Junior baccalaureate nursing students: Factors that predict success

Baccalaureate nursing education strives toward comprehensive preparation of diverse nursing students to meet current healthcare workforce demands. Identification of factors that predict academic success is imperative to meet this goal. The purpose of this study was to discover whether specific academic and noncognitive variables predicted baccalaureate nursing students’ academic success, as defined by junior-year grade point average (GPA) and persistence in nursing education. This post-facto correlational study was conducted over two semesters. Junior year nursing students (N = 150) answered the Short Grit Survey and the Noncognitive Questionnaire, and their academic records were examined for previous college grades (GPAs) and SAT scores. Demographic groups were compared using t-tests, and the data were regressed on junior-year student GPAs and persistence in the major to determine predictors of success. Several significant differences between the participant group responses were noted. Only early-college GPAs predicted junior-year success. SAT scores, grit and noncognitive factors, as well as demographic variables, did not predict academic success. These results inform baccalaureate education programs about priorities for admitting and advising students, and support the use of early-college GPAs to predict the academic success of junior-year baccalaureate nursing students.

The Promise of Noncognitive Factors for Underrepresented College Students

We use confirmatory factor analysis (CFA) to test the validity and reliability of three non-cognitive factors—resilience, grit, and growth mindset—as well as to examine whether those factors predict academic success for a sample of students primarily represented by first-year African American students at three Historically Black Colleges and Universities (HBCUs) and one Minority Serving Institution (MSI). The findings indicate that initial growth mindset and grit scores predicted GPA, whereas changes in resilience over the academic year predicted the number of credit hours taken at the end of the first year. Results add to the ongoing debate about the credibility and utility of noncognitive factors for fostering success.

Yes, Creativity Can Predict Academic Success!

Tests of creativity can meaningfully predict academic and other outcomes in schooling, over and above the prediction provided by standardized tests. However, for such prediction to occur, the tests must measure creativity in a meaningful way and success in school must in some way be linked to creative performance. We should change our tests and schooling to require the creativity that is so important for a world in which rapid change is the norm rather than the exception.

On-Campus Social Support and Hope as Unique Predictors of Perceived Ability to Persist in College

The psychological construct of hope, characterized by goal-directed thinking rooted in personal agency and the ability to develop pathways to achieve goals, has long been demonstrated to predict academic success. A sample of 994 undergraduates participated in this study to better understand the role of hope and on-campus social support in predicting students’ perceived ability to persist and succeed in college. Results demonstrated that on-campus support, particularly from teachers and professors, significantly predicted academic outcomes and hope. In addition, we found evidence of a support gap in which students from underrepresented ethnic minorities were far more likely to report that they had no support from educators on campus. Findings demonstrate the need for more research on the role of social support in developing hope in college students and highlight the value of encouraging meaningful relationships between students and faculty on campus.

Growth, Maturation, and Exercise During Youth—The Year That Was 2017

For “The Year That Was 2017,” I have selected 3 papers in the area of growth, maturation, and exercise during youth. The first paper has been chosen because it provides for the first time the relative age, maturation, and anthropometric biases on position allocation in elite youth soccer players participating in talent identification programs in professional soccer league. Specific anthropometrical attributes characterized playing positions with a bias toward these athletes who are comparatively tall and heavy for their age already in younger ages, whereas position-specific physical attributes do not become apparent until the later stages of talent development. The second paper was selected because it provides a unique perspective on the contributions of different types of sport activities to the development of soccer performance. This paper demonstrated that early specialization and concentration on one sport only during growth is not beneficial in elite youth soccer. In contrast, variable early sporting experience, and not different physiological parameters, facilitates subsequent soccer performance development. The third paper provided some evidence that the consequence of physical activity during adolescence can be far reaching as physical activity might not only predict academic success during compulsory basic education but also boost educational outcomes in adulthood.

Adult Intelligence: The Construct and the Criterion Problem

Over 100 years have passed since Binet and Simon proposed scales for assessment of intelligence of children to predict academic success and failure. The extension of these assessments to adults largely resulted from efforts of psychologists to provide insights for military selection in World War I. At the time, relatively little thought was given to how adult intelligence might differ from child and adolescent intelligence. Traditional approaches for assessing adult intelligence have largely survived. However, there is little reference to adult intellectual functioning outside of laboratory-based tasks and clinical assessments of pathology. The result is that there are insufficient criterion measures for adult intelligence. Moreover, researchers have shifted from treating intelligence tests as predictors to treating them as criterion measures. The result is a disconnection between basic research on one hand and understanding adult intelligence on the other hand. This lack of connection is a serious impediment for predicting individual differences in performance on tasks which adults perform in their day-to-day work and nonwork lives. This article explores how the field has come to the current situation, and what remedies might be explored. Ultimately, a fundamental reexamination of how adult intelligence is studied and applied is suggested.

Analysis of relations among scientific process skills, academic success and multiple intelligence levels of grade 7-8 students7 ve 8 sınıf öğrencilerinin bilimsel süreç becerileri, akademik başarı ve çoklu zekâ düzeyleri arasındaki ilişkilerin analizi

Learning skills of individuals may be related to their types of intelligence, scientific process skills and other affective skills and capacities. Relations among these may be used to predict academic success. For this reason, the aim of this study is to analyze the relations among multiple intelligence, scientific process skills and academic success. A multiple intelligence inventory, scientific process skills test eas administered to a total of 98 students attending a state and a private secondary school, 47 of whom are female and 51 of which are male. Their grade point average were collected from e-school database.Academic success is not correlated with general intelligence that is assumed to be the sum of all types of multiple intelligences but is positively correlated with all basic, high level and general scientific process skills. There is no correlation with academic success and any type of multiple intelligences. Musical intelligence is positively correlated with space and time relational skills and logical intelligence is positively correlated with prediction skills of basic scientific process skills. Extended English abstract is in the end of PDF (TURKISH) file. ÖzetBireylerin öğrenme becerileri, bilimsel süreç becerilerindeki yeterlikleri, diğer duyuşsal kapasite ve özelikleri ve farklı zekâ alanlarına yatkınlıklarıyla ilgili olabilir. Bunlar arasındaki ilişkiler akademik başarıyı yordamada da kullanılabilir. Bu nedenle bu çalışmayla ortaokul öğrencilerinin bilimsel süreç becerileri, akademik başarıları ve çoklu zekâ türleri ve değerleri arasındaki ilişkilerin çalışılması amaçlanmıştır. Bu doğrultuda İzmit ilinde biri özel biri kamu iki okulda 7 ve 8 sınıf larda 47 kadın 51 erkek olmak üzere toplam 98 öğrenciye bilimsel süreç becerileri testi, çoklu zekâ envanteri uygulanmış ve e-okul sisteminden öğrencilerin akademik ortalamaları alınmıştır.Akademik Başarı çoklu zekâ türleri toplamı olarak varsayılan genel zekâyla anlamlı bir ilişki içinde görülmemektedir ancak tüm temel, üst ve genel bilimsel süreç becerileriyle yüksek anlamlı ilişkiler sergilemektedir. Akademik başarı ile çoklu zekâ türleri ve dereceleri arasında bir ilişki gözlenmemiştir. Çoklu zekâ alanlarından ritmik zekâ temel bilimsel süreç becerilerinden uzay zaman ilişkisi kurma ile ve sayısal zekâ da tahmin yapma becerisiyle anlamlı ilişkiler göstermiştir. Diğerleri arasındaki ilişkiler anlamsızdır.

Prediction Modeling for Academic Success in Professional Master's Athletic Training Programs

Context: A common goal of professional education programs is to recruit the students best suited for the professional career. Selection of students can be a difficult process, especially if the number of qualified candidates exceeds the number of available positions. The ability to predict academic success in any profession has been a challenging proposition. No studies to date have examined admission predictors of professional master's athletic training programs (PMATP). Objective: The purpose of this study was to identify program applicant characteristics that are most likely to predict academic success within a PMATP. Design: Cohort-based. Setting: University professional PMATP. Patients or Other Participants: A cohort of 119 students who attended a PMATP for at least 1 year. Intervention(s): Common application data from subjects' applications to the university and the PMATP were gathered and used to create the prediction models. Main Outcome Measure(s): Sensitivity, specificity, odds ratio, and relative frequency of success were used to determine the strongest set of predictors. Results: Multiple logistic regression analyses yielded a 3-factor model for prediction of success in the PMATP (undergraduate grade point average ≥ 3.18; Graduate Record Examination quantitative [percentile rank] ≥ 141.5 [≥12]; taking calculus as an undergraduate). A student with ≥2 predictors had an odds ratio of 17.94 and a relative frequency of success of 2.13 for being successful in the PMATP. This model correctly predicted 90.5% of PMATP success. Conclusions: It is possible to predict academic success in a PMATP based on common application data.