Over one million students drop out of high school in the United States each year (Pettyjohn & LaFrance, 2014). When students fail to earn credit in a course, the likelihood of them dropping out increases drastically (Frazelle, 2016; Oliver & Kellog, 2016). To support students in staying in school, 71% of high schools in the United states offer online credit recovery (CR) programs (Pileggi et al., 2020). These CR courses help students quickly regain credits and increase the likelihood that they will graduate.

The success of credit recovery programs is contingent upon many factors, from how each program measures success to how funds are used to support the program. There is no consistent definition of success across credit recovery contexts (Rickles et al., 2018, Nourse, 2019). Some programs define success as the student earning lost credit, while others define success as preparedness for future learning and student persistence to graduation. Nourse (2019) and others highlight the relationship of quality content to student outcomes, but there is little discussion in the literature about what would constitute quality CR content. This article highlights some considerations related to the quality design of online CR products. For those purchasing online CR programs, these suggestions could be used as evaluation criteria for content to maximize the impact of the product. Broadly, these suggestions are grouped by their relationship to academic content, scaffolds, and content structure.

Design Considerations for Online Credit Recovery Content

The academic content of online CR programs should clearly be rooted in the belief that all students can achieve grade-level work and expectations. Content should include the depth and breadth of content that would: 1) support student success in future courses in the content area and 2) foster educator belief that the content is appropriately rigorous for the grade level. Instructional strategies should be pedagogically sound and research-based. Content should emphasize active learning; this includes strategically using technology to support exploration and construction of knowledge,  rather than simply converting lectures and textbooks onto a digital platform. Interesting and relevant experiences that motivate learning of academic content and processes should be offered to students. Activities should be thought-provoking and dissuade students from copying and pasting the answer from an online resource; students frequently seek help by accessing the work of others online, so content should engage them with personal, meaningful learning. It is key that students are aware of what they will learn and why, as well what is expected of them to successfully complete the course.

Online CR content should provide scaffolding and resources for students to maximize their success. Some students may have content gaps and need remedial instruction to access grade-level learning, including modeling, explanations, or supplementary activities. To support CR teachers in addressing content gaps, materials should include teacher-facing materials that help address differentiation. Students need to spend their cognitive resources on the content, not the technology. Programs should provide simple and intuitive user experiences, as well as in-product tutorials that help students develop the technological skills and digital literacy needed to use the program. Finally, content should provide students with early experiences of success in the program so they begin to develop a sense of self-efficacy and motivation in their online learning.

The structure of the content should support students in both gaining lost credit and acquiring sufficient academic knowledge for future coursework. Online CR programs can employ mastery learning by using assessment data to remove mastered content, thereby reducing redundancy and disengagement. Students earn credit faster when they are not required to study previously mastered content. Assessments for mastery learning should be rigorous enough to ensure that students have learned skills to the depth needed for future content within the domain. Customization features that allow instructors to add, omit, and organize content also support right-sizing the content for each student. Programs should have features that allow instructors to learn about students’ identities, skills, and areas for growth to plan for individual support. Programs should offer useful reporting that aids instructors in data-driven decision making. Features that provide real-time data to instructors about students’ progress and alert the instructors when an interaction may help a student can drastically increase effectiveness.

Conclusion

Online credit recovery will continue to be an important strategy in decreasing dropout rates and encouraging student persistence in high school. When designing a credit recovery program, it is important for each program leader to define the metrics of success within their context. After defining success, leaders should align funding, staffing, scheduling, grading, and content decisions to their definition. When thinking about content for online CR, designers and decision makers should consider the academic content, scaffolds and support, and the structure of the program. High-quality content will provide grade-level work, support students in achieving that work, and be customizable based on students’ needs.

References

Frazelle, S. (2016). Successful strategies for providing online credit recovery in Montana. Regional Educational Laboratory Northwest.

Nourse, D. (2019). Factors influencing student academic performance in online credit recovery. Journal of Interdisciplinary Teacher Leadership 4(1). https://doi.org/10.46767/kpf.2016-0030

Oliver, K., & Kellogg, S. (2015). Credit recovery in a virtual school: Affordances of online learning for the at-risk student. Journal of Online Learning Research 1(2), 191-218.

Pettyjohn, T., & LaFrance, J. (2014). Online credit recovery: Benefits and challenges. Education Leadership Review of Doctoral Research, 1(1), 204–219.

Pileggi, M., Turner, A., Liu, L., Fontana, J., Philadelphia Education Research Consortium (PERC), & Research for Action. (2020). Recovering credits in the school district of Philadelphia: High school student credit recovery utilization in 2018-19. Philadelphia Education Research Consortium.

Rickles, J., Heppen, J. B., Allensworth, E., Sorensen, N., & Walters, K. (2018). Online credit recovery and the path to on-time high school graduation. Educational Researcher 47(8), 481-491. https://doi.org/10.3102/0013189X18788054