P834: Student performance in organic chemistry problems with different cognitive requirements

Author: Nathan Barrows, Grand Valley State University, USA

Co-Author: Ian R. Gould and Ara Austin, Arizona State University, USA

Date: 8/6/14

Time: 3:05 PM3:25 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.

P433: One intelligent tutoring system for general organic chemistry

Author: Ian R. Gould, Arizona State University, USA

Co-Author: Kurt Van-Lehn and Refika Koseler, Arizona State University, USA

Date: 8/5/14

Time: 12:10 PM12:30 PM

Room: LTT 102

Related Symposium: S17

This presentation will describe an intelligent tutoring system for teaching and learning in the two-semester general organic chemistry course. The system currently has over 1000 original homework problems that have been categorized into over 400 individual knowledge components. Confidence levels for learning are estimated using probabilistic reasoning in the form of a Bayesian network, that makes use of student input to the website in addition to prior data. The student interface allows multiple ways of interacting with the material, and includes a dashboard that incorporates adaptive task suggestion (although modification to adaptive task selection would be straightforward). The design of the website, the student interface and the results of a pilot study will be described.

P19: Constructivist approach to the general organic chemistry lecture course

Author: Ian R. Gould, Arizona State University, USA

Co-Author:

Date: 8/3/14

Time: 3:40 PM4:00 PM

Room: LMH 176

Related Symposium: S3

Constructivism is often equated with discovery learning. Ausubel, however, suggested that learning from others can be as meaningful as discovery learning (meaningful reception learning theory), and placed emphasis on good expository teaching, where information is presented in close to final form and in a way that relates to existing knowledge. Here we describe such an approach to the general organic chemistry lecture course that builds on the fundamental concepts of electron energy and Lewis acid/base theory as the base knowledge that allows students to construct a general understanding of organic structure and reactivity. Topics that are sometimes considered to be more advanced, such as retrosynthetic analysis in terms of synthons and pericyclic reactions, fall naturally out of this approach.