Calculus Self-Efficacy Inventory: Its Development and Relationship with Approaches to learning

This study was framed within a quantitative research methodology to develop a concise measure of calculus self-efficacy with high psychometric properties. A survey research design was adopted in which 234 engineering and economics students rated their confidence in solving year-one calculus tasks on...

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Main Authors: Yusuf F. Zakariya (Author), Simon Goodchild (Author), Kirsten Bjørkestøl (Author), Hans K. Nilsen (Author)
Format: Book
Published: MDPI AG, 2019-07-01T00:00:00Z.
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100 1 0 |a Yusuf F. Zakariya  |e author 
700 1 0 |a Simon Goodchild  |e author 
700 1 0 |a Kirsten Bjørkestøl  |e author 
700 1 0 |a Hans K. Nilsen  |e author 
245 0 0 |a Calculus Self-Efficacy Inventory: Its Development and Relationship with Approaches to learning 
260 |b MDPI AG,   |c 2019-07-01T00:00:00Z. 
500 |a 2227-7102 
500 |a 10.3390/educsci9030170 
520 |a This study was framed within a quantitative research methodology to develop a concise measure of calculus self-efficacy with high psychometric properties. A survey research design was adopted in which 234 engineering and economics students rated their confidence in solving year-one calculus tasks on a 15-item inventory. The results of a series of exploratory factor analyses using minimum rank factor analysis for factor extraction, oblique promin rotation, and parallel analysis for retaining extracted factors revealed a one-factor solution of the model. The final 13-item inventory was unidimensional with all eigenvalues greater than 0.42, an average communality of 0.74, and a 62.55% variance of the items being accounted for by the latent factor, i.e., calculus self-efficacy. The inventory was found to be reliable with an ordinal coefficient alpha of 0.90. Using Spearman’ rank coefficient, a significant positive correlation <inline-formula> <math display="inline"> <semantics> <mrow> <mi>ρ</mi> <mrow> <mo>(</mo> <mrow> <mn>95</mn> </mrow> <mo>)</mo> </mrow> <mo>=</mo> <mo> </mo> <mn>0.27</mn> <mo>,</mo> <mo> </mo> <mi>p</mi> <mo><</mo> <mo> </mo> <mn>0.05</mn> </mrow> </semantics> </math> </inline-formula> (2-tailed) was found between the deep approach to learning and calculus self-efficacy, and a negative correlation <inline-formula> <math display="inline"> <semantics> <mrow> <mi>ρ</mi> <mrow> <mo>(</mo> <mrow> <mn>95</mn> </mrow> <mo>)</mo> </mrow> <mo>=</mo> <mo> </mo> <mo>−</mo> <mn>0.26</mn> <mo>,</mo> <mo> </mo> <mi>p</mi> <mo><</mo> <mo> </mo> <mn>0.05</mn> </mrow> </semantics> </math> </inline-formula> (2-tailed) was found between the surface approach to learning and calculus self-efficacy. These suggest that students who adopt the deep approach to learning are confident in dealing with calculus exam problems while those who adopt the surface approach to learning are less confident in solving calculus exam problems. 
546 |a EN 
690 |a self-efficacy 
690 |a deep approach 
690 |a surface approach 
690 |a higher education 
690 |a parallel analysis 
690 |a Education 
690 |a L 
655 7 |a article  |2 local 
786 0 |n Education Sciences, Vol 9, Iss 3, p 170 (2019) 
787 0 |n https://www.mdpi.com/2227-7102/9/3/170 
787 0 |n https://doaj.org/toc/2227-7102 
856 4 1 |u https://doaj.org/article/e62b95ed6a8544e5a8965a926cbd08e8  |z Connect to this object online.