Page 84 - Secondary school students’ university readiness and their transition to university Els van Rooij

Systematic review of rst-year success
3
83
Table I (continued) Overview of the characteristics and main results of the included studies
Ref. Author (year) nr.
Country / Level of education
/ Degree programme
Analysis
Outcome Category: independent variables used in variables the study
Main ndings (pertaining to the review)
11 De Wit, Heerwegh, & Verhoeven
Flanders / University / All programmes at one university
Regression
EC Ability: secondary school GPA
GPA Demographic: gender, SES
Persistence Prior education: secondary school hours of
Predictors of retention were secondary school hours of mathematics, ambivalence towards the study choice (negative e ect), secondary school GPA, and secondary school hours of classical languages. Predictors of study e ciency (i.e., percentage of exams passed, comparable to EC) and GPA were secondary school GPA, secondary school hours of mathematics, ambivalence towards the study choice (negative e ect), secondary school hours of classical languages, intrinsic motivation, and educational level of the parents.
(2012)
mathematics, secondary school hours of classical languages
Motivation: intrinsic motivation Psychosocial: engagement in social activities, ambivalent attitude towards study choice
12 Ferla, Valcke, & Schuyten (2010)
Flanders / University / Psychology and Educational Sciences
Path analysis
GPA Motivation: academic self-e cacy, self- e cacy for self-regulation, academic self-
Academic self-e cacy substantially predicted GPA. Persistence (positive) and surface learning (negative) also predicted GPA. Perceived level of understanding (negative), self-e cacy for self-regulated learning, mastery goals, and performance approach goals in uenced persistence, and perceived level of understanding negatively in uenced surface learning.
concept, perceived level of understanding, mastery goals, performance achievement goals, performance avoidance goals Learning strategies: deep learning, surface learning
Engagement: persistence