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Predictors of Inclusive Course Enrollments in Higher Education by Students With Intellectual and Developmental Disabilities.

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Title: Predictors of Inclusive Course Enrollments in Higher Education by Students With Intellectual and Developmental Disabilities.
Authors: Papay, Clare1 clare.papay@umb.edu, Grigal, Meg1, Hart, Debra1, Ngai Kwan1, Smith, Frank A.1
Source: Intellectual & Developmental Disabilities. Dec2018, Vol. 56 Issue 6, p458-470. 13p.
Subject Terms: *Education of people with intellectual disabilities, *Individualized instruction, *Developmental disabilities, *Learning disabilities, *Intellectual disabilities
Abstract: Higher education programs for students with intellectual and developmental disabilities (IDD) offer opportunities to engage in college experiences including access to typical college courses. The purpose of the present study was to examine data from federally funded programs in order to describe and identify predictors of inclusive course enrollments. Data on 672 first-year students with IDD who enrolled in 3,233 inclusive college courses were analyzed. Significant predictors were the age of the student, whether the student attended a program that offered access to regular student advising or provided an official transcript, whether the student took any specialized courses, and whether the student had a paid job or participated in particular career development experiences. Implications for higher education programs are discussed. [ABSTRACT FROM AUTHOR]
Copyright of Intellectual & Developmental Disabilities is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Predictors of Inclusive Course Enrollments in Higher Education by Students With Intellectual and Developmental Disabilities.
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  Data: <searchLink fieldCode="JN" term="%22Intellectual+%26+Developmental+Disabilities%22">Intellectual & Developmental Disabilities</searchLink>. Dec2018, Vol. 56 Issue 6, p458-470. 13p.
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  Data: *<searchLink fieldCode="DE" term="%22Education+of+people+with+intellectual+disabilities%22">Education of people with intellectual disabilities</searchLink><br />*<searchLink fieldCode="DE" term="%22Individualized+instruction%22">Individualized instruction</searchLink><br />*<searchLink fieldCode="DE" term="%22Developmental+disabilities%22">Developmental disabilities</searchLink><br />*<searchLink fieldCode="DE" term="%22Learning+disabilities%22">Learning disabilities</searchLink><br />*<searchLink fieldCode="DE" term="%22Intellectual+disabilities%22">Intellectual disabilities</searchLink>
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  Data: Higher education programs for students with intellectual and developmental disabilities (IDD) offer opportunities to engage in college experiences including access to typical college courses. The purpose of the present study was to examine data from federally funded programs in order to describe and identify predictors of inclusive course enrollments. Data on 672 first-year students with IDD who enrolled in 3,233 inclusive college courses were analyzed. Significant predictors were the age of the student, whether the student attended a program that offered access to regular student advising or provided an official transcript, whether the student took any specialized courses, and whether the student had a paid job or participated in particular career development experiences. Implications for higher education programs are discussed. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Intellectual & Developmental Disabilities is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Dec2018
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