1. Population file updates

2. Contents of the population file
Student background variables will be used for reporting purposes and to verify the representativeness of the sample.
Course-related variables are required to develop the sample frame and to pre-populate sections of the survey.
Student address details will only be used to send letters to students who do not respond the invitation.
E315 Gender code
E316 Aboriginal and Torres Strait Islander code
E348 Language spoken at home code
E386 Disability
E913 Age of student in years
E307 Course code
E308 Course name - full
E310 Course of study type code
E327 New basis for admission to current course
E329 Mode of attendance code
E330 Type of attendance code
E350 Course of Study Load
E455 Combined course of study indicator
E461 Field of education code
E462 Field of education supplementary code
E534 Course of study commencement date
E560 Credit used value

3. Derived variables Age Concurrent /major course indicator
Cumulative EFTSL since commencement
Enrolment status
Exclusions
Sample frame (set to blank in population file)
Defining commencing and final year students
Strata
Subject area

4. Sample frame exclusions
Enrolled in a postgraduate or non-award course
Offshore undergraduates
Onshore undergraduates in middle year of a course
Onshore undergraduates enrolled concurrently in another course
Onshore undergraduates in strata with six or fewer students
Onshore undergraduates randomly excluded from very large strata

5. Defining final year students
The ratio of ‘EFTSL completed successfully’ (E355) and ‘currently in progress’ (E339) to the total EFTSL for the course (E350) represents a student’s progression to date.
The standard solution adjusts for attendance mode (E330) and course duration (E350) and requires a greater proportion of cumulative EFTSL for longer courses.
Final year enrolment estimates for 2014 accord reasonably well with course completions in 2013
Option 1
IF (E327 ≠ 1) Stage=1. [Commencing student]
DO IF (E327 = 1).
IF (E330 = 1 AND (CumEFTSL+E339 < E350*.750)) Stage=2. [Full-time middle year]
IF (E330 = 2 AND (CumEFTSL+E339 < E350*.875)) Stage=2. [Part-time middle year]
IF (E330 = 1 AND (CumEFTSL+E339 ≥ E350*.750)) Stage=3. [Full-time final year]
IF (E330 = 2 AND (CumEFTSL+E339 ≥ E350*.875)) Stage=3. [Part-time final year]
END IF.
Option 2
IF (E327 ≠ 1) Stage=1.
DO IF (E350 < 2.5).
IF (E330 = 1 AND (CumEFTSL+E339 < E350*.7500)) Stage=2.
IF (E330 = 2 AND (CumEFTSL+E339 < E350*.8750)) Stage=2.
IF (E330 = 1 AND (CumEFTSL+E339 ≥ E350*.7500)) Stage=3.
IF (E330 = 2 AND (CumEFTSL+E339 ≥ E350*.8750)) Stage=3.
DO IF (E350 ≥ 2.5 AND E350 < 3.5).
IF (E330 = 1 AND (CumEFTSL+E339 < E350*.8333)) Stage=2.
IF (E330 = 2 AND (CumEFTSL+E339 < E350*.9167)) Stage=2.
IF (E330 = 1 AND (CumEFTSL+E339 ≥ E350*.8333)) Stage=3.
IF (E330 = 2 AND (CumEFTSL+E339 ≥ E350*.9167)) Stage=3.
DO IF (E350 ≥ 3.5 AND E350 < 4.5).
IF (E330 = 1 AND (CumEFTSL+E339 < E350*.8750)) Stage=2.
IF (E330 = 2 AND (CumEFTSL+E339 < E350*.9375)) Stage=2.
IF (E330 = 1 AND (CumEFTSL+E339 ≥ E350*.8750)) Stage=3.
IF (E330 = 2 AND (CumEFTSL+E339 ≥ E350*.9375)) Stage=3.
DO IF (E350 ≥ 4.5).
IF (E330 = 1 AND (CumEFTSL+E339 < E350*.90)) Stage=2.
IF (E330 = 2 AND (CumEFTSL+E339 < E350*.95)) Stage=2.
IF (E330 = 1 AND (CumEFTSL+E339 ≥ E350*.90)) Stage=3.
IF (E330 = 2 AND (CumEFTSL+E339 ≥ E350*.95)) Stage=3.

6. Sample strata
The sampling strata were built on the 45 Subject Areas reported on the MyUniversity website.
The code ‘2236_LY_29’ refers to Curtin University of Technology (2236) where final year students (LY) were enrolled in the Subject Area Business Management (29).
Students in combined/double degrees are allocated to the Subject Area with the fewest students.

7. What we need you to do
The information required to conduct the survey has already been compiled - well almost. We need you to do four things:
Inspect the data file for correctness, but not forensically.
Update students’ current enrolment status to make sure we don’t contact students who are not currently enrolled.
Provide addresses for all students (and mobile phone numbers if you want us to SMS).
Provide term addresses for onshore international students.

8. What we need you to tell us about
Were there any significant changes in your student profile between 2013 and 2014 that might affect subject areas and stages of enrolment?
Have different fields of education been allocated to the same courses in 2013 and 2014?
Are course duration (E350 Course of Study Load) values correct?
Cumulative EFTSL….
Is there anything else we need to know about your data?

9. Sampling

10. (not so) Random terms…
Confidence level – the percentage of all possible samples that can be expected to include the true population parameter
Confidence interval – a measure of the reliability of an estimate (margin of error)
Sample factor – the number of records required to achieve an completed survey

11. Sampling & percentages
The accuracy of an estimate also depends on the percentage of a sample that selects a particular answer.
In general, it is easier to be sure about extreme answers so if 95% of respondents agree with a statement, the chances of making an error are small.
If 51% of people agree then the changes are greater that an error will be made because of the general ambivalence in relation to the statement.
Sampling theory suggests that percentages be treated conservatively and estimates be made from the worst case, middle of the road scenario of 50%

12. Previous approach to sampling
Focus on obtaining a 35% response rate
Estimates of the sample factor based on 2012 UES
Difficult to determine accurately due to sample frame, response rate and mode issues
Sampling focused at an institutional level not a strata (subject area) level
Large strata capped at 1,333 records irrespective of size

13. 2014 approach to sampling
Focus on a response rate that supports reporting at a 90% confidence level +/- 7.5%
Required response rates are different for different strata. The smaller the subject area, the better the response rate needs to be.
Sample factor estimates informed by the 2013 UES allowing for better estimation of differential response rates across strata
For large strata, the required sample records depends on the number of students and the 2013 response rate

14. Complexity…
This approach means that the sample factor is calculated separately for each strata (ie institution by subject area) taking into account whether the student is commencing or in their final year
Our assumptions are conservative estimating that responses to key items are 50% rather than the 70% to 80% we actually obtain in response to key items
We are also sampling on the basis of a stretch goal which based on a reporting standard of 90% confidence level +/- 5% (rather than +/-7.5%)

15. What does this mean?
We have sampled more records than we theoretically need (but we’re still a bit paranoid, it’s early days with the survey)
Despite this, there are a larger number of strata that are samples rather than a census in 2014 (due to the retirement of the 1,333 rule)
Quotas will be set at 90%, +/-7.5% but we are aiming for 5%

16. These workings are from SRC
These workings are from SRC. If you would like access to the full version of this excel file, please contact SRC.

17. Research framework &
data collection

18. What’s ‘the same’? HEIMS provides the sample frame
Surveying at the level of the course, not the student
100% online data collection
Letters used as the primary non-response follow-up strategy
Incentives and prize draw are unchanged
Live reporting of data collection
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19. What’s new (questionnaire pt 1) ?
Using a standard rather than a rotated presentation of the questionnaire modules,
Removal of the Graduate Qualities Scale (GQS) and the Learning Community Scale (LCS) from the CEQ
Presentation of the CEQ scales to a sample of students in their final years across all institutions rather than undertaking a census of all students at a selection of universities (n=400 completed surveys)

20. What’s new (questionnaire pt 2)?
Removal of the Student Support focus area item ‘At university during (year x), to what extent have you used university services to support your study?’, and
Adding two additional items at the conclusion of the UES confirming graduation intentions and collecting a private address to facilitate interfacing the UES with the 14/15 AGS.

21. What’s new (fieldwork)?
Option to use SMS instead of or as a supplement to the reminder

22. Live Reporting Module

23. The Basics - Access Example: username = admin password = jpcNHb
Your institution will be given a username and password just prior to your field date commencement to access your admin page:
Example:
html
username = admin password = jpcNHb
Please note: usernames and passwords are case sensitive

24. The Basics – Summary Tab
Your summary page will provide a quick overview of how the project is tracking

25. Live Data – Record Search
This dialog allows you to search for specific records by different variables, or combinations of variables. For example, you could search for all records where Q1=5 (Variable Name "Q1", Operator "=", Value "5").

26. Live Data - Data reports
The Data Reports area lets you run…
frequency tabulations
cross-tabulations
charts
…of the data in real- time.
Note: open-ended responses cannot be extracted with this function.
Columns(banners): cross-tab variables here.
Rows (stubs): the question you are tabulating.
Run the tabulation. You can save a report once it’s created
Filter by complete, partial or all respondents

27. Live Data – Download raw data set
Open-ended responses can be accessed with this function.
Downloading data provides quick and easy access to the raw data set in excel format.

28. Important points: You’re dealing with live unedited data.
Downloading data and report outputs will be cumulative (i.e., Day 1, 2 & 3’s data will be in the output on Day 3, not just Day 3’s).
Getting too excited and creating lots of reports or downloading data during the first few days of launch can affect the performance of the survey.
You will receive a guide to the Admin Module

29. Additional populations
& items

30. Additional populations
Enabling
Middle years
Offshore
Post graduate
Subsampling international students
Subsampling coursework students
No requests for benchmarking?

31. Additional populations & fieldwork
Additional populations are removed from the monitoring fields in the reporting module
They are assigned an out of range subject area
The non-response follow-up strategy is tailored to each institution
Institutions that elect not to send a letter are aware of the 5% to 10% reduction in response rate
This data is not shared with the department or distributed in the National UES file
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32. Additional items Workplace Relevance Scale – six institutions
Appropriate Workload Scale – one institution
Net Promoter Score – two institutions
‘how likely is it that you would recommend university x to friends/family/colleagues?’
Follow up for potential leavers – three institutions
‘you mentioned you were considering leaving. Would it be OK if someone contacted you to discuss options / what support you might need?’
Institution specific – seven institutions
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33. Additional items & fieldwork
All additional items are located in Module 5 before the CEQ except…
For those institutions that have added or reinstated a CEQ scale
CEQ scales over and above the ‘core scales’ are contained in Module 6 in the correct order for the administration of the CEQ
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