DUET Seminar Series
DUET is a DUE Education Talk series sponsored by the Office of the Dean for Undergraduate Education (DUE) and organized by the Teaching and Learning Laboratory. This monthly series emphasizes current research on learning, cognitive psychology, educational technology, educational assessment, among other areas. All members of the MIT community interested in learning more about education are welcome to attend. DUET’s goal is to provide access to educational research that can support individual and institutional efforts to enhance residential student learning.
If you are interested in joining the mailing list to receive email reminders about DUET and other education talks of potential interest, send an email to firstname.lastname@example.org.
DATE: Wednesday, March 2, 2016
TIME: 2:00 p.m. - 3:30 p.m.
The Science of Learning: Retrieval as an Effective and Efficient Classroom Strategy
Are our teaching strategies effective? What can we do to improve student learning? Especially for science and engineering learning, how can we turn short-term cramming into long-term learning? How can we encourage flexible knowledge, where students remember basic information and also apply it in complex situations?
Supported by nearly 100 years of research, cognitive scientists have established robust teaching strategies that substantially improve student learning. These strategies reliably improve performance for diverse age groups, subject areas, and education rigor. In addition to an overview of these teaching strategies and research findings from cognitive science, specific approaches for implementation and potential challenges will be addressed.
Pooja K. Agarwal received her Ph.D. in Cognitive Psychology from Washington University in St. Louis, where she conducted basic memory research, as well as applied learning research in classroom settings. For more than 10 years, Agarwal has collaborated with distinguished memory scholar Henry L. Roediger, III (author of Make It Stick: The Science of Successful Learning). Agarwal’s research focuses on the use of retrieval as a teaching tool and also as a study strategy. A growing literature on retrieval practice demonstrates that when emphasis is placed on pulling information “out” (i.e., retrieving information from one’s mind), long-term learning is greatly improved compared to when emphasis is placed on getting information “in” (e.g., cramming or rereading textbook chapters). Agarwal’s dissertation, “Examining the relationship between fact learning and higher order learning via retrieval practice” was one of the initial examinations of the benefits from retrieval practice on complex college-level information.
Agarwal’s work has been published in leading journals, including the Journal of Educational Psychology, the Journal of Experimental Psychology: Applied, and the Journal of Applied Research in Memory and Cognition. She also served as Guest Editor for a special issue of Educational Psychology Review, entitled “Advances in cognitive psychology relevant to education” (September 2012). In addition to her career as a scientist, Agarwal earned elementary teacher certification and has enjoyed diverse teaching experiences at both K-12 and university levels. Agarwal is a recipient of the National Science Foundation (NSF) Graduate Research Fellowship, the American Psychological Association (APA) Early Graduate Student Researcher Award, and the Harry S. Truman Scholarship for her commitment to bridging the gaps between research, teaching, and policy.
DATE: Thursday, January 28, 2016
TIME: 2:00 p.m. - 3:30 p.m.
Educating Students: A Constant Balancing Act
We need to balance intellectual exploration and discovery with professional preparation and practical skills in the education we provide to our students—because of the changing nature of the workplace and the continuing skills gap noted by employers across industries (the very skills that we “believe” are foundational in what we do/teach). Dr. Ambrose will discuss a variety of the “balances” we need to consider:
- disciplinary content and intellectual skills
- intellectual skills and professional skills
- traditional literacies, competencies, skills and ever evolving literacies, competencies and skills
- HOW students learn with WHAT students learn
- engaging learner-centric pedagogy with appropriate technology
She will also offer suggestions about how we might achieve this, e.g., recognizing our own expert blind spot, promoting and fostering a growth mindset, explicit focus on calling out the skills embedded in the content we teach.
Dr. Ambrose is co-author of four books, most recently How Learning Works: Seven Research-based Principles for Smart Teaching (Jossey-Bass, 2010), which has been widely praised for integrating fundamental research in the cognitive sciences and practical application. She served as Associate Provost for Education, Director of the Eberly Center for Teaching Excellence, and a Teaching Professor in the Department of History at Carnegie Mellon before joining Northeastern in August 2012. She is an internationally recognized expert in college-level teaching and learning, and has conducted workshops and seminars for faculty and administrators throughout the United States and around the world. She is credited with building the international reputation of CMU’s Eberly Center as a center that translates research to practice in the design of curricula, courses and educational experiences for both undergraduate and graduate students.
Mitchel Resnick, LEGO Papert Professor of Learning Research and head of the Lifelong Kindergarten group at the MIT Media Lab, explores how new technologies can engage people in creative learning experiences. Resnick's research group developed the "programmable brick" technology that inspired the LEGO Mindstorms robotics kit. He co-founded the Computer Clubhouse project, a worldwide network of after-school centers where youth from low-income communities learn to express themselves creatively with new technologies. Resnick's group also developed Scratch, an online community where children program and share interactive stories, games, and animations
Director of the Pittsburgh Science of Learning Center
Using big data to discover tacit knowledge and improve learning
Despite our strong sense of conscious awareness of what we know and learn, most of what we know and learn is outside our conscious awareness. One estimate is that the knowledge we are aware of represents only about 30% of what we know. As a consequence, the typical approach of designing educational materials and technologies based on intuition and introspection is limited, even error-prone. Instead, educational design is better based on accurate cognitive models of student knowledge and learning. And accurate cognitive models are best built by combining constraints from computational modeling and from statistical models of student performance data. Online educational technology use is a great source of such data. I will illustrate these points with projects that employ 1) educational data mining and computational modeling to discover better cognitive models and 2) “close the loop” experiments to demonstrate that redesigning personalized online instruction based on these models improves student learning.
Professor Koedinger's background includes a BS in Mathematics, a MS in Computer Science, a PhD in Cognitive Psychology, and experience teaching in an urban high school. This multi-disciplinary preparation has been critical to his research goal of creating educational technologies that dramatically increase student achievement. Toward this goal, he creates "cognitive models", computer simulations of student thinking and learning, that are used to guide the design of educational materials, practices and technologies. These cognitive models provide the basis for an approach to educational technology called "Cognitive Tutors" in which he creates rich problem solving environments for students to work in and provide just-in-time learning assistance much like a good human tutor does.
Koedinger is a co-founder and board member of Carnegie Learning, Inc. and the CMU director of the Pittsburgh Science of Learning Center (PSLC). The PSLC is a $25 million National Science Foundation center that will provide researchers with the "LearnLab", an international resource for creating, running, and analyzing realistic and rigorous experiments on human and machine learning.
Differentiating Four Levels Of Engagement In Learning: The ICAP Hypothesis
Professor Chi will describe the ICAP hypothesis, embedded in a framework that differentiates overt engagement activities. The framework suggests that any learning activity can be classified into one of four distinct categories based on students’ overt behaviors or mode of engagement: Interactive or dialoguing, Constructive or generating, Active or selecting, and Passive or receiving. Based on this framework, the ICAP hypothesis predicts that as students become more cognitively engaged with the learning material, from passive to active to constructive to interactive, their learning will increase. Empirical support for the ICAP hypothesis will be provided by numerous studies in the literature, by studies undertaken in our lab, as well as in classrooms whose teachers we have trained. Limitations of the hypothesis, caveats to its generalizability, and benefits of the hypothesis for research and instructional design will also be discussed. Our immediate effort is the development of an online module to train teachers how to design and improve classroom activities that move students from one level of engagement to a higher level of engagement. If time permits, I will also describe briefly our findings about learning from observing videos of tutorial dialogues.
Improving Learning and Reducing Costs: New Models for Online Learning
Colleges and universities are offering thousands of fully online courses, ostensibly altering centuries-old methods of teaching and learning. Few of these courses, however, make significant improvements in either the cost or quality dimensions of student learning. Instead, they frequently replicate face--to-face pedagogies and organizational frameworks rather than taking advantage of IT's capabilities to design new learning environments. Using examples drawn from NCAT's work with more than 200 colleges and universities, this presentation will discuss new models for online learning that improve the quality of student learning and reduce instructional costs.