OpenEssayist : an automated feedback system that supports university students as they write summativeessays Conference or Workshop Item

OpenEssayist is an automated, interactive feedback system designed to provide an acceptable level of support for students as they write essays for summative assessment. There are two main components to the system: (1) a linguistic analysis engine and (2) a web application that generates feedback for students The main pedagogical challenge in the e-assessment of free text is how to provide meaningful “advice for action” in order to support students writing their summative assessments. We have built a first working version of the system in which we use unsupervised graph-based ranking algorithms (following Mihalcea & Tarau, 2005) to automatically extract key words, phrases and sentences from student essays. We have developed several external representations of these summarisation techniques. For examples, key words and key phrases can be viewed in a word cloud or in a dispersion graph, and they can be explored and organised into groups. Holistic approaches have also been tested using ‘mash ups’ where key words and key sentences are highlighted in context in the essay itself, helping students to investigate the distribution of key words and its potential implications for the clarity of the narrative. This paper will report the findings from our pilot studies of the interactive models associated with the summarisation techniques.