The Shrewd Guess: Can a Software System Assist Students in Hypothesis-Driven Learning for Organic Chemistry?

Julia E. Winter, Alchemie Solutions, Inc.
Joseph Engalan, Alchemie Solutions, Inc.
Sarah E. Wegwerth, Alchemie Solutions, Inc.
Gianna J. Manchester, Alchemie Solutions, Inc.
Michael T. Wentzel, Augsburg University
Michael J. Evans, Georgia Institute of Technology
James E. Kabrhel, University of Wisconsin-Green Bay
Lawrence J. Yee, Hartnell College


The mechanism maps that guide student instruction in organic chemistry curricula are structural representations of bond-breaking and bond-making events that transform a reactant into a product. For students, these pathways represented by electron pushing formalism (EPF) can be challenging to navigate. For instructors, providing formative feedback to students to support their learning of the EPF arrow system is difficult to provide in a timely manner. The Mechanisms App ("the App") was developed as a method for students to explore the electron movement of organic chemistry through a touch screen interface of a smart phone or tablet with real-time feedback of these moves. In this paper, the pedagogical content of the App and its backend system is described. This system produces a graphical record of a user's move within the App and is called a decision tree. A study of students' use of the App in two different modes was devised to understand whether the in-app experience can facilitate a hypothesis-driven approach to learning EPF. Examples of classroom implementation for the App in a variety of institutions and future research are also described.