P834: Student performance in organic chemistry problems with different cognitive requirements
: Nathan Barrows, Grand Valley State University, USA
Co-Author: Ian R. Gould and Ara Austin, Arizona State University, USA
Time: 3:05 PM – 3:25 PM
Room: MAK BLL 126
Related Symposium: S53
Most studies of cognitive ability in organic chemistry have focused on particular problem types (e.g. synthesis, stereochemistry). However, we are interested in the way that students perform across problem types that require very different cognitive strategies to solve. For example, whereas solving nomenclature problems requires the application of memorized rules, complex mechanism or multistep synthesis problems require students to apply their content knowledge in potentially unfamiliar contexts. In this presentation, we will describe our analytical methods (e.g. factor analysis, multiple linear regression) and report the findings of a multiple-year study that examined the correlations between performance on specific problem types with overall performance in the organic chemistry course. Although some problem types are much better predictors of overall performance than others, the findings indicate that the abilities of the top students are far more heterogeneous than initially believed. Specific results will be discussed in relation to other major determinants of success, specifically, student motivation and cultural capital.
P704: Online delivery of concept-rich OB labs
: Mary Karpen, Grand Valley State University, USA
Co-Author: Nathan Barrows and Harvey Nikkel, Grand Valley State University, USA
Time: 11:10 AM – 11:30 AM
Room: LOH 164
Related Symposium: S41
Teaching both organic and biochemistry in one semester is challenging, and students need ample opportunities to engage with the material for deeper learning to take place. We have developed and implemented several concept-rich laboratories for a one semester organic and biochemistry course at Grand Valley State University. Our laboratories are designed to reinforce concepts learned in lecture. In addition, we coded several of these labs into WebAssign, an online homework system. The laboratory manual is part of this system, with students inputting data and drawing conclusions via the online interface. Feedback for conceptual questions and data representations (approximate values, units, significant figures) is given immediately. We find the online, instant feedback prompts students to ask questions of the instructor and clear up misconceptions during the laboratory. In this presentation, we will describe our labs, demonstrate the online system, and present results from both student and instructor feedback.