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REL Central Ask A REL Response

Beating the Odds

January 2021


What are effective methods to help students who are struggling with learning loss to assist them in catching up to grade level content?


Following an established research protocol, REL Central conducted a search for research reports as well as descriptive study articles to help answer the question. The resources included ERIC and other federally funded databases and organizations, research institutions, academic databases, and general Internet search engines. (For details, please see the methods section at the end of this memo.)

References are listed in alphabetical order, not necessarily in order of relevance. We have not evaluated the quality of the references provided in this response, and we offer them only for your information. We compiled the references from the most commonly used resources of research, but they are not comprehensive and other relevant sources may exist.

Research References

Fazal, M., & Bryant, M. (2019). Blended learning in middle school math: The question of effectiveness. Journal of Online Learning Research, 5(1), 49–64. Retrieved from

From the abstract:

“Blended learning models can help teachers leverage the power of technology to customize student learning and differentiate instruction for students at varying achievement levels. Research on the effectiveness of blended learning in K–12 education has largely relied on case studies, and findings suggest differences in achievement outcomes based on content areas and grade levels. This paper reports findings from a quantitative comparative study conducted to investigate the effects of blended learning, specifically using the station rotation model, on the math achievement of 413 6th grade students. Scores on the State of Texas Assessments of Academic Readiness (STAAR), as well as the Measure of Academic Progress (MAP) were used. Student groups were selected based on teacher responses on a survey in which they were asked to identify what portion of their class was spent on blended learning practices and on face-to-face teaching. A t-test was conducted to determine the differences in the scores of students taught in traditional fully face-to-face classrooms and those taught in blended learning classrooms. Findings showed that students instructed through blended learning scored higher on the MAP assessment (M = 11.12, SD = 7.88) than students in a fully face-to-face environment (M = 8.84, SD = 7.40), t(411) = 3.02, p < 0.01. On the other hand, students instructed in a face-to-face setting scored higher on STAAR (M = 29.96, SD = 11.84) than those in blended learning settings (M = 26.75, SD = 11.06), t(411) = 2.85, p < 0.01. Blended learning was more effective in facilitating growth in math learning as compared to meeting grade level criteria. These findings indicate that schools can benefit from implementing blended learning particularly for students who are behind academically and need additional academic growth in one school year.”

Hart, C. M. D., Berger, D., Jacob, B., Loeb, S., & Hill, M. (2019). Online learning, offline outcomes: Online course-taking and high school student performance. AERA Open, 5(1), 1–17. Retrieved from

From the abstract:

“This article uses fixed effects models to estimate differences in contemporaneous and downstream academic outcomes for students who take courses virtually and face-to-face–both for initial attempts and for credit recovery. We find that while contemporaneous outcomes are positive for virtual students in both settings, downstream outcomes vary by attempt type. For first-time course takers, virtual course taking is associated with decreases in the likelihood of taking and passing follow-on courses and in graduation readiness (based on a proxy measure). For credit recovery students, virtual course taking is associated with an increased likelihood of taking and passing follow-on courses and being in line for graduation. Supplemental analyses suggest that selection on unobservables would have to be substantial to render these results null.”

Kraft, M. A., & Falken, G. T. (2021). A blueprint for scaling tutoring across public schools (EdWorkingPaper No. 20-335). Annenberg Institute at Brown University. Retrieved from

From the abstract:

“In this thought experiment, we explore how tutoring could be scaled nationally to address COVID-19 learning loss and become a permanent feature of the U.S. public education system. We outline a blueprint centered on ten core principles and a federal architecture to support adoption, while providing for local ownership over key implementation features. High school students would tutor in elementary schools via an elective class, college students in middle schools via federal work-study, and full time 2- and 4-year college graduates in high schools via AmeriCorps. We envision an incremental, demand-driven expansion process with priority given to high-needs schools. Our blueprint highlights a range of design tradeoffs and implementation challenges as well as estimates of program costs. Our estimates suggest that targeted approaches to scaling school-wide tutoring nationally, such as focusing on K–8 Title I schools, would cost between $5 and $15 billion annually.”

Kuhfeld, M., & Soland, J. (2020). The learning curve: Revisiting the assumption of linear growth across the school year (EdWorkingPaper No. 20-214). Annenberg Institute at Brown University. Retrieved from

From the abstract:

“Important educational policy decisions, like whether to shorten or extend the school year, often require accurate estimates of how much students learn during the year. Yet, related research relies on a mostly untested assumption: that growth in achievement is linear throughout the entire school year. We examine this assumption using a data set containing math and reading test scores for over seven million students in kindergarten through 8th grade across the fall, winter, and spring of the 2016–17 school year. Our results indicate that assuming linear within-year growth is often not justified, particularly in reading. Implications for investments in extending the school year, summer learning loss, and racial/ethnic achievement gaps are discussed.”

Kuhfeld, M., Soland, J. Tarasawa, B., Johnson, A., Ruzek, E., & Liu, J. (2020). Projecting the potential impact of COVID-19 school closures on academic achievement. Educational Researcher, 49(8), 549–565. Retrieved from
Full text available from

From the abstract:

“As the COVID-19 pandemic upended the 2019–2020 school year, education systems scrambled to meet the needs of students and families with little available data on how school closures may impact learning. In this study, we produced a series of projections of COVID-19-related learning loss based on (a) estimates from absenteeism literature and (b) analyses of summer learning patterns of 5 million students. Under our projections, returning students are expected to start fall 2020 with approximately 63 to 68% of the learning gains in reading and 37 to 50% of the learning gains in mathematics relative to a typical school year. However, we project that losing ground during the school closures was not universal, with the top third of students potentially making gains in reading.”

Kuhfeld, M., & Tarasawa, B. (2020). The COVID-19 slide: What summer learning loss can tell us about the potential impact of school closures on student academic achievement. NWEA. Retrieved from

From the brief:

“As the coronavirus (COVID-19) pandemic closes schools across the nation, education systems are scrambling to meet the needs of schools, families, and 55.1 million students during these unprecedented times. The economic impacts and trauma of recent events will also have far reaching effects that will likely exacerbate long-standing opportunity gaps. While it is difficult to speculate on what missing months of school may mean for student achievement, research on seasonal learning and summer learning loss can offer some insights that can help educators, policy makers, and families understand, plan for, and address some potential impacts of this extended pause in classroom instruction when students return to school.”

Nickow, A. J., Oreopoulos, P., & Quan, V. (2020). The impressive effects of tutoring on preK–12 learning: A systematic review and meta-analysis of the experimental evidence (EdWorkingPaper No. 20-267). Annenberg Institute at Brown University. Retrieved from

From the abstract:

“Tutoring–defined here as one-on-one or small-group instructional programming by teachers, paraprofessionals, volunteers, or parents–is one of the most versatile and potentially transformative educational tools in use today. Within the past decade, dozens of preK–12 tutoring experiments have been conducted, varying widely in their approach, context, and cost. Our study represents the first systematic review and meta-analysis of these and earlier studies. We develop a framework for considering different types of programs to not only examine overall effects, but also explore how these effects vary by program characteristics and intervention context. We find that tutoring programs yield consistent and substantial positive impacts on learning outcomes, with an overall pooled effect size estimate of 0.37 SD. Effects are stronger, on average, for teacher and paraprofessional tutoring programs than for nonprofessional and parent tutoring. Effects also tend to be strongest among the earlier grades. While overall effects for reading and math interventions are similar, reading tutoring tends to yield higher effect sizes in earlier grades, while math tutoring tends to yield higher effect sizes in later grades. Tutoring programs conducted during school tend to have larger impacts than those conducted after school.”

Sloan McCombs, J., Augustine, C. H., Schwartz, H. L., Bodilly, S. J., McInnis, B., Lichter, D. S., & Brown Cross, A. (2012). Making summer count: How summer programs can boost children’s learning. Education Digest: Essential Readings Condensed for Quick Review, 77(6), 47–52. Retrieved from
Full text available from

From the ERIC abstract:

“During summer vacation, many students lose knowledge and skills. By the end of summer, students perform, on average, one month behind where they left off in the spring. Participation in summer learning programs should mitigate learning loss and could even produce achievement gains. Indeed, educators and policymakers increasingly promote summer learning as a key strategy to improve the achievement of low-performing students. Rigorous studies have shown that strong summer programs can achieve several important goals: (1) reverse summer learning loss; (2) achieve learning gains; and (3) give low-performing students the chance to master material that they did not learn during the school year. The authors recommend that districts and other providers invest in staffing and planning for summer learning programs, actively incorporate practices that will help ensure the success of programs, and maximize the benefits of partnerships and a variety of funding sources. They also offer recommendations for policymakers and funders who are interested in supporting summer learning programs.”

Wyse, A. E., Stickney, E. M., Butz, D., Beckler, A., & Close, C. N. (2020). The potential impact of COVID-19 on student learning and how schools can respond. Educational Measurement: Issues and Practices, 39(3), 60–64. Retrieved from
Full text available from

From the abstract:

“There is no denying the impact that the coronavirus disease (COVID-19) outbreak has had on many aspects of our lives. This article looks at the potential impact of COVID-19 on student learning as schools abruptly morphed into virtual learning environments using data from several instructional, practice, and assessment solutions offered by Renaissance. First, three hypothetical learning scenarios are considered using normative data from Star assessments to explore the potential impact on reading and math test performance. Next, data on Focus Skills are used to highlight which grades may have missed the most foundational math and reading content if instruction was stopped or reduced. Last, data from two of Renaissance’s practice tools are used to evaluate whether students were practicing key skills following school closures. The article concludes that academic decline will likely occur but may be tempered by the increased use of practice tools; effects may look different for math and reading; and may impact grades and schools differently. As such, schools may need to leverage decision-making frameworks, such as the Multi-tiered Systems of Support/Response-to-Intervention (MTSS/RTI) framework, more than ever to identify needs and target instruction where it matters most when school begins in fall 2020.”

Additional Resources to Consult

What Works Clearinghouse:

From the website:

“The What Works Clearinghouse (WWC) reviews the existing research on different programs, products, practices, and policies in education. Our goal is to provide educators with the information they need to make evidence-based decisions. We focus on the results from high-quality research to answer the question ‘What works in education?’”


Keywords and Strings

The following keywords and search strings were used to search the reference databases and other sources:

  • “Academic persistence”
  • “Educational strategies”
  • Intervention
  • “Learning loss”
  • “Mathematics achievement”
  • “Reading achievement”
  • “Student centered learning”
  • “Student improvement”
  • Tutoring

Databases and Resources

REL Central searched ERIC for relevant references. ERIC is a free online library, sponsored by the Institute of Education Sciences, of over 1.6 million citations of education research. Additionally, we searched Google and Google Scholar.

Reference Search and Selection Criteria

When searching for and reviewing references, REL Central considered the following criteria:

  • Date of the Publication: The search and review included references published between 2011 and 2021.
  • Search Priorities of Reference Sources: Search priority was given to ERIC, followed by Google and Google Scholar.
  • Methodology: The following methodological priorities/considerations were used in the review and selection of the references: (a) study types, such as randomized controlled trials, quasi-experiments, surveys, descriptive analyses, and literature reviews; and (b) target population and sample.

This memorandum is one in a series of quick-turnaround responses to specific questions posed by educational stakeholders in the Central Region (Colorado, Kansas, Missouri, Nebraska, North Dakota, South Dakota, Wyoming), which is served by the Regional Educational Laboratory Central at Marzano Research. This memorandum was prepared by REL Central under a contract with the U.S. Department of Education’s Institute of Education Sciences (IES), Contract ED-IES-17-C-0005, administered by Marzano Research. Its content does not necessarily reflect the views or policies of IES or the U.S. Department of Education nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.