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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Student success is a critically important concept in educational assessment and research, yet a comprehensive synthesis of its defining elements remains absent. To address this gap, a scoping review was conducted, identifying 274 peer-reviewed studies published between 2011 and 2022. From these studies, data pertaining to conceptualizations of student success and related factors were extracted and analyzed using inductive coding to uncover key themes and recurring patterns. The review culminated in a comprehensive definition of student success, encompassing five core dimensions: persistence and academic progress, academic performance, attainment of learning objectives, satisfaction, and career success. Additionally, four distinct categories of factors related to student success were identified, including background and pre-college experiences, psychosocial capital, educational experiences, and institutional factors. These findings provide grounds for moving beyond traditional narrow interpretations of student success by acknowledging its multidimensional nature. This understanding of student success’ multidimensionality is essential to equip educational institutions in better preparing students to navigate the complexities of contemporary societal challenges, leading to the development of more well-rounded and successful graduates.
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TitleDefining Student Success as a Multidimensional Concept: a Scoping Review (additional files)DescriptionStudent success is a critically important concept in educational assessment and research. Yet, a universal definition of the concept has not been established. A comprehensive scoping review was conducted to define student success and take inventory of associated factors. This page contains files pertaining to the publication that presents the findings.
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Introduction Student success is positively linked to engagement, but negatively linked to emotional exhaustion. Though both constructs have been conceptualized as opposites previously, we hypothesize that students can demonstrate high or low engagement and emotional exhaustion simultaneously. We used quantitative and qualitative data to identify the existence of four student profiles based on engagement and exhaustion scores. Furthermore, we studied how profiles associate to study behaviour, wellbeing and academic achievement, and what risks, protective factors and support requirements students and teachers identify for these profiles. Methods The Student Wellbeing Monitor 2021, developed by Inholland University of Applied Sciences, was used to identify profiles using quadrant analyses based on high and low levels of engagement and emotional exhaustion (n= 1460). Correlation analyses assessed profile specific differences on study behaviours, academic delay, and wellbeing. Semi-structured interviews with students and teachers are currently in progress to further explore the profiles, to identify early signals, and to inspect support requirements. Results The quadrant analysis revealed four profiles: low engagement and low exhaustion (energised-disengaged; 9%), high engagement and low exhaustion (energised-engaged; 15%), low engagement and high exhaustion (exhausted-disengaged; 48%), and high engagement and high exhaustion (exhausted-engaged; 29%). Overall, engaged students demonstrated more active study behaviours and more social connections and interactions with fellow students and teachers. The exhausted students scored higher on depressive symptoms and stress. The exhausted-engaged students reported the highest levels of performance pressure, while the energised-disengaged students had the lowest levels of performance pressure. So far, students and teachers recognise the profiles and have suggested several support recommendations for each profile. Discussion The results show that students can be engaged but at the same time are exhausting themselves. A person-oriented mixed-methods approach helps students and teachers gain awareness of the diversity and needs of students, and improve wellbeing and student success.
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Kick-Start College is a three-day pre-academic program (summer school) for prospective first year students of Inholland Rotterdam, University of Applied Sciences. The aim is to integrate students academically and socially, which could make the transition to higher education easier and eventually lead to lower dropout rates of students. Research has been conducted on both student experiences with the program as well as effects of the program. Method: pretest-posttest with academic-, social-, professional- and university integration1, self-esteem, motivation, evaluation.
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Mastering academic language (AL) by elementary school students is important for achieving school success. The extent to which teachers play a role in stimulating students’ AL development may differ. Two types of AL stimulating behavior are distinguished: aimed at students’ understanding and at triggering students’ production of AL. As mathematics requires abstract language use, AL occurs frequently. The instructional methods teachers use during mathematics instruction may offer different opportunities for AL stimulating behavior. In our first study, based on expert opinions, instructional methods were categorized according to opportunities they offer for stimulating students’ AL development. In the second study, video-observations of mathematics instruction of elementary school teachers were analyzed with respect to AL stimulating behavior and instructional methods used. Results showed that actual AL stimulating behavior of teachers corresponds to the expert opinions, except for behavior shown during task evaluation. Teachers differ in time and frequency of their use of instructional methods and therefore in opportunities for stimulating AL development. Four teaching profiles, reflecting different AL stimulating potential, were constructed: ‘teacher talking’, ‘balanced use of methods’, ‘getting students at work’ and ‘interactive teaching’. Teachers showed more types of behavior aimed at students’ AL understanding than at production.
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The transition from secondary education to the first year of higher education is a phase in which students are faced with many challenges. First-year students may lack the academic capital that is needed to understand explicit and implicit rules of higher education. We investigated students’ participation in a preacademic program and the development of their academic capital. In a mixed method study, we showed that first-year students who participated in a preacademic program perceived peer mentors and teachers to be relevant sources of information, learned how to overcome educational barriers, and became more acquainted with explicit and implicit college requirements.
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Injuries can have a major impact on the physical performance and academic career of physical education teacher education (PETE) students. To investigate the injury problem, risk factors, and the impact of injuries on academic success, 252 PETE students were followed during their first semester. Risk factor analysis was conducted by means of logistic regression analysis with a differentiation for upper body, lower body, acute, overuse, and severe injuries. An incidence of 1.26 injuries/student/semester was found. Most injuries involved the lower body (61%), were new injuries (76%), occurred acutely (66%), and were sustained during curricular gymnastics (25%) or extracurricular soccer (28%). Significant risk factors for lower body acute injuries were age (OR=2.14; P=.01), previous injury (OR=2.23; P=.01), and an injury at the start of the year (OR=2.56; P=.02). For lower body overuse injuries, gender (OR=2.85; P=.02) and the interval shuttle run test score (OR=2.44; P=.04) were significant risk factors. Previous injury (OR=2.59; P=.04) and injury at the start of the year (upper body: OR=4.57; P=.02; lower body: OR=3.75; P<.01) were risk factors for severe injuries. Injury‐related time loss was positively related to total academic success (r=.20; P=.02) and success in theoretical courses (r=.24; P=<.01). No association was found between time loss and academic success for sport courses.
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The COVID-19 pandemic has forced higher education (HE) to shift to emergency remote teaching (ERT), subsequently influencing academic belonging and social integration, as well as challenging students' engagement with their studies. This study investigated influences on student engagement during ERT, based on student resilience. Serial mediation analyses were used to test the predictive effects between resilience, academic belonging, social integration, and engagement.
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This article describes the relation between mental health and academic performance during the start of college and how AI-enhanced chatbot interventions could prevent both study problems and mental health problems.
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