Simulation makes the grade for teacher screening

New research has found that simulations are an effective on-entry screening tool for teaching candidates, exposing university students to authentic classroom dynamics, increasing their confidence, and providing a safe learning environment. The study is published in the Journal of Education for Teaching.

Australian universities are now required to implement non-academic on-entry evaluations for all teacher education candidates.

To meet this requirement, universities have introduced a variety of assessment methods, including interviews, written applications, psychometric tests, and most recently, simulation.

Murdoch University was the first university in Australia to implement teaching simulations and augmented learning environments into the general course structure, using Mursion technology (SimLab).

Murdoch University Dean and Head of the School of Education, Associate Professor Peter Whipp said his recent research sought to understand how useful these simulation tools could be in the initial screening of teaching students.

“The implications of our findings are significant for policy and practice,” Professor Whipp said.

“Our research showed that simulation can reliably evaluate students’ teaching dispositions, as well as provide insights into their motivations, planning, communication skills and how we can best support them.

“Students themselves also said they perceived simulation as an effective means to evaluate their on-entry performance, reporting that the experience was valuable and that it helped with their confidence, so they felt more prepared for the real classroom.

“The on-entry evaluations are important, so that we can help our students be the best they can be as a teacher in our education system once they graduate.

“The simulation process is efficient and effective. We are pleased to be a leader in this space and encourage other higher education institutes to embrace the technology.”

The next steps in this research program include exploring the predictive nature of data captured at course entry and how this translates over time and experience.

The study results also emphasized the need to continue to expand the evidence base around this process.