• MGSE Master of Teaching (2013-2018)
  • MGSE Master of Teaching (Secondary) Internship (2015 - 2017)
  • DoE Tasmania Teacher Intern Placement Program (2016 - 2018)
  • Sydney Catholic Education Office Internship Initiative (2016 - 2018)
  • Curtin University Teacher Profile Guide (2017 - 2018)
  • DEECD / DET Science Graduate Scholarship (2013 - 2015)
  • TeachNext (2012)

About Teacher Capability Assessment Tool (TCAT)

Welcome to TCAT

Teaching is amongst the most challenging professions, and requires a complex mix of knowledge and personal skills. TCAT is a web-based assessment tool that has been developed to help us understand the competencies, characteristics and attributes of people interested in a teaching career. TCAT combines the evidence-based knowledge and technology to make a user-friendly suite of activities. To date, no other cohesive or comprehensive research-based selection tool has been developed for pre-service teacher selection. It has applications for:

TCAT asks about your previous experience and your reflections on teaching. The tool includes a series of questions, which concentrate on teaching candidate's ability, self, and social interaction. Research has demonstrated that tests of ability are predictive of occupational performance, personal qualities are related to higher job performance and self-efficacy. Furthermore, effective teachers must be both mindful of and pro-actively work with and adapt their practice to the needs of their students and school community context, as well as the teaching standards.

The assessments within the tool focus on tests of ability (such as literacy, numeracy and spatial reasoning), and assessments of your disposition, personal characteristics, communication style, ethics, and cultural sensitivity and awareness in relation to a being a teaching student and as a future teacher professional.

The TCAT provides student feedback reports, which may assist them to set individual goals relevant to work placement and preparation for teaching practice. TCAT data can also assist in planning and fine tuning of the course offerings to help better prepare candidates for classroom teaching.

About the research

Research into good teachers and good teaching

Research into the characteristics of effective teachers is led by Associate Professor Janet Clinton, and a team of research staff and students at the Melbourne Graduate School of Education. The research associated with the project will have an impact on teacher selection nationally and internationally. Importantly the research-based selection process will lead to better selection of teachers resulting in better outcomes for career teachers and their students.

The conduct of the research has been approved by the University's Human Research Ethics Committee, and all information is used in accordance with the privacy policy of the University of Melbourne which can be found at by clicking here.

For further information on the study please contact: Associate Professor Janet Clinton - Project Research Coordinator


  • Reference:
    Bowles, T., Hattie, J., Dinham, S., Scull, J., & Clinton, J. (2014). Proposing a comprehensive model for identifying teaching candidates. The Australian Educational Researcher, 41(4), 365-380. doi: 10.1007/s13384-014-0146-z


Janet Clinton
  • PhD, MEd (Hons), BEd, DipTeaching, BA
  • Director, Centre for Program Evaluation, MGSE, University of Melbourne
  • Project Chief Investigator
John Hattie
  • PhD, MA
  • Professor of Education, Associate Dean Research, Director of Melbourne Education Research Institute
  • Project Chief Investigator
Janet Scull
  • PhD, MEd, GradDipEd, BEd, DipEd
  • Senior Lecturer (Literacy and Literacy Acquisition)
  • Project Chief Investigator
Stephen Dinham
  • PhD, MEdAdmin, BA, DipT
  • OAM, FACE FACEA FAIM, Chair of Teacher Education and Director of Learning and Teaching
  • Project Chief Investigator
Gerard Calnin
  • DEd, MEd, GCE, BA
  • Senior Fellow
Georgia Dawson
  • PGDipPsych, BEc
  • Research Manager
Lee Kiong Au
  • MBiotech, BSc (Hons)
  • Project Manager
Daniel Arifin
  • MEd, BCompSci, BSc (Mathematics)
Patrick Mclaren
  • BSocSc, BBeSc(Hons)
Acknowledgement to Past Members of the Research Team