Learning Style, Academic Belief Systems, Self-report Student Proficiency and Academic Achievement in Higher Education

Cassidy, Simon; Eachus, Peter

doi:10.1080/713663740

Cited by 209 publications

(169 citation statements)

References 15 publications

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“…Cassidy and Eachus (1999), having looked at self-assessment of efficiency, approaches to learning, and achievement with 130 health and social policy undergraduates, failed to identify consistent relationships, though they did show some relationships between both proficiency and achievement and 'strategic' (correlates positively) and 'surface' (correlates negatively) learning. Conversely, Van Zwanenberg, Wilkinson and Anderson (1999) found no relationships between performance and two measures of learning style.…”

Section: Introductionmentioning

confidence: 99%

“…Examples include approaches to studying (Cassidy and Eachus, 1999;SadlerSmith, 1999a;Sadler-Smith and Tsang, 1998), learning preferences (Sadler-Smith ,1999b), instructional design (Clancey, Geertshuis, Holmes and Bristol, 2000;Sadler-Smith, 1996), form of assessment (Au, 1997), and even selfmanagement of learning under the National Vocational Qualifications scheme in the UK (Priddy and Williams, 2000). There are also a number of limited comparative studies in educational settings that look at differential results across measures of style but fail to link or compare these with other factors (e.g.…”

Section: Introductionmentioning

confidence: 99%

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The impact of approaches to learning and cognition on academic performance in business and management

Spicer

2004

Education + Training

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Results of a study into the relationships between students' academic performance and their cognitive and learning styles are presented. A questionnaire containing three instruments assessing learning and cognition was distributed to second and final year undergraduates studying on a general and business management degree. The outcomes of this are explored and analysed in relation to the students' selection of modules and performance in assessments.The research explores whether students' approaches to learning and cognition influences their selection of and performance in modules. This paper incorporates consideration of the impact on performance of a range of other factors, including gender, age, initial entry qualifications, mode of study, the type of assessment, and the cognitive styles of lecturers. Results show some impact of style and other factors, but these are not consistent. The implications of this for higher education practice and learning and cognitive style research are discussed.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The impact of approaches to learning and cognition on academic performance in business and management

Spicer

2004

Education + Training

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“…15 The literature has shown anxiety, perceived proficiency, and self-confidence can be used as indicators of performance and competence. [16][17][18] Faculty members hypothesized that students' selfratings of anxiety, proficiency, confidence, and ability to perform injections based on faculty observations would be better after using the higher-fidelity injection arm than after using the low-fidelity injection pad. The North Dakota State University Institutional Review Board approved the informed consent document and instruments used in this study.…”

Section: Designmentioning

confidence: 99%

Comparison of Low- and Higher-Fidelity Simulation to Train and Assess Pharmacy Students' Injection Technique

Skoy

Eukel

Frenzel

2013

American Journal of Pharmaceutical Education

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Objective. To evaluate 2 forms of simulation used to train and assess third-year pharmacy students' subcutaneous and intramuscular injection techniques. Design. A cross-over comparison was used to evaluate an injection pad vs a patient simulator injection arm to train students in injection administration. Assessment. Students completed a survey instrument rating their proficiency, confidence, and anxiety before and after each form of simulated practice. All students demonstrated competence to administer an injection to a peer after using both forms of simulation. Students' self-ratings of proficiency and confidence improved and anxiety decreased after practicing injections with both forms of simulation. The only significant difference in performance seen between students who used the 2 types of simulations was in students who first practiced with the injection pad followed by the injection arm. Conclusion. Student ability to administer an injection and their self-perceived levels of confidence, proficiency, and anxiety were not dependent on the type of simulation training used.

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“…Of the diverse factors used to determine academic achievement, the most relevant are: prior achievement, learning strategies, expectations of success, sex, psychosocial factors (Cassidy & Eachus, 2000;Makinen & Olkinuora, 2004;Van den Berg & Hofman, 2005), and more recently, factors related to the educational institutions ( Van den Berg & Hofman, 2005;Yorke, 2004). Educational research has shown that prior achievement is the best predictor of future achievement (Goberna, López, & Pastor, 1987;House, Hurst, & Keely, 1996;Mathiasen, 1984;McKenzie & Schweitzer, 2001;Wilson & Hardgrave, 1995;Zeegers, 2004).…”

Section: Palabras Clave: Regresión Logística Versus Regresión Linealmentioning

confidence: 99%

Prediction of University Students' Academic Achievement by Linear and Logistic Models

Ayán

García

2008

Span. J. Psychol.

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University students' academic achievement measured by means of academic progress is modeled through linear and logistic regression, employing prior achievement and demographic factors as predictors. The main aim of the present paper is to compare results yielded by both statistical procedures, in order to identify the most suitable approach in terms of goodness of fit and predictive power. Grades awarded in basic scientific courses and demographic variables were entered into the models at the first step. Two hypotheses are proposed: (a) Grades in basic courses as well as demographic factors are directly related to academic progress, and (b) Logistic regression is more appropriate than linear regression due to its higher predictive power. Results partially confirm the first prediction, as grades are positively related to progress. However, not all demographic factors considered proved to be good predictors. With regard to the second hypothesis, logistic regression was shown to be a better approach than linear regression, yielding more stable estimates with regard to the presence of ill-fitting patterns. Keywords: logistic versus linear regression, prediction, credits, academic achievement, advance in careerSe estudia el efecto de dos tipos de factores sobre el rendimiento de estudiantes universitarios: variables académicas de rendimiento previo y variables demográficas, mediante modelos lineales y logísticos. El principal objetivo del trabajo es comparar los resultados obtenidos con ambas técnicas estadísticas, para determinar cuál de ellos es más adecuado en términos de ajuste y capacidad predictiva cuando se pretende explicar y predecir el rendimiento académico, en función de variables de rendimiento previo y factores sociodemográficos. Como medida del rendimiento a predecir se empleó el avance en la carrera. Las hipótesis planteadas son: 1) El avance está directamente relacionado con las calificaciones en materias básicas de primer año y con variables demográficas y 2) Los modelos logísticos son más adecuados que los modelos lineales, ya que presentan mayor capacidad predictiva. Los resultados permiten confirmar la primera hipótesis en su primera parte, ya que el rendimiento previo está directa y significativamente asociado al avance en la carrera. Pero se cumple de forma parcial por lo que se refiere al efecto factores demográficos. Con respecto a la segunda hipótesis, la regresión logística mostró ser más adecuada que la lineal, pues arroja estimaciones más estables en relación con la presencia de patrones de mal ajuste. Palabras clave: regresión logística versus regresión lineal, predicción, créditos, rendimiento académico, avance en la carrera

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Learning Style, Academic Belief Systems, Self-report Student Proficiency and Academic Achievement in Higher Education

Cited by 209 publications

References 15 publications

The impact of approaches to learning and cognition on academic performance in business and management

The impact of approaches to learning and cognition on academic performance in business and management

Comparison of Low- and Higher-Fidelity Simulation to Train and Assess Pharmacy Students' Injection Technique

Prediction of University Students' Academic Achievement by Linear and Logistic Models

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