June 26, 2011
June 26, 2011
June 29, 2011
22.1166.1 - 22.1166.13
Predicting Conceptual Gain in an Atomic Bonding Module from Proficiency in "Engineering Speak"Engineering education has focused on understanding student conceptual developmentwith 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 theeffect of different strategies on differences in conceptual gains. At this time, theMaterials Concept Inventory (MCI) is the only validated pre-post course assessment toolfor measuring student conceptual gain in introductory materials courses. But, becausesuch courses are often broad in scope, topics may differ from those found on the MCIand can be difficult to assess. Developing alternative assessment tools that effectivelyelicit student misconceptions and measure conceptual change may take time, resources,and significant numbers of students. In this study we seek to answer the question, “Whatkind of model is there that can be constructed to predict conceptual change using studentunderstanding which easy to use for acquisition and analysis of data.?” One method tofor doing this, which is reported in this research, is to code student responses to variousquestions on a given topic for the level of quality of technical “engineering speak”."Engineering speak" refers to expert consensus of the means of describing materialsconcepts and phenomena in a particular topical area. In this work we report on studentresponses in the area of atomic bonding. Such responses were either assigned a value of 0(for no response), 1 (for colloquial speak), 2 (for quasi colloquial/engineering speak), or 3(for technical engineering speak). It was found that level of engineering speak alonecould significantly predict 52.7% of the variance in conceptual gain scores in the area ofatomic bonding over the course of a semester, R2 = .527, t(35) = 6.33, p < .01. Additionalpredictors will be examined to see if a simple model can be created to explain additionalvariance in conceptual gain. A simple model such as this has the potential to giveinstructors easier access to assessment of student conceptual change. The model also hasthe potential to track the impact of teaching and learning materials on student progress inlearning of topical content for different engineering disciplines.
Kelly, J. E., & Krause, S. J., & Baker, D. R. (2011, June), Predicting Conceptual Gain in an Atomic Bonding Module Paper presented at 2011 ASEE Annual Conference & Exposition, Vancouver, BC. https://peer.asee.org/18838
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