The U.S. National Science Foundation-funded project started in August 2023 and leverages QubitVR, a quantum-education VR application previously developed at 麻豆原创 through the computer science senior design program.

The project will evaluate QubitVR and intelligent tutoring versions of the VR application through lab-based studies and undergraduate QIS courses. The project will also result in the development of desktop and smartphone versions of QubitVR for broader impacts.

麻豆原创 will be responsible for the iterative development of QubitVR 鈥� including the machine-learning-based intelligent tutoring versions, conducting the lab-based studies and evaluating QubitVR through an undergraduate QIS course. 麻豆原创 has received $500,000 for these efforts, and Ryan McMahan, an associate professor of , is the lead principal investigator for the project at 麻豆原创. Eduardo Mucciolo, a professor of at 麻豆原创, is also senior personnel for the project.

Quantum computing leverages quantum mechanics principles in which particles can be in multiple places and states simultaneously to achieve vastly enhanced processing power.

鈥淔or example, the encryption that keeps your email safe and your password safe 鈥� a quantum computer could crack that in minutes,鈥� McMahan says. 鈥淪o, there’s a lot of potential power there.鈥�

McMahan says the possibilities of quantum computing are enormous, but the complexity of the field, including misconceptions about phenomena such as superposition and components such as quantum logic gates, can be a barrier to entry.

But by using VR, educators can provide tangible, visual understandings of quantum mechanics that empower students and professionals to harness the power of quantum computing, he says.

Training the Workforce

McMahan says that currently many of the people working in quantum computing have very strong ties to quantum physics, but there are fewer computer scientists involved who would have the skills for writing new quantum algorithms.

鈥淚f we can train people where they have a good conceptualization for the quantum mechanics but also have strong algorithmic backgrounds, we’ll actually see more quantum computing algorithms develop,鈥� McMahan says. 鈥淐urrently, there are only a few well-known quantum computing algorithms because it’s so hard to understand these concepts and how to utilize them to take advantage of quantum computing.鈥�

These algorithms could be used for cryptography, security, big data analysis and more.

Several companies and institutions have developed quantum computers, although the technology is still in the early stages of development. These computers also face limitations, such as the need to operate them at extremely low temperatures to minimize environmental interference of quantum bits of information.

Keerthan Reddy Rajulapally, a 麻豆原创 student pursuing a master鈥檚 degree in computer science, is working as a graduate research assistant on the project. His role includes developing the software and the QubitVR application.

鈥淥ur goal is to create a VR application which has an intelligent tutoring system implementing different machine learning models to teach 鈥榟ard to understand subjects or topics鈥� with ease,鈥� Reddy says. 鈥淭hrough QubitVR, we are trying to teach quantum computing, but we can always design a different application tailored for a specific subject.鈥�

The graduate research assistant says he has always been interested in gaming, and after being introduced to VR gaming and then McMahan鈥檚 virtual reality engineering course, he became hooked and wanted to pursue research in the field.

鈥淲ith this project we hope to help both the teachers and students alike,鈥� he says. 鈥淲e are revolutionizing teaching and redefining 鈥榣earning鈥� by giving students an interactive, fun 3D experience where they can truly understand the essence of a topic.鈥�

Collaborative Research

The project started as the result of a conversation McMahan had with Michael Kolodrubetz, an assistant professor of physics at the University of Texas at Dallas, about how VR might be great for education on challenging concepts such as quantum mechanics.

鈥淲e got to talking and started collaborating on QubitVR soon after,鈥� Kolodrubetz says.

Kolodrubetz鈥檚 role in the project will be as the quantum expert, through both his research on non-equilibrium quantum mechanical systems and his teaching on quantum mechanics for non-physicists.

鈥淢y group will help adapt QubitVR to target the most salient, hard-to-grasp points in quantum information science and allow students to visualize them in the context of VR,鈥� he says.

Kolodrubetz says that quantum mechanics and information is becoming increasingly relevant to technology as it scales down to small enough sizes where classical physics ceases to be a useful explanation.

鈥淒espite this, most STEM students learn little to no quantum science, and those that do often struggle to understand quantum phenomena due to misconceptions about how quantum systems should behave based on their experience in the classical world,鈥� Kolodrubetz says. 鈥淏y allowing interactions with quantum systems of technological relevance, QubitVR will lower the barrier to breaking these misconceptions and provide groundwork for understanding that may lead to further technological advancement.鈥�

Kelley Durkin, a research assistant professor with Vanderbilt University who studies children鈥檚 misconceptions in mathematics, will serve as the learning scientist on the team.

She will help develop a new assessment of students鈥� knowledge of quantum information sciences, identify misconceptions students show when learning about quantum information sciences and will suggest ways to adapt QubitVR to directly address students鈥� misconceptions.

鈥淥ften, people just try to address students鈥� misconceptions by telling them they are wrong and showing them the correct answer,鈥� she says. 鈥淨ubitVR provides a unique opportunity to not only identify where students鈥� misunderstandings are but also to provide them with problems to challenge those misconceptions in real-time.鈥�

鈥淗opefully, QubitVR will reduce barriers to students understanding quantum information sciences and will make the field more accessible to students,鈥� she says.

Researcher Credentials

McMahan received his doctoral degree in computer science and application from Virginia Tech and joined 鲍颁贵鈥檚 Department of Computer Science, part of the , in 2019.

Through this project, Resilience, Education and Advocacy Center for Hazard preparedness (REACH) hubs will be developed thanks to a recently announced $50,000 grant from the U.S. National Science Foundation鈥檚 (NSF) Civic Innovation Challenge program. They could be deployed any time a disaster 鈥� whether natural or human-made 鈥� strikes.

Leading the project is a team of 麻豆原创 faculty, including Assistant Professor Kelly Stevens and Associate Professor Yue 鈥淕urt鈥� Ge, Assistant Professor L. Trenton Marsh, and College of Engineering and Computer Science professor Liqiang Wang and Pegasus Professor Zhihua Qu.

The REACH hubs will be able to serve two primary roles. Following disasters or local emergencies, the hubs will provide critical services such as cooling, broadband internet and reliable electricity to areas whose access to those needs may already be unstable. The hubs also will serve as hazard-preparedness and hands-on STEM education centers.

鈥淒ifferent types of hubs are being developed and used across the U.S., but ours is unique in that it has an equally important use during non-emergency times,鈥� Stevens says. 鈥淢aking a solar-powered, portable hub is technically challenging, but the benefits it can provide to communities whose access to standard services may already be restricted without an external shock make it well worth it.鈥�

Stevens says that the grant also paves the way for partnership opportunities.

鈥淭he NSF CIVIC program is unique because it focuses on civic partnerships that can be quickly implemented and ultimately sustained long-term by participating local partners,鈥� she says. 鈥淲e will host a local stakeholder meeting next month with our partners and two public input meetings in December to really get feedback from the whole community.鈥�

She says the community meetings will help determine factors ranging from what services the hubs will provide and where they will be deployed after a disaster to which educational topics should be covered during non-emergency events.

Beyond the external partnerships, Stevens says this project opens the door for new cooperation with other 麻豆原创 colleagues across different disciplines.

鈥淭he research we are doing builds on interdisciplinary coordination from public administration, computer science and engineering across 麻豆原创,鈥� she says.

The research team will have six months to prepare a plan for the REACH hub and submit it to the NSF, after which they are eligible for up to $1 million in awarded funds to execute the project.

About the Research Team

Stevens received her doctorate in public administration from Syracuse University and joined 鲍颁贵鈥檚 School of Public Administration, part of 鲍颁贵鈥檚 College of Community Innovation and Education, in 2017. 聽She is a member of 鲍颁贵鈥檚 Resilient, Intelligent, and Sustainable Energy Systems (RISES) Cluster and

After joining 麻豆原创 in 2018, Ge has since been appointed co-lead of the Urban Resilience Initiative based at 麻豆原创 Downtown. He has also served on the RISES faculty research cluster since 2021. He holds a doctorate in urban and regional science from Texas A&M University.

Marsh earned his doctorate in urban education from New York University and joined 鲍颁贵鈥檚 College of Community Innovation and Education in 2019.

Qu arrived at 麻豆原创 in 1990 after earning a doctorate in electrical engineering from the Georgia Institute of Technology. Currently the Thomas J. Riordan and Herbert C. Towle Chair of 鲍颁贵鈥檚 , he is also the founding director of both the RISES, a university research center on energy systems, and the multi-institutional (FEEDER).

Wang earned his doctorate in computer science from Stony Brook University in 2006 and joined the 麻豆原创 in 2015.

鲍颁贵鈥檚 (SMST) is already a national leader in modeling and simulation research and education. The Department of Defense employs many of our doctoral graduates as do a range of commercial companies. Now, thanks to a Department of Education $1 million grant, 麻豆原创 will strengthen its existing graduate program, create a new undergraduate modeling and simulation curriculum and launch outreach programs for high schools, all to create a pipeline of talent that will help lead the nation in this exploding area of innovation.

鈥淚t is essential to build a future workforce with the critical skills and competencies in modeling and simulation so that we retain our competitiveness in national security and space,鈥� says Grace Bochenek, the school鈥檚 director and a co-investigator on the grant. 鈥淭he new skills are going to be necessary across many industries from security and space to education and healthcare.鈥�

Congress declared modeling and simulation a National Critical Technology as early as 2007. It has only become more important since then as the technology has advanced. At 麻豆原创, modeling and simulation research has helped train firefighters, co-pilots, fighter pilots, law enforcement, teachers, clinicians and military medics, among others. There鈥檚 also ongoing research using simulation that focuses on teams that will travel together on long missions to other planets and asteroids.

Even some of the most popular video games kids are playing are simulations 鈥擣ortnite, Halo, etc. 聽One of the hottest holiday toys of 2021 was the Oculus, a virtual reality home system that transports users into a simulated world.

鈥淲e can鈥檛 lose sight of the human element in the design and use of intelligent machines for training and education,鈥� says SMST Professor Roger Azevedo, the lead investigator on the grant. He specializes in intelligent system design 鈥� the intersection of intelligent machines and how humans use them.

Part of Azevedo鈥檚 work will focus on ensuring the new courses and curriculum developed accounts for the human element. The new courses and curriculum will take into consideration the role of cognitive, metacognitive, affective, and motivational self-regulatory processes during learning with advanced learning technologies, which is Azevedo鈥檚 area of expertise. He focuses on understanding the complex interactions between humans and intelligent learning systems by using interdisciplinary methods to measure cognitive, metacognitive, emotional, motivational, and social processes and their impact on learning, reasoning, performance, and transfer. Even more critical is that students learn how to take on complex challenges by using critical thinking/problem solving skills to solve societal challenges using innovative and transformative new immersive technologies and platforms, such as Metaverse, as research, learning, training, and assessment tools.

鈥淭his is exciting work, and the future is full of possibility because simulation and modeling has so many potential applications to help people and our society as a whole,鈥� Azevedo says. 鈥淲e can鈥檛 wait to get started.鈥�

Azevedo also has affiliations with 鲍颁贵鈥檚 departments of computer science and internal medicine. He co-leads 鲍颁贵鈥檚 Learning Sciences cluster, which develops new technologies to improve learning outcomes and human performance, exploring how we interact with and learn using machines. He received his doctorate in educational psychology from McGill University and completed postdoctoral training in cognitive psychology at Carnegie Mellon University. He joined 麻豆原创 in 2018 and in 2021 he was named among the top 2% of researchers in his field by the journal PLOS Biology.

The award comes during SMST鈥檚 40^th anniversary year, which has seen modeling and simulation go from small scale projects to being used in practically every field.

Other grant team members are:

• Azevedo, professor in the SMST
• 聽Bochenek, engineering professor and SMST director
• Charles Hughes, professor in computer science and interim graduate program director in the SMST
• Mary Jean Amon, assistant professor in the SMST
• Bruce Caulkins, research associate professor and Director for the Modeling and Simulation of Behavioral Cybersecurity Program
• Pamela Douglas, assistant professor in the SMST
• Joseph Kider, assistant professor in SMST
• Yao Li, assistant professor in SMST
• Sean Mondesire, assistant research professor in SMST

However, not seeing a doctor face-to-face brings its own challenges, such as an increased likelihood of missing a symptom of an illness which can lead to a misdiagnosis, or finding ways to perform tests, such as a blood pressure check, remotely.

That鈥檚 why 麻豆原创 researchers are working on a new U.S. National Science Foundation-funded project to improve patient outcomes in telehealth medicine by using artificial intelligence to improve healthcare training and diagnostic reasoning, so signs and symptoms are not missed during remote doctor visits.

Artificial intelligence could help, for example, doctors remember to check for signs that might be hard to see in a telehealth setting, such as a way a person walks or holds themselves.

For the study, the researchers will look at how to best implement AI and new technologies into telehealth by observing doctor and patient communication in telehealth settings. This includes tracking physicians鈥� and patients鈥� biophysical responses such as eye movement, heart rate, and verbal and nonverbal communication, as well as recording the accuracy of physician diagnoses and any disruptions in the diagnostic reasoning process.

The researchers will also work with physicians, psychologists, engineers, and industry leaders in artificial intelligence to make recommendations on what is possible in telehealth and what could be on the horizon, such as ways to remotely perform tests, such as blood pressure checks and more using AI-based immersive virtual environments.

The ultimate goal is to use evidence collected from the project to provide recommendations for improving diagnostic reasoning in telehealth and offer ways immersive virtual technologies could improve the process.

鈥淎s technology advances in healthcare, it can facilitate ease of use, reduced travel time and more,鈥� says Roger Azevedo, the project鈥檚 principal investigator and a professor in 鲍颁贵鈥檚 School of Modeling Simulation and Training. 鈥淏ut there鈥檚 also new problems that arise, including the potential for medical errors.鈥�

鈥淲e want to use AI to enhance the patient experience, so they get the care they need, and improve the doctor鈥檚 experience by facilitating diagnostic reasoning,鈥� he says.

The project鈥檚 co-principal investigators are Varadraj Gurupur, an associate professor in 鲍颁贵鈥檚 School of Global Health Management and Informatics; Mark Neider, a professor in and the associate chair of 鲍颁贵鈥檚 Department of Psychology; Mindy Shoss, an associate professor in 鲍颁贵鈥檚 Department of Psychology; and Dario Torre, a professor of medicine and director of Programs Assessment in 鲍颁贵鈥檚 College of Medicine.

The project is scheduled to begin in January 2022.

Azevedo received his doctorate in educational psychology from McGill University and his postdoctoral training in cognitive psychology at Carnegie Mellon University. He received his master鈥檚 in educational technology and bachelor鈥檚 in psychology from Concordia University. Azevedo is the co-lead of 鲍颁贵鈥檚聽Learning Sciences Cluster聽and the director of the Laboratory for the Study of Metacognition and Advanced Learning Technologies. He joined 麻豆原创 in 2018.

A 麻豆原创 researcher has developed a computer-based, artificial intelligence tutoring tool 鈥� MetaTutor 鈥� that monitors students鈥� learning activities, facial expressions, eye movements, and interactions with avatars, and adapts its instruction delivery to help students learn more effectively.

The tool is featured in the U.S. Department of Education鈥檚 What Works Clearinghouse report .

鈥淗umans struggle and face serious challenges when learning, reasoning and problem solving,鈥� says Roger Azevedo, a professor in 鲍颁贵鈥檚 College of Community Innovation and Education who developed the tool. 鈥淪o, we as psychologists are finding ways of understanding what those challenges or limitations are so we can help people overcome them.鈥�

MetaTutor works by placing students inside an AI-supported learning environment they access through their computer. As they navigate the content they are studying, the tool monitors the information they are accessing and for how long. If students start going down the wrong track, the computer鈥檚 AI will recognize this and will begin to help them readjust.

鈥淔or example, what if the student selects content that is part of the topic but isn鈥檛 relevant to the current learning goal?鈥� Azevedo says. 鈥淚f a student persists with that content, then after a certain amount of time, one of the tool鈥檚 four avatars, Mary the Monitor, pops up on the screen.鈥�

鈥淢ary starts a dialogue,鈥� Azevedo says. 鈥淪he says, 鈥楬ey, do you think this content is relevant to your current learning goal?鈥� If the student says 鈥榶es,鈥� then they have to explain to Mary why it鈥檚 relevant. Depending on their response, Mary provides individualized instructional techniques and feedback.鈥�

These prompts help students stay focused and augment their ability to discern the material most relevant to their planned and current learning goals. This helps improve their metacognition, or ability to be aware of what they are learning.

Azevedo and his interdisciplinary research team are focused on improving student learning outcomes, which is why they are also continuously collecting data about what people are doing and what is happening to them during the learning process.

This includes tracking their eye movements across the screen, monitoring their facial expressions of emotions and interactions and dialogue with the four avatars. The team also monitors the physiological responses of each participant during complex learning.

These data about how students examine and react to content can then be entered back into the system to improve the tool鈥檚 educational effectiveness.

For example, the data can predict and select what material is more likely to be associated with students鈥� current learning goals or offer a better way to examine and learn the material based on how students used their eyes to scan multimedia instructional materials.

In the future, the data being collected will allow the AI-based learning and training system to provide real-time, individualized feedback and support to meet each student鈥檚 learning needs, Azevedo says.

The tool is currently designed to teach college students about human body systems, but knowledge gleaned from researching it as a learning tool could be applied to educational material for other fields as well. Research has focused on college students but could eventually include testing the system with high school and middle school students as well as medical professionals.

Work on MetaTutor began in 2010, and the research has been supported with National Science Foundation grants through the years that total $4 million, as well as funding from the Social Sciences and Humanities Research Council of Canada.

Azevedo鈥檚 research has shown that 73 to 86 percent of people who use the AI-based version of MetaTutor outperform people who use the non-AI based version that does not adapt to the user.

A version of MetaTutor is currently being used in Spain to teach college students with learning disabilities, and Azevedo says there are plans to expand its reach, including designing a version for high school and middle school students to fit their curriculum needs.

Azevedo received his doctorate in educational psychology from McGill University and his postdoctoral training in cognitive psychology at Carnegie Mellon University. He received his master鈥檚 in educational technology and bachelor鈥檚 in psychology from Concordia University. Azevedo is the lead scientist in 鲍颁贵鈥檚 Learning Sciences Cluster and has joint appointments in 鲍颁贵鈥檚 . He joined 麻豆原创 in 2018.