Whence a healthy mind: Correlation of physical fitness and academic performance among schoolchildren

Background. Public schools are a key forum in the fight for child health because of the opportunities they present for physical activity and fitness surveillance. However, because schools are evaluated and funded on the basis of standardized academic performance rather than physical activity, empirical research evaluating the connections between fitness and academic performance is needed to justify curriculum allocations to physical activity. ^ Methods. Analyses were based on a convenience sample of 315,092 individually-matched standardized academic (TAKS™) and fitness (FITNESSGRAM®) test records collected by 13 Texas school districts under state mandates. We categorized each fitness result in quintiles by age and gender and used a mixed effects regression model to compare the academic performance of the top and bottom fitness groups for each fitness test and grade level combination. ^ Results. All fitness variables except BMI showed significant, positive associations with academic performance after sociodemographic covariate adjustments, with effect sizes ranging from 0.07 (95% CI: 0.05,0.08) in girls trunklift-TAKS reading to 0.34 (0.32,0.35) in boys cardiovascular-TAKS math. Cardiovascular fitness showed the largest inter-quintile difference in TAKS score (32-75 points), followed by curl-ups. After an additional adjustment for BMI and curl-ups, cardiovascular associations peaked in 8th-9 th grades (maximum inter-quintile difference 142 TAKS points; effect size 0.75 (0.69,0.82) for 8th grade girls math) and showed dose-response characteristics across quintiles (p<0.001 for both genders and outcomes). BMI analysis demonstrated limited, non-linear association with academic performance after adjustment for sociodemographic, cardiovascular fitness and curl-up variables. Low-BMI Hispanic high school boys showed significantly lower TAKS scores than the moderate (but not high) BMI group. High-BMI non-Hispanic white high school girls showed significantly lower scores than the moderate (but not low) BMI group. ^ Conclusions. In this study, fitness was strongly and significantly related to academic performance. Cardiovascular fitness showed a distinct dose-response association with academic performance independent of other sociodemographic and fitness variables. The association peaked in late middle to early high school. The independent association of BMI to academic performance was only found in two sub-groups and was non-linear, with both low and high BMI posing risk relative to moderate BMI but not to each other. In light of our findings, we recommend that policymakers consider PE mandates in middle-high school and require linkage of academic and fitness records to facilitate longitudinal surveillance. School administrators should consider increasing PE time in pursuit of higher academic test scores, and PE practitioners should emphasize cardiovascular fitness over BMI reduction.^

Simulation of academic performance rates, estimation of indicators of subjects and of a complete degree

The purpose of this paper is to present a program written in Matlab-Octave for the simulation of the time evolution of student curricula, i.e, how students pass their subjects along time until graduation. The program computes, from the simulations, the academic performance rates for the subjects of the study plan for each semester as well as the overall rates, which are a) the efficiency rate defined as the ratio of the number of students passing the exam to the number of students who registered for it and b) the success rate, defined as the ratio of the number of students passing the exam to the number of students who not only registered for it but also actually took it. Additionally, we compute the rates for the bachelor academic degree which are established for Spain by the National Quality Evaluation and Accreditation Agency (ANECA) and which are the graduation rate (measured as the percentage of students who finish as scheduled in the plan or taking an extra year) and the efficiency rate (measured as the percentage of credits which a student who graduated has really taken). The simulation is done in terms of the probabilities of passing all the subjects in their study plan. The application of the simulator to Polytech students in Madrid, where requirements for passing are specially stiff in first and second year subjects, is particularly relevant to analyze student cohorts and the probabilities of students finishing in the minimum of four years, or taking and extra year or two extra years, and so forth. It is a very useful tool when designing new study plans. The calculation of the probability distribution of the random variable "number of semesters a student has taken to complete the curricula and graduate" is difficult or even unfeasible to obtain analytically, and this is even truer when we incorporate uncertainty in parameter estimation. This is why we apply Monte Carlo simulation which not only provides illustration of the stochastic process but also a method for computation. The stochastic simulator is proving to be a useful tool for identification of the subjects most critical in the distribution of the number of semesters for curriculum vitae (CV) completion and subsequently for a decision making process in terms of CV planning and passing standards in the University. Simulations are performed through a graphical interface where also the results are presented in appropriate figures. The Project has been funded by the Call for Innovation in Education Projects of Universidad Politécnica de Madrid (UPM) through a Project of its school Escuela Técnica Superior de Ingenieros Industriales ETSII during the period September 2010-September 2011.

Learning Analytics and Interactions in Virtual Learning Environments. A Comparative Study of Typologies and their Relationship with Academic Performance

Analysis of learning data (learning analytics) is a new research field with high growth potential. The main objective of Learning analytics is the analysis of data (interactions being the basic data unit) generated in virtual learning environments, in order to maximize the outcomes of the learning process; however, a consensus has not been reached yet on which interactions must be measured and what is their influence on learning outcomes. This research is grounded on the study of e-learning interaction typologies and their relationship with students? academic performance, by means of a comparative study between different interaction typologies (based on the agents involved, frequency of use and participation mode). The main conclusions are a) that classifications based on agents offer a better explanation of academic performance; and b) that each of the three typologies are able to explain academic performance in terms of some of their components (student-teacher and student-student interactions, evaluating students interactions and active interactions, respectively), with the other components being nonrelevant.

Predicting academic performance with learning analytics in virtual learning environments: A comparative study of three interaction classifications

Learning analytics is the analysis of static and dynamic data extracted from virtual learning environments, in order to understand and optimize the learning process. Generally, this dynamic data is generated by the interactions which take place in the virtual learning environment. At the present time, many implementations for grouping of data have been proposed, but there is no consensus yet on which interactions and groups must be measured and analyzed. There is also no agreement on what is the influence of these interactions, if any, on learning outcomes, academic performance or student success. This study presents three different extant interaction typologies in e-learning and analyzes the relation of their components with students? academic performance. The three different classifications are based on the agents involved in the learning process, the frequency of use and the participation mode, respectively. The main findings from the research are: a) that agent-based classifications offer a better explanation of student academic performance; b) that at least one component in each typology predicts academic performance; and c) that student-teacher and student-student, evaluating students, and active interactions, respectively, have a significant impact on academic performance, while the other interaction types are not significantly related to academic performance.

Teamwork, motivational profiles and academic performance in computer science engineering

The present work is aimed at discussing several issues related to the teamwork generic competence, motivational profiles and academic performance. In particular, we study the improvement of teamwork attitude, the predominant types of motivation in different contexts and some correlations among these three components of the learning process. The above-mentioned aspects are of great importance. Currently, the professional profile of engineers has a strong teamwork component and the motivational profile of students determines both their tendencies when they come to work as part of a team, as well as their performance at work. Taking these issues into consideration, we suggest four hypotheses: (H1) students improve their teamwork capacity through specific training and carrying out of a set of activities integrated into an active learning process; (H2) students with higher mastery motivation have a better attitude towards teamwork; (H3) students with different types of motivations reach different levels of academic performance; and (H4) students show different motivation profiles in different circumstances: type of courses, teaching methodologies, different times of the learning process. This study was carried out with Computer Science Engineering students from two Spanish universities. The first results point to an improvement in teamwork competence of students if they have previously received specific training in facets of that competence. Other results indicate that there is a correlation between the motivational profiles of students and their perception of teamwork competence. Finally, results point to a clear relationship between some kind of motivation and academic performance. In particular, four kinds of motivation are analyzed and students are classified into two groups according to them. After analyzing several marks obtained in compulsory courses, we perceive that those students that show higher motivation for avoiding failure obtain, in general, worse academic performance.

Student academic performance stochastic simulator based on the Monte Carlo method

In this paper, a computer-based tool is developed to analyze student performance along a given curriculum. The proposed software makes use of historical data to compute passing/failing probabilities and simulates future student academic performance based on stochastic programming methods (MonteCarlo) according to the specific university regulations. This allows to compute the academic performance rates for the specific subjects of the curriculum for each semester, as well as the overall rates (the set of subjects in the semester), which are the efficiency rate and the success rate. Additionally, we compute the rates for the Bachelors degree, which are the graduation rate measured as the percentage of students who finish as scheduled or taking an extra year and the efficiency rate (measured as the percentage of credits of the curriculum with respect to the credits really taken). In Spain, these metrics have been defined by the National Quality Evaluation and Accreditation Agency (ANECA). Moreover, the sensitivity of the performance metrics to some of the parameters of the simulator is analyzed using statistical tools (Design of Experiments). The simulator has been adapted to the curriculum characteristics of the Bachelor in Engineering Technologies at the Technical University of Madrid(UPM).

Subclinical social anxiety and academic performance in adolescence: analysis of theoretical and practical implications

This study analyses the relationship between self-reported social anxiety and academic performance in a sample of 1,616 Spanish students (52.1% males) in compulsory secondary education, aged 12 to 16 years old. Social anxiety was assessed by the Social Phobia and Anxiety Inventory (SPAI) and academic performance was measured with school grades and failing grades. Results reveal that adolescents with social anxiety show a similar academic performance to adolescents without social anxiety. Although t tests found some significant differences in academic grades and number of failing grades, the effect size analysis showed that these differences had no empirical relevance. These findings are discussed considering the gender and grade levels and their theoretical and practical implication.

Facebook and Academic Performance: A Positive Outcome

The objective sought with the present paper consists in analyzing the literature about Facebook in order to know the conclusions of the different works with regard to its influence on those results. The examination of 37 papers devoted to this thematic area allows us to know which journals publish more about the impacts that Facebook has on academic performance, which data collection methods are more often used, which topics emerge in parallel to the use of Facebook in the academic context, and which countries are more prolific in this field. The conclusions suggest that, despite the divergence of results, the overall outcome is positive when it comes to the use of Facebook in academic environments.

Perceived academic performance, self-esteem and locus of control as indicators of need for assessment of adolescent suicide risk: implications for teachers

Introduction: There is currently a need for research into indicators that could be used by non-clinical professionals working with young people, to inform the need for referral for further clinical assessment of those at risk of suicide. Method: Participants of this repeated measures longitudinal study, were 2603, 2485, and 2246 school students aged 13, 14, and 15, respectively, from 27 South Australian Schools. Results: Perceived academic performance, self-esteem and locus of control are significantly associated with suicidality. Further, logistic regression of longitudinal results suggests that perceived academic performance, over and above self-esteem and locus of control, in some instances, is a good long-term predictor of suicidality. (C) 2004 Published by Elsevier Ltd. on behalf of The Association for Professionals in Services for Adolescents.

Comparative academic performance of medical students in rural and urban clinical settings

OBJECTIVE To determine whether the academic performance of medical students learning in rural settings differs from those learning in urban settings. DESIGN Comparison of results of assessment for 2 full cohorts and 1 part cohort of medical students learning in rural and urban settings in 2002 (209 students), 2003 (226 students) and 2004 (220 students), including results for each specialist rotation in the 3rd year and end-of-year examinations in the 2nd and 4th years. SETTING University of Queensland School of Medicine, Brisbane. Students spent the whole 3rd year (of a 4-year graduate entry programme) conducting 5 specialist 8-week rotations in either the rural clinical division (rural students) or in Brisbane (urban students), all following the same curriculum and taking the same examinations. RESULTS For the 2002 cohort there were no statistically significant differences in academic performance between rural and urban students. For the 2003 cohort the only significant difference was a higher score for rural students in the end of the 4th-year clinical skills examination (65.7 versus 62.3%, P = 0.025). For the 2004 cohort, rural students scored higher in the 3rd-year mental health rotation (79.3 versus 76.2%, P = 0.038) and lower in the medicine rotation (65.5 versus 68.6%, P = 0.037). CONCLUSION Academic performance among students studying in rural and urban settings is comparable.

The effects of faking on non-cognitive predictors of academic performance in University students

This study examined the extent to which students could fake responses on personality and approaches to studying questionnaires, and the effects of such responding on the validity of non-cognitive measures for predicting academic performance (AP). University students produced a profile of an ‘ideal’ student using the Big-Five personality taxonomy, which yielded a stereotype with low scores for Neuroticism, and high scores for the other four traits. A sub-set of participants were allocated to a condition in which they were instructed to fake their responses as University applicants, portraying themselves as positively as possible. Scores for these participants revealed higher scores than those in a control condition on measures of deep and strategic approaches to studying, but lower scores on the surface approach variable. Conscientiousness was a significant predictor of AP in both groups, but the predictive effect of approaches to studying variables and Openness to Experience identified in the control group was lower in the group who faked their responses. Non-cognitive psychometric measures can be valid predictors of AP, but scores on these measures can be affected by instructional set. Further implications for psychometric measurement in educational settings are discussed.

The influence of learning styles, enrolment status and gender on academic performance of optometry undergraduates

Purpose: This cross-sectional study was designed to determine whether the academic performance of optometry undergraduates is influenced by enrolment status, learning style or gender. Methods: Three hundred and sixty undergraduates in all 3 years of the optometry degree course at Aston University during 2008–2009 were asked for their informed consent to participate in this study. Enrolment status was known from admissions records. An Index of Learning Styles (http://www4.nscu.edu/unity/lockers/users/f/felder/public/Learning-Styles.html) determined learning style preference with respect to four different learning style axes; active-reflective, sensing-intuitive, visual-verbal and sequential-global. The influence of these factors on academic performance was investigated. Results: Two hundred and seventy students agreed to take part (75% of the cohort). 63% of the sample was female. There were 213 home non-graduates (entrants from the UK or European Union without a bachelor’s degree or higher), 14 home graduates (entrants from the UK or European Union with a bachelor’s degree or higher), 28 international non-graduates (entrants from outside the UK or European Union without a bachelor’s degree or higher) and 15 international graduates (entrants from outside the UK or European Union with a bachelor’s degree or higher). The majority of students were balanced learners (between 48% and 64% across four learning style axes). Any preferences were towards active, sensing, visual and sequential learning styles. Of the factors investigated in this study, learning styles were influenced by gender; females expressed a disproportionate preference for the reflective and visual learning styles. Academic performance was influenced by enrolment status; international graduates (95% confidence limits: 64–72%) outperformed all other student groups (home non graduates, 60–62%; international non graduates, 55–63%) apart from home graduates (57–69%). Conclusion: Our research has shown that the majority of optometry students have balanced learning styles and, from the factors studied, academic performance is only influenced by enrolment status. Although learning style questionnaires offer suggestions on how to improve learning efficacy, our findings indicate that current teaching methods do not need to be altered to suit varying learning style preferences as balanced learning styles can easily adapt to any teaching style (Learning Styles and Pedagogy in Post-16 Learning: A Systematic and Critical Review. London, UK: Learning and Skills Research Centre, 2004).

Entry characteristics and academic performance of students in a master of pharmacy degree program in the United Kingdom

Objective. Evaluate the characteristics of a cohort of Master of Pharmacy (MPharm) students upon entry and examine any associations between entry qualifications, type of school attended, socioeconomic deprivation, age and academic performance in the MPharm programme. Methods. A retrospective cohort analysis of data recorded on Aston University’s central database for each individual exiting the MPharm programme during the five year period 2005-6 – 2009-10 (n=644). Results. Entrants were disproportionately drawn from socioeconomically deprived areas and independent (private) schools. Achievement prior to admission was related to the type of school attended but not to deprivation. Performance on the programme was not related to type of school or deprivation but was strongly correlated with prior achievements. Conclusions. Prior achievement is the most important predictor of performance on the MPharm programme but the superior prior achievement of independent school pupils is not seen at the point of graduation. This may have implications for admissions policies.