Introduction

COVID-19 has impacted teaching at ANU and so the Research School of Management (RSM) aims to address the difficulties students are facing under these new circumstances. The purpose of this

paper is to propose how to document the issues reported by online students. Actions to address them and changes over the semester are addressed elsewhere.

Problem Definition

Currently, where courses are offered online those are the only classes provided. Online classes are thus much larger than usual (Figure 1).

Figure 1: Comparison of 2020 enrolments for online classes across semesters (ANU 2020)

This larger number encompasses a very different profile of students. Normally these courses would be made up of professionals studying while working in Australia or overseas. Now 83% of students are pre-experience students who would normally study full-time on campus (ANU 2020), and a

higher proportion of them are international students rather than domestic students. The problem is we do not understand the needs of this mix of students in an online environment.

Stakeholder analysis

Of the 4 significant stakeholder groups, students are critical because their needs shape the actions required of the other three groups (Table 1).

Table 1: Stakeholder groups impacted by the shift to online classes in RSM

Further analysis of the stakeholders makes clear that there is also an ethical need to address student needs, as they have little influence in the situation but are disproportionately impacted by it (Figure 2).

Figure 2: Stakeholder groups dissected by impact and influence

Method

A short anonymous survey distributed via Wattle during the first and second week of the semester is proposed. A key parameter of the situation is the off-campus location of students. Accordingly data  must be sought online. Understanding the lived experience of the students is the goal, so

exploratory and descriptive data is required, and a survey is an appropriate means of obtaining both qualitative and quantitative data for this purpose. One intention is to resolve any reported problems as quickly as possible, so waiting until the SELT survey is conducted at the end of semester is

inappropriate. However, the students maybe concerned that if they respond negatively then this may impact their relationship with the University, and accordingly anonymity is required.

Excel is selected for coding and analysis of the data. It is a familiar tool for staff, and the

exploratory and descriptive nature of the evidence to be collected does not require more complex functions.

Scales and questions

The questionnaire is made up of two parts, addressing different aspects of the problem:

Part A: Because of the immediacy and specificity of the problem, 4 questions were tailored to the circumstances of the problem (Appendix A). These are intended to identify particular issues for

rectification. To ensure maximum usability of results, these questions were designed by a teaching staff member.

Part B: In addition, a scale for assessing student satisfaction with online learning more broadly is

employed (Arbaugh 2000).  This will enable broader assessment of overall satisfaction. It will also   permit some comparison with other institutions and research as well as with subsequent years of the same courses. The questions are derived from Sun, Tsai, Finger, Chen and Yeh (2008), adapted as    required for this specific learning situation.

Critical appraisal

In previous studies response rates have been below 50%, so sample size could be a concern. A

minimum response rate of 48 across the population of 161 students would be adequate for 90%

confidence and 90% margin of error. Previous similar surveys have generated around 25-26%

response rates, which equates to 40-42 responses for this population. However, for an exploratory study such as this, 40 responses would be a useful sample size.

There are some other likely sources of bias. There maybe sampling bias, as some students may not find the survey in time to respond to it, particularly late enrolments. There may also be some

selection bias, with confused students over-represented in the sample.

Finally, it is possible that there is an administrative error in questions 1 and 2, which areworded as they are for consistency with other surveys previously administered locally. It is possible that

students could be confused in the first couple of days, but then growing familiarity with the Wattle   page enables them to find the information they need. This scenario would drive an apparent conflict

in responses; students concerned about quantity of study material also reporting sufficient information to get started. This issue should be monitored in analysing the survey results.

Conclusions

The purpose of the survey is to identify students' difficulties and proposals for change. Useful data maybe expected from a relatively low number of responses.

REFERENCES

ANU 2020. (2020). Wattle [database]. Retrieved 10 August 2020 from

https://wattlecourses.anu.edu.au/.

Arbaugh, J.B. (2000). "Virtual classroom characteristics and student satisfaction with internet-based MBA courses". Journal of Management Education. 24(1), pp.32-54. doi:

https://doi.org/10.1177/105256290002400104

Sun, P., Tsai, R.J., Finger, G., Chen, Y. & Yeh, D. (2008). "What drives a successful e-Learning?   An empirical investigation of the critical factors influencing learner satisfaction". Computers & Education, 50(4), pp.1183-1202. doi: https://doi.org/10.1016/j.compedu.2006.11.007