Scaffolded Projects for the Social Good (SPSG) equips computing educators with a low-barrier framework for embedding sustainable, community-partnered software projects into existing software-engineering and capstone courses. In this three-hour, hands-on tutorial participants will step through the full SPSG lifecycle using a realistic nonprofit case study. Interactive segments include rapid feasibility vetting with a partner conversation guide; creation of a Team Agreement to set expectations; simulated client interviews that seed a well-scoped product backlog; application of detailed sprint-evaluation rubrics that deliver formative feedback; and knowledge-transfer techniques that enable seamless hand-off between semesters. Small-group work and whole-room debriefs provide immediate practice and peer feedback. The session culminates in an implementation clinic where facilitators help participants sketch a first-semester adoption plan aligned with local constraints and program learning outcomes. Attendees will leave with an editable toolkit including rubrics, deliverable templates, project-screening checklists, and other adoption aids, ready for use next term. After completing the tutorial, participants will be able to (1) identify feasible, socially impactful projects and build productive relationships with community partners; (2) scaffold student deliverables with meaningful, iterative feedback; and (3) sustain multi-semester projects without adding new courses or staff. The tutorial targets instructors of upper-division software-engineering, capstone, or project-based courses who seek to broaden students' technical competence, professional identity, and civic responsibility through authentic computing-for-social-good experiences.

We describe a lightweight approach to community-engaged service learning, structured as a semester-long hackathon where students explore socially relevant problems through problem definition, ethical analysis, and rapid prototyping. By eliminating the logistical challenges of traditional service-learning projects, this approach provides a scalable way to integrate Computing for the Social Good into the curriculum while retaining key educational benefits.

The work describes a model for graduate-undergraduate mentorship that enhances the learning of both groups, while also enabling more opportunities for students to get real-world experience in a way that benefits the university's greater community.

Recent publications strongly support refocusing undergraduate CS education toward competency-based learning. This shift places increased responsibility on departments to prepare responsible computing practitioners who appreciate how computing is inextricably intertwined with society. It emphasizes that content coverage is less important than authentic experiences that develop both ethical decision-making and industry-desired technical skills. One timetested successful strategy that helps meet these goals is communitybased service learning (CBSL). However, while CBSL has a strong track record, service learning can be challenging to implement and may not always guarantee successful student experiences.

Successfully implementing service learning presents many challenges. This is particularly true when working with community partners which are frequently small, understaffed non-profits, lacking in technical expertise. Participating faculty not only manage the student end of the partnership, but often need to manage/educate the community partner as well.

This innovative practice work in progress paper presents a systematic approach for screening and aligning service-learning projects that maximize student learning outcomes. We introduce a feasibility assessment model with criteria evaluated through a standardized rubric that guides instructors to critically assess the project fit to help in proactively identifying risks to student outcomes. The rubric serves a dual purpose: guiding the assessment process and prompting discussions with potential project partners. These discussions elicit crucial details about the project scope, potential challenges, and other critical factors. This not only facilitates effective project selection but also allows for necessary adjustments to project parameters, significantly improving the chances of successful student completion. This work builds on the experience accumulated by CCSU's Software Engineering Studio which connects community project partners with teams of 4–5 seniors working on software development projects spanning one or several semesters. Since 2014, the Software Engineering Studio has facilitated over 65 distinct projects and engaged over 550 students. By capturing the lessons learned across a wide range of successful service-learning projects, we show the value of using a feasibility assessment model to evaluate potential projects based on criteria including alignment with course goals, student skill sets, workload manage-ability, educational engagement, and other considerations. The application of this model is illustrated with a case study, which demonstrates how this model helps instructors align projects with academic goals while considering scope, risks, and other critical elements. This example demonstrates how the model facilitates communication with project partners, identifies potential risks, and guides project adjustments to ensure a successful learning experience for students. The approach is transferable to other disciplines with adaptations for project types and student skills. This work contributes to the field of service learning by offering a practical framework for integrating valuable real-world projects into the curriculum while prioritizing student learning outcomes.

This innovative practice work in progress paper describes an interdisciplinary course, “Industry 4.0 Robotics,” aimed at fostering deep learning and innovation in students across Manufacturing, Robotics, Computer Science, Software Engineering, Networking, Cybersecurity, and Technology Management. The course, jointly taught by faculty from different domains, emphasizes interdisciplinary connections in Industry 4.0 (IN4.0) Robotics through a combination of lectures, real-world insights from industry guest speakers, and hands-on interdisciplinary project-based learning. The contribution of this work lies in its innovative approach that combines proven best practices in education, inspiring deep learning, and an appreciation of interdisciplinary teamwork. The course design builds upon education research on the benefits of leveraging student creativity and requirements engineering practices as learning tools that allow students to develop a deeper understanding. While the benefits of these practices, commonly cited for developing enhanced problem-solving and cognitive flexibility skills, are becoming well understood in many individual disciplines, far less has been published on best practices for achieving this in interdisciplinary thinking. This course design explores this through using hybrid experiential problem based learning and project based learning for students to develop an understanding of interdisciplinary challenges and opportunities. While the benefits of individual educational practices have been studied within specific disciplines, this work extends the understanding of these practices when applied to interdisciplinary challenges, such as those encountered in Industry 4.0 robotics. The course design aims to bridge the gap between the technical aspects of individual disciplines and the social dimensions inherent in interdisciplinary work. This work in progress seeks to share early results showcasing the benefits of interdisciplinary teamwork and problem-solving. By articulating observations of commonalities and differences with prior work within individual disciplines, the paper aims to highlight the unique advantages of this interdisciplinary learning experience, offering insights into the potential impact on student learning. The chosen approach stems from the anticipation of future challenges increasingly necessitating interdisciplinary solutions. The goal of this work is to understand how best practices from individual disciplines can be effectively incorporated into interdisciplinary courses, maximizing student learning, and uncovering unique learning outcomes resulting from this innovative approach. The course design intentionally bridges the gap between the technical aspects of individual disciplines and the social dimensions inherent in interdisciplinary work, to encourage effective communication and collaboration within mixed student teams. While this remains a work in progress, initial observations reveal a heightened interdisciplinary curiosity among students, driving deep learning as they explore the interconnectedness of their own discipline with others within their teams. This curiosity propels self-led exploration and understanding of how their expertise intersects with diverse knowledge areas, creating opportunities for innovative solutions at these disciplinary intersections. This work contributes to the broader landscape of engineering and computing education by offering insights into the practical application of interdisciplinary learning in preparing students for the complex challenges of Industry 4.0.

Software development projects sourced from external organizations can serve as an excellent platform to help build student competencies because they often provide an environment where students can practice applying their knowledge and skills in an authentic context. However, there are many challenges and risks that can jeopardize the successful execution of such projects. In this report, we discuss some of the lessons learned about the pain points encountered by computing faculty with over a decade of experience running a software engineering studio where teams of undergraduate students work on long-term projects sourced from external partners. Our experience is based on working with a mix of project partners with a major emphasis on non-profit and community organizations and non-technical project partners. We focus on a strategy to carefully screen prospective projects to reveal possible challenges in order to avoid or minimize risks that could impact student learning outcomes.

Scaffolded Projects for the Social Good (SPSG) is an adaptable service-learning framework with a low adoption threshold based on the studio model. Its goal is to enable instructors to easily embed externally sourced projects supporting Computing for the Social Good (CSG) concepts into existing software engineering or similar courses and addresses the barriers common to service learning, as well as other frameworks with similar CSG-related objectives. Establishing connections between computing and its societal benefits has proven to be an effective strategy for attracting students, especially those from underrepresented groups within the discipline. Furthermore, this work supports competency-based learning by offering students an opportunity to solve real-world problems in an authentic environment using current industrial practices and tools coupled with strong mentoring support from volunteer professionals and near-peers. Using a studio model helps overcome the timing impedance between the length of a single academic term and the timeframes required to complete real-world projects with student teams.

Community-engaged learning is an emerging term for a wide spectrum of learning activities that bring together students and community partners in a mutually beneficial way. Service learning is a subcategory of community-engaged learning which traditionally involves the students using their skills or expertise on a project that will directly benefit the community partner. In computer science, service learning projects often include a deliverable, such as designing and building an application. Community-based service learning is service learning with a community partner, usually a non-profit, whose mission is to improve the social, environmental, or economic situation for community members.

One of the primary goals of computer science education is preparing students to apply what they learn in the classroom to any problem they may encounter in the future. Due to the rapidly changing landscape of technology, regardless of the comprehensiveness of their coursework, at some point students will be required to apply their knowledge to a context they have not encountered before, and understand how what they have learned applies. One of the content areas where this is particularly relevant is helping students recognize the variety of technologies and applications in which object oriented design patterns can produce significant practical benefits. To foster this aptitude, we sought to leverage the students' own creativity with a Raspberry Pi and a multitude of sensors, displays, cameras, and actuators to boost exploration of technologies and student understanding of how course concepts apply outside of constructed examples. This paper presents the experience of using student creativity with the Raspberry Pi to drive their learning in an upper level software design patterns course.

The Internet of Things (IoT) represents a new computing paradigm that may soon add a new dimension to the skillset expected from a well-rounded computing professional. Computer Science education is addressing these demands by adding IoT-centric courses to the curriculum and including relevant content into a broad range of existing courses. This paper presents the experience of incorporating IoT projects into an existing Systems Programming course. We examine several suitable hardware platforms, provide a sampling of student projects implemented using the Raspberry Pi with a variety of sensors, and discuss a number of lessons learned that could benefit other educators planning to incorporate the IoT material into their coursework.

Recent work has focused on creating models for generating traveler behavior for micro simulations. With the increase in hand held computers and GPS devices, there is likely to be an increasing demand for extending this idea to predicting an individual’s future travel plans for devices such as a smar