About

Chris Riesbeck is an Associate Professor of Computer Science at Northwestern University and serves as the Director of the Master of Science in Computer Science Program. He is also the Co-Director of the Center for Computer Science and Learning Sciences. His research interests include agile software development, technology-enabled educational reform, and experiential knowledge-based language understanding and reasoning. Riesbeck has contributed to the fields of engineering design practices, problem-based learning, and educational technology, with publications focusing on iterative practices in engineering design teams, overcoming barriers in volunteer advising for project-based learning, and tools to support coaching in educational settings. He holds a Ph.D. in Computer Science from Stanford University, an M.A. in Computer Science from Stanford University, and a B.A. in Mathematics from Alfred University.

Research topics

• Computer Science
• Knowledge management
• Engineering
• Algorithm
• Engineering management
• Software engineering
• Psychology
• Operations management

Selected publications

• Research Slices

  EDeR Educational Design Research · 2024-02-26

  articleOpen accessSenior author

  Educational Design Research (EDeR) methodologists argue that iteration is a core component of EDeR. Iteration is currently defined as a process of gathering more information through actions, such as testing, and using that information to improve the design. In this paper, we seek to tighten the definition of iteration to help EDeR teams conduct iterations more effectively. We argue that EDeR teams should organize their research in slices that deliver small but real value to end users while informing the design research. EDeR should pick slices that are: (a) minimal and focused, (b) deployed in a real context, (c) valuable to the end users, and (d) informative to the research. Slicing helps EDeR teams increase ecological validity when they test because it allows testing which is within real-world educational contexts or with the stakeholders who will use and be impacted by the design. Increasing ecological validity of testing is particularly important because EDeR projects tackle highly complex real-world problems with many unknown elements and relational complexity—this means it is challenging to predict what designs will have the desired impact without real-world deployment. Effective iteration through organizing research in slices helps EDeR teams to better support stakeholder goals, develop more impactful theory, and have greater and earlier impact upon education.

  PublisherOA PDFDOI

• Encouraging engineering design teams to engage in expert iterative practices with tools to support coaching in problem‐based learning

  Journal of Engineering Education · 2023 · 11 citations

  • Computer Science
  • Computer Science
  • Knowledge management

  Abstract Background To create design solutions experienced engineering designers engage in expert iterative practice. Researchers find that students struggle to learn this critical engineering design practice, particularly when tackling real‐world engineering design problems. Purpose/Hypothesis To improve our ability to teach iteration, this study contributes (i) a new teaching approach to improve student teams' expert iterative practices, and (ii) provides support to existing frameworks—chiefly the Design Risk Framework—that predict the key metacognitive processes we should support to help students to engage in expert iterative practices in real‐world engineering design. Design/Method In a 3‐year design‐based research study, we developed a novel approach to teaching students to take on real‐world engineering design projects with real clients, users, and contexts to engage in expert iterative practices. Results Study 1 confirms that student teams struggle to engage in expert iterative practices, even when supported by problem‐based learning (PBL) coaching. Study 2 tests our novel approach, Planning‐to‐Iterate, which uses (i) templates, (ii) guiding questions to help students to define problem and solution elements, and (iii) risk checklists to help student teams to identify risks. We found that student teams using Planning‐to‐Iterate engaged in more expert iterative practices while receiving less PBL coaching. Conclusions This work empirically tests a design argument—a theory for a novel teaching approach—that augments PBL coaching and helps students to identify risks and engage in expert iterative practices in engineering design projects.

  PublisherDOI

• In Memoriam: Roger C. Schank, 1946–2023

  AI Magazine · 2023-07-31

  articleOpen accessSenior author

  A summary of Roger Schank's career might initially appear fairly typical for an eminent academic. Following a PhD in linguistics at the University of Texas at Austin in 1969, Roger held faculty positions in linguistics and computer science at Stanford, computer science and psychology at Yale, and computer science and education at Northwestern. He served terms as chair of computer science at both Yale and Northwestern. After Northwestern, he was Chief Educational Officer for Carnegie Mellon's Silicon Valley campus. He authored over 30 books spanning AI, cognitive science, psychology and education. He advised nearly 50 PhD students. He was a Fellow of AAAI. But the hundreds of people who worked or interacted with Roger over the years know there was nothing typical about him. Roger was a force of nature. He questioned everything, especially (and gleefully) focusing on topics that were supposed to be canon. He came in, broke things apart, and built new things in their place. In linguistics, he rejected the Chomskyian approach to divorce the study of language from the study of meaning, with his seminal work on semantic primitives. In AI, where language processing focused on the propositions, he argued for the importance of much larger memory structures such as scripts and plans, and for memory processes, such as remindings, for modeling understanding. He argued for examples, that is, cases, rather than logical rules, for modeling human reasoning. Much of his work elicited initial pushback, which then transitioned to wary toleration, and finally arrived at such widespread acceptance that now his ideas are often assumed without attribution. Roger relished debate, and engaged avidly in ongoing discourse on the issues he studied. Where many labs have weekly “discussions” or “chats”, Roger fashioned weekly “Friday fights” and an “Indefensible position” seminar. One facet of these was the Socratic investigation of complex topics; another was as a crucible for the courage to make bold claims and the skills to distill, defend, and question them. He questioned loudly. But under the disputative bearing, to those who knew and worked with him he had abundant loyalty and good will. He was an explorer of the mind and of the world, an astute observer of humans and human nature: an intuitive psychologist. He had a knack for identifying key questions, always noticing customs, behaviors, and anomalies to explain, gathering data and categorizing to generate theories. His travels and knowledge of wine and food were a rich source of examples for his work and camaraderie. He did things in a big way, from academic passions like studying how language and the mind work and how people learn, to personal passions like food and football. Many stories about Roger occur at restaurants because meals were events. Many fans watch weekend football, but Roger created a room with half a dozen separate TVs, most with picture in picture, to monitor a dozen games simultaneously. Roger believed strongly in developing communities, not only in research labs and departments, but at the national and international level. He founded new fields in order to create lasting communities of like minds, in cognitive science and education. His studies of human memory led to launching the field of case-based reasoning, holding its 31st international conference this year. He was a co-founder of the field of Cognitive Science, the Cognitive Science Society, and the journal Cognitive Science. His PhD students at Stanford, Yale, and Northwestern, along with many developers, artists, and content creators at his companies and the Institute for the Learning Sciences will attest to the communities and cultural traditions he established over and over. For example, it is not unusual to hold a party when a PhD student finishes their dissertation, but Roger's parties had an extra. Every student with a PhD (prior and current) had to present a talent (real, imagined, feigned, or facetious) to the group, culminating with the new PhD revealing their secret talent. This ritual created a human connection among students beyond the academic. As his passion shifted to education, he led establishment of the field of the Learning Sciences, combining education, cognitive science, and computer science. In 1989 at Northwestern, he formed the Institute for the Learning Sciences and created the first Learning Sciences MS and PhD programs in the School of Education. He pioneered the study of stories in AI, spurring development of innovative story-based educational environments. He was himself a great story-teller; he used stories to connect, illuminate, and educate, both in his personal life and in his books. Finally, Roger cared deeply about impact. Long before the startup culture arose as a way for faculty to commercialize their ideas, Roger started companies because he believed that changes in how people should interact with technology, and how education should be done, would mainly happen through the business world. While at Yale, he started Cognitive Systems for building knowledge-rich intelligent systems, and Compu-Teach for building K-12 educational systems for personal computers. While at Northwestern he started Cognitive Arts and later Socratic Arts to develop learn-by-doing systems for training and education. In 2000 he left academics to focus on nothing less than transforming education with systems to support hands-on project-based teaching. His website lists some of the topics he cared about: “Making school less miserable for kids”, “fixing corporate training”, “getting the right information to people at the right time” “building the right kind of artificial intelligence systems”, “empowering people to develop effective learning experiences”, and, always and most importantly, “understanding how the human mind works”. Roger will be missed, but he also will still be here: his work continues to have a persistent and profound impact on a range of fields that are focused on the scientific study of the human mind. The authors declare that there is no conflict. Richard Granger received his Bachelor's and Ph.D. from MIT and Yale. He is a Professor at Dartmouth with joint appointments in the Department of Psychological and Brain Sciences, the Thayer School of Engineering, and the Cognitive Science Program; he directs Dartmouth's interdisciplinary Brain Engineering Laboratory (brainengineering.org), with publications and patents ranging from computation to cognition to basic neuroscience. He advises multiple technology corporations and government research agencies, is co-inventor of FDA-approved devices and drugs in clinical trials, and has been the principal architect of a series of advanced computational systems for military, commercial, and medical applications. David Leake received his PhD from Yale University. He is a Professor of Computer Science in the Luddy School at Indiana University (IU), where he served as Executive Associate Dean from 2012−2020, and a member of the IU Cognitive Science Program. His current research areas include case-based reasoning, explanation, and neuro-symbolic AI. He has authored/edited over 200 publications. He is Editor in Chief Emeritus of AI Magazine after 17 years as Editor in Chief. In 2014 he received the AAAI Distinguished Service Award. He is a Senior Member of AAAI. Christopher K. Riesbeck is an Associate Professor of Computer Science at Northwestern University, a Fellow of AAAI, the director of the CS Master's program, and co-director of the Center for Computer Science and the Learning Sciences.

  PublisherOA PDFDOI

• The Logic of Effective Iteration in Design-Based Research.

  ICLS · 2020 · 10 citations

  • Computer Science
  • Computer Science
  • Algorithm
  Publisher

• Enriching Students' Laboratory Experience: Using Software And Socratic Methods To Foster Reflective Thought In An Engineering Laboratory

  2020-09-03 · 1 citations

  articleOpen access1st authorCorresponding

  We have developed SASK (Socratic ASK * ), a domain-independent and rule-based architecture for implementing Socratic dialogs to foster better learning in well defined tasks by encouraging deeper reflections by the student. We have used SASK to build the Dialysis Mentor, a program that uses Socratic questioning to improve student performance and learning in an undergraduate biomedical engineering lab. Small usability tests and a pilot run in a dialysis lab suggests that Dialysis Mentor and SASK systems in general can improve the value of pre-defined learn-bydoing task experiences. We are now working on improving our SASK Mentors 1 and building authoring tools for them.

  PublisherOA PDFDOI

• Planning to iterate: Supporting iterative practices for real-world ill-structured problem-solving

  2018-01-01 · 9 citations

  article
  Publisher

• Overcoming barriers between volunteer professionals advising project‐based learning teams with regulation tools

  British Journal of Educational Technology · 2017-03-06 · 11 citations

  articleSenior author

  Abstract To provide the substantial support required for project‐based learning (PBL), educators can incorporate professional experts as design coaches . However, previous work shows barriers incorporating design coaches who can rarely meet face‐to‐face: (1) communication online is time‐consuming, (2) updating coaches online is not perceived as valuable, (3) students do not seek help, (4) coaches are not proactive online and (5) coaches struggle to gain the awareness from student online communications. How might we design socio‐technical systems that can incorporate professionals coaching? In a 6‐week university PBL product design program with three teams (four members per team) and five coaches, teams met with coaches on campus for 2‐hours a week, but otherwise communicated with teams online. We created and tested StandUp , a system designed to overcome coaching barriers online that: prompts team planning, goal setting and monitoring of progress and displays this information online to coaches. We collected and analyzed interview, observation and log data. We found StandUp helped participants overcome coaching barriers by providing students a way to regulate group learning which in turn automatically emailed reports to coaches thereby supporting coach awareness; coach awareness in turn prompted both online coaching and face‐to‐face coaching. This work provides evidence from one context. Future work should measure learning and explore different regulation scripts.

  PublisherDOI

• Simple Discrimination Nets

  2014-01-21

  article
  PublisherDOI

• Macros and Read-Macros

  2014-01-21

  article
  PublisherDOI

• Data Structures and Control Structures in Lisp

  2014-01-21

  article
  PublisherDOI

Frequent coauthors

• Eugene Charniak

  15 shared

• Drew McDermott

  14 shared

• James Meehan

  Roslin Institute

  13 shared

• Roger C. Schank

  8 shared

• Baba Kofi Weusijana

  7 shared

• Lin Qiu

  7 shared

• Lin Qiu

  7 shared

• Daniel Rees Lewis

  6 shared