Assessing recall, conceptualization, and transfer capabilities of novice biochemistry students' across learning style preferences as revealed by self -explanations

The research described herein is a multi-dimensional attempt to measure student's abilities to recall, conceptualize, and transfer fundamental and dynamic protein structure concepts as revealed by their own diagrammatic (pictorial) representations and written self-explanations. A total of 120 participants enrolled in a 'Fundamentals of Biochemistry' course contributed to this mixed-methodological study. The population of interest consisted primarily of pre-nursing and sport and exercise science majors. This course is typically associated with a high (<30%) combined drop/failure rate, thus the course provided the researcher with an ideal context in which to apply novel transfer assessment strategies. In the past, students within this population have reported very little chemistry background. In the following study, student-generated diagrammatic representations and written explanations were coded thematically using a highly objective rubric that was designed specifically for this study. Responses provided by the students were characterized on the macroscopic, microscopic, molecular-level, and integrated scales. Recall knowledge gain (i.e., knowledge that was gained through multiple-choice questioning techniques) was quantitatively correlated to learning style preferences (i.e., high-object, low-object, and non-object). Quantitative measures revealed that participants tended toward an object (i.e., snapshot) -based visualization preference, a potentially limiting factor in their desire to consider dynamic properties of fundamental biochemical contexts such as heat-induced protein denaturation. When knowledge transfer was carefully assessed within the predefined context, numerous misconceptions pertaining to the fundamental and dynamic nature of protein structure were revealed. Misconceptions tended to increase as the transfer model shifted away from the context presented in the original learning material. Ultimately, a fundamentally new, novel, and unique measure of knowledge transfer was developed as a main result of this study. It is envisioned by the researcher that this new measure of learning is applicable specifically to physical and chemical science education-based research in the form of deep transfer on the atomic-level scale.