DUET Speaker Series
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.
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DATE: WED, October 26, 2016
TIME: 10:30 a.m. -12:00 noon
Mindbugs: The Ordinary Origins of Bias
Conscious experience provides an immediate, compelling, and incomplete account of mental life. Much of perception, thinking, and action is shaped by mental activity that occurs outside of conscious awareness or conscious control. Because of that, judgment and action can be unintentionally influenced by factors that we do not recognize, and may not value.
There will be three parts to the session: (1) demonstrations of perceptual and cognitive illusions illustrating that we don't have complete access to or control over our own minds, (2) examples of how this can translate to social judgment of ourselves and others, and (3) research evidence and implications for diversity and inclusion in teaching.
Humans use a variety of effective strategies for translating the world outside the mind into a mental representation inside the mind. However, these processes are not direct translations of reality. Experience is a combination of the immediate input and our expectations and theories of how the world operates derived from previous experience. These processes are highly efficient, largely unconscious, and prone to surprising, sometimes amusing, ‘errors.’ Research in cognition and perception reveals some of the basic processes that occur outside of awareness to manage interpretation and interaction with reality.
The basic mental processes also impact our perception, judgment, and action as social beings. We develop expectations, beliefs, and attitudes about social groups. Some of these expectations are explicit in that we know we have them, we endorse them as being valid, and use them to inform judgment. Others are implicit in that we do not necessarily know that we have them, nor might we be aware that they are guiding our judgment. Sometimes, the explicit and implicit beliefs can be in conflict creating a circumstance that one’s intention might be to behave one way, and one’s actions might be different.
These processes have application in many aspects of social life, but the particular focus of this discussion is on their implications for diversity. The focus of this discussion is on their implications for diversity and inclusion in teaching. Implicit expectations influence judgments of self and others, and may play a role in areas including (but not limited to) bias in grading, participation in class discussions, and inclusion in classroom settings.
Calvin Lai received his PhD in Social Psychology from the University of Virginia in 2015. His research concerns unconscious thoughts which contribute to discrepancies between what people value (e.g., racial equality) and what people end up doing (e.g., racial discrimination). His work employs large-scale comparative methods to find the most effective interventions for combating unconscious biases and their impacts on discrimination. Lai's work has been published in leading journals such as the Science, Journal of Experimental Psychology: General, and Perspectives on Psychological Science.
Dr. David Miele, Buehler Sesquicentennial Assistant Professor, Counseling, Developmental, and Educational Psychology Department
DATE: WED, Novebmer 30, 2016
Increasing Student Motivation through Instructional Practices
This session will address two types of instructional practices for increasing student motivation. The first type involves fostering students' "growth mindsets"; that is, helping them to think about intelligence and ability as something that can be improved over time with effort. The second type aims to enhance the perceived utility or relevance of course content. We'll review theory and discuss empirical research examining the efficacy of these practices in different learning contexts and for diverse groups of students.
Improved Learning and Retention by Augmenting STEM Curriculum with Computational Thinking, Self-Assessment and Student-Created Visualizations
We are teaching materials science and mathematics to sophomores through problem-based learning in the context of their current and future coursework. The students are required to create, code, and visualize concepts from their discipline.
This is part of a larger project called CodeSeal (http://codeseal.org) . CodeSeal provides a framework of curated content, authoring tools, LMS, and data collection and analysis. CodeSeal’s goals are to crowd-source computational STEM curriculum and research its effectiveness in different contexts.
Learning is modular. Within each module, a student is presented a scaffolded set of exercises. These exercises culminate in an interactive graphical descript and scientific narrative that each student produces and presonalizes for themselves. Each scaffold in the process contains a problem that the student must complete before proceeding. After submitting a solution, a student is given access to a step-by-step “expert solution.” These problem/solution cycles can prompt a student to perform a technical task or ask a student to reflect on how to craft a compelling narrative or visualization to communicate a particular concept to others. This is a modern form of “learning-by-doing” and “apprentice-based learning.”
The modules have built-in frequent recall and require the student to reuse concepts they have recently acquired. Computational thinking is interleaved with core concepts from materials science and mathematics. The modules also employ gamification wherein they can exchange points they have earned by performing related tasks for subsequent hints on problems.
CodeSeal has been used in several different modalities. A selected set of modules have been used to teach semester long topics at MIT and elsewhere. We have used CodeSeal to deliver week-long master classes around the world and via web-conferencing.
We are collecting data on how students are approaching problems, including standard interaction data about time-on-task, keystrokes, and button presses. We also record each piece of code a student writes while they prepare their final solution. In addition to a student's final solution, this data provides insight into how much effort went into developing it and how they arrived at it. This data will eventually allow us to create an automated teaching and grading assistant that can help flag students who need immediate intervention, classify students programming style, classify different learning paths, and identify important learning moments within those learning paths.
Dr. Diane H. Soderholm, Senior. Instructional Designer, Department of Mechanical Engineering, MIT
Education Director, AIM Photonics Academy
Education, Director, Bernard M. Gordon-MIT Engineering Leadership Program
Using Instructional Design Models for Course Design
This will be a participatory, interactive session using and comparing two instructional design models to design a course. As we design, we'll discuss topics such as constructive alignment, backwards design, how learning works, value of ID models, among others.
Diane Soderholm received her Ph.D. in Instructional Design, Development and Evaluation from Syracuse University where she also an instructional designer in The Center for Instructional Development. For the past 18 years Dr. Soderholm has collaborated with faculty design, development, implementation and evaluation of courses, seminars, programs, workshops, and other learning experiences in technical, leadership and professional skills areas, with the Center for Innovation in Product Development, AeroAstro, CDIO Initiative in Engineering Education, the Bernard M. Gordon-MIT Engineering Leadership Program, and the MIT-Skoltech Initiative. Prior to MIT, she designed and developed training and education for University of Maryland University College, Coalition for Juvenile Justice, and a variety of Fortune 100 companies through the consulting company Information Mapping.
How to Motivate Your Students
In this workshop, Professor Escrig will address the student motivation from the perspective of motivational levers. He will provide teaching tips to activate and sustain student motivation. By the end of the workshop, you will be able to:
1) identify the presence or the absence of motivational levers in teaching activities; and 2) propose teaching activities that activate student motivation.
Benoît ESCRIG received the Eng. degree in Electrical Engineering from IPB-ENSEIRB-MATMECA, Bordeaux, France in 1992, and the M.Sc. degree in Signal Processing from the Institut National Polytechnique Toulouse in 1993. From 1993 to 1997, he worked as a research engineer in High Frequency (HF) modems with Rockwell-Collins France Inc. In December 1997, he received the Ph.D. degree in Signal Processing from the Institut National Polytechnique Toulouse, within the Signal and Communication Group of the IRIT Laboratory. From 1998 to 1999, he was a postdoctoral research associate at the French Space Agency.
From 1999 to 2013, Benoît was an Assitant Professor with IPB-ENSEIRB-MATMECA. Since september 2013, he has been an Associate Professor with INP-ENSEEIHT. As a researcher, he works with the Signal and Communication group of the IRIT Laboratory.
In 2014, Benoît ESCRIG was appointed as a Pedagogical Advisor for the Institut National Polytechnique Toulouse.
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.
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.