To meet the need of teaching faculty in computing and information sciences, many institutions of higher education in North America have been actively seeking and successfully recruiting full-time teaching faculty without requiring PhD While these pathways are becoming more established, there remain significant challenges in preparing, recruiting, and supporting teaching faculty in ways that reflect their unique positions in academia.

Technical interviews have long been used for assessing candidates for software engineering roles in industry, but given the recent advent of generative AI tools, a growing number of instructors have been investigating their role as an assessment in the computer science classroom. As a type of oral assessment, technical interviews dynamically evaluate students' ability to not only demonstrate technical skills but also communicate about their problem-solving approaches. However, there are some concerns about equity and accessibility in designing and implementing technical interviews, such as how language proficiency, neurodiversity, and familiarity with the interview format might affect a student's performance.

Demand for teaching faculty in the computing and information sciences is very high. To address this demand, many institutions of higher education in North America have been actively seeking and successfully recruiting full-time teaching faculty without requiring PhD. However, there remain many significant challenges around preparing, recruiting, and supporting these teaching faculty that are unique to their position and experience in academia. This Birds of a Feather session welcomes faculty on both sides of the hiring table as well as post-secondary students interested in teaching careers to discuss and envision how our community can better support diverse-degree pathways to full-time teaching faculty careers. We anticipate supporting questions and conversations from people with experience at all levels: conversation topics may include how to navigate the job market, how roles vary between institutions (with regards to degree requirements, workload, job security, service responsibilities, and expectations of scholarship), and how to better prepare and support students interested in this career track.

Demand for computer science teaching faculty is skyrocketing. In response, many colleges and universities are beginning to advertise for and hire teaching candidates without a PhD. In this panel, we discuss our experiences as faculty in this position and explore how we can promote and support the important contributions that non-PhD faculty have on students. Throughout this interactive panel, we will engage in-person and virtual participants from all levels of higher education to discuss the experiences surrounding teaching track faculty without a PhD. Additionally we will reflect and envision how our community can systematically support and create alternative paths within academia that will allow potential faculty to earn a terminal Master's degree and learn how to be effective teachers at the same time.

Instructors who teach large-scale technical courses, especially on data science and programming, must do a large amount of logistical work when updating their courses. All of this behind-the-scenes labor takes time away from the pedagogically-meaningful work of teaching students. Over the past five years, the authors of this paper have created and updated eight courses for an undergraduate data science program that serves over 2,000 students per year. We present four case studies from our teaching experiences that highlight major challenges in maintaining and updating technical courses: 1) There were intricate dependencies between course materials, so making updates to one part of the course would require updating many other parts. 2) We needed to maintain several variants of course materials such as assignments. 3) We wrote large amounts of ad-hoc custom software infrastructure to manage logistics. 4) We could not easily reuse software written by others. Our case studies point to design ideas for instructor-oriented tools that can reduce the logistical complexities of teaching at scale, thus letting instructors focus on the substance of teaching rather than on mundane logistics.

Demand for computer science teaching faculty is skyrocketing. In response, many colleges and universities are beginning to advertise for and hire teaching candidates without a PhD. In this panel, we discuss our experiences as faculty in this position and explore how we can promote and support the important contributions that non-PhD faculty have on students. Throughout this interactive panel, we will engage in-person and virtual participants from all levels of higher education to discuss the experiences surrounding teaching track faculty without a PhD. Additionally we will reflect and envision how our community can systematically support and create alternative paths within academia that will allow potential faculty to earn a terminal Master's degree and learn how to be effective teachers at the same time.

This summer, we introduced a number of structural changes to an existing upper-division data science course to optimize it for remote instruction. With hundreds of students situated in various time zones, a purely synchronous model was not feasible. Our course included a menu of synchronous and asynchronous activities, allowing students to consume content in the way they found most convenient and desirable.