Social and Behavioral Sciences Commons^™

Understanding Subtle Gender Bias Recognition Among Witnesses In A Stem Undergraduate Context, Darnishia Lashalle Morris

Dissertations, Master's Theses and Master's Reports

This dissertation builds on knowledge of how witnesses recognize subtle gender bias (often referred to as gendered microaggressions) in a STEM undergraduate context. This body of work provides a better understanding of the implications of observing these events of subtle bias and the role that recognition plays in providing opportunities to adopt stereotype defying behaviors. The impressions and influences on both witnesses who belong to the marginalized group (target witnesses) and those in majority groups (non-target witnesses) were examined. Three interrelated studies explored how recognition might disrupt the cyclic impact of subtle gender bias when participants witness collaborative STEM team …

Exploring Usability In Exercise Interventions: From Conceptualization To Measurement And Application, Anne Inger Mørtvedt

Dissertations, Master's Theses and Master's Reports

Exercise interventions hold promise for preventing and treating numerous conditions, diseases, and injuries. However, these interventions will only be effective if they are being used. Unfortunately, uptake and adherence to prescribed exercise and physical activity guidelines are insufficient. Some reasons for this include lack of knowledge, resources, flexibility, and enjoyment. Exercise program developers need to not only consider the effectiveness of the program during the development phase, but also involve end-users and receive feedback on program usability to determine likelihood of uptake and adoption. Usability testing can be used to detect barriers to use and implementation likelihood but has not …

Types Of Questions Teachers Ask To Engage Students In Making Sense Of A Student Contribution, Nishat B. Alam

Dissertations, Master's Theses and Master's Reports

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 …

Making Scientific Information Usable: Development And Assessment Of A Novel Intervention To Boost Healthy Lifestyle Decision-Making, Brittany Nelson

Dissertations, Master's Theses and Master's Reports

Context—Improving diet can reduce the risk of chronic health conditions such as cancer and heart disease. However, people continue to make poor dietary health decisions. A novel intervention based on the science of behavior change and incorporating Human-Centered Design (HCD) methodology is needed to boost informed dietary decision-making.

Objective—This research presents a Behavior Change Wheel (BCW), Human-Centered Design (HCD) approach to develop a novel high-usability video intervention that will increase informed decision-making for whole-grain dietary decisions. The intervention will target college students, improving habits that can carry on throughout later adulthood.

Design—Study 1 consisted of preliminary data …

Explicit Rule Learning: A Cognitive Tutorial Method To Train Users Of Artificial Intelligence/Machine Learning Systems, Anne Linja

Dissertations, Master's Theses and Master's Reports

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 …

Investigating Collaborative Explainable Ai (Cxai)/Social Forum As An Explainable Ai (Xai) Method In Autonomous Driving (Ad), Tauseef Ibne Mamun

Dissertations, Master's Theses and Master's Reports

Explainable AI (XAI) systems primarily focus on algorithms, integrating additional information into AI decisions and classifications to enhance user or developer comprehension of the system's behavior. These systems often incorporate untested concepts of explainability, lacking grounding in the cognitive and educational psychology literature (S. T. Mueller et al., 2021). Consequently, their effectiveness may be limited, as they may address problems that real users don't encounter or provide information that users do not seek.

In contrast, an alternative approach called Collaborative XAI (CXAI), as proposed by S. Mueller et al (2021), emphasizes generating explanations without relying solely on algorithms. CXAI centers …

Online Retirement Planning Training: The Effects Of Usability On Cognitive Load And Retirement Planning Activity Levels, Natasha Hardy

Dissertations, Master's Theses and Master's Reports

The shift from defined benefit to defined contribution retirement plans for the current generation of retiree planners, Generation X, has placed the onus on individuals to gather, comprehend, and utilize complex financial information in order to plan their own retirement. Low savings rates and retirement planning activity indicate that individuals are not up to the challenge. This research investigates the interplay of three facets of cognitive load, usability, tech and retirement anxiety and the effects of a usability intervention on retirement planning activity levels.

Study 1 used semi-structured interviews and cognitive task analysis to explore themes of computer and retirement …

Investigating The Impact Of Online Human Collaboration In Explanation Of Ai Systems, Tauseef Ibne Mamun

Dissertations, Master's Theses and Master's Reports

An important subdomain in research on Human-Artificial Intelligence interaction is Explainable AI (XAI). XAI aims to improve human understanding and trust in machine intelligence and automation by providing users with visualizations and other information explaining the AI’s decisions, actions, or plans and thereby to establish justified trust and reliance. XAI systems have primarily used algorithmic approaches designed to generate explanations automatically that help understanding underlying information about decisions and establish justified trust and reliance, but an alternate that may augment these systems is to take advantage of the fact that user understanding of AI systems often develops through self-explanation (Mueller …