The document discusses a text analytics evaluation of a first-year engineering project-based unit at Griffith University, focusing on the use of student feedback for course improvement. It employs linguistic, statistical, and machine learning techniques to analyze comments from surveys on what students found good about the course and areas for improvement. The evaluation utilized KH Coder for text processing and identified common themes in student feedback, demonstrating a new method for course evaluation.

1. Stuart Palmer(@s_palm ) – Deakin University
Wayne Hall – Griffith University
Australia
A Text Analytics Evaluation
of a First-year Engineering
Project-based Unit

2. New 1st year unit employing PBL, includes:
•underpinning lecture series
•design work including group project activities
•individual Computer Aided Drawing exercises
•group oral presentation on design
1006ENG Design and Professional Skills

3. Griffith University employs a ‘Student Experience
of Course’ (SEC) online survey
SEC7 - What did you find particularly good about
this course? and
SEC8 - How could this course be improved?
1006ENG evaluation

4. “… a set of linguistic, statistical, and machine
learning techniques that model and structure
the information content of textual sources for
business intelligence, exploratory data analysis,
research, or investigation.” (Hu & Liu, 2012, p.
388)
Text analytics

5. Uses KH Coder – http://khc.sourceforge.net/en/
Stop word removal
Stemming for root word consolidation
Text unit of analysis is paragraph
Co-occurrence Network
Hierarchical cluster analysis
Comment text processing

6. Co-occurrence network

7. Co-occurrence network

8. Hierarchical
Cluster
Analysis

9. Hierarchical
Cluster
Analysis

10. ‘Particularly good’

11. ‘Particularly good’

12. ‘Particularly good’

13. ‘Particularly good’

14. ‘Particularly good’

15. ‘Particularly good’

16. ‘Particularly good’

17. ‘Particularly good’

18. ‘Be improved’

19. ‘Be improved’

20. ‘Be improved’

21. ‘Be improved’

22. ‘Be improved’

23. ‘Be improved’

24. ‘Be improved’

25. A simple text analytics method for analysing
student evaluation comments was developed
CON and HCA identify similar comment themes
Appears to be a helpful form of evaluation
Identified themes similar to those from a
separate unit evaluation
Conclusions

26. Thank you for your time
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