Students' performance on statistics course through online learning

• Published in: AIP Conference Proceedings
• Main Author: Kamarudin A.N.; Nor S.R.M.; Ibrahim N.
• Format: Conference paper
• Language: English
• Published: American Institute of Physics 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188449248&doi=10.1063%2f5.0192506&partnerID=40&md5=317cdc4e1a16e81f1c58cb060a4adb98

Online learning has taken place since COVID-19 pandemic that force the immediate migration. Despite current challenges of online education, learning statistics has added extra difficulty to the students as this subject requires proper visualization for the unseen theoretical concept. Thus, many studies have been conducted on the appropriate online tools for learning statistics and have suggested flexibility in the assessment method. Researchers have more excitement in comparing the achievement of students between face-to-face and online learning, but still lack in investigating the performance during entire online learning period in pandemic. This study is focused on to investigate the achievement of statistics course among second year engineering students during one of the semesters when it is conducted fully online until the end of the semester. The objectives of this study are, to determine the overall achievement of engineering students towards statistics course, to find whether there is any significant difference of performance between genders, type of students and schools, and lastly to list common errors when answering probability questions. Results found concluded that all course learning outcome are successfully achieved although during online learning. There is no significant difference found between male and female students and local students have gained more marks as compared to international students in some assessments. During Test 1, when answering question relating to probability, there are five mistakes identified which are misinterpret of the problem, inaccurate in calculating the probability, unable to identify the distribution, lack of understanding of a distribution, and incomplete solution. The findings from this study may help lecturers in develop assessment questions to tackle the common errors and strategize an impactful online teaching. © 2024 Author(s).