Educational Processes and Learning at Home During COVID-19: Parents’ Experiences with Distance Education
Bibliographic record
Abstract
Due to the lockdown measures and severe restrictions taken to reduce COVID-19 transmission, which has globally been inflicted on people since March 2020, a new type of education in the form of online homeschooling has brought the role of parents to the forefront. Using online semi-structured interviews, this study aimed to investigate parents’ views on the implementation of distance education during COVID-19 in Istanbul, Turkey. The data obtained from parents with different socioeconomic backgrounds and whose children were at public and private schools were coded using initial, process, and emotion qualitative coding techniques. The data were categorized into three main themes: beginning of distance education, process of distance education, and outcomes of distance education. The beginning theme was further analyzed under three subcategories: problems related to the child, problems related to parents, and problems related to public schools. The problems encountered during the process of distance education were investigated under three subheadings: problems related to the child’s academic and social life, problems related to parents, and problems related to parent–child relationships. Data under the main theme, outcomes of distance education, were defined as positive or negative outcomes in terms of the child and parents. Results revealed that at the beginning of the process, during the process, and during the outcomes of distance education, parents experienced problems with digital technology, the new education model, teachers, themselves, and their children, as well as economic, social, and psychological problems. Parents also had various constructive suggestions about distance education during COVID-19.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".