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1. The Accessible Learning Labs: Supporting Accessibility Education

   Moses, Heather; Wedner, Jaden; Malachowsky, Sam; Krutz, Dan (January 2022, IEEE/ACM International Conference on Automated Software Engineering)

   Mature and robust software applications should demonstrate several crucial qualities; namely, they should supply the functionality expected by the stakeholder(s), perform efficiently, be secure, and be accessible. However, despite government legislation and growing demonstrated need, accessibility is not a priority for a compelling amount of software applications being developed currently. The primary objective of our Accessible Learning Labs is to not only educate participants on how to properly create accessible software, but also effectively illustrate the need to create accessible software. Our experiential labs enable practitioners, instructors, and students to engage with the material using only a browser. This tutorial will benefit a wide spectrum of participants in the software engineering community, ranging from beginning-level students to experienced practitioners who want to ensure that they are properly creating inclusive and accessible software. Complete project material is publicly available on the project website: https://all.rit.edu 

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2. ALL: Accessibility Learning Labs for Computing Accessibility Education

   Khan, Saad; Moses, Heather; Malachowsky, Sam; Krutz, Dan (June 2021, INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION)

   null (Ed.)

   Our Accessibility Learning Labs not only inform participants about the need for accessible software, but also how to properly create and implement accessible software. These experiential browser-based labs enable participants, instructors and practitioners to engage in our material using only their browser. In the following document, we will provide a brief overview of our labs, how they may be adopted, and some of their preliminary results. Complete project material is publicly available on our project website: http://all.rit. edu 

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3. Presenting and Evaluating the Impact of Experiential Learning in Computing Accessibility Education

   https://doi.org/10.1145/3377814.3381710  

   El-Glaly, Yasmine; Shi, Weishi; Malachowsky, Samuel; Yu, Qi; Krutz, Daniel (January 2020, Proceedings of the International Conference on Software Engineering)

   Studies indicate that much of the software created today is not accessible to all users, indicating that developers don’t see the need to devote sufficient resources to creating accessible software. Compounding this problem, there is a lack of robust, easily adoptable educational accessibility material available to instructors for inclusion in their curricula. To address these issues, we have created five Accessibility Learning Labs (ALL) using an experiential learning structure. The labs are designed to educate and create awareness of accessibility needs in computing. The labs enable easy classroom integration by providing instructors with complete educational materials including lecture slides, activities, and quizzes. The labs are hosted on our servers and require only a browser to be utilized. To demonstrate the benefit of our material and the potential benefits of our experiential lab format with empathy-creating material, we conducted a study involving 276 students in ten sections of an introductory computing course. Our findings include: (I) The demonstrated potential of the proposed experiential learning format and labs are effective in motivating and educating students about the importance of accessibility (II) The labs are effective in informing students about foundational accessibility topics (III) Empathy-creating material is demonstrated to be a beneficial component in computing accessibility education, supporting students in placing a higher value on the importance of creating accessible software. Created labs and project materials are publicly available on the project website: http://all.rit.edu 

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4. FORE: A Student-Centered Framework for Accessible Robotics Education through Simulation and Interactive Learning

   Jamali, H; Debolt, A; Dalton, H; Layosa, J; Macy, I; Shill, P; Feil-Seifer, D; Harris, F; Dascalu, S; Wu, R (June 2025, 2025 ASEE Conference)

   Robotics education is often constrained by the high cost and limited accessibility of physical robots, which can hinder the learning experience for many students. To address this challenge, the Fundamentals of Robotics Education (FORE) project, part of a larger NSF-funded collaborative work, was developed to create an accessible and comprehensive online learning platform. FORE provides a student-centered approach to robotics education, featuring a robust code editor, real-time simulation, and interactive lessons. This paper presents the architecture and implementation of the FORE platform, highlighting its key components, including the backend simulation using Gazebo and ROS2, a frontend visualizer built with Three.js, and the integration of a Python-based coding environment. We discuss the development process, the contributions of the student team, and the challenges encountered during the project. The results demonstrate the platform’s effectiveness in making robotics education more easily available. These findings originate from software testing and utilization by senior computer science students, as well as feedback from participants at the University of Nevada, Reno College of Engineering’s annual Capstone Course Innovation Day. The platform allows students to gain hands-on experience without the need for physical hardware. Its adaptability enables it to serve a broad audience of undergraduate students, offering an encompassing and accessible solution for modern robotics education. 

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5. Do Users Act Equitably? Understanding User Bias Through a Large In-person Study

   Lui, Yang; Moses, Heather; Sternefeld, Mark; Malachowsky, Sam; Krutz, Daniel (July 2023, 2023 IEEE/ACM 45th International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS))

   Inequitable software is a common problem. Bias may be caused by developers, or even software users. As a society, it is crucial that we understand and identify the causes and implications of software bias from both users and the software itself. To address the problems of inequitable software, it is essential that we inform and motivate the next generation of software developers regarding bias and its adverse impacts. However, research shows that there is a lack of easily adoptable ethics-focused educational material to support this effort.To address the problem of inequitable software, we created an easily adoptable, self-contained experiential activity that is designed to foster student interest in software ethics, with a specific emphasis on AI/ML bias. This activity involves participants selecting fictitious teammates based solely on their appearance. The participant then experiences bias either against themselves or a teammate by the activity’s fictitious AI. The created lab was then utilized in this study involving 173 real-world users (age 18-51+) to better understand user bias.The primary findings of our study include: I) Participants from minority ethnic groups have stronger feeling regarding being impacted by inequitable software/AI, II) Participants with higher interest in AI/ML have a higher belief for the priority of unbiased software, III) Users do not act in an equitable manner, as avatars with ‘dark’ skin color are less likely to be selected, and IV) Participants from different demographic groups exhibit similar behavior bias. The created experiential lab activity may be executed using only a browser and internet connection, and is publicly available on our project website: https://all.rit.edu. 

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