Online Learning: Does It Help Low-Income and
Bibliographic record
Abstract
Advocates of online learning are optimistic about its potential to promote greater access to college by reducing the cost and time of commuting and, in the case of asynchronous approaches, by allowing students to study on a schedule that is optimal for them. The enthusiasm surrounding recent innovative, technology-based education initiatives, combined with an ongoing acceleration in online course enrollments (Allen & Seaman, 2010) has led educators to ask whether the continuing expansion of online learning could be leveraged to increase the academic access, progression, and success of low-income and underprepared college students. To provide an evidence-based perspective on these questions, this Brief, based on a longer review, summarizes the literature on online learning and provides recommendations for policymakers and practitioners. Summary of the Literature The larger review, summarized briefly here, considered studies that compared online (80 % or more of the course conducted online) and face-to-face (less than 30 % of the course conducted online) learning in the postsecondary education setting. The postsecondary inclusion criterion distinguishes this review from other recent analyses of the online learning literature, which each included studies from a mixed variety of settings, including K-12, college, and work-based employee training contexts (Bernard et al., 2004; Zhao, Li, Yan, Lai, & Tan, 2005; U.S. Department of Education, 2009). This review was also limited to studies that compared online and face-to-face courses in terms of students ’ course enrollment, completion, performance, or subsequent academic outcomes. Studies that were discarded include those published prior to 2000, studies that focused on short educational interventions (e.g., a one-week treatment), and studies that allowed students to self-select into either online or face-to-face courses without attempting to control for any potential differences between the student groups. Finally, the review considered only studies conducted in the United States and Canada. This review thus included 34 papers (some with multiple studies, for a total of 36 studies). A detailed breakdown of findings can be found in the full review.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".