Assessing Change in Learners’ Causal Understanding Using Sequential Analysis and Causal Maps

Abstract

New methods and software tools are needed to assess the quality of learners’ causal maps (maps that convey a learner’s understanding of complex phenomena) and the quality of learners’ discourse used to help justify changes and refinements in learners’ causal maps. New methods and software tools are needed to assess the dialog move sequences observed in group discourse that trigger changes in causal maps and to measure and visualize across time the extent to which changes in causal maps of the individual or collective group progress toward group consensus and target maps. The software tool called jMAP was developed to enable learners to individually produce and submit causal maps, download and aggregate the maps of other learners. It also generates aggregated maps to reveal similarities between individual/group maps, the percentage of maps sharing particular causal links, average causal strength assigned to each link, and degree of match between the maps of the collective group and the target/expert diagram. jMAP also supports the use of sequential analysis to measure and visualize (with transitional state diagrams) how learner’s causal maps change over time and how dialogic processes of argumentation conducted in online discussions trigger changes in learner’s causal maps. This chapter presents findings from two case studies to illustrate how jMAP can be used to support the assessment of causal understanding, and to identify areas for future research and development.