Research-based learning findings
Here we summarize several researched-based findings that have been shown to facilitate student learning and are useful for in-class and online learning. Click on each finding to find out more about each each, including implications for teaching, examples of their usage at MIT and references.
Spaced and interleaved practice: Spacing and interleaving problems types (A1B1C1....B2C2A2....C3A3B3) result in greater learning gains and better descrimination among problem types than asking students to do similar problem types in succession over a single period of time (A1A2A3B1B2B3C1C2C3). .
Pre-/Post-testing: Students’ prior knowledge could be correct, incomplete and/or faulty. If prior knowledge is faulty (misconceptions) students might resist or ignore new information that conflicts with it. Pre-/post-testing also allows instructors to determine what misconceptions students come with and how much conceptual change happens during a module or course .
Active learning: Instruction that requires students to engage cognitively and meaningfully with content results in better learning than instruction where students are solely exposed to information passively. Distinguishing between behavioral activity and cognitive activity is critical to designing effective active learning.
"Active learning leads to increases in examination performance that... raise average grades by half a letter. ." Discussing concept questions, solving problems, and annotating one another's work are examples of implementations of active learning in the classroom.
First principles of instruction: David Merrill synthesized the key principles common among leading instructional design frameworks . Namely, learning is promoted when:
- learners solve tasks; problems that integrate multiple pieces of skills and knowledge
- existing knowledge is activated as a foundation for new knowledge
- new knowledge is demonstrated to the learner,
- new knowledge is applied by the learner with feedback, and
- new knowledge is integrated into the learner’s world, providing a foundation for the next cycle of learning
Four-component instructional design (4C/ID): The 4C/ID model is a specific framework, consistent with David Merrill’s principles (see ‘First principles of instruction’), and based on research on the limitations of working memory (cognitive load theory) . Instructional blueprints are described using four basic components:
- supportive information
- procedural information, and
- part-task practice
For questions on research findings and/or instructional frameworks, please contact the Residential Education team in the Open Learning.
 Roediger, H. L., & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15(1), 20–27. DOI
 Roediger, H. L., & Pyc, M. A. (2012). Inexpensive techniques to improve education: Applying cognitive psychology to enhance educational practice. Journal of Applied Research in Memory and Cognition, 1(4), 242–248. DOI
 Renkl, A. (2014). Learning from worked examples: How to prepare students for meaningful problem solving. In V. A. Benassi, C. E. Overson, & C. M. Hakala (Eds.). Applying science of learning in education: Infusing psychological science into the curriculum. HTTP (downloaded PDF available)
 Adams, W. K., & Wieman, C. E. (2011). Development and validation of instruments to measure learning of expert‐like thinking. International Journal of Science Education, 33(9), 1289–1312. DOI
 Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410–8415. DOI
 Merrill, M. D. (2002). First principles of instruction. Educational Technology Research and Development, 50(3), 43–59. DOI
 van Merrienboer, J. J. G., Clark, R. E., & De Croock, M. B. M. (2002). Blueprints for complex learning: The 4C/ID model. Educational Technology Research and Development, 50(2), 39–64. DOI
In addition to these resources, we have found the following teaching-and-learning frameworks extremely valuable:
 Krathwohl, D. R. A revision of Bloom's taxonomy: An overview (2002). Theory Into Practice, 41(4), 212-218. This article reviews the framework of the original Taxonomy of Educational Objectives, a scheme for classifying educational goals, objectives, and standards, describing how the revised Taxonomy differs from the original. DOI
 Chi, Michelene TH, and Ruth Wylie. The ICAP Framework: Linking Cognitive Engagement to Active Learning Outcomes (2014). Educational Psychologist , 49(4), 219-243. This article proposes that the engagement behaviors can belong to one of four modes (from most to least active): Interactive, Constructive, Active, and Passive (ICAP). The ICAP hypothesis predicts that the students learn more as they engage with learning materials from passive to active to constructive to interactive mode. PDF, DOI
 Tom Bennett (2013). Teacher proof: why research in education doesn't always mean what it claims, and what you can do about it. Routledge.
 Richard E. Mayer, ed. (2014). The Cambridge handbook of multimedia learning. 2nd edition. Cambridge University Press.
 M. David Merrill (2013). First principles of instruction: Identifying and designing effective, efficient and engaging instruction. Pfeiffer.
 Jeroen J. G. van Merriënboer and Paul A. Kirschner (2012). Ten steps to complex learning. Routledge.