Category: Graduate

ACSHF Forum: Kyle Wilson, Seeing Machines

The Applied Cognitive Science and Human Factors (ACSHF) Forum will be held from 2-3 p.m. Monday (Feb 21) virtually via Zoom. Our speaker is Kyle Wilson, Ph.D. Kyle is a Human Factors Senior Scientist and Team Lead at the company Seeing Machines in Canberra, Australia.

Title: Driver behaviors and safety risks surrounding new in-cabin technology: Three case studies from human factors research in automotive and rail environments. 
Brief Description: Dr. Wilson will discuss three human factors studies he was involved with in the transport space – each with a focus on how people experience new technology and related implications on safety and performance. He’ll cover:

  • One of the world’s first on-road automated vehicle studies with a primary focus on driver behaviour
  • Field research involving 10+ hour night shifts in the cramped cabin of a coal train
  • An on-road study evaluating safety and usability of an app that tells drivers when the traffic light is going to change

For each study he’ll discuss the goals, approach taken, findings and outcomes. Throughout, he also intends to highlight challenges and lessons learned, in what was sometimes ‘messy’ applied research.

ACSHF Forum: Grad Student Presentations

The Applied Cognitive Science and Human Factors (ACSHF) Forum will be held from 2-3 p.m. Monday (Feb 7) virtually via Zoom. There will be two speakers: Anne Linja and Lauren Monroe, both ACSHF graduate students.

Linja will present “Examining Explicit Rule Learning in Cognitive Tutorials: Training learners to predict machine classification“.

Artificial Intelligence (AI)/Machine Learning (ML) systems are becoming more commonplace and relied upon in our daily lives. Decisions made by AI/ML systems guide our lives. For example, these systems might decide whether we get a loan, what our medical diagnoses are, and the full-self driving car we’re sharing the road with even makes decisions. However, we may not be able to predict, or even know whether, or when these systems might make a mistake.

Many Explainable AI (XAI) approaches have developed algorithms to give users a glimpse of the logic a system uses to come up with its output. However, increasing the transparency alone may not help users to predict the system’s decisions even though users are aware of the underlying mechanisms.

One possible approach is Cognitive Tutorials for AI (CTAI; Mueller, Tan, Linja et al., 2021), which is an experiential method used to teach conditions under which the AI/ML system will succeed or fail. One specific CTAI technique that was proposed involved teaching simple rules that could be used to predict performance; this was referred to as Rule Learning. This technique aims to identify rules that can help the user learn when the AI/ML system succeeds, fails, the system’s boundary conditions, and what types of differences change the output of the AI system. To evaluate this method, I will report on a series of experiments in which we compared different rule learning approaches to find the most effective way to train users on these AI/ML systems. Using the MNIST data set, this includes showing positive and negative examples in comparison to providing explicit descriptions of rules that can be used to predict the system’s output. Results suggest that although examples help people learn the rules (especially examples of errors), tutorials that provided explicit rule learning and provided direct example-based practice with feedback led people to best predict correct and incorrect classifications of an AI/ML system. I will discuss approaches to developing these tutorials for image classifiers and autonomous driving systems.

Monroe will present “Don’t throw a tempo tantrum: the effects of varying music tempo on vigilance performance and affective state“.

Vigilance tasks, or sustained attention tasks, involve an operator monitoring an environment for infrequent and random critical signals buried among more frequent neutral signals for an extended period of time. In addition to an observable decline in task engagement, task performance, and arousal over time, these tasks are also related to an increased subjective workload. Previously, music has been shown to have a positive impact on operator engagement and reaction times during sustained attention. The present study (N=50) examined the effects of music played at different tempos on a selection of performance metrics and subjective measures of mood, engagement, and workload. Results indicated that varying the tempo of music did not have an effect on the decline in the correct detection of critical signals. There also was not an observable impact on measures of engagement and stress but the fast tempo condition had a slightly significant positive impact on worry from pre to post task subjective measures. 

ACSHF Forum: Grad Student Presentations

The Applied Cognitive Science and Human Factors (ACSHF) Forum will be held from 2-3 p.m. Monday (Jan. 24) virtually via Zoom.

There will be two speakers: Pomm Khaewratana and Alex Watral, both ACSHF graduate students.

Pomm Khaewratana:
Title: Learning with word game: Effects of crossword and elaboration on learning scientific vocabulary
Abstract: Crosswords have been used in a variety of science classrooms as a supplementary tool to help students learn technical vocabulary and to improve scientific thinking. However, the majority of crossword studies showed positive findings only for the former and almost none for the latter. We currently lack evidence for the usefulness of crossword in learning anything beyond the vocabulary and their definition or associated context provided as crossword hints. In this presentation, I will describe a continuation of the series of my experiments that evaluate the effect of crossword with an add-on elaboration task. The task supposedly enhances learning and retention of learned vocabulary by having learners generate sentences from technical words that depict an application-based use of the words. Fifty undergraduate students were recruited as participants in the aforementioned within-subject-design experiment. Results indicated significant improvement on memory level but not on the higher level of application.

Alex Watral:
Title: Online Assessment of Motor Learning in Younger and Older Adults
Abstract: Motor learning is a specific type of learning that occurs through repetition of a movement following the law of practice wherein rapid improvements in performance occur initially, followed by more gradual improvements as practice continues. In this sense, we can think of motor skill learning as unfolding in two phases that may rely on different cognitive mechanisms. Evidence has shown that motor learning abilities change with healthy aging such that older adults are slower to learn novel motor tasks initially while ultimately they are still able to learn to the same degree as young adults. One of the gold-standard approaches to studying motor learning is called the visuomotor rotation (VMR) paradigm. Motor learning tasks like the VMR paradigm are typically implemented in our lab using a robotic device called a Kinarm. As our understanding of motor learning evolves, we need to focus on options for testing that are more accessible than laboratory limited approaches. We have created a web-based application to assess visuomotor adaptation in a remote setting. No application downloads are required on the part of the participant. The only requirement is for them to have a computer (laptop or desktop) and an internet connection. This makes the application far more accessible than current laboratory and portable platforms. The overarching goal of this project is to validate the web-based application in younger adults as well as healthy older adults. We are also interested in verifying that previously identified correlations between the early and late stages of motor learning and implicit memory, spatial working memory, and visual-spatial abilities can be observed with this online app. Healthy younger adults (n=21) and healthy older adults (n=17) participated in this study. Each participant met with a researcher via Zoom and shared their screen while performing the VMR task and cognitive battery so that the researcher could troubleshoot as needed. Preliminary results suggest that the online application produced results similar to the laboratory task. Further analyses will be conducted to determine if there were significant differences between the two collection methods (app vs laboratory) and to see how cognitive constructs correlate with performance on the VMR app.

KCP Future Faculty Fellow – Brittany Nelson

It started when I took a critical thinking class where I learned how irrational many of my, and most people’s decisions, are. Many hold a misconception that we are rational creatures that we weigh pros and cons of each choice and choose the option that has the most utility. I was immediately fascinated that this is not the case; decisions are influenced by biases, environment, emotions, fatigue, and more. As an undergraduate, I conducted a blind experiment that measured the impact of reading a free will philosophy pamphlet on behaviors such as stealing candy and donating money. (Those who read the pamphlet that suggests we don’t have free will are more likely to steal candy and not donate money!) After learning how little we make rational decisions —without even being aware— I understood the potential the field of cognitive science has for helping people.

My interest in teaching allowed me to take many powerful lessons from my Masters’ degree in Applied Cognitive Science and share them with students when I was a visiting professor at Finlandia University. This position opened my eyes to how instructors can empower students through teaching. From this experience, I gained a passion for and concrete skills in how to be a professor.

Under the advisement of Dr. Erich Petushek, my current Ph.D. research at MTU involves identifying, measuring, and improving key factors that impact healthy lifestyle decisions. Lifestyle behaviors cause 60% of premature deaths and lead to 10 years longer life expectancy free of major chronic diseases. I hope that the long-term impact of this research is saved lives and a significant improvement in quality of life.

It is my goal to become a professor in psychology. As a professor, I can empower students to reach their potential and lead a lab devoted to helping people make good decisions. I am so grateful and honored to receive the King-Chávez-Parks Future Faculty Fellowship. I know it will help pave my way toward my goal.

ACSHF Forum: Monday, January 10

The first Spring 2022 Applied Cognitive Science and Human Factors (ACSHF) Forum will be held from 2-3 p.m. on Monday (January 10) in the Harold Meese Center (Meese), Room 109, and virtually via Zoom. There will be two speakers: Lisa Casper and Betsy Lehman, both ACSHF graduate students.

Lisa Casper’s Abstract:
Perspective shifting in design: Evidence of innovation in makerspaces

One of the critical 21st-century skills students need is to be able to think differently.  Makerspaces and design thinking have become part of university innovation education strategies across the world to help students develop these skills.  But how do we support innovation in makerspaces?   At Michigan Tech, we use design thinking in conjunction with the makerspace.  Most research and evidence of innovation in makerspaces is anecdotal.  My research is taking a cognitive engineering approach to supporting and developing innovation in makerspaces.  In this talk, I will review research on makerspaces and innovation theories with a backdrop of the design thinking process.  Using cognitive task analysis, we interviewed expert makers from Europe and the United and conducted a thematic analysis of the data.  Themes from these interviews suggest focus areas for innovations in makerspaces that will support future experiments. 

Betsy Lehman’s Abstract:
Taking It Easy: Ease of Generating Alternative Explanations As A Mediator Of Counterfactual Reasoning In Ambiguous Social Judgments

It is important to know how people make sense of situations and question their theories. Questioning one’s perspective may be critical in many situations, such as taking action against climate change, improving diversity and equity at work, or even promoting vaccine adoption.  According to sensemaking theory (Klein et al., 2007), people must first question their theory of a situation before they can shift their perspective. However, research on how people question their frame is limited.  Using counterfactual theory (Roese & Olson, 1995), we examined factors and strategies affecting this part of the sensemaking process in two studies.  In Study 1, 80 participants generated explanations and predicted outcomes in five ambiguous social  situations. Data were analyzed using path analysis to compare fit between a base model (i.e., ease, malleable factors, and missing information all predicting outcome likelihood judgments) and a model based on counterfactual generation theory (Roese & Olson, 1995). Results indicated that the latter model fit was better, indicating that ease of generation may be a critical mediator in the sensemaking process. Based on this result, Study 2 was designed to experimentally test this effect by manipulating ease of generation and a focusing strategy. This work contributes to research focused on understanding of the mechanisms of perspective shifts to support applications for system design and training, such as programs to reduce implicit bias.  

Q&A with Dr. Natasha Hardy

In the week leading up to Mid-year Commencement 2021, we got to chat with ACSHF PhD recipient Natasha Hardy and hear about her journey from starting the program in Spring 2011 to accepting her current position with a multi-billion dollar, publicly-traded company. Read along to learn more.

Hello Dr. Hardy – First and foremost, congratulations on successfully completing your dissertation and earning your PhD degree in Applied Cognitive Science and Human Factors (ACSHF) at Michigan Technological University. Before we get into specifics, can you briefly walk us through how you got to where you are today?

I’ve always been very driven to grow and improve myself and I’ve pursued education with an almost single-minded determination since graduating from high school. Looking back, I can’t believe I made it through but my first mentor – Dr. Wayne Wright – always said, “I didn’t come this far to turn back now” and I took that philosophy very much to heart.

I started in the ACSHF program in Spring 2011 and began working and going to school full-time in 2014. In that time, I’ve had 7 jobs with 5 employers and I’ve grown from an entry-level analyst with a small non-profit to a senior level researcher with a multi-billion dollar, publicly-traded company.


Q: When did you first realize this was the type of career you wanted to pursue?

A: My catalyst for coming to Michigan Tech was working on my capstone thesis for my Master’s degree: I was so inspired by researching adult learning theory I really wanted to find a program where I could better understand the psychology of learning. I was fortunate to meet Dr. Cokely and begin my journey at Michigan Tech.

Q: What excites you about your work and/or the field of behavioral research?

A: Understanding the way people think is so fundamental to living – it helps us understand the choices people make, the things they say and do – and I just find it so incredibly interesting and inspiring. Whether you are sitting down with one person and hearing their personal story and diving into key decisions in their life or looking at a nice big fat excel file of data and seeing those decisions in aggregate numbers, there’s just no end to what we can learn and interpolate about people and how they do things. I was inspired to work in UX because every day we encounter things that are unnecessarily challenging due to poor or sub-optimal design.

Q: Looking back, can you tell us a bit about the challenges and lessons you’ve learned along the way?

A: There are too many lessons to count, honestly. I have been heart-broken and sobbing, scared, angry, and frustrated beyond reason at some point in my academic journey. Everyone’s path is different, but I think the most important thing I had to learn was to take care of myself and my mental health. There was a point where the anxiety and pressure I felt ate away at me until I was physically ill. I’ve had to learn not to bottle up my thoughts and feelings and instead rely on supportive relationships to help me through hard times. Working with Kelly [Dr. Steelman, advisor and CLS chair] was one of those supportive relationships that carried me through some of my most challenging times.

Q: What piece of advice would you like to give to a first-year psychology / human factors student?

A: Statistics is the most important class you will take, embrace it! I think a lot of people are inspired to come to psychology because they want to have a positive impact on people’s lives. In order to know if you are having an impact, you need to be able to measure, compare, and predict. I use statistics constantly in my work and have had to learn many new statistical techniques. Even though I find it very difficult to learn and understand statistics, it’s also incredibly rewarding.

Q: What do you see for the future of human behavior and design / human factors?

A: This field is going to continue to grow. In industry there is both a top-down and bottom-up push to improve user experience. I think there are two paths you can take. One is creating experiences that inspire people to use them and the other is creating experiences that reduce failure. So, for example, my work with Rocket Mortgage focuses on understanding how people think about and approach home ownership – from the time they start looking at houses through purchasing and into maintaining. This information drives how we design products and tools that help people achieve that goal in the most frictionless way possible. In this case, a good UX should be unnoticeable at worst and delightful at best. On the other hand, my husband built and coded a process to reduce pacemaker failure by improving anchoring coils to give more torsional stiffness but not reduce flexibility, so the anchors wouldn’t break inside the human body. In this case, product failure can be deadly. Which one of these inspires you?

Q: How do you practice a healthy work-life balance?

A: First, I want to acknowledge that being able to say, ‘No’ to work is a privilege. Some people absolutely do not have that luxury. I also know that as a mid-career professional I can probably be more pushy about what I want from an employer than someone who is fresh from school. I stop working at five to prepare dinner for my family and I also always take my vacation time that I earn at work. Only you can decide what is good and appropriate for you. And you should do that proactively so that you know what to look for in an employer.

Q: What is next for you on your life journey?

A: I have so many projects I want to work on! I’m planning to get a certificate in plant-based nutrition from Cornell next – I’m so inspired by the health outcomes associated with plant-based nutrition I just want to learn more. I’m also moving to a new job at Indeed as a UX researcher for their data platform.

Q: Is there anything else you would like to share with us?

A: Navigating people is central to successful work in UX. It’s not about you, it’s about other people and how they think, feel, and act. As a researcher, it’s important to seek to understand the mindset of others by asking questions and challenging your own preconceived notions.

Congratulations to all Fall 2021 graduates and best wishes for your future! Please stay in touch.

Isaac Flint (PhD, CLS) receives HRI Fellowship

The Health Research Institute (HRI) at Michigan Tech is pleased to award fellowships to three individuals for the spring 2022 semester. Congratulations to all recipients!

HRI Spring Fellowship awardees are:

  • Shobhit Chaturvedi, Chemistry
  • Manas Warke, Biological Sciences
  • Isaac FlintCognitive and Learning Sciences

The mission of the Health Research Institute is to establish and maintain a thriving environment that promotes translational, interdisciplinary, and increasingly convergent health-related research and inspires education and outreach activities.

ACSHF Forum: Monday, December 6

The Department of Cognitive and Learning Sciences will host speaker Joel Suss (Assistant Professor of Psychology, Wichita State University) at the next Applied Cognitive Science and Human Factors forum. The presentation, “Trials and tribulations of doing research with police agencies”, will be from 2:00 to 3:00 p.m. Monday (December 6) via Zoom only. Dr. Suss will present stories and insights of his research from a National Institute of Justice grant about police decision making.

Abstract: Come and hear research tales from a National Institute of Justice grant about police decision making. It’s been a real roller-coaster ride. Do you want stories about ethical dilemmas? I have those. Do you want stories of critical equipment failures? I have those too. This study had a training component—so come and hear about the level of compliance we achieved. I will demonstrate the experimental task (i.e., interacting with a video scenario) and then take you through the stimulated recall procedure that I used to probe participants’ underlying cognition (yielding qualitative data). There are no results yet, but plenty of stories about the challenges that the team encountered during the research.

ACSHF Forum, 2pm Monday Nov. 08: Anne Inger Mørtvedt and Lamia Alam (Meese 109 and via Zoom)

The Department of Cognitive and Learning Sciences will host two speakers at the next Applied Cognitive Science and Human Factors forum. Anne Inger Mørtvedt (PhD Student ACSHF) will present, “Information usability evaluation to increase implementation of injury prevention training in sports”, and Lamia Alam (PhD Student ACSHF) will present “Assessing cognitive empathy elements within the context of diagnostic AI chatbots”. The presentations will be from 2:00 to 3:00 p.m. Monday (November 8) in Meese 109 and via Zoom. Abstracts for the two presentations are as follows:

Anne Inger Mørtvedt

“Information usability evaluation to increase implementation of injury prevention training in sports”

Abstract: Several sports related injuries can be prevented through implementation of evidence-based injury prevention training (IPT). However, actual use remains very low – and lowest in rural and resource scarce areas. Coaches’ comprehension of the injury and prevention strategies has been identified as the main modifiable barrier for implementation of IPT. However, there is a lack of accessible and usable information to improve representative understanding or comprehension. We recently developed a brief animated video to fill this gap but formal usability assessment of this informational video has yet to be conducted. In this presentation, we aim to present our initial usability data and tentative next steps for developing a more usable educational animation with the ultimate goal of increasing the likelihood of IPT implementation in the target population.

Lamia Alam

“Assessing cognitive empathy elements within the context of diagnostic AI chatbots”  

Abstract: Empathy is an important element for any social relationship and it is also very important in patient-physician communication. There are many aspects and dimensions of empathy applicable in such communication. As Artificial Intelligence is being heavily deployed in healthcare, it is critical that there is a  shared understanding between patients and the AI systems if patients are directly interacting with those systems. But many of the emotional aspects of empathy may not be achievable by AI systems at present and cognitive empathy is the one that can genuinely be implemented through artificial intelligence in healthcare. We need a better understanding of the elements of cognitive empathy and how these elements can be utilized effectively. In this research, the goal was to investigate whether empathy elements actually make a difference to improve user perception of AI empathy.  We developed a scale “AI Cognitive Empathy Scale (AICES)” for that purpose and conducted a study where the experimental condition had both emotional and cognitive empathy elements together. The AICES scale demonstrated reasonable consistency, reliability, and validity, and overall, empathy elements improve the perceived empathy concern within diagnostic AI chatbots.

Guest Blog: Virtually Possible (How the Pandemic Forced Us to Rethink Data Collection)

The pandemic’s impacts on our campus research ecosystem are many and varied. In his guest blog, Kevin Trewartha shares how the halt in face-to-face interactions compelled his team to find alternatives with applications far beyond current challenges.

In the Aging, Cognition, and Action Lab, we investigate the relationship between age-related changes in cognitive and motor function and the neurophysiological basis for those changes. Like so many others who study human behavior and physiology, our research relies on volunteers to perform tasks in the laboratory while we record their performance.

The pandemic caused a sudden and unexpected end to all face-to-face data collection, and an astounding pause in the research methods I have relied on for almost two decades. Yet, as is often opined, great challenges bring great opportunities.

Challenge: Face-to-Face Data Collection Paused

Our understanding of human cognitive, motor, social, and physiological function is dependent on our ability to gather data from participants who volunteer their time in the spirit of scientific inquiry. For many scholars, collecting data means bringing participants into the laboratory to perform a variety of tasks in close contact with the experimenters.

In my lab, we study age-related changes in neurophysiological, cognitive, and motor function by testing individuals 65 and older. Collecting data with human participants means working closely with the Institutional Review Board (IRB) to ensure that our protocols do not present any significant physical or psychological risk to our participants. As researchers, we have a moral and ethical responsibility to ensure their safety. Any risks to the participant must be minimized and reasonable in relation to the expected benefits and importance of the knowledge to be obtained by the research.

The COVID-19 pandemic suddenly elevated the risk of recruiting participants for face-to-face data collection. Prior to widespread availability of a vaccine, the risk of developing serious illness after contracting the virus meant that it was no longer safe to bring participants into the lab. Data collection initiatives like ours were suspended in labs all over the world as we learned more about the virus.

As the weeks passed, a clear picture emerged about the relative risk of severe illness and death due to COVID-19. Older individuals and those with underlying medical conditions were at disproportionate risk for adverse outcomes. With careful planning and review, the IRB worked closely with researchers to mitigate the risks involved and allow human subjects research to eventually resume. However, work with individuals over 65 years old was deemed too risky for the participant.

On a personal level, too, I was unwilling to run the risk of a participant getting severely sick or dying just because they chose to volunteer for research in my lab. Although we expected the shutdown to be temporary, it ended up being more than 15 months before we could prepare to resume data collection with our most vulnerable participant populations.

One of our current National Institutes of Health-funded research projects involves working with older adults with mild cognitive impairment (MCI) or early stages of Alzheimer’s disease. We are investigating whether subtle changes in motor learning behavior could be a sign of early cognitive impairment. The very same week in March 2020 that Michigan Tech and the State of Michigan recognized the need to change our day-to-day operations, we were collecting data with this high-risk population. Immediately, we recognized the need to pause our data collection — an incredibly frustrating albeit necessary decision, given that we were about halfway through our three-year project at the time.

Having to halt most progress on our funded project for almost as much time as we had been working on it provided an opportunity to refocus on one of the biggest challenges we face in behavioral and physiology labs: How do we collect data from human participants if we cannot meet with them face-to-face?

In fact, this was a problem we recognized. There were already well-known, existing disparities between the types of individuals who participate in research and those who do not. Much of the human performance literature is based on data collected from more urban centers, from people who have the physical and financial means to travel to our labs. Fewer studies tend to recruit rural populations, especially those living in more isolated communities and those who have physical and financial barriers to traveling. We once wrote a grant that included a request for funds to develop and test a mobile (tablet-based) platform for motor learning and cognitive testing. Unfortunately, it was not funded, and the idea was set aside.

Solution: Initiate Remote Data Collection

Although the pandemic levied a devastating blow to our research program, it also provided an important opportunity for us to revisit the mobile testing idea and develop a method to collect data remotely. The development of such technology was beyond my expertise, so we reached out to a colleague in the College of Computing: Robert Pastel, who agreed to collaborate with us on this new project.

At the time, travel was ill advised, so we had some time to work through the development of a web-based app for administering the same motor learning experiments we typically run on our sophisticated equipment in the lab. One of my graduate students was then able to shift the focus of her master’s thesis to testing the validity of this new app with healthy younger and older adults by administering the experiment remotely over Zoom.

There were several added challenges to shifting this focus that we did not anticipate at the time. We grow comfortable with our standard methodologies, and shifting to something completely different takes time. Anticipating hiccups along the way is difficult when you enter personally uncharted waters.

The pandemic imposed great challenges outside of work as well. Sudden losses of child care; sharing remote workspaces with family or roommates; trying to help care for family members who live elsewhere; figuring out how to stay physically active; and managing stress, isolation, fear and ever-shifting public health guidance were struggles we all shared. Trying to manage those challenges while trying to launch a new line of research was daunting, especially while working to stay as productive as we could with our existing projects. Despite all those challenges, we made steady progress and expect to finish our initial remote data collection project during the fall 2021 semester.

We are excited about this new line of research and fully expect to continue exploring remote data collection after the pandemic is over. This new approach is a silver lining to a year fraught with barriers to our research productivity. We also consider ourselves fortunate that it was feasible to shift some of our work to an online platform. Many methods of measuring human behavior and physiology, including some of our own, are simply not possible through remote data collection, at least with existing technology. But as is the case with many aspects of our daily lives, the pandemic taught us to adapt, think outside the box and be resilient.

Additional challenges will arise, even as the spread of SARS-CoV-2 wanes. For human subjects research, it will take time to ramp up data collection initiatives to normal levels. Testing sessions may also be slowed down by the need to practice careful mitigation strategies to further limit the risk of spreading the virus. It also remains unclear what lingering impact the pandemic may have on participant recruitment. Some individuals may be more hesitant to volunteer, especially high-risk populations. Regardless, I am so proud of my students, colleagues, collaborators and clinical consultants for their agility, patience and hard work this past year, and I am confident we will meet any new challenges that arise.

The new directions in our lab’s research program this past year are a testament to the importance of interdisciplinary and multidisciplinary collaborations. Without the expertise and efforts of Pastel, our new line of remote testing research wouldn’t have happened. Our interactions during the development process also taught me a lot about considerations programmers need to make when developing apps like this. Collaborations of this sort really start with an informal conversation among colleagues. We have plenty of work to do in this area in the future, but I am excited for a new and somewhat unexpected direction for my research program.

The resilience and adaptability of human subjects researchers will continue to be put to the test for the foreseeable future. This pandemic is not over. We all look forward to a day when we can resume “normal” life again. That day can happen soon, but it requires that we acknowledge the pandemic for what it is — a worldwide public health crisis that does not care about our politics.

Thanks to scientists who have dedicated their lives to developing health technologies, we have access to several safe and effective vaccines that not only prevent people from getting sick and dying, but will prevent the virus from mutating to a point that it evades our immune system defenses and puts us back to square one. When it comes to vaccination, we need to ignore the media, social media, armchair “researchers” and politicians in favor of seeking advice from our trusted medical professionals. As we collectively band together to end this pandemic, we are coming out the other side with new innovations that will make society better.

About the Author

Kevin Trewartha

Research Interests

  • Cognitive Aging
  • Cognitive Neuroscience
  • Motor Learning
  • Sensorimotor Control
  • Memory
  • Cognitive Control

Researcher Profile

Michigan Technological University is a public research university founded in 1885 in Houghton, Michigan, and is home to more than 7,000 students from 55 countries around the world. Consistently ranked among the best universities in the country for return on investment, the University offers more than 125 undergraduate and graduate degree programs in science and technology, engineering, computing, forestry, business and economics, health professions, humanities, mathematics, social sciences, and the arts. The rural campus is situated just miles from Lake Superior in Michigan’s Upper Peninsula, offering year-round opportunities for outdoor adventure.