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Objective Analysis. Effective Solutions.

Media literacy (ML) education has emerged as a promising approach to slowing the spread of Truth Decay, described as the diminishing role that facts, data, and analysis play in political and civil discourse. Several factors contribute to Truth Decay, including a rapidly evolving information ecosystem and overburdened educational institutions. Many teachers believe their students lack the complex skills that are necessary to navigate today's information-saturated world. This gap—between students' existing competencies and those required to engage responsibly in a fast-paced media environment—could lead to negative consequences for individuals and society writ large.

However, teachers report a lack of guidance around promoting ML education in their practice, and rigorous research about what kinds of ML education work best, and in what conditions, remains limited. This report presents a framework for implementing and evaluating ML educational efforts. Following an introduction to the framework, the authors discuss six steps of ML implementation and evaluation: setting ML learning expectations; identifying conditions that can influence ML instructional efforts; exploring instructional resources; identifying measures of ML competencies; monitoring progress; and finally, measuring the summative impacts of ML education on student learning. By bringing this information together for implementors—such as district decisionmakers and teachers—as well as evaluators, the authors emphasize the important connections between these too often separate groups.

• Chapter One

  Introduction to the Framework

• Chapter Two

  Identifying Media Literacy Learning Expectations

• Chapter Three

  Exploring Conditions to Support Media Literacy Instruction

• Chapter Four

  Selecting Media Literacy Learning Materials

• Chapter Five

  Identifying Measures of Media Literacy Competencies

• Chapter Six

  Monitoring Interim Progress

• Chapter Seven

  Evaluating the Effects of Media Literacy Instruction

• Chapter Eight

  Conclusion

• Appendix

  Enhancements to Evaluation Designs Discussed in Chapter Seven