In this blog we describe a learning model that is used successfully in many diverse environments and across age groups. We focus on K-12 education(1) but it works just as well with adult learning and industry teaching and learning.(2) Learning models are not new. They have been used for centuries (e.g., Plato, Aristotle, Rousseau, Pestalozzi, Froebel, Locke, Jefferson, Mann, Dewey, Piaget, Pavlov, Skinner, Simon, Montessori, Vygotsky) to enhance teachers’ roles in the classroom.(3)

A large body of empirical research has emerged that help learning scientists define learning environments and understand learning outcomes. What is new in today’s learning world draws from the deployment of neuroscience knowledge and techniques in classrooms. This iterative learning cycle model, which originated in a time when neuroscience was not translated into classrooms, is nevertheless ideally suited to a world of learning that employs traditional and nuanced methodologies and techniques. It is unique in many ways. Having emerged from “anchored instruction” experiments conducted at Vanderbilt in the 1990’s, it was used across the

Figure 1: The Challenge Cycle

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U.S. Later.(4) Concepts from this model were incorporated into the 1999 National Academies Press publication: How People Learn,(5) and it is still used around the world today. In this blog we connect neural substrates to the articulation of the model in the learning environment and outline why adherence to certain prescribed application works. We describe each component of the model and offer empirical evidence for why it is so successful in classrooms for teachers and for students who love to engage with it.

This cyclical approach embraces a constructive theory of learning by actively engaging learners in the process itself. Students engage in explicit problem solving (challenges) and work to find meaningful solutions. The model ‘makes visible’ what students already know (prior knowledge) and ties existing knowledge with new information in a comprehensive way that promotes deep understanding. The philosophy behind using an iterative cycle is rooted in the concept of Adaptive Expertise (AE)(6), with the stated intention of preparing students for future learning (PFL). Many learning models in use in schools today tend to focus on what learning scientists refer to as sequestered problem solving (SPS) methodologies.(7) With such methodologies, a teacher introduces curricular content, students memorize facts and procedures intended to show that they engaged in the learning process, and the teacher tests students’ retention and recall of the content based on summative tests. Typically, students pass or fail based on their responses. These are not learning measures that support deep understanding.(8) Unfortunately and more ruinous that this, such methodologies tend to contribute to “mile wide, inch deep” environments where inert fragments of knowledge remain disconnected in the students’ mind.(9)

An iterative learning cycle turns this model on its head. Students are allowed, even encouraged, to make mistakes and are given the opportunity to reflect on and learn from them. Mistakes viewed in a cyclical iterative process that rewards decision-making, risk-taking, and discourse.(10) Furthermore, students engage the problem-solving nature of each challenge by working collaboratively in groups to achieve sense making and understanding as a result of discussions with peers and experts relating to information presented through short powerful perspectives. Finally, endemic to this model are elements of solid pedagogical enunciation where metacognitive presences are instantiated in a reflective and inclusive manner.(11) The resulting corpus of understanding after students have moved successfully through a cycle is progressively incorporated into the next iterative approach. This way, students do not perceive their effort as “busy work” or routinized scripts to “turn in” for a grade, but develop deep meaning in the learning process that uncovers new information relevant to a meaningful project in their lives.

Future blogs will introduce each segment of the cyclical encounter and add the neuroscience of pedagogy that enables the learning engagement and satisfaction from the learner’s standpoint.

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REFERENCES

  1. T. Martin et al., paper presented at the American Educational Research Association (AERA), San Francisco, April 17, 2006 2006.
  2. T. K. O’Mahony et al., A comparison of lecture-based and challenge-based learning in a workplace setting: Course designs, patterns of interactivity, and learning outcomes. Journal of the Learning Sciences, Routledge 21, 182-206 (2012).
  3. J. T. Gatto, The underground history of American education: A schoolteacher’s intimate investigation into the problem of modern schooling. (The Odysseus Group, New York, 2000).
  4. PT3 Group at Vanderbilt, Three AMIGO3s: Using “Anchored Modular Inquiry” to help prepare future teachers. Educational Technology, Research and Development 51, 105-123 (2003).
  5. J. D. Bransford, A. L. Brown, R. Cocking, How People Learn: Brain, Mind, Experience and School. (National Academy Press, Washington, DC, 2000).
  6. G. Hatano, K. Inagaki, in Child development and Education in Japan, H. Stevenson, H. Azuma, K. Hakuta, Eds. (Freeman, New York, 1986), pp. 262-272.
  7. D. L. Schwartz, J. D. Bransford, D. Sears, in Transfer of learning: Research and perspectives, J. Mestre, Ed. (Information Age Publishing, Greenwich, CT, 2005), pp. 1-51.
  8. L. Darling-Hammmond, B. J. Barron, P. D. Pearson, A. H. Schoenfeld, E. K. Stage, Powerful learning: What we know about teaching for understanding. (John Wiley & Sons Inc, 2008).
  9. A. N. Whitehead, The aims of education. (MacMillan, New York, 1929).
  10. J. Willis, Research-based strategies to ignite student learning: Insights from a neurologist and classroom teacher. (Association for Supervision and Curriculum Development, Alexandria, VA, 2006).
  11. D. Wilson, M. Conyers, Five big ideas for effective teaching: Connecting Mind, Brain, and Education Research to Classroom Practice. (Teachers College Press, New York, NY, 2013).