Antecedents of academic performance of university students: academic engagement and psychological capital resources

Predicting academic performance is of key importance to the success, wellbeing and prosperity of students, their families, the economy, and the society at large. This study investigates the relationship between academic engagement, psychological capital (PsyCap) and academic performance. Data were collected in two different universities, one in Spain and another in Portugal. Students completed two self-report questionnaires regarding academic engagement and Psychological Capital. Academic performance was assessed through Grade Point Average, provided by the universities at the end of the exam period. The samples consisted of 389 and 243 undergraduate students, respectively. Results showed a positive relationship between academic engagement and PsyCap, on the one hand, and academic performance on the other, in both samples. Results also supported PsyCap as a full mediator in the relationship between academic engagement and academic performance. Exploration of alternative models yielded superior fit for the proposed model. Accordingly, academically engaged students were likely to experience higher levels of PsyCap, which in turn positively impacted their academic performance. The results point to the importance of considering psychological predictors, rather than the prevalent reliance on traditional predictors of academic performance

The Relationships between High School Subjects in terms of School Satisfaction and Academic Performance in Mexican Adolescents

Adolescents’ academic performance and the way it is related to their subjective wellbeing are issues of great interest across educational systems. The purpose of this study was to ascertain how satisfaction with high school subjects can predict school satisfaction and academic performance in Mexican students. The sample consisted of 457 high school students in the Baja California and Nuevo León states in Mexico (247 boys, 210 girls); their mean age being 14.10 (SD = 0.84). We used a questionnaire featuring a subject satisfaction scale, an intrinsic school satisfaction scale, and one related to academic grades. We used descriptive analyses, correlations, and structural regression models. In terms of results, the high satisfaction and academic performance levels in physical education, Spanish and English are worth highlighting. Geography and history are the most relevant predictors of academic grades, while Spanish predicts school satisfaction and physical education predicts boredom. In conclusion, satisfaction with mathematics, Spanish, and English are strong predictors of satisfaction (SATF), and the latter in turn predicts Mexican high school students’ academic performance

How Do Student and School Characteristics Influence Youth Academic Performance in Ghana? A Hierarchical Linear Modeling of Baseline Data From the YouthSave Ghana Experiment

Student and school characteristics are associated with academic performance of high school students. However, few attempts have been made to examine the simultaneous influence of student and school factors on academic performance of youth in sub-Saharan Africa. Using hierarchical linear modeling, we examine student- and school- level predictors of academic performance of Ghanaian junior high school students. As other researchers have found, we note that age and gender are significant predictors of academic performance. Student traits, including academic self-efficacy and commitment to school, are positively associated with math and English scores. Class size and presence of a toilet facility are significant predictors of English scores. No school-level characteristic is significantly associated with math performance. Through this study, we suggest that student characteristics have more impact on youth’s academic performance than school characteristics

Self-concept in learning disabled children : relationship to perceived competence, social support and task performance : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science at Massey University

Examined how some children with learning disabilities (LD) sustain higher levels of general self-worth despite academic difficulties. Global self-worth was examined for a relationship with academic self-concept, non-academic self-concept, and perceived social support. Self-concept was additionally examined for any relationships with task performance indicators. Data were collected from 41 students aged between 7 and 15 years using a multitrait-multimethod assessment methodology. Self-concept was assessed by the Self-Perception Profile for Children (Harter, 1985a), and perceived social support was assessed by the Social Support Scale for Children (Harter, 1985b). Task performance was assessed by a battery of academic and motor skill measures. Findings indicated that most LD children in this sample reported low levels of academically based self-concept. However, most also reported high levels of global self-worth. The study found students with high global self-concept perceived they were more competent/adequate in some non-academic domains (e.g., physical appearance and behavioural conduct), and perceived being socially supported, particularly by teachers. Perceptions of academic self-concept were not found to be as related to perceptions of global self-concept as non-academic domains. In regression analyses, perceptions of physical appearance followed by perceptions of athletic competence were found to be predictors of global self-worth. No predictors were found to be significant for academic self-concept. Classmate support predicted aspects of social self-concept (i.e., social acceptance). No pattern of significant relationships were found between task performance indicators and various domains of self-concept. Discussion includes using data to dispel myths some may have about the global self-worth of LD children as well as in intervention programmes. This study replicated and extended research in this area. Caveats and recommendations for future research are discussed

Sleep and Academic Performance in Undergraduates: A Multi-measure, Multi-predictor Approach

The present study examined the associations of sleep patterns with multiple measures of academic achievement of undergraduate university students and tested whether sleep variables emerged as significant predictors of subsequent academic performance when other potential predictors, such as class attendance, time devoted to study, and substance use are considered. A sample of 1654 (55% female) full-time undergraduates 17 to 25 yrs of age responded to a self-response questionnaire on sleep, academics, lifestyle, and well-being that was administered at the middle of the semester. In addition to self-reported measures of academic performance, a final grade for each student was collected at the end of the semester. Univariate analyses found that sleep phase, morningness/eveningness preference, sleep deprivation, sleep quality, and sleep irregularity were significantly associated with at least two academic performance measures. Among 15 potential predictors, stepwise multiple regression analysis identified 5 significant predictors of end-of-semester marks: previous academic achievement, class attendance, sufficient sleep, night outings, and sleep quality (R(2)=0.14 and adjusted R(2)=0.14, F(5, 1234)= 40.99, p < .0001). Associations between academic achievement and the remaining sleep variables as well as the academic, well-being, and lifestyle variables lost significance in stepwise regression. Together with class attendance, night outings, and previous academic achievement, self-reported sleep quality and self-reported frequency of sufficient sleep were among the main predictors of academic performance, adding an independent and significant contribution, regardless of academic variables and lifestyles of the students

The efficacy of using data mining techniques in predicting academic performance of architecture students.

In recent years, there has been a tremendous increase in the number of applicants seeking placement in the undergraduate architecture programme. It is important to identify new intakes who possess the capability to succeed during the selection phase of admission at universities. Admission variable (i.e. prior academic achievement) is one of the most important criteria considered during selection process. The present study investigates the efficacy of using data mining techniques to predict academic performance of architecture student based on information contained in prior academic achievement. The input variables, i.e. prior academic achievement, were extracted from students' academic records. Logistic regression and support vector machine (SVM) are the data mining techniques adopted in this study. The collected data was divided into two parts. The first part was used for training the model, while the other part was used to evaluate the predictive accuracy of the developed models. The results revealed that SVM model outperformed the logistic regression model in terms of accuracy. Taken together, it is evident that prior academic achievement are good predictors of academic performance of architecture students. Although the factors affecting academic performance of students are numerous, the present study focuses on the effect of prior academic achievement on academic performance of architecture students. The developed SVM model can be used a decision-making tool for selecting new intakes into the architecture program at Nigerian universities

Age is no barrier: predictors of academic success in older learners

Although predictors of academic success have been identified in young adults, such predictors are unlikely to translate directly to an older student population, where such information is scarce. The current study aimed to examine cognitive, psychosocial, lifetime, and genetic predictors of university-level academic performance in older adults (50–79 years old). Participants were mostly female (71%) and had a greater than high school education level (M = 14.06 years, SD = 2.76), on average. Two multiple linear regression analyses were conducted. The first examined all potential predictors of grade point average (GPA) in the subset of participants who had volunteered samples for genetic analysis (N = 181). Significant predictors of GPA were then re-examined in a second multiple linear regression using the full sample (N = 329). Our data show that the cognitive domains of episodic memory and language processing, in conjunction with midlife engagement in cognitively stimulating activities, have a role in predicting academic performance as measured by GPA in the first year of study. In contrast, it was determined that age, IQ, gender, working memory, psychosocial factors, and common brain gene polymorphisms linked to brain function, plasticity and degeneration (APOE, BDNF, COMT, KIBRA, SERT) did not influence academic performance. These findings demonstrate that ageing does not impede academic achievement, and that discrete cognitive skills as well as lifetime engagement in cognitively stimulating activities can promote academic success in older adults

Contextual Factors Associated with the Achievement of African American and European American Adolescents: A Diversimilarity Approach

The current study is an extension of Luster & McAdoo\u27s 1994 study of African American children and ecological factors impacting academic performance of these children. Luster and McAdoo found that maternal educational level, income, number of children and living conditions were related to how well children performed in school. Those children from impoverished backgrounds with uneducated mothers had lower quality academic performance. Using the Nation Longitudinal Survey of Youth data (1992), the current study investigated similarities and differences in the impact of ecological factors in European American(n = 266) and African American adolescents (n = 400). The results indicated that the home environment best predicts academic performance in African American adolescents while neighborhood conditions are better predictors of academic performance in European American adolescents. This difference may be related to the function of education for the two groups. Education may be a vehicle for status enhancement for European American adolescents. For African Americans, education may enhance class but not social status associated with racial minority status. These results suggest that educational efforts be developed to assist all adolescent in achieving both status and class objectives

The Contribution of Psychological Maturity and Personality in the Prediction of Adolescent Academic Achievement

Numerous studies show that intelligence and impulsiveness are important predictors of academic achievement in adolescence. However, it is not clear what contribution is made by the big five personality traits, because some studies suggest that Conscientiousness, Extraversion and Openness to experience are predictors while others show precisely the opposite. Direct aggression, through its relationship with impulsiveness, is another factor that has been linked to academic achievement. However, no previous studies have been made on the relationship that indirect aggression and psychological maturity have with academic achievement. For this reason, the purpose of this study is to determine the relative importance of psychological maturity, indirect aggression and the big five personality traits in predicting academic achievement in adolescents. As was expected, results show that intelligence and impulsivity are important predictors of academic performance. As far as psychological maturity is concerned, only the Work orientation component is related to academic performance. However, indirect aggression is not related to academic performance. The results pertaining to the big five personality traits suggest that Conscientiousness and Openness to experience are important for predicting academic achievemen