Virginia Tech® home

Grant & Award Recipients - 2023-2024

During the 2023-2024 fiscal year TLOS working with the Provost’s Office awarded more than $330,000 in grants and awards. Funds were used for the development or redesign of flexible and online learning experiences, and the exploration of innovative approaches to teaching and learning using technology. Grants and awards were given in the following categories:

4-VA is a collaborative partnership between eight Virginia universities intended to promote collaborations that leverage the strengths of each university. Funding for Collaborative Research awards is provided up to $30,000 to support pilot research headed by a Virginia Tech faculty member collaborating with at least one faculty partner in a 4-VA member institution. This seed funding is designed to lay the groundwork and increase the potential for proposals to external granting agencies such as the National Science Foundation, and the National Institute for Health. TLOS, working with the Provost's Office, awarded the following 4-VA Collaborative Research Awards in Spring 2023 for funds to be distributed in July 2023.

Chen, ​​Yan, Computer Science, Visualizing Code Changes to Understand Students' Mental Models in Programming Education at Scale with Thomas LaToza from George Mason

​​Feng, Yiming, Virginia Seafood AREC, and Zhiwu Want, Biological Systems Engineering, Hyperspectral imaging for the real-time detection of microplastic particles in seafoods with Benoit Van Aken from George Mason, and Sandeep Kumar from ODU

Hosseinichimeh, Niyousha, Industrial and Systems Engineering, Investigating Factors and Processes Affecting Stroke Readmission with Rod MacDonald from JMU

Kaufman, Eric, and Mikel Manchester, Agricultural Leadership and Community Education, David Sample, Biological Systems Engineering, Feras Batarseh, Biological Systems Engineering, and Denis Gracanin, Computer Science, CyberBioSecurity for Smart-Connected Communities (CSCC) with Mohamed Azab from VMI (Planning Grant)

Li, Huaicheng, Computer Science, Near-data Processing for Machine Learning Workloads Acceleration with Yue Cheng from UVA

Misra, Shalina, Urban Affairs and Planning/School of Public & International Affairs, Benjamin Katz, Human Development / Family Science, and Patrick Roberts, Center for Public Administration & Policy, Autonomy and Competence in the Age of Artificial Intelligence: A Study with Stephen Marrin from JMU, and Brie Haupt from VCU

Scarpa, Angela, School of Education - Virginia Cooperative Extension (VCE), Amy Azano, School of Education, Cathey Sutphin, VCE, and Kathy Hosig, Population Health Sciences, Testing the Extension for Community Healthcare Outcomes in Autism (ECHO Autism) Model for Educator Training in Rural Virginia with Micah Mazurek, and Rose Nevill from UVA  

Senger, Ryan, Biological Systems Engineering, and John Robertson, VMD, Veterinary Medicine, Detecting Bladder cancer (BCa) progression, patient clinical status, and treatment efficacy with Raman spectroscopy of urine and artificial intelligence/machine learning (AI/ML)  with Georgi Guruli MD from UVA

Weber-Lucarelli, James, Biomedical Sciences and Pathobiology, Creating an improved oncolytic virus through directed evolution with Harald Sontheimer from UVA

Yang, Chin-Cheng Scotty, James Wilson, and Aaron Gross, Entomology, Assessing the risk of cross-species spillback transmission of a major viral pathogen in bees with T'ai Roulston from UVA

Zhang, Mengxi, Department of Health Systems and Implementation Science, and Junghwan Kim, Geography, Navigating Disparities in Dental Health - a Mixed-method Investigation of Access to Dental Care in VA with Tegwyn H. Brickhouse, DDS from VCU School of Dentistry

Baniya, Sweta, English/Center for Refugee, Migrants, & Displacement Studies, and Katrina Powell, Center for Refugee, Migrants, & Displacement Studies, New American Resources: Partnerships and Initiatives at Virginia Higher Education Institutions to Strengthen Virginia’s Migration Support with Grant Rissler and Saltanat Liebert from VCU, Kristen Richards and Nicole Neitzey from JMU, and Michelle Drongold-Sermen from George Mason

Innovation in Learning (IL) Grants are designed to support the evaluation and implementation of new approaches to teaching and learning using technology. These small seed grants are awarded to individuals or teams working on pedagogical and curricular projects that push the boundaries of technology-enhanced learning and have the potential for broad institutional impact. Grant awards are typically capped at $5,000, though exceptions may be made for awards over this amount under special circumstances.

Bruce, Herbert, Assistant Professor of Practice in Food Science and Technology
Students may only operate brewing equipment twice a semester in FST 4014, Applied Malting and Brewing Science. Industry expects that students who complete the fermentation option of the FST major will be able to run equipment and conduct testing proficiently, but with limited time on brewing equipment, students cannot be proficient with equipment by the end of the course. This project will explore simulating the brewing process to increase students' confidence operating brewing equipment.

Chen, Yan, Assistant Professor in Computer Science
Tang, Xiaohang, PhD student in Computer Science (lead graduate student)
How can a 1,000-student classroom achieve the same learning outcomes as one with just 30 students? This project will study, design, and develop AI-powered learning support systems to facilitate instructors in orchestrating large-size programming classrooms. The systems will provide the instructor with insights into student discussion, engagement, and code submissions. They will also recommend how to group students to enhance their collaborative learning experiences. With these AI-powered scaffolding, our goal is to empower instructors with tools to comprehend and cater to the myriad mental models of students in large-scale classrooms, thereby elevating the learning journey and its outcomes.

Johnson, Alicia, Director for Engineering Online
Introducing new technologies poses certain risks. One is that students' cognitive load may come from the technology and not from the content of the course; another is that technologies used in a different mode, for example from an in-person to an online format, may need a new approach by instructors. This project seeks to address both these challenges. It will create a “virtual lab” for courses in the Chemical Engineering Certificate program by using Jupyter notebooks within Canvas. These asynchronous, experiential courses will help students engage with industry-specific technologies. Since using the technology in an asynchronous mode will be new to instructors and students, the project activities will include 1) user-experience testing with students on the course design and technology with the aim of having students’ cognitive load come from the content and not the technology they are using, and 2) creation of a secondary course or mini-lesson to help support faculty in developing skills to use this technology without reliance on person-to-person transfer.

Neser, Laura, Instructor in Geosciences
It can be challenging to engage students in large courses such as Introduction to Earth Science (GEOS 1004) which have more than 100 students per section with some sections taught in-person and some asynchronously online. This project will incorporate, during the topic of earthquakes, a demonstration with student-chosen controls to engage students and encourage participation. Students will choose from various design options that they think would create the most resilience to earthquake shaking. The designs will then undergo simulation of an earthquake on a tremor table. Following this, students will reflect on why certain structures were resilient while others experience structural failure, and these demonstrations will be connected to real-world scenarios. This is expected to provide students with a more interactive and enjoyable experience, while still maintaining a high level of scientific curiosity (pre-demonstration assignment questions) and comprehension (post-demonstration assignment questions).

North, Christopher, Professor in Computer Science
Harden, Jesse, PhD student in Computer Science (lead graduate student)
When students ask questions in face-to-face lectures, it can disrupt the flow of learning; in online formats, such as Zoom, it can be hard for students to follow the questions, responses, and discussion in a chat window that can potentially have a high message volume. This project seeks to enhance student learning by making it more engaging by inviting faculty to use SAGE3 (Smart Amplified Group Environment), an open-source collaboration software designed for real-time interactive information and visualization sharing, which provides the instructor and students an infinite canvas on which they can pull together and share a variety of learning materials in a variety of ways. This technology is ideally suited for use on the high-resolution display in the Data & Decision Sciences 132 Visualization Classroom, but can also be used on any laptop or in any other classroom.

Rosier, Shaun, Assistant Professor in the School of Design
Landscape architecture is a uniquely site-oriented design discipline. Teaching students to produce high-fidelity landscape models typically requires extensive hands-on practice. One technology that has recently become affordable in educational settings for this purpose is LiDAR. The latest iPhone Pro and Pad Pro models have LiDAR modules that enable students to create detailed landscape models of study sites. This project will involve purchasing several iPad Pro devices for use in studio teaching courses, aiming to help students become proficient in capturing, manipulating, and editing point-cloud data, thereby preparing them for employment in the field after graduation.

Tural, Alp, Assistant Professor in the School of Design
Students of interior design will need to produce work that demonstrates an understanding and ability to apply the knowledge of building and fire protection codes, laws, and standards, but the codes are entirely text without visuals, and the textbooks are out-of-date and do not necessarily reflect building code changes. This project will create educational escape rooms (EERs) in mixed reality as an experiential pedagogical tool. By offering an immersive means to learn for sophomore-level interior design students, this project aims to improve students' knowledge retention and flexible learning.

Yee, Gordon, Associate Professor and Director of Undergrad. Studies in Chemistry
Thompson, Rosemary, senior undergraduate student in Chemistry
Teaching the skill of assigning point group symmetry in 4000-level physical inorganic chemistry typically requires 30-60 minutes of individual instruction per student. While students are provided with an algorithm to follow to learn the skill independently, they often struggle to identify their errors. This project will explore prompt design with generative AI tools to see if AI can adopt a tutor-persona capable of helping students identify their mistakes and guiding them to the answer without disclosing it. It will also explore the factual accuracy of the generative AI's responses around this topic.

Yoo, Hyesoo, Associate Professor in the School of Performing Arts
Future music educators need exposure to diverse cultural instruments from around the world. The challenge is that these instruments are expensive and can be challenging to find. This project will explore part of a larger idea to implement an “Immersive Technology Integrated in Music” program by seeking to improve students’ cross-cultural perspective on musicality and their technology literacy through playing various virtual world music instruments. These virtual instruments will be played via iPads and can be connected to an audio mixer allowing students to perform as a virtual music instrument ensemble.