Assessment Scores of Remote and In-Person Learning for Grades Three - Six Students in an East Tennessee School District
Bibliographic record
Abstract
The purpose of this comparative, quantitative study was to explore the relationship of interim test scores among remote and in-person learners, low-income students, and students with disabilities. In March 2020, a portion of students enrolled in a K-12 school in Northeast Tennessee was moved into remote learning until the end of the school year in May 2020. In July 2020, parents were given the option for their child to attend remote or in-person learning. While some chose in-person learning, giving reasons such as child-care, work obligations, or personal preference, others chose for their children to continue to receive online learning due to health concerns brought on by the pandemic. Since these decisions were made, some parents that originally opted for online learning chose to send their child back to school due to perceived obstacles faced within the online environment. This study was conducted to determine the efficacy of online learning in comparison to in-person learning for students grades three – six separated into the following categories: general population, students with disabilities, and low-income students. Comparison of both mathematics and literacy interim third quarter checkpoint data were analyzed using SPSS software to conduct a series of independent t-tests. Data were analyzed at the 0.05 level of significance. Twelve research questions were addressed testing corresponding null hypotheses. Results included third grade online literacy scores significantly exceeding the scores of in-person. Mean literacy and math scores were approximately equal for online and in-person learners. Overall, scores for students with disabilities and low socio-economic students were approximately equal whether the learners were online or in-person.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".