When Learning Is Too Good to Be True: Addressing Common Myths, Misrepresentations, and Misconceptions to Foster Self-Regulated Learning

When Learning Is Too Good to Be True: Addressing Common Myths, Misrepresentations, and Misconceptions to Foster Self-Regulated Learning

Franklin M. Zaromb, Richard D. Roberts
DOI: 10.4018/978-1-6684-6500-4.ch002
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Students today enjoy unprecedented freedom and autonomy to choose and manage what, when, where, and how they learn. However, many students squander these opportunities by embracing learning techniques that, at best, can help them attain short-term performance objectives but are relatively ineffective at fostering long-term learning and retention. This chapter describes research findings that highlight and address some of the most common misconceptions and cognitive biases that can impede or undermine self-regulated learning processes. The authors propose several research-based recommendations for addressing these misconceptions and biases in the design of self-regulated learning programs and curricula. These include integrating “desirable difficulties” in learning; instructing students about effective learning strategies along with common myths, misconceptions, and biases of learning; and tailoring interventions to improve critical social and emotional learning skills and mitigate relevant cognitive biases.
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Conditions of learning that make performance improve rapidly often fail to support long-term learning and transfer, whereas conditions that create challenges and slow the rate of apparent learning often optimize long-term retention and transfer (Bjork & Bjork, 2011).



Recent years have witnessed extraordinary technological advances that have provided students and teachers throughout the world with a rich and rapidly expanding menu of relatively inexpensive, and often free, educational resources for both learning and instruction. With the rise and proliferation of Massive Open Online Courses (MOOCs), mobile educational apps, social media, virtual reality, and blended learning environments, people today enjoy unprecedented freedom and autonomy to choose and manage what, when, where, and how they learn. However, with such freedom and autonomy come the responsibilities and challenges of making informed judgments and decisions. What programs and learning strategies would best address each person’s educational needs? How should they manage their learning activities? And on what criteria and metrics should they base these decisions?

The challenge of attempting to answer this loaded set of questions is manifold. For example, one must have adequate information about the quality and utility of the educational resource options under consideration. But such information may be difficult or even impossible to obtain for the smartest of users, the best practitioner, or even the most accomplished of scientists. Private companies and educational institutions seldom evaluate the efficacy of their programs, possibly because they do not consider it to be critical to their business model. Or if it is, rigorous evaluation studies come with a hefty price tag.

There are resources like the What Works Clearing House (https://ies.ed.gov/ncee/wwc/) from which some of this information can be gleaned (usually from those organizations bold enough to be evaluated by such rigorous standards). In so doing, one likely is disappointed by the small number of interventions that have strong proof of efficacy. With over 1,000 interventions in the database, and nearly 12,000 studies variously meant to support these programs, less than 2% of studies provide strong support for the claims aligned to these interventions. Table 1 provides a breakdown of many types of interventions in different domains that have been provided to this independent body for evaluation and how many have strong, moderate, or no/indeterminate evidence for efficacy.

Table 1.
Summary of findings around all educational interventions submitted to the What Works Clearing House for evaluation of efficacy (https://ies.ed.gov/ncee/wwc/)
DomainStrong EvidenceModerate EvidenceNo/ Indeterminant EvidenceTotal
Literacy Interventions51
Mathematics Interventions35
Science Interventions9
Behavioral Interventions10
English Learner Interventions4
Post-Secondary Interventions67
K-12 Interventions85
All Interventions*219

* Some studies fall into one or more categories of intervention, such that this final column is not simply the sum of all previous rows.

Key Terms in this Chapter

Performance: Expression of a person's knowledge or task behavior that can be directly and immediately perceived or observed.

Social and Emotional Learning Skills: Combination of a person’s unique systems of thinking, patterns of emotions, and sets of behaviors that characterize his or her personality.

Learning Misconception: Erroneous understanding or false belief regarding the factors or strategies that foster learning.

Cognitive Bias: Deviation from normative or rational judgment and decision-making stemming from maladaptive heuristic thinking.

Learning: Enduring, latent change in a person's knowledge, understanding, or skill level that may not be directly perceptible or observable.

Retrieval Practice: Learning strategy that involves attempting to remember to-be-learned information.

Long-Term Retention: Capacity to remember information after a relatively long period of time has passed since the information was acquired.

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