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Clear the Air: Willingness to Pilot and Willingness to Pay with Leaded and Unleaded Fuel
No full textPilots reported a higher willingness to pilot (WTPilot) with traditional leaded avgas compared to the unleaded alternative. Willingness to pay (WTPay) was lower when the unleaded fuel was priced higher, showing sensitivity to cost. Results revealed that familiarity and affordability matter when considering sustainable fuel for flight training
Novel Human Factors Challenges, Unexpected Events, and Safety Hazards Associated with Operation of Battery-powered eVTOL Aircraft
No full textAs the AAM industry approaches its respective takeoff, novel dimensions of aircraft design, including propulsion systems and pilot interfaces, have emerged. These new and often complex dimensions result in operations differing from traditional aviation contexts, with the potential to influence pilot behavior and decision-making (Mendolia et al., 2022). There are also novel safety-critical events that pilots must be prepared to cope with on battery-powered aircraft. To examine these issues, we conducted an interview study with 11 pilots and engineers who have either flown, worked on, or conducted research pertaining to electrically powered aircraft. During the interview process, the participants were asked to describe and identify novel events pilots would face on electric aircraft, factors that would influence their decisions regarding power management, and challenges associated with transitioning to electric aircraft. We then conducted a qualitative analysis in which we identified themes that emerged across the interview responses related to the previous categories
Diversifying Cybersecurity: Evaluation of an Internet of Things (IoT)-Based Cybersecurity Training Course Designed to Bridge the Diversity Gap
No full textThis study aimed to evaluate the effectiveness of an eight-module Cybersecurity course at increasing the learning outcomes of middle and high school students with little to no experience, including underrepresented minorities (URMs) in Cybersecurity. Twice we administered and evaluated the Cybersecurity course, which included hands-on IoT-based activities, utilizing collaborative learning, scaffolding, and representation-based learning strategies. Using a quasi-experimental, within-subjects, repeated measures design, each participant experienced a pretest, the course, and a post-test to evaluate the impact on learners’ self-efficacy, interest, and knowledge. The results revealed that (1) at pre-test, female (p = .001) and in one course administration minority males (p = .006), knowledge was significantly less than that of non-minority males; (2) from pre-posttest, all groups experienced a significant increase in knowledge F(1, 16) = 15.76, p = .001, ηp2. = .496., and in one course administration, self-efficacy, F(1, 16) = 8.59, p = .01, ηp2. = .349, and interest, F(1, 16) = 8.19, p = .01, ηp2. = .339 as well; and (3) at post-test, there were no longer significant knowledge differences between the student groups (females vs. URM males vs. non-URM males), F(3,15) = .25, p = .25, ηp2 = .25. The results also reveal that one-size-fits-all training approaches may not be ideal to improve learning outcomes for all groups of students, as in collaborative learning activities, the composition of the groups influenced the engagement levels differently for males and females
Investigating Faculty Background, Perceptions, and Practices Associated with Course-Based Uses of Generative AI at a STEM University
No full textThis study investigated faculty uses of generative AI for teaching and assessment at one STEM university. This research is recent and limited, with no prior research AITU institutions or this university. Research questions focused on faculty: (RQ1) demographic and academic characteristics; (RQ2) experiences; (RQ3) confidence; (RQ4) benefits and impacts; (RQ5) influences; (RQ6) implementation and evaluation of AI guidelines; and (RQ7) barriers and needs.
After reviewing AI policies at AITU members, and interviewing faculty from the AI committee, an 11-section survey was developed and piloted. It assessed faculty characteristics reflected in three frameworks: Rogers’ Diffusion of Innovations, Ajzen’s Theory of Planned Behavior, and UNESCO’s AI Competencies Framework for Teachers.
Following IRB approval, all full-time faculty on the main campus were invited to participate. The e-mail invitation contained a link to the Consent Form and Survey in Qualtrics. Of 66 responses received, 57 were usable. Qualtrics data were imported into Microsoft Excel for preparation and imported into SPSS. Responses were tested for reliability and analyzed using descriptive statistics.
Respondents were experienced faculty from four colleges. Half integrating AI into their courses, yet 77% observed instances of student misuse. Confidence was moderate. Usage focused more on content generation than instructional transformation. Perceived benefits were tempered by concerns about student critical thinking. External professionals were prominent influences. While the Guideline provided flexibility, faculty struggled with enforcement. Finally, training and ethical guidance were identified as needs.
The final sections discussed (a) implications for theory, research, policy, and practice; (b) delimitations and limitations; and (c) recommendations
Identifying Barriers to the Assessment and Referral of Postpartum Depressive Symptoms in Maternal Healthcare: Patient Perceptions of Screening Procedures and Symptom Detection
No full textPostpartum depression (PPD) is a critical, global public health concern, profoundly affecting the well-being of mothers, infants, and families. Research has suggested that PPD may affect as many as 59% of pregnancies worldwide (Byatt et al., 2015). Despite its impact, standards for postpartum follow-up care remain highly variable across professional bodies, particularly with respect to the timing and scope of mental health assessment during later stages of the postpartum period (Al Hadi et al., 2022; Bauman et al., 2020; Earls, 2019; Long et al., 2018; USPSTF, 2019; Yang et al., 2024). Research has suggested that many mothers exit postpartum appointments with their mental health needs inadequately assessed, leading to adverse outcomes for all parties involved. On average, existing literature demonstrates that only 20% of women who screen positive for depression receive referrals to subsequent mental health services (Venkatesh et al., 2016). Disparities in screening practices are exacerbated by systemic healthcare limitations, sociocultural barriers, and challenges faced by low-income and minority populations, thus increasing both the incidence of PPD in these populations and obstacles to receiving comprehensive treatment.
Thus, the present study sought to evaluate the presence of standard mental health screening into postpartum care systems, specifically aiming to identify patient perceptions of screening and referral efforts from both obstetric and general populations. Participants were composed of 167 individuals who completed an online questionnaire broadly assessing personal screening and referral experiences during their respective pregnancies. Early, positive postpartum depression screens were found to significantly predict later positive postpartum depression screens, although estimation was limited by small sample size. Demographic and psychosocial variables such as race/ethnicity, social support, and history of psychological diagnoses were not found to be significant predictors of either increased or decreased depressive symptom experience during pregnancy and/or postpartum. Referral rates to mental health services for symptomatic mothers were found to exceed expected rates found within the current literature, and utilization rates amongst those referred for mental health services did not significantly differ from the hypothesized rate (Byatt et al., 2015; Lee-Carbon et al., 2022; Venkatesh et al., 2016). All mothers referred to mental health services reported attending these follow-up appointments, exceeding hypothesized rates. Finally, delivery type (i.e., medically complicated vs. medically uncomplicated) did not significantly predict screening frequency or follow-up attendance
S.L.O.S.H. - System for Liquid Orbital Supply and Handling
Full text linkWhy Manage Propellants in Microgravity? ● Deep space missions start with mastering in-orbit propellant transfer ● In microgravity, liquid propellants don’t settle–they float ● Vapor leads to system failure, engines demand pure liquid Project Objectives ● Design Propellant Management Device to handle Liquid Oxygen (LOX) ● Develop equipment to simulate operating conditions ● Conduct quantitative tests using cryogenic simulant (water) ● Evaluate/Analyze device performanc
RangerEye: Autonomous Wildfire Detection and Patrol Drone
Full text linkWildfires present a growing threat to ecosystems and infrastructure. RangerEye is an autonomous wildfire monitoring system to patrol fire-prone areas, detect heat anomalies using onboard thermal imaging, and transmit alerts in real time. The system operates independently, utilizing a drone capable of both vertical takeoff and landing (VTOL) and conventional flight, with a self-charging ground station
A Space Odyssey: Calculating the Escape Velocity from the Habitable Zone of Different Spectral Classes
Full text link• Escaping the solar system from Earth’s position requires a Δ of 42.1 km/s. A point mass in each star system (O-M & WD) requires a different escape velocity based on its unique habitable zone. • Modules for Experiments in Astrophysics² (MESA) was utilized to supplement gaps in real stellar data for synthetic luminosity values to determine the habitable zone of each stellar class. This work examines which propulsion methods would permit an interstellar probe starting from the habitable zones of different spectral classifications