A computer-based approach for translating text into concept map-like representations
Roy B. Clariana, Ravinder Koul · 2004
Abstract. Unlike essays, concept maps provide a visual and holistic way to describe declarative knowledge relationships, often providing a clear measure of student understanding and most strikingly, highlighting student misconceptions. This poster session presents a computer-based approach that uses concept-map like Pathfinder network representations (PFNets; Shavelson & Ruiz-Primo, 2000) to make visual students ’ written text summaries of biological content. A software utility called ALA-Reader (www.personal.psu.edu/rbc4/) was used to translate students ’ written text summaries of the heart and circulatory system into raw proximity data, and then Pathfinder PCKNOT software (Schvaneveldt, 1990) was used to convert the proximity data into visual PFNets. The validity of the resulting PFNets as adequate representations of the students ’ written text was considered by simply asking the students and also by comparing the correlation of human rater scores to the PFNet agreement-with-an-expert scores, (PFNet text score Pearson r = 0.69, ranked 5th out of 12). The concept-map like PFNet representations of texts provided students (and their instructor) with another way of thinking about their written text, especially by highlighting correct, incorrect, and missing propositions in their text. This paper provides an overview of the approach and the pilot experimental results. The actual poster session will in addition demonstration the free ALA-Reader software and will also how to procure and use PCKNOT software. 1