High School Students' Perspectives on Their Online Learning Experiences: A Systematic Literature Review
Bibliographic record
Abstract
ABSTRACT Background Online learning has become a popular form of education. Prior to the Covid‐19 pandemic, online learning was mainly associated with higher education, with an incremental growth at the K‐12 level. The pandemic changed this situation rapidly. Online instruction has been increasingly integrated into secondary schools and has significantly impacted students' learning experiences and outcomes, particularly for high school students experiencing the critical transition to higher education. Therefore, there is an urgent need to develop an in‐depth understanding of their perspectives through a synthesis study to provide insights into critical factors influencing their online learning. Objectives Following the PRISMA guidelines, this article systematically reviewed 46 empirical studies that examined high school students' perspectives through their experiences of taking at least one online course in synchronous and/or asynchronous learning environments by leveraging diverse technologies. Methods We extracted and summarised results from studies and applied descriptive statistics analysis and thematic analysis to identify and synthesise the major patterns/themes of findings. Results and Conclusions Students perceived the main benefits of learning online, ranging from their increased learning autonomy and communicative flexibility to their skill development across subject content areas. They identified several challenges in taking online courses, including staying motivated, lacking instructional support and social engagement, and time management issues. These findings suggested that educators and stakeholders develop evidence‐based and ‘smart’ designs of online learning environments and course structures, given careful consideration of the needs and characteristics of intended student groups and content to be delivered.
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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 | 0.015 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.025 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".