Beating The COVID-19 Slide in Education: The Impact of Pandemic-induced School Closures on Student Engagement And Education Equity in Chicago Public Schools
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Enhancing student engagement has been an important goal for schools and education reformers. Although many definitions of engagement were introduced since it first appeared in the 1930s, this paper defines engagement as the degree of student's active participation and course performance under both traditional classrooms and remote learning environments. This definition recognizes that engagement depends not only on the time (pre-pandemic or during-pandemic), but, more importantly, on the agents (students), and the place and space that these agents situate. Since the onset of the COVID-19 pandemic, traditional in-person classrooms were gradually replaced by online remote instructions beginning in March 2020. The goal of this study is to examine the effect of pandemic-induced school closures on student engagement. Using data from 406 Chicago public schools, I analyzed course grades from a total of 144,403 actively enrolled sixth- to eighth-grade students using a three-level hierarchical linear modeling technique, examining the pandemic-engagement relationship across students of various backgrounds and schools of varying resources. Analyses on students' engagement trends revealed two distinct patterns. Students earning a worse quarter grade (such as a B, C, or D) in pre-pandemic quarters demonstrated higher course performance under remote learning environments. However, students with disabilities, and schools in high poverty-concentrated neighborhoods showed significant declines in course grades in Spring 2020. Nevertheless, this study has implications for ensuring more accessible and equal education for students of different backgrounds, as well as delivering objective and accurate data to help inform policymakers and district leaders in the decision-making on remote or in-person instruction.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it