find out how we should introduce the self study material and automatically assessed exercises to the students in order to maximize their learning experience and to avoid drop outs. In addition, we surveyed the students ’ attitude towards www-based exercises by using questionaries. The students were asked what kind of exercises they would prefer to do in DSA courses as well as how they would assess their own learning experience in the three different setups (human guided, web based or mixed). All these studies were carried out simultaneously in two different universities. It is not surprising that the results suggest to introduce easy and human guided exercises at the very beginning of the course. However, we conclude that currently there is an emerging need for both webbased and classroom exercises. The recommended way to introduce the web-based exercises in DSA courses is by combining these two approaches. There is a set of exercises that are best suitable to be solved and automatically assessed on the web while the rest of the exercises are best suitable for traditional classroom sessions. We believe that the results of this study can be generalized to cover also other similar learning environments than that used in this research to give automated feedback for the students, and thus improve the learning experience