A Study of Lifelong Education for Persons with Intellectual Disabilities at the University Level
Bibliographic record
Abstract
Background: In recent years, there has been growing interest in developing lifelong education for persons with disabilities at universities and other institutions of higher learning. However, there is still a lack of practical research on people with intellectual disabilities who participate in lifelong education. Objective: This study analyzes the experiences of participants with intellectual disabilities obtained from the practice of the Lifelong Education Program for Persons with Disabilities (AULEPP). It discusses perspectives for the future development of lifelong education. Methods: Eleven persons with intellectual disabilities who participated in the AULEPP from October 2021 to February 2022 were included in the study. Three surveys were administered to these participants before and after the AULEPP and for each lecture. Results: The average number of participants in each lecture was 5.2, and four participants attended more than eight lectures. Qualitative analysis of the survey results revealed that participants acquired new knowledge, expressed the need for continuous learning, and proposed new questions. The lectures helped them recognize changes in their perspectives on daily life and society. Most of the lectures were conducted online, but there were no negative comments about this modality. Conclusions: The study revealed the need to create opportunities for participants to find meaning in lectures, the effectiveness of online media, and the role of lifelong college education in the community. It is necessary to investigate the transferability of these results to urban areas and explore outcome measures and program content to build an evidence-based lifelong learning program.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".