Statistical analysis of correlation between students' personal characteristics and academic success in engineering mechanics course

Saeed Shaeri, Hong Guan, Simon Howell

Research output: Book chapter/Published conference paperConference paper

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Abstract

BACKGROUND
Understanding the factors which lead to student success or failure has long been an important matter for educators. Researchers like Zimmer et al. (1996) have focused on a particular science course to find the factors which lead to success, whereas others like Tynjälä et al. (2005) have examined an entire engineering program or degree to investigate the reasons behind students’ performance. Although a number of factors have been identified by different scholars such as Cahan et al. (1989), there are still many aspects which have not yet been explored/examined.
PURPOSE
This research has aimed to focus on a particular engineering course to enable a better investigation tailored to engineering students. In this regard, students of two Engineering Mechanics classes (the 2012 and 2013 academic years) have been chosen at Griffith University and their personal characteristics have been explored to determine key factors leading to a satisfactory final mark in the mentioned course. The results would allow course convenors to more quickly identify vulnerable students.
DESIGN/METHOD
The parameters which have already been investigated by researchers are very broad. However, based on the available resources for this study and also considering the most important and effective parameters (inferred from Cahan et al. (1989) and Hoskins et al. (1997)), the following factors have been selected for detailed analysis: gender, age, first language, study program, prior grade point average (GPA) and overall positions (OP). Simple statistical analyses have been conducted for each of these parameters in light of the students’ final mark. In addition, the correlation between scalar parameters (such as age) and final mark has also been observed.
RESULTS
Simple descriptive analysis has shown that there are no major differences between the 2012 and 2013 cohorts. The maximum, minimum and average marks for these classes were quite close. In particular, younger students achieved both the highest and lowest marks. Age did not affect the performance of mature students who were more evenly distributed in the middle range of results. Likewise, those from non-English speaking backgrounds were reasonably competitive with the others. More interestingly, no major difference was found between genders, although Hoskins et al. (1997) and Diaz (2003) both argued that there are differences in performance based on gender. Finally, the prior GPA and OP have shown a significant contribution to a better final mark.
CONCLUSIONS
The factors studied in this research have highlighted the important parameters for students’ success. These should be noticed in the earliest stages of the semester to identify at-risk students to help them avoid becoming student-in-need later in the semester.
Original languageEnglish
Title of host publication25th Annual Conference of the Australasian Association for Engineering Education
Subtitle of host publication Engineering the Knowledge Economy: Collaboration, Engagement Employability
Pages751-759
Number of pages9
ISBN (Electronic)9780473304287
Publication statusPublished - 2014
Event25th Annual Conference of the Australasian Association for Engineering Education: AAEE 2014 - Te Papa Tongarewa National Museum of New Zealand, Wellington, New Zealand
Duration: 08 Dec 201410 Dec 2014
http://www.aaee.net.au/index.php/resources/send/7-2014/171-25th-annual-aaee-conference-handbook (Conference handbook)
https://search.informit.com.au/browsePublication;isbn=9780473304287;res=IELENG (published papers)

Conference

Conference25th Annual Conference of the Australasian Association for Engineering Education
Abbreviated titleEngineering the Knowledge Economy: Collaboration, Engagement & Employability
CountryNew Zealand
CityWellington
Period08/12/1410/12/14
Internet address

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    Shaeri, S., Guan, H., & Howell, S. (2014). Statistical analysis of correlation between students' personal characteristics and academic success in engineering mechanics course. In 25th Annual Conference of the Australasian Association for Engineering Education: Engineering the Knowledge Economy: Collaboration, Engagement Employability (pp. 751-759) https://aaee.net.au/wp-content/uploads/2018/10/AAEE2014-Shaeri_Guan_Howell-Students_personal_characteristics_and_academic_success.pdf#new_tab