[IJERE] Asst. Prof. Junjun Chen, Ph.D.


Asst. Prof. Junjun Chen, Ph.D. Mail
The Hong Kong Institute of Education, China


Junjun CHEN Ph.D.
Assistant Professor
Department of Education Policy and Leadership
The Hong Kong Institute of Education
10 Lo Ping Road, Tai Po, NT, HONG KONG SAR


2006 – 2010              Ph.D. in Education, Faculty of Education, University of Auckland, New Zealand. The thesis topic isTeachers’ Conceptions of Excellent Teaching (mixed methods);

2004 – 2005              MSc in School Effectiveness and Improvement (Hons, taught in English),

Faculty of Psychology, Education and Sociology, University of Groningen, the Netherlands. The thesis topic is Teachers’ Job Satisfaction and Its Relationship with Their Retention (quantitative method);

1994 – 1998              BA in Education, School of Physical Education, Northeast Normal University, China.



My research focus is on measuring how teachers conceive effective teaching and how to assist teachers in improving their teaching. In pursuing these concerns, I am interested in measuring teachers’ and students’ affective and cognitive attitudes, how their attitudes link to teaching practices, student engagement, and academic performance. I was a co-principal investigator for an on-going classroom research project about New Zealand teachers’ use of the Science Learning Hub website material and its impact on science teaching, learning and student engagement. Currently, I am involved in an international project, Reshaping educational practice for improvement in Hong Kong and England: How schools mediate government reforms and a regional project, teacher emotion at primary school at Hong Kong and Mainland China.


My research methodologies are mixed in nature. I am experienced for managing large-scale surveys and analysing quantitative data using techniques such as exploratory factor analysis (EFA), confirmatory factor analysis (CFA), Effect Size and Structural Equation Modelling (SEM). I am beginning to get familiar with Hierarchical Linear Modelling (HLM). I have also utilized qualitative methods including classroom observations, interviews, focus group discussions, and archival data. I can use analytic software such as SPSS, Amos, Nvivo, and Excel.