Exploring Formative Feedback on Textual Assignments with the Help of Automatically Created Visual Representations

Abstract

Learners, particularly lifelong learners, often find it difficult to determine the scope of their expertise. Formative feedback could help them do so. To use this feedback productively, it is essential to then suggest to them the remedial actions they need to overcome the gaps in their knowledge. This paper presents the design considerations of a support tool that aims at providing formative feedback on textual assignments. It does so by facilitating comparisons between learner’s input texts and group input texts with respect to the intended learning outcomes. Using language technologies, the tool automatically extracts the concepts and relations of input texts; it then creates visual representations that can be put side by side to identify conceptual overlaps and missing concepts. The paper first introduces the theoretical underpinnings of the tool – specifically those concerning expertise development, knowledge creation and assessment of knowledge. It then draws up design considerations and clarifies how the tool should work. Next, it discusses the results of an initial study in which word clouds and concept maps have been applied to generate graphical visual representations. These help learners identify overlapping and missing core concepts, both in individual texts and in a compiled group text. Finally, the paper provides conclusions and directions for future work.