Category: Human Factors

The Department of Cognitive and Learning Sciences will host Leanne Jensen, PhD at the next Applied Cognitive Science and Human Factors forum Monday October 2 in Meese 109, from 2:00 p.m. to 3:00 p.m.

Leanne R. Jensen, PhD holds a prominent role in the aerospace industry as a member of The Boeing Company’s Technical Fellowship, focusing on Human Performance Technology and human factors engineering.  Her work has led to several invention awards related to human reliability and productivity, including a patent-pending for a model-based systems engineering approach to advanced product quality planning, solidifying her reputation as an innovative thought leader.  Her expertise in developing and implementing human-centric solutions has enabled organizations to achieve higher levels of safety, productivity, quality, and operational excellence.    

Leanne’s educational journey reflects her dedication to acquiring a diverse skill set that spans technical, instructional, and performance improvement disciplines. She holds an Associate degree in Machine Design (MTU), a Bachelor of Science degree in Mechanical Engineering Technology (MTU), a Master of Science degree in Instructional Design Technology (Walden University), and a PhD in Education, specializing in Training and Performance Improvement (Capella University). This diverse educational foundation has enabled Leanne to approach her work with a holistic perspective, integrating technical and instructional principles to drive performance excellence.

Abstract: 

In an era marked by unprecedented technological advancements, the concept of Human Digital Twins has emerged as a revolutionary paradigm with profound implications for healthcare, industry, and society at large.  Rooted in the field of digital modeling and simulation, Human Digital Twins rely on data acquisition, machine learning, sensor technology, and mathematics to digitally represent an individual’s characteristics and behaviors in a digital form.   From optimizing ergonomics and user experience to fine-tuning manufacturing processes through predictive analytics, these digital counterparts will revolutionize design, prototyping, and testing across industry.  The world of Human Digital Twins promises to expand horizons and inspire innovative thinking for the next generation of engineers, setting the stage for a future where personalized, data-driven solutions redefine our approach to design.  Explore more about the concept of Human Digital Twins are and how they can drive innovation and excellence in product development.

We would like to congratulate some newly graduated PhD and MS students from the ACSHF program as of this summer:

Isaac Flint, PhD
Nishat Alam, MS
Anne Linja, PhD

Well done all!

Titles and abstracts for each can be found below:

Isaac Flint
Title:The Impact of Cognitive Ability and Age on Movement Corrections: An Exploration of the Neurocognitive and Physiological Contributors to Optimal Feedback Control

Abstract: Making successful movement corrections is an important part of navigating dynamic environments where unexpected obstructions can occur. Failure to engage in successful movement corrections can result in injury and, in some cases, death. One theory used to explain people’s ability to make movement corrections is the optimal feedback control theory, which follows the minimal intervention principle. Experiment 1 shows older adults are as likely as young adults to choose hand paths that require the least effort following a visual perturbation; however, they also commit more collisions and have slower movement speeds. Regression analyses show that success rates and movement times on the obstacle avoidance task are related to individuals’ measures of executive control and processing speed. P3b components, often associated with executive control, were elicited following medium and large cursor jumps. These ERP responses were different between the two conditions for young adults; however, they were not different for older adults. Experiment 2 shows young adults’ performance on obstacle avoidance tasks aligned with what would be predicted according to the minimal intervention principle, regardless of if responding to haptic/proprioceptive or visual feedback. The modality of the perturbation did have an impact on performance when the optimal path was ambiguous. The P3bs observed in Experiment 2 were also affected by the difference in the modality of feedback. When these findings are evaluated with the experiment’s other findings showing 1) greater P3b related activity for collision trials than non-collision trials, 2) very little differences between P3bs from trials with inward and outward movement corrections, and 3) EMG indicators of movement correction onset occur before the P3b peak, it suggests that the neural activity observed in this study has more to do with monitoring the movement corrections than path selection. The regression models from Experiment 2 also show the top-down processing of visual feedback is associated with a greater number of cognitive variables; yet some level of executive control is still associated with participants; tendency to make optimal reaching movements following physical perturbations.

Nishat Alam
Title: Types of Questions Teachers Ask to Engage Students in Making Sense of a Student Contribution

Abstract: In the student-centered classroom, a teacher’s interpretation and response to student mathematical contributions plays an important role to shape and direct students’ opportunities for sense-making. This research used a scenario-based survey questionnaire to examine what types
of questions middle and high school mathematics teachers indicate they would ask to engage
students in making sense of a high-leverage student mathematical contribution and their
reasoning about why particular questions are or are not productive. From the results, it could be
concluded that teachers asked more productive questions after seeing a set of possible questions.
Their beliefs about the productivity of the questions related to a variety of factors, including the
specificity of the question, student participation, student ability and whether incorrect solutions
should be discussed. The results could inform future work with teachers to productively use
student thinking in their teaching.

Anne Linja
Title:
EXPLICIT RULE LEARNING : A COGNITIVE TUTORIAL METHOD TO TRAIN
USERS OF ARTIFICIAL INTELLIGENCE/MACHINE LEARNING SYSTEMS

Abstract:
Today’s intelligent software systems, such as Artificial Intelligence/Machine Learning systems, are sophisticated, complicated, sometimes complex systems. In order to effectively interact with these systems, novice users need to have a certain level of understanding. An awareness of a system’s underlying principles, rationale, logic, and goals can enhance the synergistic human-machine interaction. It also benefits the user to know when they can trust the systems’ output, and to discern boundary conditions that might change the output. The purpose of this research is to empirically test the viability of a Cognitive Tutorial approach, called Explicit Rule Learning. Several approaches have been used to train humans in intelligent software systems; one of them is exemplar-based training. Although there has been some success, depending on the structure of the system, there are limitations to exemplars, which oftentimes are post hoc and case-based. Explicit Rule Learning is a global and rule-based training method that incorporates exemplars, but goes beyond specific cases. It provides learners with rich, robust mental models and the ability to transfer the learned skills to novel, previously unencountered situations. Learners are given verbalizable, probabilistic if…then statements, supplemented with exemplars. This is followed up with a series of practice problems, to which learners respond and receive immediate feedback on their correctness. The expectation is that this method will result in a refined representation of the system’s underlying principles, and a richer and more robust mental model that will enable the learner to simulate future states. Preliminary research helped to evaluate and refine Explicit Rule Learning. The final study in this research applied Explicit Rule Learning to a more real-world system, autonomous driving. The mixed-method within-subject study used a more naturalistic environment. Participants were given training material using the Explicit Rule Learning method and were subsequently tested on their ability to predict the autonomous vehicle’s actions. The results indicate that the participants trained with the Explicit Rule Learning method were more proficient at predicting the autonomous vehicle’s actions. These results, together with the results of preceding studies indicate that Explicit Rule Learning is an effective method to accelerate the proficiency of learners of intelligent software systems. Explicit Rule Learning is a low-cost training intervention that can be adapted to many intelligent software systems, including the many types of AI/ML systems in today’s world.

The Department of Cognitive and Learning Sciences will host two speakers at the next Applied Cognitive Science and Human Factors forum: Tauseef Ibne Mamun and Erin Matas, both ACSHF graduate students. Their presentations will be from 2:00 to 3:00 p.m. Monday (April 17) in Meese 109 and via Zoom.

Mamun will present  “The Use of Social Forums to Train Users about Shortcomings of Tesla Full Self-driving (FSD)”

Abstract: In the past decade, consumer adoption of commercial semi-autonomous vehicles has increased, and along with it user concerns about shortcomings of these systems, especially regarding safety. Users often turn to social media forums to discuss these shortcomings, find workarounds, and confirm their experience is common. We suggest that these forums may provide some of the best training for users to understand the limitations of AI, as they are not controlled by the vendor who has a vested interest in hiding the limitations of their systems. In two laboratory experiments, we examined how information from Tesla FSD forums impact participants’ ability to detect and predict hazardous driving situations in simulated scenarios. Drivers who received the training were better at anticipating and recognizing dangerous driving conditions, suggesting that exposure to user-generated explanations of the shortcomings of the system may in fact improve safety and acceptance of the systems.

Matas will present “Practicum Project: Leadership Program Evaluation Using Cognitive Task Analysis (CTA)”

Abstract: The Association of Research Libraries (ARL) Leadership Fellows Program is designed to prepare emerging library leaders for senior-level positions in research libraries and other types of organizations. Erin Matas is a 2021-2022 cohort Fellow. For her ACSHF practicum project, Erin used Cognitive Task Analysis (CTA) methods to identify areas where improvement is needed for the leadership program’s training and development. The Leadership Fellows program has a year-long curriculum that targets different learning topics each month. Using human factors methods, Erin analyzed challenges in the Fellows’ current jobs and compared them with the topics covered in the program to determine if there are any training gaps. Erin interviewed 7 Fellows using CTA to identify cognitively complex aspects of their work and systematically analyzed the data. She developed task diagrams from each interview, identified themes, and presents results in a concept map. To round out the project, Erin will deliver the concept map and an executive summary report of her findings and recommendations regarding training to the Director of the ARL Leadership Fellows Program. The Program Director will include the recommendations in the final assessment of the program for the year to the ARL executive leadership team. Did CTA techniques identify overlooked training topics, pinpoint where more support is needed, and/or reinforce the strength of the current curriculum? Find out on April 17th at the ACSHF Forum!

The Department of Cognitive and Learning Sciences will host two speakers at the next Applied Cognitive Science and Human Factors forum: Katrina Carlson and Brittany Nelson, both ACSHF graduate students. Their presentations will be from 2:00 to 3:00 p.m. Monday (April 3) in Meese 109 and via Zoom.

Carlson will present ” Engineering Self-efficacy and Spatial Skills: A two-part study”

Abstract:

The research team behind previous work on the increased academic and retention outcomes of students who have taken a Spatial Visualization Intervention course at MTU postulates that affective changes within the students as a result of the course may be responsible for downstream academic success. One possible explanation may be related to the students’ confidence in their ability (self-efficacy) to gain the skills needed to become an engineer.  Extensive research has been conducted on self-efficacy, and academic self-efficacy has been shown to be significantly correlated with academic performance.

The first part of this study examines the general and engineering self-efficacy of students at the beginning and end of the Spatial Skills Intervention course, Spring 2023 (N= 9), and compares these to students at the beginning and end of a first year engineering class. One hundred sixty-eight students completed general and engineering self-efficacy surveys. The General Self-Efficacy Scale was used; this tool was developed from longer scales and was found to be a reliable and valid measure of overall self-efficacy and not a specific skill area.  The Assessment of Engineering Self-Efficacy V3.0 for undergraduate engineering students  was also used. Items on this measure are related to predictions of future academic ability and their sense of belonging in engineering and STEM classes.

The second part of this study will examine students’ visual and spatial perception, memory, and skills through a battery of tasks using the PEBL Platform.  Previous research has examined the development of spatial skills and the resulting increase in problem-solving skills across domains that require spatial reasoning.  Research has also been conducted to examine whether spatial visualization, the ability to mentally maneuver 2D and 3D objects, is a single ability or is composed of more than one skill or ability. Participants (N=80) will include both Intro to Psychology students, who will also take the Purdue Spatial Visualization Test with Rotations (PSVT:R) as a part of this battery, and first year engineering students.This part of the study will examine the relationships between students’ visual and spatial skills, drawing skills (engineering students only), and their PSVT:R scores and seeks to examine a possible taxonomy of spatial skills.  This battery may serve as a reliable and valid assessment in the future of student skills at the high school and/or college level to indicate a need for additional instruction and practice of skills. There may be applications of these findings in other fields and for other purposes, such as geography, computing education, and military use.

Nelson will present “Title: Preliminary Evaluation for an Educational Intervention: Insights from a Usability Survey”

Abstract: 

Increasing whole grain intake can reduce the risk of chronic health conditions such as cancer and heart disease. However, people continue to make poor dietary health decisions, and the life expectancy for Americans is declining. Therefore, a novel intervention is needed to boost informed dietary decision-making. This study aimed to (1) provide preliminary evidence on the effectiveness, enjoyment, and efficiency of a novel intervention and (2) identify practices for making scientific information more usable. The study used a self-report online survey. Qualitative and quantitative data were collected to test the effectiveness, enjoyment, and efficiency of the educational intervention and how to improve it. Results suggest that the intervention is effective at increasing informed preventative decision-making. One hundred percent of participants showed adequate gist understanding across the four knowledge domains: habit gist understanding, whole-grain gist understanding, gist understanding of benefits, and gist understanding of susceptibility and severity. The results also revealed several strategies for increasing the usability of other educational interventions for a student sample demographic: increase/incorporate graphs, data, and references to increase the trustworthiness of an intervention. These results suggest that an educational video intervention effectively increases informed decision-making for preventative behaviors. These findings are also valuable for future intervention development and testing, making this proposal the next step for preventative care.