The Test of Accessibility of Higher Education in Israel: Instructors’ Attitudes toward High-Functioning Autistic Spectrum Students
Bibliographic record
Abstract
This study deals with a case study of a program that integrates high-functioning autistic spectrum students in Israeli academia. The case study focuses on the attitudes of students and faculty towards high-functioning autistic spectrum (HFA) students, aiming to examine their contribution to the integration of HFA students in academia, with regard to the academic-social climate and their perceived self-efficacy. The case study may serve academic institutions as a model for the adjustment and integration of autistic spectrum students, with the inclusion of academic and administrative elements. The study is based on mixed methods methodology, utilizing both qualitative and quantitative research methods. Five hundred twenty six students, 103 faculty, as well as 30 students with ASD (autism spectrum disorder) and 27 mentoring students participating in the program, were asked to complete a quantitative research questionnaire. The research findings show that the integration of HFA students in academic studies is potentially possible, predicated on awareness among faculty and students as to the nature of the disability. Variables with high significance for the program's success were detected, involving teaching tools, institutional support, and a tolerant academic-social climate. The research findings indicate that with regard to nearly all the variables the faculty have the highest awareness of and sensitivity to integrating HFA students in academic studies. The literature review, as well as the findings of the current study, support the integration of people with HFA in various institutions and confirm the conditions for this success: institutional and social motivation together with a tolerant atmosphere.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".