Student-centered practices are practices that focus on providing engaging and equitable experiences to students in our classroom. These strategies have grown in popularity over the past decade, but the general impact of these practices on student perceptions remains unclear. Building on our prior work, this study examines four such practices: late-submission, resubmission, review sessions, and meeting students across two introductory computing courses with contrasting class sizes at different institutions. We identify qualitative themes from open-ended survey responses that reveal insights about how students experience these practices, with emphasis on differences between the two courses. These findings contribute to ongoing efforts to create supportive and effective learning environments in STEM, providing actionable insights for educators aiming to improve engagement, academic confidence, and overall success.

Alternative grading practices seek to improve learning and make education more equitable. For the past few years, our community has been exploring these techniques and contextualizing them for use in computing courses. In this panel, we will present various grading techniques with a particular attention to the experience implementing them and pitfalls to be avoided. The presenters all have extensive experience exploring alternative grading techniques. Furthermore, we hope to engage the audience in a conversation about the nuance of implementing these particular techniques in the variety of courses that are typical in computing programs.

Over the past decade, Computer Science programs have seen increased interest, with classes often growing in size to accommodate this demand. While enrollment trends have recently stabilized or even declined slightly in some cases, many programs are still serving these large numbers of students. One common response has been to expand the number of course sections, which requires hiring additional faculty to handle the increased load. However, this solution is often constrained by budget limitations and the availability of qualified instructors.

Pedagogical practices that promote equity in the classroom play a crucial role in broadening participation and enhancing student success. These practices directly address the critical challenge of low diversity in the field of computing.

In this research full paper, we report on the results of a large-scale study to answer the following research question: What is the impact of the late submission practice on students' perception of their sense of belonging, confidence, and performance, their actual performance in the course, and other experiences in their course?; Does the impact differ by different socioeconomic, and demographic student groups (e.g. ethnicity/race, gender, first-generation, transfer-student status, work status, etc.), and whether students utilized or did not utilize the practice? Being intentional in fostering an environment where diverse groups of students can thrive in a discipline can contribute to increasing diversity in the corresponding workforce. This is especially true for fields like Computer Science and Engineering where lack of diversity continues to be a major challenge. One way to broaden participation and increase student success is the adoption of equitable pedagogical and grading practices. In this paper, we describe students' perception of performance, confidence, and sense of belonging (SoB) when they are permitted to submit coursework past a set deadline. We report on the data in the context of the different student groups outlined above. Our hypothesis is that such practice contributes to improved student performance by focusing on learning rather than grades. Our results show that students highly valued this practice and provided a 4+ rating on a 5-point Likert scale, indicating a positive perception and more specifically perceived them as having a positive impact on their SoB, confidence, and performance. This practice also helped in improving students' course performances. This work will help in understanding the empirical evidence of the impact of this practice on student experiences across various student groups.

Understanding computing concepts is one of the foundational elements of computational thinking, which helps students formulate logic and algorithms for effectively developing and designing codes. However, novice learners often struggle to understand basic computing concepts, such as variables, loops, arrays, conditionals, and functions. This is often caused by the invisibility of the computing mechanism and the complexity of language syntax and conventions. Moreover, challenges in learning computing concepts can be compounded for learners with atypical conditions (e.g. visual, cognitive, and learning impairment, attention deficit, and neurodivergence). To tackle this, teachers of typical ability learners frequently use notional machines (NMs) - simplified representations (e.g. diagrams, flow charts, and analogies) created to assist novice programmers in understanding abstract concepts, program execution, and dynamics. In addition, traditional learning activities may need assistive learning interventions (ALIs) and learner-oriented practices like physical tactile models, computing artifacts, and interactive learning tools. NM approaches tend to focus on the explanation of concepts from instructor to learner, while ALIs tend to focus on learner support in activities. Both methods can provide advantages for learning, and we expect that a combined approach would provide even greater synergy for all learners. However, little consideration has been given to how NM and ALI approaches could be effectively combined. This research investigates how NM and ALI can be effectively brought together more holistically as an inclusive pedagogical tool - notional machines for inclusive learning (NMIL). In this full paper, we develop the conceptualization of NMIL, grounded in previous NM and ALI research. We also propose a structured method for creating NMIL. Finally, we also develop a physical NMIL model, based on the structured NMIL creation method, to teach lists in Python, as part of an introductory computer science course.

Lack of diversity is a major challenge in CS education. One way to broaden participation and increase student success is the adoption of equitable pedagogical and grading practices. Lack of evaluation of such practices within the context of undergraduate CS education results in less adoption. This study is the first step in a broader project examining such practices and their impact on undergraduate CS students. Factors such as confidence and sense-of-belonging have been linked to increase students' success. In this study, we report on the evaluation of four practices commonly adopted in pursuit of equity, in terms of students' perceptions and how they impact students' sense-of-belonging, confidence, and performance in a computer science course. We report on students' feedback from a CS2 course in the Spring 2023 semester. Our results show that students valued these practices and perceived them as having a positive impact on their course experience in relation to these constructs. Students also reported that these practices gave them better control of their learning, allowed them to learn from their mistakes, and have a better understanding of the course content.

The design of online learning environments has a fundamental and immediate impact on how students experience learning in these environments and particularly on the students’ satisfaction and learning engagement. The COVID-19 pandemic has resulted in students participating in online learning on a large scale and forcing educational institutions to adopt various communication and virtual teaching environments: this has provided an opportunity to study and compare different online learning environments. To understand the design performance of the currently available virtual learning environments, they should be considered and evaluated from the students’ point of view. Identifying their pros and cons gives designers a better idea of how to enhance the design of virtual learning environments and provide a positive educational experience for students. The two most broadly used types of virtual learning environments are video conferencing and virtual worlds. These two mediums provide different affordances for students to experience and interact with the learning materials as well as to interact with the instructor and other students. This paper reports on a study comparing the use of Zoom as an example of video conferencing and Gather.Town as an example of a virtual world in online learning during the COVID-19 pandemic. The study is based on students’ responses to an online survey asking them to compare the two environments based on their experience in their courses. The participants were CS undergraduate students exposed to both environments and experiences with both platforms. A qualitative analysis of the data collected showed that students realized certain values from the affordances offered by the virtual world environment that facilitated collaborative learning with peers and instructors and made the learning experience more effective and engaging.

The COVID-19 pandemic led the majority of educational institutions to rapidly shift to primarily conducting courses through online, remote delivery. Across different institutions, the tools used for synchronous online course delivery varied. They included traditional video conferencing tools like Zoom, Google Meet, and WebEx as well as non-traditional tools like Gather.Town, Gatherly, and YoTribe. The main distinguishing characteristic of these nontraditional tools is their utilization of 2-D maps to create virtual meeting spaces that mimic real-world spaces.

In this project, we explore how academic integrity and teaching computer ethics have evolved within the SIGCSE community over the past 50 years. We apply Natural Language Processing (NLP) techniques to identify the topics in the records in 50 years of SIGCSE Symposia. We extract records that include these two themes and apply a temporal model identifying periods with an increase in the number of records that include these themes and a significant increase in 2017-2018.

Geovisualization has traditionally played a critical role in analysis and decision-making, but recent developments have also brought a revolution in widespread online access to geographic data and integration tools, particularly for map-based interfaces. This next generation of geovisualization applications is often characterized by high interactivity and strong end-user participation in both development and use. Building the most effective tools to support user-centered geographic visualization faces a significant challenge, though: very little is known about how people interact with maps. To date, map use research has typically focused on higher order use goals or cognitive interpretations of static map representations. Our research employs Human-Computer Interaction approaches in order to investigate user behaviors that contribute to interactive map use and understanding. This paper describes our approach to studying geovisualization interaction and presents our pilot user studies and initial interaction model. By building a better understanding of how people interact with map interfaces, we will be able to design better user-centered geographic visualizations and learn how to best customize these applications to specific user groups.