Knowledge Organization and Enhanced Learning
Adapted and expanded by Esther Jordan from How Learning Works (Ambrose, et al et al, 2010)
If we help students to organize their knowledge, they will be more likely to make connections and build knowledge networks. This enables them to apply that knowledge in new contexts, retain it over time, and think critically about new information.
The second principle of learning is that “How students organize knowledge influences how they learn and apply what they know.” (Ambrose, et al, 44) If we help students to organize their knowledge, they will be more likely to make connections and build meaningful knowledge networks. This enables them to apply that knowledge in new contexts, retain it over time, and think critically about new information. (Bradshaw & Anderson, 1982; Reder & Anderson, 1980; Smith, Adams, & Schorr, 1978; Biggs and Tang, 2011). Knowledge organization can be developed over time and can be improved through instructor support.
While novices organize knowledge with sparse and superficial connections, experts (such as instructors) organize knowledge with dense and meaningful connections (Ambrose, et al, 46). Learning is enhanced when instructors facilitate guided opportunities for students to increase the density and meaning of the connections students make as they are exposed to and use new information. This essay will provide a brief overview of how knowledge organizations develop, how experts organize knowledge, and how instructors can help students develop more advanced knowledge networks for enhanced learning.
How knowledge organizations develop
The way people organize knowledge is based on patterns of experiences (Ambrose, et al, 46). These patterns tend to fall into three categories: cause and effect, shared meaning, and perceptual similarities. When we experience temporally contiguous events repeatedly (flipping a switch turns something on, etc.), we begin to build causal connections in our minds. When we are introduced to related ideas, such as fairness and equality or liberty and freedom, we begin to build associations of shared meaning. When we identify similar characteristics across distinct observations, we generate relational associations, such as category-member relationships, like mammal-dog, color-blue, or government system-democracy (Ambrose, et al, 47).
Another way we organize knowledge is through stories, or the narrative we construct to give meaning to new information or experiences. Purposeful narrative construction is a process that can help learners make explicit connections and derive meaning from them (Jordan 2018). For example, The Moth storytelling project suggests that stories must have “stakes” or be important, that they must have a clear theme, and that they should succinctly reach a resolution. Likewise, learners can construct stories to identify the meaning of new information, assign it a theme that fits within a larger framework, and describe it succinctly in a way that resolves why it should matter and how it can be used in similar or new contexts (Jordan, 2018).
What is important for instructors to keep in mind is that students tend to be better at providing evidence of learning when there is alignment between how they organize knowledge and the form of the assignments they complete (Eylon and Reif, 1984). We must consider how students will need to access and use the knowledge, and help them organize knowledge in a way that will facilitate effective retrieval and use of that knowledge (Ambrose, et al, 49). This can be done in many ways, such as asking students to identify patterns, categorize concepts, assign meaning to those categorizations, articulate the cause and effects of processes (such as in problem-solving or experimentation), or construct stories tie new knowledge together in meaningful ways.
How experts organize knowledge
Experts have developed dense and complex knowledge organization structures that enable them to not only recall information, but to be able to apply and make meaning of that information in entirely new or different contexts (Biggs and Tang, 2011). They tend to organize knowledge hierarchically, by fitting parts into a larger structure, such as theoretical approaches. They also tend to cross reference ideas and identify when a new idea does not fit into the existing theoretical approaches (Ambrose, et al, 51). They make use of multiple knowledge organizations, or as Ambrose, et al et al put it, “a web of classifications and connections” based on a multitude of variables (56). This web is “dense,” full of “meaning,” and “practically useful” (Ambrose, et al, 49, 55). It facilitates efficient retrieval, transfer, application, analysis, and creativity.
In addition to Ambrose, et al’s hierarchical depiction of knowledge organization, Biggs and Tang’s Structure of the Observed Learning Outcome, “SOLO,” Taxonomy provides a helpful depiction of how a learner progresses in developing knowledge organization (Biggs and Tang, 2011). A novice starts with thinking about ideas in isolation from each other, to being able to think in relative terms, integrate ideas into a larger structure, and to ultimately consider them in new contexts or use them to create original ideas, as an expert does.
How to help students begin to develop more advanced knowledge networks
The challenge for instructors is to reflect on how they organize knowledge, how they expect their students to do so, and facilitate knowledge organization activities for students to develop accordingly. It is not safe to assume that when students are taught about different ideas in isolation from each other, that they will automatically know how to relate those ideas to each other and draw upon them when they are given prompts to do so in new contexts. It is this inability to effectively transfer such knowledge from a first exposure or practice assignment to a summative assessment that can lead students to do well on homework or in class activities and then underperform on exams term projects and papers (Jordan, 2018).
There are simple strategies an instructor can implement to help students develop their knowledge networks for greater retention and transfer. The following is a list of such strategies, provided by Ambrose, et al et al (59-65). The book detailed explanations of each strategy.
- Create A Concept Map to Analyze Your Own Knowledge Organization
- Analyze Tasks to Identify the Most Appropriate Knowledge Organization
- Provide Students with The Organizational Structure of The Course
- Explicitly Share the Organization of Each Lecture, Lab, or Discussion
- Use Contrasting Boundary Cases to Highlight Organizing Features
- Explicitly Highlight Deep Features
- Make Connections Among Concepts Explicit
- Encourage Students to Work with Multiple Organizing Structures
- Ask Students to Draw A Concept Map to Expose Their Knowledge Organizations
- Use A Sorting Task to Expose Students’ Knowledge Organizations
- Monitor Students’ Work for Problems in Their Knowledge Organization
Ambrose, et al, S. A., Bridges, M. W., DiPietro, M., Lovett, M. C., & Norman, M. K. (2010). How learning works: 7 research-based principles for smart teaching. San Francisco, CA: Jossey-Bass.
Anderson & Krathwol. A Taxonomy for learning, teaching and assessing; a revision of bloom’s taxonomy of educational objectives. New York: Longman, 2001.
Biggs and Tang. Teaching for Quality Learning at University (fourth edition) by New York: McGraw Hill, 2011.
Bradshaw, G. L., & Anderson, J. R. (1982). Elaborative encoding as an explanation of levels of processing. Journal of Verbal Learning and Verbal Behavior, 21, 165-174.
Eylon, B., & and Reif, F. (1984). Effects of knowledge organization on task performance. Cognition and Instruction, 1, 5-44.
Jordan, E. S. (2018). Faculty Development Workshop: My Students Do Well on
Homework and Class Activities, but Not on Exams, Help! Kennesaw, GA: The Center for Excellence in Teaching and Learning, Kennesaw State University.
The Moth: True Stories Told Live. (2018, November 20). Retreived from https://themoth.org/share-your-story/storytelling-tips-tricks
Reder, L. M., & Anderson, J. R. (1980). A partial resolution of the paradox of interference: The role of integrating knowledge. Cognitive Psychology, 12, 447-472.
Smith, E. E., Adams, N., & Schorr, D. (1978). Fact retrieval and the paradox of interference. Cognitive Psychology, 10, 438-464.