Using Cognitive Science Research on Learning to Improve Education
What are powerful ways to help people learn and to produce lasting change in their behavior and habits?
What principles and techniques lead to excellent educational programs?
Every time we teach or learn, we are making decisions and taking actions that can be understood as implicitly (often automatically) answering these two questions. Social science research is unlikely to provide definitive laws and generalizations, whether it relies on experiments (psychology & education), qualitative observations (education & sociology), or defining concepts and reasoning logically about theories (philosophy). But we can use the knowledge gained from social sciences to substantially improve how we understand and reason about the knowledge and processes that underlie learning.
For any topic we can imagine, there is relevant information on it, even if dredging it up requires a collaboration between an expert, their favorite search engine, and Google Scholar. Scientific research in Cognitive Science and Education has produced literally thousands of journal papers, edited volumes, analyses of teaching techniques, evaluations of technology, mass media books, and practical guides. Since exposure to research can range from non-existent to overwhelming, this document contains a selection of reading material to provide a condensed answer to those original two questions.
While these choices obviously can’t be definitive or comprehensive, they represent principles that play a central theoretical role in understanding learning and whose value has been evident across many practical contexts. They have recurred repeatedly in my experience trawling through thousands of papers and books on human learning and reasoning, considering practical educational implications while in hundreds of lectures, discussions, and meetings, and examining at least a hundred different e-learning and online education programs and multimedia. I wish I had first read each of these when I started to formally study learning seven years ago, and would recommend them to anyone who has limited time.
These are links to abstracts or slides from overview presentations I gave that synthesize research in order to apply it to practical online contexts, such as improving learning from MOOC videos, interactive mathematics exercises, corporate e-learning, and acquiring general learning strategies. They were at Google (Tech Talk), Bloomsburg's Corporate Advisory Council Meeting, Khan Academy, and EdX.
This is a workshop paper that focuses on motivation and learning through explanation, and includes demos of how to apply this research to a specific MOOC video and Khan Academy math exercise.
Williams, J.J. (2013). Applying Cognitive Science to Online Learning. Paper presented at the Data Driven Education Workshop at Conference on Neural Information Processing Systems.
Hess, F. M., & Saxberg, B. (2013). Breakthrough Leadership in the Digital Age: Using Learning Science to Reboot Schooling. Corwin Press.
Benassi, V. A., Overson, C. E., & Hakala, C. M. (Eds.) (2014). Applying science of learning in education: Infusing psychological science into the curriculum. Washington, D.C.: Society for the Teaching of Psychology. (PDF)
Pashler, H., Bain, P. M., Bottge, B. A., Graesser, A., Koedinger, K., McDaniel, M., & Metcalfe, J. (2007). Organizing Instruction and Study to Improve Student Learning. IES Practice Guide. NCER 2007-2004. National Center for Education Research. (online pdf)
Ambrose, S. A., Bridges, M. W., DiPietro, M., Lovett, M. C., & Norman, M. K. (2010). How learning works: Seven research-based principles for smart teaching. Jossey-Bass. (Amazon)
Clark, R. C., & Mayer, R. E. (2011). e-Learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning (3rd ed.). Pfeiffer. (Google Books)
Willingham, D. T. (2010). Why Don't Students Like School. Jossey-Bass. (Amazon)
Tucker, M. S. (2011). Surpassing Shanghai: An Agenda for American Education Built on the World's Leading Systems. Harvard Education Press. Cambridge, MA. (Amazon) (Google Books)
Sawyer, R. K. (Ed.). (2006). The Cambridge handbook of the learning sciences. Cambridge: Cambridge University Press.
Bransford, J., Brown, A., & Cocking, R. (2000). How people learn: Brain, mind, experience, and school. National Academy Press.
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14, 4-58.
Hyperlinked Reading List from New Approaches from Cognitive Science to Learning and Education, Psychology Graduate Seminar at Indiana University taught by Rob Goldstone in Fall 2013.
Williams, J.J. (2013). Improving Learning in MOOCs by Applying Cognitive Science. Paper presented at the MOOCshop Workshop, International Conference on Artificial Intelligence in Education, Memphis, TN. (paper)
Willingham, D. T. (2012). When can you trust the experts: How to tell good science from bad in education. Wiley. [Google Books]
Koedinger, K. R., Corbett, A. C., & Perfetti, C. (2012). The Knowledge-Learning-Instruction (KLI) framework: Bridging the science-practice chasm to enhance robust student learning. (PDF)
APS Observer - Toward the Tipping Point - Grover Whitehurst, IES
APS Observer, How We Learn, Hal Pashler
Intuitively, we often seem to think of learning as adding information to a bucket – facts and concepts go in, and get retrieved later. One of the substantive insights of research in memory, high-level cognition, and education is to instead use a framework in which the goal of education is to produce transfer of knowledge. How do you get people to process and encode knowledge so that it is spontaneously transferred – retrieved and applied in relevant future contexts?
Bransford, J. D., & Schwartz, D. L. (1999). Rethinking transfer: A simple proposal with multiple implications. Review of Research in Education, 24, 61-100. (online PDF)
Mestre, J. P. (2005). Transfer of learning from a modern multidisciplinary perspective. Information Age Pub Incorporated. (Google Books) (Hammer et al chapter) (Schwartz et al chap.)
Barnett, S. M., & Ceci, S. J. (2002). When and where do we apply what we learn?: A taxonomy for far transfer. Psychological Bulletin, 128(4), 612–637. doi:10.1037//0033-2909.128.4.612 (online PDF)
One of the most effective ways to improve learning may not stem from a direct focus on learning, but instead by changing people's implicit underlying assumptions about whether intelligence is a quality that is fixed, or a quality that is malleable and can grow.
It may seem obvious – or at least most would agree once it's pointed out to them – that people will be more likely to learn if they think they can succeed at it. But many interventions to change behavior or improve learning don't target the specific belief about the nature of intelligence, even if they might offer encouragement. The key value of the work on implicit theories is explicating what form this knowledge takes, how it can be changed, and what the impact is.
Studies by PERTS have revealed extremely impressive findings: two 45 minute classes teaching middle school students and undergraduates that intelligence is malleable (rather than fixed) can improve their actual grades. Very few interventions impact such an important and broad measure, despite using far more time and resources. They are also often restricted to just one content area or set of skills.
Dweck, C.S. (2008). Can personality be changed? The role of beliefs in personality and change. Current Directions in Psychological Science, 17, 391-394. (online pdf)
Paunesku, D., Walton, G.M., Romero, C.L., Smith, E.N., Yeager, D.S., & Dweck, C.S. (2015). Mindset Interventions are a Scalable Treatment for Academic Underachievement. Psychological Science.
Extended List of References about Mindset Research and Interventions
Walton, G. M. (2014). The new science of wise psychological interventions. Current Directions in Psychological Science, 23(1), 73-82.
Yeager, D. S., & Walton, G. M. (2011). Social-Psychological Interventions in Education: They're Not Magic. Review of Educational Research, 81(2), 267–301. doi:10.3102/0034654311405999
Cohen, G. L., Garcia, J., Apfel, N., & Master, A. (2006). Reducing the racial achievement gap: A social-psychological intervention. science, 313(5791), 1307-1310. (online reference)
Wilson, T. D. (2006). Behavior. The power of social psychological interventions.Science (New York, NY), 313(5791), 1251. [online pdf]
Hulleman, C. S., & Harackiewicz, J. M. (2009). Promoting interest and performance in high school science classes. Science, 326(5958), 1410-1412. [online pdf]
Case-based reasoning is a topic that gets at issues of how people learn from studying cases that manifest abstract principles, and are then generalized in encountering new situations and new problems. It's an interesting context to think about issues like how people are able to use abstract generalizations, by linking them to specific features of cases or conditions in which they are relevant.
Kolodner, J. L. (1992). An introduction to case-based reasoning. Artificial Intelligence Review, 6(1), 3-34.
Kolodner, J. L. (1997). Educational implications of analogy: A view from case-based reasoning. American psychologist, 52(1), 57. [Online Reference]
Kolodner, J. L. (Ed.). (1993). Case-based learning (Vol. 10, No. 3). Springer. [Google Books Preview]
Benjamin, A. S. & Ross, B. H. (in press). The causes and consequences of reminding. In A. S. Benjamin (Ed.), Successful remembering and successful forgetting: A Festschrift in honor of Robert A. Bjork. New York, NY: Psychology Press.
Sweller, J. (2006). The worked example effect and human cognition. Learning and Instruction, 16(2), 165-169. (online reference)
Atkinson, R. K., Derry, S. J., Renkl, A., & Wortham, D. (2000). Learning from examples: Instructional principles from the worked examples research. Review of educational research, 70(2), 181-214. (online reference)
Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition and Instruction,2(1), 59-89.
Engaging in comparison or 'analogical encoding' (e.g. figuring out how an atom and the solar system are similar and different) has also been found to be an effective way of discovering abstract relationships. Even if you haven't thought about comparison much, you can probably find a way to link it to a learning topic or use it beneficially to improve learning – it’s a good examples of a domain-general learning strategy.
Gentner, D., Loewenstein, J., & Thompson, L. (2003). Learning and transfer: A general role for analogical encoding. Journal of Educational Psychology, 95(2), 393-408. doi: 10.1037/0022-0663.95.2.393.
Many acts of interpreting and representing a new situation or educational materials (e.g. think of learning math) can be interpreted as involving analogies to past experience. Providing analogies that appropriate relate new concepts and principles to a knowledge structures that a learner already possesses are extremely helpful for deep and lasting learning, although we often instead seem to communicate abstract concepts primarily through words.
Richland, L.E., Zur, O., & Holyoak, K. (2007). Cognitive supports for Analogies in the mathematics classroom. Science, 316, 1128-1129. (online PDF)
Gentner, D. & Smith, L. (2012). Analogical reasoning. In V. S. Ramachandran (Ed.) Encyclopedia of Human Behavior (2nd Ed.). pp. 130-136. Oxford, UK: Elsevier.
Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235-266.
Schwartz, D. L., & Martin, T. (2004). Inventing to prepare for future learning: The hidden efficiency of encouraging original student production in statistics instruction. Cognition and Instruction, 22(2), 129-184. [Online PDF]
Kolodner, J. L., Camp, P. J., Crismond, D., Fasse, B., Gray, J., Holbrook, J., & Ryan, M. (2003). Problem-based learning meets case-based reasoning in the middle-school science classroom: Putting learning by design into practice. The journal of the learning sciences, 12(4), 495-547. [online reference]
Peer instruction involves making lectures interactive by pausing for students to explain concepts to each other or solve problems, as opposed to lecturing continuously, and is very popular now in the concept of the "flipped lecture". "Reciprocal Teaching” is a learning technique that teaches students about what is needed to understand written content deeply, by alternating between learners trying to teach others as well as being taught. Both topics tie in well with theoretical issues in cognitive science, development, and education – like how generating explanations helps people learn.
Explanation and Learning reading list
Farewell, Lecture? Eric Mazur, Science. (2009)
Peer Instruction: Ten Years of Experience and Results. (2001)
Palinscar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering and comprehension-monitoring activities. Cognition and instruction, 1(2), 117–175. (online pdf)
There is an excellent literature on "testing effects" and the benefits of "retrieval practice". These studies demonstrate that testing people's knowledge of study materials can enhance learning more than additional time spent studying. The empirical work has focused on recall from memory, but you can also consider "tests" more broadly in a way that might be relevant to you: Answering any kind of question, doing a writing exercise, generating explanations, or solving problems.
Karpicke, J. D., Blunt, J. R. (2011). Retrieval practice produces more learning than elaborative studying with concept mapping. Science, 331(6018), 772-775. (internal link)
Roediger, H. L., III, Putnam, A. L., & Smith, M. A. (2011). Ten Benefits of Testing and Their Applications to Educational Practice. Psychology of Learning and Motivation-Advances in Research and Theory. (Google Books Link)
Rohrer, D. (2009). The effects of spacing and mixing practice problems. Journal for Research in Mathematics Education, 40(1), 4-17.
There are more references here: http://psych.wustl.edu/memory/TELC/
Koedinger, K. R. & Corbett, A. T. (2006). Cognitive Tutors: Technology bringing learning science to the classroom. In K. Sawyer (Ed.) The Cambridge Handbook of the Learning Sciences, (pp. 61-78). Cambridge University Press.(online pdf)
Ritter S., Anderson, J. R., Koedinger, K. R., & Corbett, A. (2007). Cognitive tutor: Applied research in mathematics education. Psychonomic Bulletin & Review, 14 (2):249-255. (online pdf)
Aleven, V., McLaren, B. M., & Sewall, J. (2009). Scaling up programming by demonstration for intelligent tutoring systems development: An open-access website for middle-school mathematics learning. IEEE Transactions on Learning Technologies, 2(2), 64-78. (online pdf)
VanLehn, K. (2006) The behavior of tutoring systems. International Journal of Artificial Intelligence in Education. 16, 3, 227-265. (online pdf)
Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in education, 5(1), 7-74. (online pdf)
Nicol, D. J., & Macfarlane‐Dick, D. (2006). Formative assessment and self‐regulated learning: A model and seven principles of good feedback practice. Studies in higher education, 31(2), 199-218. (online pdf)
Gikandi, J. W., Morrow, D., & Davis, N. E. (2011). Online formative assessment in higher education: A review of the literature. Computers & Education, 57(4), 2333-2351. (citation)
Shute, V. J. (2008). Focus on formative feedback. Review of educational research, 78(1), 153-189. (citation)
It would be impossible for either of these resources to be comprehensive, but I think it is worth making a modest effort. The goal is for these to be resources I wish I had been aware of when I first tried to connect basic research on learning to practical educational contexts. The website has a list of sites that serve similar functions, and feel free to email omissions.
These statements by the Editor-in-Chief at Science capture the motivation well:
“When I began my academic career as an assistant professor at Princeton University in 1966, I sought to learn everything about what others had discovered previously, before beginning my research on chromosome replication. Yet when I taught, I rarely sought to build on what other teachers had developed before me.”
“The World Wide Web is a fantastic information resource, but it can be overwhelming. Many had hoped, for example, that the U.S. National Science Digital Library Project might go a long way toward solving this problem. But the collection of science education Web sites that resulted, although a valuable resource, contains so many entries that additional guidance seems warranted.”
Even though there’s extensive research on learning across many fields, this is often not synthesized and presented in a form that teachers, developers of educational technology, or even researchers can use, evaluate, and extend. And while the internet provides extensive content, developing a website or wiki focused on scientifically supported and practically proven learning principles can organize online content, make it readily accessible, and allow a forum for different approaches to interact and multiple opinions to be expressed. For example, at the moment, is there a single website you could confidently endorse for a busy educator or researcher?
CognitiveScience.co/Learn is an old website (no longer under development) with links to research on learning that I've found particularly useful.