Mental models: towards a cognitive science of language, inference, and consciousness
Mental models: towards a cognitive science of language, inference, and consciousness
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Advanced digital technologies present both new types of texts and learning environments for learning scientists to study. These same technologies also support new ways of capturing and analyzing information on student thinking. This paper reports on research that used a digital learning environment (complete with prose, graphics, animations, and agents) to provide elementary school readers a scientific text containing embedded free-response assessment items to capture information on their thought processes. This paper explores methodological issues associated with coding and analyzing constructed response items of this type. Drawing on established approaches to propositional analysis with extensions to reflect the multimodal nature of the text and the task, we present a methodological approach developed to balance detail and nuance in students' use of language with a systematized approach to analyzing those data. This discussion is presented for both its value to the learning sciences and as a contribution to critical discussions about assessing student learning in complex learning environments.