Abstract
CONTEXT: The workload is a constant issue in students' lives and is used as a measurement to evaluate students' performance and engagement in their studies. The introduction of a quantitative tool to predict the workload in advance to the teaching team can be useful to plan and moderate the workload and can assist the students in managing their time.
PURPOSE OR GOAL: In two previous papers (AAEE2019 and 2020 (Mansouri et al., 2019 and 2020)), we introduced a tool to predict the assessment loading dispersion across the semester and a data analysis method to observe student workload during the semester. The target of this pilot study paper is to understand if the tool can be helpful for students to have better time management and if it is possible to encourage the teaching team to plan the assessment schedule by using this tool.
APPROACH: The research was designed based on initiating group discussions as a qualitative approach to gain an understanding of academic interpretation and student sights on the quantitative tool. In this preliminary research, the tool was demonstrated for one group of students and for one group of academics. The workload was calculated based on the four units and shown to the academics to give them a measure of the workload for students.
ACTUAL OR ANTICIPATED OUTCOMES: It was determined from the group discussions that students develop a sense of time management as they progress through the degree. Although academics mentioned the tool was helpful for them to view workload across the semester; the assignment submission dates have been scheduled following the weekly topics and it was difficult to reschedule them even though it clearly clashed with another assignment.
CONCLUSIONS/RECOMMENDATIONS/SUMMARY: Overall, the quantitative tool received positive feedback from the participants, showing prospects for further research and using the tool in workload planning. The results obtained from the pilot study show a positive prospect for the tool to be included as a pre-learning activity for future students.
PURPOSE OR GOAL: In two previous papers (AAEE2019 and 2020 (Mansouri et al., 2019 and 2020)), we introduced a tool to predict the assessment loading dispersion across the semester and a data analysis method to observe student workload during the semester. The target of this pilot study paper is to understand if the tool can be helpful for students to have better time management and if it is possible to encourage the teaching team to plan the assessment schedule by using this tool.
APPROACH: The research was designed based on initiating group discussions as a qualitative approach to gain an understanding of academic interpretation and student sights on the quantitative tool. In this preliminary research, the tool was demonstrated for one group of students and for one group of academics. The workload was calculated based on the four units and shown to the academics to give them a measure of the workload for students.
ACTUAL OR ANTICIPATED OUTCOMES: It was determined from the group discussions that students develop a sense of time management as they progress through the degree. Although academics mentioned the tool was helpful for them to view workload across the semester; the assignment submission dates have been scheduled following the weekly topics and it was difficult to reschedule them even though it clearly clashed with another assignment.
CONCLUSIONS/RECOMMENDATIONS/SUMMARY: Overall, the quantitative tool received positive feedback from the participants, showing prospects for further research and using the tool in workload planning. The results obtained from the pilot study show a positive prospect for the tool to be included as a pre-learning activity for future students.
| Original language | English |
|---|---|
| Title of host publication | Australasian Association for Engineering Education (AAEE) |
| Subtitle of host publication | Future of Engineering Education |
| Number of pages | 9 |
| Volume | 33 |
| Publication status | Published - 3 Dec 2022 |
| Event | AAEE - Annual Conference of Australasian Association for Engineering Education 2022 - Western Sydney University, Sydney, Australia Duration: 4 Dec 2022 → 7 Dec 2022 Conference number: 33rd https://aaee.net.au/conferences/ https://search.informit.org/doi/book/10.3316/informit.9781925627756 (Proceedings) |
Conference
| Conference | AAEE - Annual Conference of Australasian Association for Engineering Education 2022 |
|---|---|
| Abbreviated title | AAEE 2022 |
| Country/Territory | Australia |
| City | Sydney |
| Period | 4/12/22 → 7/12/22 |
| Internet address |