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Related Concept Videos

Correlations02:20

Correlations

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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Longitudinal Research02:20

Longitudinal Research

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Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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Longitudinal Studies01:26

Longitudinal Studies

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Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
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Correlation and Regression00:53

Correlation and Regression

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In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
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Cross-Sectional Research01:50

Cross-Sectional Research

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In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
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Multiple Regression01:25

Multiple Regression

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Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
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Exploring the Correlation Between Nontraditional Variables and Student Success: A Longitudinal Study.

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    This study found no significant correlation between emotional intelligence (EI) or critical thinking (CT) scores and traditional grade point averages for predicting nursing student success. However, developing these skills remains crucial for nursing practice.

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    Area of Science:

    • Nursing Education
    • Higher Education Assessment

    Background:

    • Traditional admission criteria like GPA may not fully predict student success.
    • Exploring alternative metrics such as emotional intelligence (EI) and critical thinking (CT) is essential.
    • Understanding predictors for upper-division student outcomes is vital in nursing programs.

    Purpose of the Study:

    • To determine if emotional intelligence (EI) or critical thinking (CT) scores correlate with grade point averages (GPA) in predicting nursing student outcomes.
    • To investigate the predictive validity of EI and CT scores against traditional academic metrics.
    • To assess the relationship between EI, CT, and undergraduate nursing student success.

    Main Methods:

    • A quantitative, longitudinal research design was employed.
    • The study involved 112 junior-level undergraduate nursing students.
    • Data were collected during the initial semester of a five-semester nursing program.

    Main Results:

    • Emotional intelligence (EI) scores did not significantly correlate with key outcome variables.
    • HESI® Critical Thinking (CT) scores showed no significant correlation with main analysis variables.
    • Neither EI nor CT scores were found to be significant predictors of student success in this cohort.

    Conclusions:

    • Despite non-significant findings, integrating EI and CT development into the nursing curriculum is recommended.
    • Fostering critical thinking and emotional intelligence is vital for developing nurses capable of effective practice.
    • These skills are considered essential for overall success in nursing practice, irrespective of predictive correlation in this study.