NEURODIVERSITY IN HIGHER EDUCATION: TIME SERIES DATA ANALYSIS OF THE NEPTUN UNIFIED EDUCATION SYSTEM

T. Zsofia J., Erat David, Varga Aranka
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Abstract

This paper is linked to the current Diversity, Equality, and Inclusion research in higher education. It uses the Process Model of Inclusion to describe educational data of student groups with special needs, with a particular focus on neurodiversity at the University of Pécs (UP). It explores differences that can be identified when comparing student groups over a 10-year time-series analysis of student data from the Neptun Unified Education System (N = 47,194). Using SPSS, we explore admission rates and faculty distribution at entry, supporting factors during the process, and achievement indicators at the time of exiting university. Our results reveal that neurodivergent students appear in the largest proportion among student groups, nearly half of them receive scholarships, about a third of them acquire language proficiency exam certificates before graduation, and only a quarter of them receive dormitory placement. However, the logistic regression analysis substantiates the rather surprising outcome that neurodivergent students are the most likely to graduate successfully from UP, and they are the least likely to defer semesters during their course of study. Our macro-statistical data provide valuable starting points for our ongoing qualitative research that strives to look beyond these numbers for explanations. Keywords: Process Model of Inclusion, higher education, neurodiversity.
高等教育中的神经多样性:对 NEPTUN 统一教育系统的时间序列数据分析
本文与当前高等教育中的多样性、平等和全纳研究有关。它使用 "全纳过程模型"(Process Model of Inclusion)来描述有特殊需求的学生群体的教育数据,尤其关注佩奇大学(UP)的神经多样性。通过对海神统一教育系统的学生数据(N = 47,194)进行 10 年时间序列分析,探讨在比较学生群体时可发现的差异。通过使用 SPSS,我们探讨了入学时的录取率和院系分布、入学过程中的支持因素以及大学毕业时的成就指标。结果显示,神经分裂学生在学生群体中占最大比例,近一半的学生获得奖学金,约三分之一的学生在毕业前获得语言能力考试证书,只有四分之一的学生获得宿舍安排。然而,逻辑回归分析证实了一个相当令人惊讶的结果,即神经变异学生最有可能从大学顺利毕业,而且他们在学习过程中推迟学期的可能性最小。我们的宏观统计数据为我们正在进行的定性研究提供了宝贵的起点,该研究致力于从这些数字之外寻找解释。关键词包容过程模型、高等教育、神经多样性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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