Predicting Academic Success of Autistic Students in Higher Education
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| Title: | Predicting Academic Success of Autistic Students in Higher Education |
|---|---|
| Language: | English |
| Authors: | Bakker, Theo (ORCID |
| Source: | Autism: The International Journal of Research and Practice. Aug 2023 27(6):1803-1816. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 14 |
| Publication Date: | 2023 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Predictor Variables, Academic Achievement, Autism Spectrum Disorders, Models, Accuracy, Undergraduate Students, Scores, School Holding Power, Bachelors Degrees, Foreign Countries |
| Geographic Terms: | Netherlands (Amsterdam) |
| DOI: | 10.1177/13623613221146439 |
| ISSN: | 1362-3613 1461-7005 |
| Abstract: | Individuals with autism increasingly enroll in universities, but little is known about predictors for their success. This study developed predictive models for the academic success of autistic bachelor students (N = 101) in comparison to students with other health conditions (N = 2465) and students with no health conditions (N = 25,077). We applied propensity score weighting to balance outcomes. The research showed that autistic students' academic success was predictable, and these predictions were more accurate than predictions of their peers' success. For first-year success, study choice issues were the most important predictors (parallel program and application timing). Issues with participation in pre-education (missingness of grades in pre-educational records) and delays at the beginning of autistic students' studies (reflected in age) were the most influential predictors for the second-year success and delays in the second and final year of their bachelor's program. In addition, academic performance (average grades) was the strongest predictor for degree completion in 3 years. These insights can enable universities to develop tailored support for autistic students. Using early warning signals from administrative data, institutions can lower dropout risk and increase degree completion for autistic students. |
| Abstractor: | As Provided |
| Entry Date: | 2023 |
| Accession Number: | EJ1386540 |
| Database: | ERIC |
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| Abstract: | Individuals with autism increasingly enroll in universities, but little is known about predictors for their success. This study developed predictive models for the academic success of autistic bachelor students (N = 101) in comparison to students with other health conditions (N = 2465) and students with no health conditions (N = 25,077). We applied propensity score weighting to balance outcomes. The research showed that autistic students' academic success was predictable, and these predictions were more accurate than predictions of their peers' success. For first-year success, study choice issues were the most important predictors (parallel program and application timing). Issues with participation in pre-education (missingness of grades in pre-educational records) and delays at the beginning of autistic students' studies (reflected in age) were the most influential predictors for the second-year success and delays in the second and final year of their bachelor's program. In addition, academic performance (average grades) was the strongest predictor for degree completion in 3 years. These insights can enable universities to develop tailored support for autistic students. Using early warning signals from administrative data, institutions can lower dropout risk and increase degree completion for autistic students. |
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| ISSN: | 1362-3613 1461-7005 |
| DOI: | 10.1177/13623613221146439 |
