Thermodynamics is a core subject that engineers need to master to be able to design systems that meet society's energy needs in the 21^st century. However, students find this subject particularly difficult to master. One reason for the difficulty is the diverse and challenging set of concepts that they must coherently synthesize and be able to apply in a diverse range of contexts. In this NSF TUES project we have developed and implemented seven Interactive Virtual Laboratories (IVLs) to help students identify and learn these threshold concepts.

In the IVLs, students are guided through a set of frames where they are asked to respond to questions that ask them to predict, observe, or reflect on phenomena related to a specific threshold concept. The three main parts include (i) a molecular simulation that students are tasked with manipulating in certain ways; (ii) a macroscopic, graphical representation of the simulated phenomena (located to the right of the molecular simulation); and (iii) a box to read instructions and provide answers to questions (below the molecular simulation). An automated IVL assessment facility has been implemented to provide instructors with numerical scores for students who complete each IVL. These IVLs will remain available to the engineering community after the project through their integration into the AIChE Concept Warehouse, which was developed with NSF funding.

During the project, about 5,000 students at seven institutions have used the IVLs. The capability of IVLs to generate large amounts of data present opportunity to understand student learning and provide formative feedback and adaptive instruction. To complement the implementation data we have conducted clinical studies using a think aloud protocol on individuals and teams. In total, 45 students participated as they worked through three different IVLs. We have analyzed the transcripts of the audio recordings to uncover the student thinking process that led them to the answers they input in IVL. We especially tried to recognize (1) common misconceptions that led students to common wrong numerical answers of procedural questions; (2) productive discussion in conceptual questions regardless of whether answers to procedural questions were accurate; and (3) reasoning that was canonical and also led students to arrive at the correct answers to procedural questions. This analysis provided us a spectrum of student thinking and responses, in continuum, from wrong-answers with wrong-reasoning, to partly-correct reasoning, to correct-answers with correct-reasoning.

Our original conception in creating the IVLs was that given the "right way of thinking" and simulations of microscopic behavior to make emergent macroscopic phenomena visible, most students would develop mastery of the difficult concepts in thermodynamics (such as work and internal energy). However, we found that only a subset of students were able to provide responses that fully aligned with the design intent. By examining student process data from the IVLs, we have been led to shift our focus of conceptual learning away from individual mental structures that are acquired to the collaborative social activity in which students participate to learn. Following a resources framework, we were able to identify the social and environmental interactions that lead students to activate resources and form ideas. As we describe in an article published in the Journal of Engineering Education (https://onlinelibrary.wiley.com/doi/abs/10.1002/jee.20237), we built on the resources framework and specifically introduce the concept of shared resources, which identifies the fruitful material and social triggers that allow students to activate resources and recognize new ideas within a technology environment (the Thermodynamic Work IVL) in a social context (working in a group in Studio) to develop mastery.

The construct of shared resources fundamentally shifts the ways we approach design and implementation of technology-based learning environments. Instructors using technology should look outside the technology itself and consider how it is deployed in learning environments to position learners to share resources. We argue that attributing student learning or their misconceptions to features of a simulation tool leads educators to place too much reliance on the technology itself. Therefore, less than satisfactory learning gains naturally lead to conclusions that we need to invest in the costly development of more effective technologies. Rather, we recognize a class environment in which an existing technology can be leveraged to become more effective. The social structure of groups in the studio setting was critical to allow for the activated resources of individual students to be shared with others. In other words, we shift the perspective from one where learning occurs through the technology to one where the technology is a useful tool in a collaborative learning environment.

Last Modified: 07/03/2019
Modified by: Milo D Koretsky