Craig Zilles
Professor and Severns Faculty Scholar, Siebel School of Computer and Data Science, University of Illinois at Urbana-Champaign | Profile
Exams with More Learning and Less Stress with a Computer-Based Testing Facility
Abstract:
Exams are an important tool for summative assessment, whose utility has only grown with the advent of large language models (LLMs) like ChatGPT, because they can be implemented in a trustworthy manner. But exams are generally not well liked by either students or faculty. Students find them stressful. For faculty (and their course staff), they represent a large administrative burden to write, proctor, and grade. This large burden means they are done infrequently in many classes, but this infrequent testing encourages cramming and leads to high test anxiety.
In this talk, the speaker will share (1) research on the benefits of frequent testing and “second-chance testing” (optional exam re-takes) on increased student learning and decreased test anxiety, and (2) how it has reduced the instructor workload at Illinois to implement frequent testing through our Computer-Based Testing Facility (CBTF). The CBTF is a collection of proctored computer labs that, in conjunction with the PrairieLearn open-source question-asking platform, enable faculty to run sophisticated exams with almost no recurring effort even in the largest classrooms. For example, the CS 1 course for majors (run by a single faculty member) ran weekly exams for 1,150 students. Key enabling ideas for the CBTF include: (1) sophisticated auto-grading questions, (2) question generators, (3) asynchronous exams, and (4) dedicated testing space and proctors. The CBTF at Illinois has been running for over 10 years and proctored over 130,000 exams last semester for 65 courses, and many other universities are starting to replicate the implementation.
Speaker Bio:
Craig Zilles is a Professor and Severns Faculty Scholar in the Siebel School of Computer and Data Science at the University of Illinois at Urbana-Champaign. His current research focuses on applying computing and data analytics to education, including the development of the Computer-Based Testing Facility (CBTF). Previously, his research focused on the interaction between compilers and computer architecture, and he developed the first algorithm that allowed rendering arbitrary three-dimensional polygonal shapes for haptic interfaces (force-feedback human-computer interfaces).
He received the IEEE Education Society’s 2010 Mac Van Valkenburg Early Career Teaching Award and an NSF CAREER award. At Illinois, he has received a wide range of teaching awards, including a 2018 Campus Award for Excellence in Undergraduate Teaching, a 2013 Illinois Student Senate Teaching Excellence Award, and the College of Engineering’s Rose Award (2007) and Everitt Award (2008) for Teaching Excellence. He holds 5 patents and his research has been recognized by a best paper awards from ASPLOS in 2010 and 2013 and by selection for inclusion in the IEEE Micro Top Picks from the 2008 Computer Architecture Conferences.
Navin Kabra
Co-Founder & CTO at ReliScore.com; Visiting Professor of Practice at IIT-Bombay | Profile
What Should We Teach When AI Can Write the Code?
Abstract:
The practice of programming is undergoing profound changes every month. AI can now write code and tests better than most students—and for that matter, most professors. But still, it can fail in unexpected and unpredictable ways. We have to prepare our students for a world where they are no longer programmers, but managers of powerful agents that are more knowledgeable than themselves, but at the same time can make dumb mistakes.
This puts CS educators in a tough spot. There is a need to redesign the curriculum in 3 ways: 1) figure out what items to drop from the curriculum entirely, because they’re no longer relevant in a world of AI agents, 2) figure out what will continue to be taught the old way, where students learn and practice without any help from AI, to prevent cognitive offloading, and 3) add new items to the curriculum where students maximize the use of AI and learn higher order skills of managing AI agents, and verifying their work (“Evals”).
In this talk, the speaker will talk about how industry is grappling with these changes, what skills they are looking for from students, and how to even think about curriculum and teaching at a time when the capabilities of AI tools are improving every month, and the entire paradigm shifts every year.
Speaker Bio:
Navin Kabra is a co-founder and CTO at ReliScore.com, a startup focused on helping companies filter job candidates based on the evaluation of actual job-related skills. He is also a visiting professor of practice at TrustLab, Computer Science and Engineering Department, IIT-Bombay; an advisor for FinIQ (a fintech company in the structured products space), Innoviti (a fintech company in the payments processing space), the Advisory Committee of NIDHI-EIR-PEP and NIDHI-PRAYAS-PC (Govt. of India initiatives in the innovation/incubation space). He is also an instructor at GenWise teaching high school students courses on diverse topics, including AI, GenAI, cryptography, game theory, blockchain technologies, critical thinking, and more.
In the past, he worked for large and small companies in India and the US; saw a successful exit, and a dotcom failure; handled product development and research; wrote consumer and enterprise software; and served as a developer, architect, and manager.
Navin did his Ph.D. with David DeWitt in Computer Sciences from the University of Wisconsin in 1999, and a B.Tech. in Computer Sciences from IIT-Bombay before that. He is interested in a number of areas of computer science, including: highly scalable systems; distributed and fault-tolerant software systems; and text search, information retrieval, and analysis of unstructured information. His latest interests include understanding what drives online communities and using technology to improve higher education (especially in CS).