Predicting conceptual gain in an atomic bonding module from proficiency in "engineering speak"

Engineering education has focused on understanding student conceptual development with a variety of assessment methods. Much research is focused on developing strategies, pedagogies, or interventions to promote effective conceptual development. However, results are dependent on the ability to accurately, efficiently, and easily measure the effect of different strategies on differences in conceptual gains. At this time, the Materials Concept Inventory (MCI) is the only validated pre-post course assessment tool for measuring student conceptual gain in introductory materials courses. But, because such courses are often broad in scope, topics may differ from those found on the MCI and can be difficult to assess. Developing alternative assessment tools that effectively elicit student misconceptions and measure conceptual change may take time, resources, and significant numbers of students. In this study we seek to answer the question, “What kind of model is there that can be constructed to predict conceptual change using student understanding which is easy to use for acquisition and analysis of data.?” One method for doing this, which is reported in this research literature, is to code the student responses to the various questions on a given topic with a quantitative rubric as a measure of the level of quality of technical “engineering speak”. The model also has the potential to track the impact of teaching and learning materials on student progress in learning of topical content for different engineering disciplines. In this research we report on the correlation between "engineering speak" and conceptual gain for the topic of atomic bonding in an introductory materials class.