Analysing Student Feedback in Higher Education Using Text-Mining to Interpret the Student Voice

Analysing Student Feedback in Higher Education provides an in-depth analysis of ?mining? student feedback that goes beyond numerical measures of student satisfaction or engagement. By including authentic student voices for understanding the student experience, this book will inform strategies for quality improvement in higher education globally.

With contributions, representing an international community of academics, educational developers, institutional data analysts and student-researchers, this book reflects on the role of computer-aided text analysis in gaining insight of student views. The chapters explore the applications of text-mining in different forms, these include varied institutional contexts, using a range of instruments and pursuing different institutional aims and objectives. Contributors provide insights enabled by computer-aided analysis in distilling the student voice and turning large volumes of data into useful information and knowledge to inform actions. Practical tips and core principles are explored to assist academic institutions when embarking on analysing qualitative student feedback.

Written for a wide audience, Analysing Student Feedback in Higher Education provides those making informed decisions about how to approach analyses of large volumes of student narratives, with the benefit of learning from the experiences of those who already started treading this path. It enables academic developers, institutional researchers, academics, and administrators to see how bringing text mining to their institutions can help them in better understanding and using the student voice to improve practice.

Preface
1. Discovering student experience: beyond numbers through words
Elena Zaitseva, Elizabeth Santhanam and Beatrice Tucker

Part I. Exploring collective student voice: approaches, tools and institutional insights

2. Automating insights: Analysing the National Student Survey data using NVivo
Steve Wright

3. You articulate, we implement – adding constructive feedback coaching and automated text analysis in the course evaluation loop
Yao WU and Graham Dawson

4. Using Structural Topic Modelling to Estimate Gender Bias in Student Evaluations of Teaching
Marshall A. Taylor, Ya Su, Kevin Barry and Sarah A. Mustillo

Part II. Listening to diversity of student voices

5. Guiding institutional analysis of diversity with coded comments
Jason Leman

6. Can you hear me now? Unmuting diverse student voices in Irish higher education
Angela Short

7. One voice? Investigating diversity in written student feedback
Natalie Holland and Elena Zaitseva

Part III. Looking across the student journey

8. Can text analytics improve prospective student engagement?
Robert Downie and Michel Rivard

9. Mining Employability Narratives – from Semantic Analysis to Institutional Strategy
Elena Zaitseva and Chris Finn

10. Accessing the student voice: Australia’s CEQuery project
Geoff Scott

Part IV. Informing actionable insights and ethical approaches to decision making

11. From anonymous student feedback to impactful strategies for institutional direction
Elizabeth Santhanam, Bernardine Lynch, Jeffrey Jones and Justin Davis

12. Supporting practical use and understanding of student evaluations of teaching through text analytics design, policies, and practices
Gregory Hum, Brad Wuetherick and Yeona Jang

13. Freeing the free-text comment: exploring ethical text mining in the higher education sector
Jill R D MacKay

14. Future directions and challenges in text analytics
Beatrice Tucker, Elizabeth Santhanam and Elena Zaitseva

Elena Zaitseva is the Academic Research and Development Officer at the Teaching and Learning Academy, Liverpool John Moores University, UK.

Beatrice Tucker is the Evaluation Lead for the School of Medicine, University of Western Australia.

Elizabeth Santhanam is an Associate Professor and Evaluation Coordinator in the Learning and Teaching Centre, Australian Catholic University.