Identifying science students at risk in the first year of higher education: the incremental value of non-cognitive variables in predicting early academic achievement

Willems, Jonas; Coertjens, Liesje; Tambuyzer, Bart; Donche, Vincent

doi:10.1007/s10212-018-0399-4

Cited by 29 publications

(21 citation statements)

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“…The aim of the current study was 2-fold: (1) to identify student profiles that include cognitive, metacognitive and motivational aspects of learning, as well as aspects of mental healthresilience, emotion dysregulation anxiety, and procrastination, and (2) to investigate whether or not students with different profiles also differ regarding GPA and success rate in their first year of study. Although current research on students' profiles has identified profiles based on cognitive, metacognitive and motivational aspects of learning, aspects of mental health and well-being have been largely neglected so far (Willems et al, 2018) despite playing a crucial role in students' transition from secondary to higher education and having an impact on students' achievement (Schaeper, 2019). Therefore, the current study focuses on determining (meta)cognitiveemotional learner profiles in first-year students in higher education and how these different profiles differ with regard to academic achievement.…”

Section: Discussionmentioning

confidence: 99%

“…In this line of thinking, the first year of studies in university appears to play an important role in students' future academic achievement and well-being, and consequently in their future professional success and their personal development (Leese, 2010;Trautwein and Bosse, 2017). Even though the predictive power of cognitive factors has been extensively studied, the investigation of a combination of non-cognitive factors such as self-regulation, motivation, and anxiety (Fonteyne et al, 2017;Willems et al, 2018) along with mental health and personality variables (Schneider and Preckel, 2017;Schaeper, 2019) should also be included as they seem to influence this crucial period in students' life.…”

Section: Introductionmentioning

confidence: 99%

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The Contribution of Learning and Mental Health Variables in First-Year Students' Profiles

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International studies focus on the successful transition into higher education, which is considered crucial for both the students and the educational institution in the context of students' learning and adjustment in higher education. The aim of the current study was to identify student profiles that include cognitive, metacognitive, and motivational aspects of learning, but also aspects of resilience, emotion dysregulation, and anxiety. The sample consists of 316 Greek undergraduate students (18.7% males and 81.3% females). The results showed four different (meta)-cognitive-emotional learner profiles: the emotionally stable and highly adaptive learner; the emotionally dysregulated and at risk learner; the emotionally dysregulated and highly adaptive learner; the emotionally stable and at risk learner. Emotionally dysregulated and at risk learner has a lower GPA than the emotional stable and highly adaptive learner, the emotionally dysregulated and highly adaptive learner and the emotionally stable and at risk learner.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Contribution of Learning and Mental Health Variables in First-Year Students' Profiles

et al. 2021

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“…A distinction must therefore be made between different types of academic motivation. Thus, we distinguish between autonomous motivation, which involves the study of a personal interest (intrinsic regulation), and controlled motivation, which involves the existence of external sources of motivation (external regulation) or a desire to rise to the expectations of others (introjected regulation) (Tang et al, 2018;Willems et al, 2019).…”

Section: Academic Motivationmentioning

confidence: 99%

The academic climate and student-teacher relationship as determinants of academic motivation

Toma

2020

Studia Doctoralia

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In this study we focus on the university students and the factors that influence their academic motivation. The participants were 202 students from different universities and specializations, 167 females and 35 males, aged 18-31 years, M = 21.33, SD = 2.15. We used Perceived Academic Climate Scale (Felner, 1993), Teacher-Student Relationship Scale (Brinkworth et al., 2018), and Academic Motivation Scale (Vallerand et al., 1992). Our objective was to identify the relationship between academic climate, teacher-student relationship (TSR), and academic motivation in the university environment, and to investigate the influence of the career anxiety on the academic motivation of students. The results show that anxiety regarding future career can moderate the relationship between school climate and academic amotivation and also between TSR and academic motivation.

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“…After analyzing the literature on the use of this terminology in different subject fields, York et al identified six elements which define it namely: academic achievement; engagement in educationally purposeful activities; satisfaction; acquisition of desired knowledge, skills and competencies; persistence; attainment of educational outcomes, and post-college performance (p. 5). Furthermore, Education Data Mining (EDM) has been used for predicting a variety of crucial educational outcomes such as performance, success, satisfaction, and achievement (Calvet Llinan and Juan Perez, 2015;Dutt et al 2017;Anoopkumar and Rahman, 2016;Martins et al 2019;Willems et al 2019). Despite all these publications, it is still difficult for faculty to effectively apply known techniques to specific academic problems.…”

Section: Introductionmentioning

confidence: 99%

Teaching all students: A holistic and collaborative approach to increasing student success

Udeogalanya¹

2020

IJHEM

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All students who enroll have success as their main goal. However, most institutions focus their resources on programs for students on honor roll, Dean's list and those progressing academically. Little resources remain for those students who stumble. In 2015, 36.2% of white students, 22.5% of black students, and 15.5% of Hispanic students had completed four years of college. This shows a 13.7% gap between black and white students and a 20.7% gap between Hispanic and white students (Wellman, 2017). How do we close this gap in educational completion? This study believes that all students can learn. Consequently, there needs to be educational equity and the development of a basis for instruction and assessment of all students' learning outcomes. This paper represents an exploratory fundamental and qualitative research that aims to present a refocus on the role of faculty in teaching and learning to reach all students in classrooms. It examines a holistic and collaborative approach to increasing student success using evidence-based qualitative analysis of best practices. This approach has four component parts. Part 1 is the Holistic Component that involves engaging all students in the institution; communicating purposefully to them in a timely manner; and providing all-inclusive comprehensive support services (HC). This part develops and implements measurable benchmarks that motivate, encourage, and enable all students. Part 2 is the Collaborative Component which involves bringing six working teams together: faculty, industry, current majors, alumni, career services, and the community (CC). This part engages the team in maintaining a living curriculum that reflects the everchanging global economy. Part 3 is Celebration of Student Success (CSS) which entails the collaborative team owning each milestone, reaffirming teamwork while building trust and persistence. Part 4 is the Assessment of Student Progress (ASP) using the holistic and collaborative approach. The paper concludes that holistic and collaborative teamwork that includes, respects, and empowers all students is the key to reducing the college completion gaps that exist among blacks and Hispanic students.

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Identifying science students at risk in the first year of higher education: the incremental value of non-cognitive variables in predicting early academic achievement

Cited by 29 publications

References 71 publications

The Contribution of Learning and Mental Health Variables in First-Year Students' Profiles

The Contribution of Learning and Mental Health Variables in First-Year Students' Profiles

The academic climate and student-teacher relationship as determinants of academic motivation

Teaching all students: A holistic and collaborative approach to increasing student success

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