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Back-to-school metrics: How to assess conditions for teaching and learning and to measure student progress during the COVID-19 pandemic

Back-to-school metrics during COVID-19

By Susan Bowles Therriault
September 28, 2020

In response to the COVID-19 pandemic, the Regional Educational Laboratory (REL) Midwest is featuring a blog series addressing the many challenges that educators, caregivers, and students are facing. In this post, Susan Bowles Therriault, Ed.D., a managing researcher at the American Institutes for Research (AIR), describes school- and classroom-level metrics that administrators and teachers can use to assess teaching and learning conditions and measure student progress and engagement in a remote or hybrid learning setting. For more pandemic-related resources, see the REL Program’s COVID-19 resources.

The continuing COVID-19 pandemic has forced school districts across the nation to quickly adapt their approach to teaching and learning, with widespread variation in the response. Preliminary results of AIR’s National Survey on Public Education’s COVID-19 Response highlight how districts varied in their approach to remote learning after the pandemic hit last spring. With a new school year now underway, several states require that schools provide some degree of in-person instruction, while other states have left such decisions up to local education and public health officials (Education Week, 2020).

In the midst of this ever-changing educational environment, district and school leaders are grappling with how to collect teacher and student data quickly to assess what supports are needed and to target resources appropriately. In this blog post, I outline school- and classroom-level metrics that administrators and teachers can use to assess teaching and learning conditions and measure student progress and engagement in a remote or hybrid (in-person and remote) learning setting.

School-level metrics: Assessing conditions for teaching and learning

Preliminary research and projections indicate that most students likely are beginning the fall semester behind academically as a result of school closures and delays this past spring (Northwest Evaluation Association, 2020; Soland et al., 2020). To assess students’ learning gaps and ensure that schools provide the appropriate conditions for learning, teachers and administrators should consider using the following school-level metrics.

Student and family wellness surveys. Attending to the whole child—that is, a child’s basic needs (safety, health, and nutrition) and well-being—is key to ensuring that students are ready to learn. Due to the varied formats of in-person, hybrid, and remote learning, families have had to take on a greater role than in the past. By administering a wellness survey to students and their families, school leaders can better understand barriers to student learning and better direct resources and supports.

A wellness survey may include questions about students’ physical and mental health as well as families’ access to food, housing, childcare, and transportation. Schools could collect this information on an ongoing basis, and student support staff could review the responses to direct appropriate supports. AIR has created a resource to help education and community leaders develop a shared understanding of the concept of the whole child, including a crosswalk aligning whole child terms to school reopening guidance and a list of resources to assist in integrating whole child supports into reopening strategies.

Formative academic assessments. To support teachers in similar content areas, school leaders can create uniform and consistent formative assessment items that teachers and leaders can use to review and make decisions about student needs and teacher supports. Within the context of teaching and learning, formative assessment is commonly understood as a multistep process in which a teacher establishes clear learning goals, gathers evidence on what and how students are learning, and uses the data to provide feedback and instruction that supports student learning (Council of Chief State School Officers, 2008). Recent research reviews indicate that formative assessments have a positive impact on student academic achievement (Apthorp, Klute, Petrites, Harlacher, & Real, 2016; Klute, Apthorp, Harlacher, & Reale, 2017).

Related REL Midwest projects: Estimating student learning loss

REL Midwest researchers are currently working with state and district officials in Illinois, Minnesota, and Ohio to help them estimate student learning loss following the extended school closures due to COVID-19. For example, REL Midwest staff are working on a descriptive analysis of possible changes to K–8 student achievement in Minnesota District 191 by examining student scores on the Formative Assessment System for Teachers (FAST) reading and mathematics assessments from the 2014/15 academic year through the first post-COVID-19 assessment period in the 2020/21 academic year. District administrators will be able to use this information to target resources to student subgroups most affected by school closures. REL Midwest plans to provide the findings to District 191 in a coaching session in late 2020 and then summarize the findings from this project in a publicly available report to be published in late 2021.

Instructional staff pulse surveys. District and school leaders can leverage existing feedback systems to “check the pulse” of teachers and other instructional staff. For example, the Comprehensive Center Network recently published the Returning to School: A Principal's Toolkit [1,950 KB PDF icon], which contains a set of four surveys [2,012 KB PDF icon] to help school leaders gather quick and timely feedback from instructional staff to identify needed supports and build upon what is working well. Such surveys can also be re-administered easily to compare responses across groups of teachers on an ongoing basis.

Classroom-level metrics: Assessing student academic progress and level of engagement

Teaching in a remote or hybrid learning environment requires that educators rethink the format of assessments to allow students to choose how they share evidence of what they have learned. Below are several strategies to consider along with supporting resources:

  • Offer more opportunities for students to learn or complete work asynchronously to account for unexpected barriers to learning. Some students may experience difficulty attending online classes at specific times due to lack of consistent access to the internet or other external barriers. This issue may require schools to explore alternative methods of instruction, such as competency-based learning. Also known as performance-based learning, competency-based learning provides flexibility in how long students take to progress in their coursework and how students demonstrate mastery of course content (Brodersen, Yanoski, Mason, Apthorp, & Piscatelli, 2016). For high school students, implementing competency-based instructional strategies has been identified as a promising practice for increasing academic achievement, graduation rates, and career and college readiness (Anderson & Fulton, 2015; Jerald, Campbell, & Roth, 2017; Sturgis & Patrick, 2010).
  • Implement deeper learning strategies, such as project-based learning and portfolio assessments. For example, ask students to create videos, write blogs, or participate in a discussion panel on a virtual platform. Visit AIR’s Spotlight on Deeper Learning to learn more.
  • Administer “temperature check” student surveys to gather quick feedback. For an example, see the Massachusetts Department of Elementary and Secondary Education’s student feedback survey, which was designed to reflect students’ day-to-day practice and yield meaningful and actionable information for Massachusetts educators.
  • Engage in rapid data-inquiry cycles, commonly called Plan-Do-Study-Act (PDSA) cycles. PDSA cycles involve identifying a problem of practice and then testing and refining a strategy to address the problem. To learn more, see the Six Core Principles of Improvement from the Carnegie Foundation for the Advancement of Teaching.

Measuring student engagement is another challenge in a remote or hybrid learning environment. A research review of measures of student engagement in technology-mediated learning identified indicators in three categories: behavioral, cognitive, and emotional, as shown in the table below (Henrie, Halverson, & Graham, 2015). Teachers can use these indicators as a way to measure student engagement in a remote or hybrid learning environment.

Indicator category

Examples of how indicators of student engagement in remote or hybrid learning environments can be operationalized

Behavioral Indicator category

  • Assignments completed
  • Frequency of logins to website
  • Number, quality, and frequency of online posts and views
  • Percentage of sessions with posting actions, views that were reads (not scans), and posts viewed at least once

Cognitive Indicator category

  • Improved understanding
  • Problem-solving behavior
  • Self-regulated interest
  • Reflection

Emotional Indicator category

  • Collaborative social interactions
  • Sense of class community
  • Student-to-student interactions
  • Expressed desire to use the tool again

Note: Adapted with permission from Table 8 in “Measuring Student Engagement in Technology-Mediated Learning: A Review,” by C. R. Henrie, L. R. Halverson, & C. R. Graham, 2015, Computers & Education, 90(1), 36–53. Elsevier Ltd.

For more information

To advance the field in identifying metrics in remote and hybrid learning settings, REL Midwest is partnering with the Region 9 Comprehensive Center to support a cross-state community of practice focused on developing guidance on school-, district-, and state-level metrics to inform continuous improvement in the 2020/21 school year.

REL Midwest is one of 10 RELs that serve designated regions of the country and work with educators and policymakers to support a more evidence-based education system. In response to COVID-19, the RELs are collaborating to produce evidence-based guidance and resources on remote teaching and learning. Browse the collection.


Anderson, L., & Fulton, M. (2015). Multiple measures for college readiness. ECS Education Trends. Denver, CO: Education Commission of the States. Retrieved September 17, 2020, from [128 KB PDF icon].

Apthorp, H., Klute, M., Petrites, T., Harlacher, J., & Real, M. (2016). Valuing a more rigorous review of formative assessment’s effectiveness. Society for Research on Educational Effectiveness.

Brodersen, R. M., Yanoski, D., Mason, K., Apthorp, H., & Piscatelli, J. (2016). Overview of selected state policies and supports related to K–12 competency-based education (REL 2017–249). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Central. [390 KB PDF icon]

Council of Chief State School Officers. (2008). Attributes of effective formative assessment. Washington, DC: Author. Retrieved September 15, 2020, from

Education Week. (2020, July 28). Map: Where are schools closed? Retrieved September 8, 2020, from

Henrie, C. R., Halverson, L. R., & Graham, C. R. (2015). Measuring student engagement in technology-mediated learning: A review. Computers & Education, 90, 36–53.

Jerald, C., Campbell, N., & Roth, E. (2017). High schools of the future: How states can accelerate high school redesign. Washington, DC: Center for American Progress.

Klute, M., Apthorp, H., Harlacher, J., & Reale, M. (2017). Formative assessment and elementary school student academic achievement: A review of the evidence (REL 2017–259). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Central.

Northwest Evaluation Association. (2020, May 27). Researchers estimate students coming back after COVID-19 closures may have greater variances in academic skills [Press release]. Retrieved September 15, 2020, from

Soland, J., Kuhfeld, M., Tarasawa, B., Johnson, A., Ruzek, E., & Liu, J. (2020, May 27). The impact of COVID-19 on student achievement and what it may mean for educators. The Brookings Institution. Retrieved September 15, 2020, from

Sturgis, C., & Patrick, S. (2010). When success is the only option: Designing competency-based pathways for next generation learning. Vienna, VA: International Association for K–12 Online Learning.

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Author Information

Susan Bowles Therriault Staff Picture

Susan Bowles Therriault

Managing Researcher | REL Midwest


Beating the odds (2)

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College and Career Readiness (42)

Data Use (32)

Discipline (4)

Early Childhood (31)

Educator Effectiveness (36)

English Learners (10)

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Online Courses (7)

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