Students' statistics perception towards Difficulty of Calculus 3 course in UiTM Seremban Campus / Muhammad Syabil Tajuddin, Nur Amalina Mohamad Saleh and Nurul Hadfina Nor Azlan

Tajuddin, Muhammad Syabil and Mohamad Saleh, Nur Amalina and Nor Azlan, Nurul Hadfina (2019) Students' statistics perception towards Difficulty of Calculus 3 course in UiTM Seremban Campus / Muhammad Syabil Tajuddin, Nur Amalina Mohamad Saleh and Nurul Hadfina Nor Azlan. [Student Project] (Unpublished)
Abstract

Calculus is the branch of mathematics that extremely important for many areas of science and engineering in the career and industry. In Universiti Teknologi Mara (UiTM), Calculus 3 has the highest failure rate because most of the students who have problem with understanding the concept and theory of basic mathematics usually they lack of cognitive skills. This research is to describe the demographic profile towards student"s perception on difficulty of Calculus 3 and to classify the student into the category of final grade Calculus 3 course at UiTM Seremban Campus. This study used a primary data which is collected from questionnaires. The researcher obtained 150 samples of respondents at UiTM Seremban Campus. The data is analyses by using Discriminant Analysis method since the dependent variables are categorical. From the result the researcher found that 33% of students have been affected by the lecturer in learning Calculus 3 and the highest contribution to the final grade of A and Final Grade of B in Calculus 3 course was affected by lecturer teaching style but students who get final grade of C are affected by confidence and the least affected is lecturer teaching style. In addition, the researchers had classified the respondents into categories of grade among students in UiTM Seremban Campus based on several factors. The assumption of covariance matrices were meet. The result shows that the original classified group model is 51.3% to make a prediction about students' grade with 48.7% of error rate. Therefore, these functions were not good enough to be used in classification since the error rate is more than 20%.

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