Collaborative Research: Research Initiation: Complementary affordances of virtual and physical laboratories for developing engineering epistemic practices
National Science Foundation
Milo Koretsky; Collaborator: Jeffrey Nason, Oregon State University
In addition to being able to competently perform engineering calculations, professional engineers must be prepared to work effectively in teams, consider problems in context, make evidence-based decisions, and persist and learn from failure. Laboratory work provides an important tool for professional formation, allowing university engineering students to develop these skills. Successful laboratory task designs should provide rich opportunities to develop these skills but also must fit into the constraints of the educational setting. This study will investigate the ways that a virtual (simulation-based) and physical (hands-on) laboratory based on the same realistic engineering process prepares students for the profession. In particular, we will investigate if the virtual and physical laboratory modes develop different but complementary skills. The knowledge gained will better position engineering educators to design and employ virtual and physical laboratories, including cases where students are place-bound and may not have access to physical equipment. While this study will focus on a process specific to environmental engineering, the knowledge gained has the potential to broadly impact teaching and learning practices across all engineering and science disciplines that rely on laboratory investigation in the curriculum.
Collaborative Research: Machine Learning for Student Reasoning during Challenging Concept Questions
National Science Foundation
Milo Koretsky; Collaborator: Anna Rumshisky, UMass Lowell
Artificial Intelligence (AI), and more specifically, language models, have been drastically changing how students and instructors think about learning and assessment. While there are legitimate concerns about how the use of these tools could be detrimental to learning, this research project aims to leverage language models to better prepare engineering learners of the 21st Century. The research project will use modern AI and machine learning (ML) tools to automate analysis of student-written responses to challenging concept questions. These qualitative questions are often used in large STEM classes to support active learning pedagogies; they require minimum calculations and focus on the application of underlying physical and chemical phenomena to various situations. With previous NSF funding, we have developed the Concept Warehouse (NSF DUE 1023099, 1821439, 2135190), a classroom response system where students provide written justifications to concept questions. Providing written justifications targets development of reasoning and sense-making skills in students and can also better prepare them for discussions with peers resulting in broader effectiveness of active learning pedagogies. However, expository prose also presents a daunting amount of information for instructors to process. In this project, we will leverage recent advancements in machine learning tools and natural language processing technologies to develop automated processes to analyze student-written justifications to challenging concept questions.
Design Talks
National Science Foundation
Kristen Wendell; Collaborator: Jessica Watkins, Vanderbilt University
In collaboration with Jessica Watkins at Vanderbilt University, Design Talks is an NSF DRK-12 funded project focusing on the structure and dynamics of whole-class engineering design conversations, including talks about the macro-ethics of design. The Design Talks team includes teachers and education researchers who collaborate to plan and record classroom Design Talks with distinct purposes. We then use discourse analysis to build theory on the characteristics of classroom talk that supports elementary students’ knowledge construction and socio-ethical reasoning in engineering design contexts. Funded by NSF grant 2010139.
Increasing Engagement and Access in STEM: Development of Virtual Laboratories that Elicit Engineering Epistemic Practices.
CREEdo Seed Grant
Milo Koretsky; Collaborator: Jeff Nason, Oregon State University
In this seed project, we will develop and assess the use of a virtual laboratory for (1) eliciting engineering epistemic practices not easily accomplished with in-person university laboratories and (2) increasing the accessibility of laboratory content for students studying in online environments. A virtual laboratory will be developed based on a physical lab (jar testing) common in most undergraduate and graduate environmental engineering programs. The team will partner with instructors to deliver both the physical and virtual versions of the jar testing laboratory, comparing student motivation, epistemic practices, and development of engineering identity through surveys and discourse analysis of video-recorded observations of teams.
Collaborative Research: Understanding Context: Propagation and Effectiveness of the Concept Warehouse in Mechanical Engineering at Five Diverse Institutions and Beyond
National Science Foundation
Milo Koretsky; Collaborators: California Polytechnic State University, San Luis Obsipo (Lead), University of Washington, Bucknell University, University of Puerto Rico Mayaguez, Allan Hancock College.
This project seeks to substantially increase the adoption of evidence-based, highly effective, concept-based active learning throughout undergraduate engineering programs. It builds from previous success developing the Concept Warehouse (CW), an NSF-funded, web-based instructional tool that decreases barriers for faculty to adopt these pedagogies. Concept-based active learning has been shown to improve student performance, especially for traditionally underrepresented students, and to increase academic retention of students in STEM programs. This proposal seeks to expand the use of the CW from its initial Chemical Engineering audience to Mechanical Engineering and to thereby directly impact 50,000 new undergraduate students during the project and additional students beyond. The project will directly study how instructor decisions to adopt the CW are embedded within educational systems at five diverse institutions: a large research public university, a small private university, a two-year college serving a large number of under-represented students, a large non-PhD granting public university, and a bilingual research university. We take an ecosystems approach to examine how elements of educational setting (institutional context, instructor context, learner context and features of the innovation itself) influence uptake and use of the innovation and the resulting student learning.
The Mechanics of Inclusion and Inclusivity in Mechanics
California Learning Lab, State of California
Milo Koretsky; Collaborators: California Polytechnic State University, San Luis Obsipo (Lead), UC Santa Barbara, Allan Hancock College
Mechanics is a core topic in both physics and engineering that is rife with nonintuitive concepts and content that proves challenging to master for many undergraduates. Scholars have grappled for decades with developing educational approaches to complex mechanics topics. At the same time, existing research and institutional data point to significant gaps in both performance and equity for non-traditional and underrepresented minority students. However, although mechanics includes core topics across both engineering and physics, many faculty do not form strong connections between disciplinary treatments of these common principles in ways that might enhance performance, identity, belonging, and ultimately persistence in STEM. To address these issues, our project establishes an interdisciplinary partnership across California Community Colleges, the California State University, and the University of California systems. In particular, our proposal seeks to eliminate the equity and performance gaps in mechanics courses by (a) developing a suite of web-based tools that incorporate videos that motivate why a topic is relevant to the real world, ConcepTests, Instructional Tools, and Computerized Adaptive Testing, while (b) leveraging those cognitive tools and special non-cognitive/affective interventions to establish a sense of belonging, a strong STEM identity, and deep conceptual understanding. Parallel to these online efforts will be the implementation of evidence-based practices in the face-to-face classroom, such as the integration of Learning Assistants, implementation of hands-on experiments, and development of a collaborative, team-based learning environment, in which collaborative norms minimize microaggressions and toxic gendered interactions among team members.
Improving Students’ Sociotechnical Literacy in Engineering
National Science Foundation
Ethan Danahy, Jennifer Cross, Ellise LaMotte, Deborah Sunter, Desen Ozkan, Chelsea Andrews
This project seeks to make the social, political, and economic contexts of engineering assumptions and decisions visible in an introductory engineering curriculum. Building on a pilot project funded by Tufts Springboard, the NSF funding will allow the work to expand from two sections of ES-2 to all sections. Up to thirty Equity Learning Assistants (ELAs) will facilitate modules around engineering as a sociotechnical endeavor. The modules will include activities that push students to critique the assumptions and decisions embedded in data sets and technologies that become apparent when situated in social, political, and economic contexts. The ELAs will partake in a co-current seminar led by Desen Ozkan and Chelsea Andrews to dive deeper into module topics in the ES-2 classes.
Connecting the Dots between Organic Chemistry and Social Justice through Mechanistic Reasoning
Tufts Springboard
Ira Caspari & Rebecca Scheck
In this re-design of the course Chem 150 “Mechanistic Reasoning in Organic Chemistry” and its in-depth evaluation, we implement and investigate six modules that authentically combine elements fostering students’ mechanistic reasoning in organic chemistry with reframing privileged agreements of academia into agreements that support wholeness, justice, and liberation.
Facilitation Practices of Instructional Assistants
National Science Foundation
Ira Caspari & Vesal Dini
A study of how undergraduate learning assistants and graduate teaching assistants (LAs and TAs) facilitate student learning in introductory chemistry and physics lectures, starting Fall 2020; Ira Caspari and Vesal Dini, in collaboration with Hannah Sevian at UMass Boston. We use a sociocultural perspective to model four dimensions of LAs’ and TAs’ facilitation practices: the nature of the interactions, their purposes, in-the-moment learning that occurs, and the integration of the interactions into the whole class.
Engineering Tools for Education Research
National Science Foundation
Mark Hempstead, Shuchin Aeron, Sameer Sonkusale, Ayanna Thomas, Kristen Bethke-Wendell, Julia Gouvea, David Hammer, Eric Miller
This is a collaboration of faculty from Electrical and Computer Engineering, Psychology, and IRLI to develop tools for research on learning. We’re supported by two grants, both by NSF. One is a Convergence RAISE award, for three years, to develop (1) biosensors to measure stress through unobtrusive wearable patches and (2) machine learning (ML) approaches to support qualitative research. COVID has slowed work on 1, but 2 is proceeding apace, so far focusing on ML support for qualitative analysis of the structure of students’ arguments in biology lab reports. And the second is a planning grant, to support our proposing an Engineering Research Center, to do a lot more of this kind of work.
How students frame what they’re doing in labs
National Science Foundation
David Hammer, Ian Descamps
We are collaborating with Profs Natasha Holmes, at Cornell, and Rachell Scherr, at the U Washington Bothell, to study how students approach reformed laboratories in introductory physics. The formal title at NSF is “Investigating How to Better Prepare Undergraduate Students for Physics Labs that Focus on Experimental Science.” We’re working to (a) identify the various ways students frame activities in introductory physics labs, (b) identify ways students shift or change how they frame lab activities, and, ultimately, (c) formulate testable predictions for ways to help students develop stable, productive frames for experimental science. We will especially look for whether students expect labs to replicate established results based on concepts and ideas from lecture, or whether they expect to draw their own conclusions from the data they collect.
The Listening Project
Howard Hughes Medical Institute
Roger Tobin, Lara Appleby, David Hammer, Diren Turner, Vesal Dini
This is mainly a project in faculty development, focused on introductory science courses, and funded by the Inclusive Excellence initiative at HHMI. It is a collaboration across the departments of Physics & Astronomy, Biology, and Chemistry, and the Center for the Enhancement of Learning and Teaching (CELT). The core focus is on helping instructors (faculty and graduate student teaching assistants) hear and make sense of students’ thinking. We are drawing on the project to conduct some early research on faculty listening. For more information, see The Listening Project website.
Undergraduate Learning Assistants and Engineering Problem-Solving
Tufts University, IRLI
Kristen Wendell, Hoda Koushyar, Isabella Stuopis
This is a pilot study examining how undergraduate learning assistants (LAs) support student interaction and reasoning during collaborative open-ended problem-solving tasks in mechanical engineering.
Personalized Problems for Enhanced Thermo-Fluids Learning
Erica Kemmerling, Kristen Wendell, Isabella Stuopis, Katie Melsky
In this project, we are designing and studying the implementation of thermal-fluid problems that have been personalized for students’ self-reported interests, hobbies, and backgrounds. Data analysis is exploring the ways in which personalized problems are distinct from traditional generic textbook problems in their support for student engagement and knowledge construction.
Hybrid Labs
Tufts Innovates, The Davis Foundation
Julia Gouvea, Aditi Wagh, Lara Appleby, Matthew Simon, Robert Hayes
The Hybrid Labs Project was a design based research project that developed pedagogical supports and curricular materials for a reformed biology lab course at Tufts. Notable contributions include a hybrid “wet-lab” (organismal) and “dry-lab” (computational) curricular structure, and a support course to train graduate student instructors in responsive teaching pedagogies. Research is ongoing to identify and disseminate elements of the intervention which supported students’ reasoning, framing, and engagement in practices in science.
Data Driven Decision Making
National Science Foundation
Shafik Islam, Remco Chang, David Hammer, Jon Lamontagne, Abani Patra
This is a 5-year, cross-school project in data science education, funded by NSF’s Research Traineeship program (NRT). The goal is to develop new curriculum, in the form of interdisciplinary “Modular Course Elements” and “Problem-Based Immersions” IRLI is playing a supportive role at the outset, with the possibility of research on the learning taking place once the program is developed and running. See the Tufts Now article.