Evaluating parental experiences in using technology for remote learning to teach students with special needs during the COVID-19 pandemic
Bibliographic record
Abstract
Background The 2020–2021 school year shut down because of the COVID-19 pandemic brought an unprecedented burden on parents, especially those with special needs children. Parents with children with special needs were left to assist their children with remote learning at home using technology for the first time. These students with special needs were used to face-to-face and one-to-one classroom learning by skilled educators but are now left to be educated by their parents. Objective This study explored parents’ experiences assisting their special needs children with remote learning for the first time, using technology at home during the COVID-19 pandemic. Method A transcendental (descriptive) phenomenology was undertaken to explore the experiences of nine participants, recruited from two school divisions in Manitoba, Canada, on their child’s education and the challenges they experienced during remote learning from home. A purposive sampling technique was used, and data were collected through telephone interviews. Results Eight out of nine parents reported a negative experience with remote learning. Four major themes emerged after the data analysis: participants’ fear and anxiety during remote learning, difficulty maintaining routines during remote learning, students’ behavioral issues and mental health changes during remote learning, and lack of home support during remote learning. Furthermore, results indicated that integrating technology in remote learning for students with special needs was ineffective. Conclusion This study suggests poor communication between parents and teachers, and parents’ desire to be involved in planning remote learning for students with special needs during the COVID-19 pandemic lockdown was not met. This study also suggests that schools failed to meet students’ IEPs during remote learning. Furthermore, this study highlights that remote learning for special-needs students is inappropriate without educational assistance.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".