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Beyond the log-in: Improving student engagement and learning in online credit recovery

Thursday, November 5, 10:15 to 11:45am, Property: Boston Marriott Copley Place, Floor: 3rd Floor, Room: MIT

Abstract

The delivery of core (required) courses for high school graduation through online learning platforms has been accelerating over the last two decades and increased substantially following the onset of the COVID pandemic. High course failure rates and increased absenteeism contributed to a post-pandemic surge in the use of online learning platforms for credit recovery, in which students are provided an opportunity to recover (failed) courses that are required for graduation (Barshay, 2022; Reeves, 2022; Viano, 2023, Peko-Spicer et al., 2025). Even before the pandemic, 71% of credit recovery courses nationally were delivered online.

One of the persistent and growing concerns about online credit recovery (OCR) is “suboptimal” student engagement in online learning, which has been observed in multiple settings (Heinrich et al., 2019; Rickles et al., 2023). Communication between students and instructors (or instructional resources) is often primarily asynchronous in OCR, with teacher roles limited to addressing classroom management and technology access issues (Stevens et al., 2016; Heinrich et al., 2019). While a growing body of research confirms that OCR increases student credits earned and high school graduation rates (Kirsch, 2017; Powell, Roberts, & Patrick, 2015; Tyner & Munyan-Penney, 2018; Malkus, 2019; Rickles et al., 2018; Heinrich & Darling-Aduana, 2021; Viano, 2021; Viano & Henry, 2024), most studies have found insignificant or negative associations between OCR use and student test scores (Heinrich et al., 2019; Viano, 2021, 2023; Viano & Henry, 2024). As the use of OCR continues to expand in all 50 states, it is imperative to identify promising implementation models and ways their use can be expanded to increase student engagement and learning.

This research uses school district and OCR vendor administrative data to address the following research questions: are there discernible types (and intensity) of OCR use that affect student engagement in learning and their learning outcomes? How does the initiation of OCR affect students’ subsequent educational trajectories, including course-taking, school performance, absenteeism, and progression to graduation? Do some subgroups of students engage more or less effectively in OCR (e.g., students far behind academically or with special educational needs)? What OCR implementation models show promise for improving student engagement and outcomes, and what are the constraints to scaling them in school districts across the U.S.? This research will generate practical knowledge that can assist school districts in reducing problematic types of OCR use and improving student outcomes following OCR initiation.

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