Recent advances in artificial intelligence (AI), including the widespread adoption of foundational models, have triggered changes across Computing Science (CS) programs. Developments include, but are not limited to, revisions to assessment practices, updates to academic integrity policies, curriculum redesign to integrate emerging concepts, and the growing use of conversational agents to support instruction. These developments aim to address effective preparation of graduates for an evolving AI innovation landscape.

In addition to achieving learning outcomes, project-based learning (PBL) in groups is known to foster communications, team building, collaboration, and leadership skills, all essential for computer scientists in the workforce. Academic risk-taking, enabling students to attempt more complex problems and challenging projects, is a valuable skill for high academic achievement, making it a desirable skill for students in a fast-paced discipline. To explore the possibility of fostering academic risk-taking in PBL as a valuable skill for computer scientists, we focused on the impact of scaffolding to improve the PBL outcomes for diverse learners and its impact on risk-taking. We report on our initial findings and navigating grade-related risks, incentives, and timing constraints.

Evidence supports offering research experiences for undergraduate computing science students as a means of broadening participation in computing[7, 10, 11]. However, student perceptions about computing science research, how students become interested in these research experiences, and the details of effective design and delivery of programs capable of attracting and retaining this interest are less explored. In this study, we investigate the design and delivery of undergraduate research programs. We expand on and explore several factors, including but not limited to cultural relevance, the presence of a cross-disciplinary high-level view, task assignment, entry point, and support elements of a program.

One of the less explored approaches to foster equity, diversity, and inclusion (EDI) in Computer Science (CS) is through changes to the curriculum. Despite sporadic work on the adoption of Culturally Responsive Computing (CRC) and Universal Design for Learning (UDL), the inclusion of equity-minded courses, or modifications on specific elements of the curriculum such as introductory programming courses, there has never been a wide exploration or adoption of a successful equity-minded undergraduate CS curriculum.

Open Educational Resources (OER) are changing how we teach and learn computing science. In this study, aiming to inform open textbook development for a computing science course, we explore student preferences in using educational resources. Our initial findings show while students like to purchase and keep textbook for theoretical and foundational courses, there is a strong preference for using OER, especially video resources, either lectures or short topic-based videos, for learning technical course materials.

Computing science education has experienced low attendance and historic declines in registration from different minority groups. The past decade of enrollment surge in computer science undergraduate programs has increased the number of women and minorities in the field, but the improvements are inconsistent and less than expected. An increase in the use of computing science and in the demand of technology workforce is expected in the upcoming years. Thus, computing science is set to shape the future of technology for a diverse set of technology users. Therefore, it is important to analyze how undergraduate program admission procedures are affecting Equity, Diversity, and Inclusion of historically marginalized groups in computing science.

A series of previous Working Groups has met at ITiCSE conferences to explore ways of incorporating cloud computing into courses and curricula, including mapping industry job skills to knowledge areas (KAs) and KAs to student learning objectives (LOs). The importance of industry-standard learning content and certification, produced by cloud vendors and others, was apparent throughout this work. This Working Group will focus on the role of certification within cloud computing curricula, from the viewpoints of a range of stakeholders: students, graduates, institutions, vendors and other certification providers; and employers. Areas for study will include: the scope of available certifications and their mapping to our KAs and LOs; approaches to integrating certification in academic cloud curricula, and challenges involved in doing so; and perceptions of the stakeholders of the role and value of certifications in evidencing employability. The outcome of the work will include a set of recommendations for best practice.

Effective technical communication, collaboration, and leadership are among essential skills required from computer scientists. Project-based learning using open-ended projects is praised for fostering these skills in the context of software development. Our observations, in the context of a systems course, suggest that while learning outcomes are achieved, open-ended projects are stressful for students. We investigate the appropriate methods, levels of specification, and scaffolding to help students learn the concepts while implementing real-world web projects in student-formed groups.

With advancements in wireless communication technologies, broadband wireless services will be prevalent in the near future. Meanwhile, the capability of mobile devices is drastically increasing the mobile data usage, which is far in excess of mobile network capacities. Therefore, despite the high availability of these networks, the large scale of users they support, and their improved spectral efficiencies, effective utilization of wireless resources is still required to keep up with the ever increasing user demands for mobile services. This paper targets high-throughput data transmission in advanced cellular wireless networks that have been widely used for broadband access and are constantly enhanced for future applications. We present a power-efficient resource allocation solution to meet the transmission requirements for bandwidth-intensive applications -- video streaming. In particular, our design strategically groups mobile users into multicast groups with different video quality requirement, and utilizes cellular resource to meet their video requirements. We compare our proposed methods with state-of-the-art solutions and prove their effectiveness: our design achieves 5% to 18% improvement in base station power consumption, and 13% to 25% improvement in user device power conservation.

The popularity of wireless local area networks has led to a dramatic increase in the density of access points, especially in urban areas. These access points are individually owned, placed, and power-tuned for their local users and are generally oblivious to others. On the other hand, the abundance of access points that mostly share the same upstream provider, offers opportunities for optimization of association to mitigate the negative impact of the overlapped coverage. We use this opportunity to enable collaboration by using a share of each access point's bandwidth to serve non-local users and gain access to their bandwidth in return. We extend the conventional proportional fair association through sharing and collaboration among individual networks, and present centrally optimized solutions. Our performance evaluation, based on data traces collected in 100 residential locations, demonstrate the superiority of our solution, outperforming the throughput of non-collaborative optimal access by up to 140%.

Virtual MIMO (Multiple Input Multiple Output) groups multiple single-antenna mobile devices to form an antenna array, offering higher degrees of freedom and improved spatial diversity gain as a real MIMO does, yet with much lower costs. In this paper, we focus on the user grouping problem in uplink transmission from multiple single-antenna users to one multiple-antenna base station. State-of-the-art solutions mostly target two single-antenna users, solving a pairing problem. Having more than two uplink users in a grouping has yet to be addressed. Intuitively, a higher number of users in a VMIMO group offers better spectrum efficiency, and thus more throughput gains could be expected; the group dynamics however becomes higher too, making fairness harder to be achieved with reasonable computation overhead. To address these challenges, we present a novel solution that decomposes the VMIMO user grouping into two steps. We lighten the computations in user grouping by using instantaneous signal to noise ratio (SNR) as selection criteria, and combining it with proportional fairness for larger groups of users. Lightweight computation in using instantaneous SNR in our solution allows faster grouping and feasible scheduling for a large number of users, as well as fast decision on the efficiency of the number of users in each group. We have evaluated our solution under different network configurations, and the results demonstrate that it achieves much higher data throughput as compared to existing solutions and also well preserves fairness.

The recent advent of high speed trains introduces new mobility patterns in wireless environments. The LTE-A (Long Term Evolution of 3GPP - Advanced) networks have largely tackled the Doppler effect problem in the physical layer and are able to keep wireless service with 100Mpbs throughput within a cell in speeds up to 350 km/h. Yet the much more frequent handovers across cells greatly increases the possibility of service interruptions, and the problem is prominent for multimedia communications that demand both high-throughput and continuous connections. In this paper, we present a novel LTE-based solution to support high throughput and continuous multimedia services for high speed train passengers. Our solution is based on a Cell Array that smartly organizes the cells along a railway, together with a femto cell service that aggregates traffic demands within individual train cabins. Given that the movement direction and speed of a high-speed train are generally known, our Cell Array effectively predicts the upcoming LTE cells in service, and enables a seamless handover that will not interrupt multimedia streams. To accommodate the extreme channel variations, we further propose a scheduling and resource allocation mechanism to maximize the service rate based on periodical signal quality changes. Our simulation under diverse network and railway/train configurations demonstrates that the proposed solution achieves much lower handover latency and higher data throughput, as compared to existing solutions. It also well resists to network and traffic dynamics, thus enabling uninterrupted quality multimedia services for passengers in high speed trains.

We examine power-efficient high-quality scalable video streaming in LTE networks through its eMBMS service. We consider scalable video streaming and download services offered by eMBMS service over LTE networks. We propose an effective and practical solution to jointly optimize user experience and power consumption in both UE and eNodeB. To perform power efficient multimedia transmission in LTE networks, we face three key trade-offs: (1) maximizing energy saving vs. minimizing delay, (2) maximizing sleep time vs. minimizing lost packets, (3) maximizing quality of video vs. minimizing unnecessary video transmissions. We provide a balanced solution that addresses the trade-off by including user preference. Our simulation results indicate 5% to 18% improvement in base station power consumption and 13% to 25% improvement in UE power conservation chances. The provided solution also decreases the transmitted data in the network while preserving the user perceived quality of the video.

Location information improves the routing effectiveness and facilitates the development of diverse novel applications in mobile networking. While they can lead to better user experiences, given privacy concerns and hardware constraints, a mobile user often exposes a limited number of locations only. We are thus interested in the Trajectory Exposure Problem in this context, i.e., to what degree that the user's trajectory (i.e., its route) is exposed? Furthermore, can the user adaptively control the exposure of its trajectory and yet offer useful information for location-based services? In this paper, we explore Gaussian Process Regression, an effective tool to re-construct the trajectory of the mobile user with selected exposed locations. We examine how the re-constructed trajectory differs from the real trajectory, i.e., evaluating the exposure rate. We present an effective heuristic that adaptively controls the trajectory exposure rate by carefully choosing the exposed locations. We further demonstrate a practical routing protocol, MoRPTE, which, controlled by a single parameter, utilizes location information flexibly and adaptively in the spectrum from zero knowledge to full knowledge to fit the applications' demands.