Effects of childhood setting and interaction with nature on academic performance in introductory college-level courses in the environmental sciences

This study explored the relationships between student background and academic performance in college introductory environmental science (ES) courses at a large U.S. research university with the premise that this analysis may inform teaching practices, curricula, and efforts to increase retention. We surveyed over 700 students across eleven introductory ES courses and used multiple linear mixed-effects regressions to model the data. We found that students who grew up in rural settings or who had frequent childhood interactions with natural environments earned higher grades, on average, than students from urban settings or with fewer childhood interactions with natural environments. Our results indicate that students reporting frequent childhood interactions with forests, for example, were projected to earn grades up to 1.5 letter grades higher in these courses than students with no such interactions. In addition, students with frequent childhood interactions with nature were likelier to report that such interactions helped them in their ES course, suggesting that these students may recognize the value of these experiences. Greater interest in the subject matter also correlated with higher ES course grades, whereas amount of prior ES coursework did not. We discuss the possible implications of these correlations for ES academic performance and educational practice.     

Latent variable modeling in the hierarchical modeling framework in longitudinal studies: a fully bayesian approach

This paper presents a strategy for specifying latent variable regressions in the hierarchical modeling framework (LVR-HM). This model takes advantage of the Structural Equation Modeling (SEM) approach in terms of modeling flexibility—regression among latent variables—and of the HM approach in terms of allowing for more general data structures. A fully Bayesian approach via Markov Chain Monte Carlo (MCMC) techniques is applied to the LVR-HM. Through analyzing the data from a longitudinal study of educational achievement, gender difference are explored in the growth of mathematical achievement across grade 7 through grade 10. Allowing for the fact that initial status effect to rates of change may differ for girls and boys, the LVR-HM is specified in a way that rates of change parameters are modeled as a function of initial status parameters and the interaction between initial status and gender.     

Gender differences in academic performance in a large public university in Turkey

The paper attempts to determine whether there are significant gender differences in academic performance among undergraduate students in a large public university in Turkey based on three indicators; university entrance scores, performance in the English preparatory school and in the program the student is majoring in. The paper finds that a smaller number of female students manage to enter the university and when they do so, they enter with lower scores. However, once they are admitted to the university, they excel in their studies and outperform their male counterparts. This result holds after controlling for the field of study and individual attributes.     

Latent variable models: Applications in education

Most theories in the social sciences involve relationships among constructs which are not directly observable. Behavioral measures exist of all constructs, such as intelligence, creativity, and other cognitive traits, aggressiveness, sociability, and other personality and affective characteristics; but these observed measures are usually assumed to be imperfect indicators of the (presumed) underlying construct. The imperfections exist because of errors of measurement and because the observed behavior may be influenced by other underlying constructs in addition to the one of primary interest. Statistical methods, called latent variable models, have been developed to provide rigorous tests of theories involving unobserved variables. This paper describes the major types of latent variable models, shows how they can be applied in educational research, and gives representative examples of their use from the literature.     

Gender differences in the academic career

This study examines sources of satisfaction, indicators of stress, academic performance, and reward structure in the academic careers of male and female faculty at a major midwestern state university. Faculty pairs were selected from five academic divisions. A total of 58 matched pairs were identified. Of these, 63 faculty responded, yielding data for 23 matched pairs. Subjects were mailed the Academic Career Development Survey, consisting of 144 items. Results indicated that self-reported physical and mental health, and professional and personal life satisfaction were high for both males and females. Both males and females placed high importance on their career and on marriage/other intimate relationships; however, both reported high levels of dissatisfaction with these factors. Gender differences were found in both satisfaction and type of stress reported; no gender differences were found in composite teaching and research performance indices. Salary data, obtained for 42 matched pairs, indicated similar salary levels for men and women. Results were discussed with respect to prior research on gender differences and the academic career.     

Ameliorating gender differences in attitudes about science: A cross-national study

The outcomes of two studies reported here indicate that the teacher inservice workshops, combined with activity-based science lessons, affected students' attitudes and perceptions about electricity. Australian and U.S. studies produced different patterns explored and explained in the paper.This material is based upon research supported by the National Science Foundation under grant MDR-88-50570 in the United States and supported by a grant from the Special Projects Program of the Commonwealth Schools Commission in the Education of GirlsDD section of Projects of National Significance in Australia. Any opinions, findings and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the National Science Foundation or the Commonwealth Schools Commission.     

Transition-from-early-to-sophisticated-literacy (TESL) as a factor in cross-national achievement differences

The PISA studies of reading achievement of 15 year old students in OECD and partner nations show Anglophone nations to have continuing high proportions of weak readers (≤Level 2), with no improvement in this area from 2000 to 2006 (OECD, Science competencies for tomorrow’s world: Executive summary, 2007). The nations which have decreased their proportions of low achievers all use highly regular (transparent) orthographies, which expedite the development of efficient reading and writing skills (Galletly and Knight, Aust J Learn Disabil 9(4):4–11, 2004). While international scrutiny is being focussed on socio-cultural differences in education as a basis of nations’ achievement differences, little consideration is currently being applied to the speed of reading accuracy and spelling development. This is surprising, given the volume of research showing that orthographic regularity significantly expedites development of reading—accuracy and spelling—with very low rates of reading difficulties in nations with highly regular orthographies (Seymour et al., Br J Psychol 94:143–174, 2003, p. 174; Share, Psychol Bull 134(4):584–615, 2008, p. 615). This paper proposes Transition-from-early-to-sophisticated-literacy (TESL) as a variable for use when considering cross-national achievement differences. It is proposed that Complex TESL nations (including Anglophone nations) will need paradigmatically different mechanisms to those used by Resolved and Facilitated TESL nations, for improved literacy and academic outcomes by lower achievers.     

comparison of three growth modeling techniques in the multilevel analysis of longitudinal academic achievement scores: Latent growth modeling, hierarchical linear modeling, and longitudinal profile analysis via multidimensional scaling

This study introduces three growth modeling techniques: latent growth modeling (LGM), hierarchical linear modeling (HLM), and longitudinal profile analysis via multidimensional scaling (LPAMS). It compares the multilevel growth parameter estimates and potential predictor effects obtained using LGM, HLM, and LPAMS. The purpose of this multilevel growth analysis is to alert applied researchers to selected analytical issues that are required for consideration in decisions to apply one of these three approaches to longitudinal academic achievement studies. The results indicated that there were no significant distinctions on either mean growth parameter estimates or on the effects of potential predictors to growth factors at both the student and school levels. However, the study also produced equivocal findings on the statistical testing of variance and covariance growth parameter estimates. Other practical issues pertaining to the three growth modeling methods are also discussed.     

Ethnic, gender, and socio-economic group differences in academic performance and secondary school selection: A longitudinal analysis

This study examined gender, socio-economic (SES), and ethnic group differences in academic performance (measured at 14 and 16 years) in a sample of 517 British pupils (mean age = 16.5 years). White pupils outperformed their Black and Pakistani counterparts and high SES pupils consistently outperformed their low SES counterparts. Results from two Multiple Indicators Multiple Causes (MIMIC) models showed that controlling for IQ variance minimizes these group differences. The MIMIC models also revealed that Pakistani pupils and girls tend to underperform academically relative to White pupils and boys, respectively, at 14 years, once IQ and SES have been partialed out. These and other, more specific, findings are discussed with reference to predictive test bias, selection and streaming procedures, and implications for educational policy.     

Soft skills in higher education: importance and improvement ratings as a function of individual differences and academic performance

Three UK studies on the relationship between a purpose‐built instrument to assess the importance and development of 15 ‘soft skills’ are reported. Study 1 (N = 444) identified strong latent components underlying these soft skills, such that differences between‐skills were over‐shadowed by differences between‐students. Importance and improving ratings on these skills predicted academic performance and accounted for the effects of personality on academic performance. Study 2 replicated the structure of the soft skills inventory and associations with academic performance in a larger sample (N = 1309). Examination of mean differences across faculties (humanities, life sciences, hard sciences) revealed higher soft skills ratings in ‘softer’ courses. Study 3 (N = 87) incorporated an IQ measure, which was found to be negatively related to importance ratings on soft skills. Results highlight the cohesive structure of beliefs concerning various non‐academic skills and their significant links to educationally relevant individual differences. Theoretical, methodological and applied implications are considered.     

Gender differences in academic self-efficacy: a meta-analysis

A meta-analysis of 187 studies containing 247 independent studies (N?=?68,429) on gender differences in academic self-efficacy identified an overall effect size of 0.08, with a small difference favoring males. Moderator analysis demonstrated that content domain was a significant moderator in explaining effect size variation. Females displayed higher language arts self-efficacy than males. Meanwhile, males exhibited higher mathematics, computer, and social sciences self-efficacy than females. Gender differences in academic self-efficacy also varied with age. The largest effect size occurred for respondents aged over 23 years old. For mathematics self-efficacy, the significant gender differences emerged in late adolescence. Future research should longitudinally examine gender differences in academic self-efficacy to determine the prevalence of gender differences during different life stages.     

Executive function mediates socio-economic and racial differences in early academic achievement

Although associations between socio-economic status, race, and academic achievement are well established, the specific mechanisms that underlie the relation remain incompletely understood. This longitudinal investigation, involving a sample of 206 children from economically and racially diverse backgrounds, examined the influence of executive function and expressive vocabulary assessed in kindergarten on academic achievement in Grade 1. The use of structural equation modeling revealed that both SES and race had indirect effects on achievement test scores through their effects on executive function, even when accounting for differences in expressive vocabulary. As expected, executive function was more strongly related to math than literacy achievement. The results provide support for the importance of targeting executive skills and intervening early in efforts to improve academic performance in young children. Moreover, the findings suggest that improving executive function may mitigate the impact of social risk factors on academic achievement.     

Predictors of university academic performance in Colombia

This chapter describes the available information about the prediction of college performance in Colombia (South America). Before graduating from high school, students must take a national examination which includes 400 questions grouped into four major areas: sciences (biology, chemistry, and physics), social sciences, language (verbal aptitude and Spanish), and mathematics (mathematical attitude and mathematical knowledge). ICFES scores are used as a major criterion for university admission. Existing research suggests that the correlations between ICFES scores and GPAs tend to be quite small and vary widely from one academic program to another. Other variables (e.g., high school grades) are better predictors of college GPA, quite likely because the same set of personal and socio-cultural variables are needed for both high school and college success.     

Promoting academic satisfaction and performance: Building academic resilience through coping strategies

The aim of this article is twofold: (a) to validate the psychometric properties of the Academic Resilience Scale (AR‐S) in a Spanish university context; and (b) to test a model where different coping strategies are antecedents of AR, and where academic satisfaction and performance are its consequences. The studies were conducted with 185 (study 1) and 780 (study 2) students. In study 1, the construct validity, reliability, and convergent and divergent validity of the AR‐S were analyzed. The hypothesized model (study 2) was tested using structural equation modeling. The results confirmed the good psychometric properties of the AR‐S in the Spanish context, providing evidence of its validity. Furthermore, the distinctive role of different coping strategies in resilience was confirmed, as well as the relationship between resilience and academic satisfaction. No direct relationship between resilience and performance was found, highlighting the full mediation of satisfaction.     

Preferred field of study and academic performance

This paper investigates the impact of studying the first-choice university subject on dropout and switching field of study for a cohort of students in Germany. Using detailed survey data, and employing an instrumental variable strategy based on variation in the local field of study availability, we provide evidence that students who are not enrolled in their preferred field of study are more likely to change their field, delay graduation and drop out of university. The estimated impact on dropout is particularly strong among students of low socio-economic status and is likely to be driven by lower effort and motivation.     

Personality, assessment methods and academic performance

This study examines the relationship between personality and two different academic performance (AP) assessment methods, namely exams and coursework. It aimed to examine whether the relationship between traits and AP was consistent across self-reported versus documented exam results, two different assessment techniques and across different faculties. There were 1,013 (622 female) university students from four British Universities in four faculties namely arts/humanities, social sciences, life/biological sciences and mathematical sciences. Participants completed a brief version of the Big Five inventory and a self-report measure of AP. Conscientiousness and Agreeableness were the strongest personality predictors of AP. Structural equation model showed that sex and personality effects on AP were invariant across different areas of study or degree types (humanities, social sciences, life sciences and hard sciences). Personality variables are stable, robust and predictable correlates and determinants of AP. Conscientiousness, Openness and Agreeableness were positive predictors as measured by good grades whilst Neuroticism and Extraversion were correlates of weaker performance. Implications of these results refer how teachers choose to examine their pupils and to what extent students choose courses because of their known examination procedures.