A winning formula how to pick the best teachers

Australian governments, most notably the NSW government and their commonwealth counterparts, have made “lifting the bar” to entry into the teaching profession a priority. Most recently, education minister Christopher Pyne announced plans to have aspiring teachers sit examsbefore getting into the classroom. While other states are trying to set university entrance score cutoffs for teaching.A winning formula how to pick the best teachers

These governments are seeking to tackle the perception (and, in some cases, reality) that there is a decline in the standard of entry into the teaching profession. Indeed, it is true that the average Australian Tertiary Admission Ranks (ATAR) for undergraduate teacher education have been slipping year on year, with some universities accepting applicants into teaching with ATARs below 50.

But ATAR cutoffs aren’t the best measure for the quality of pre-service teachers, and they would only likely affect the 40% of people who use ATARs to get into teaching in the first place.

But with quality teaching having such a big impact on student achievement, we should be looking at ways to better select teachers before they enter the classroom. If not, just to address the problem of so many new teachers dropping out.

TeacherSelector

We, along with colleagues at the Melbourne Graduate School of Education (MGSE), have developed one tool that could be used, called TeacherSelector.

A web-based tool, TeacherSelector is comprised of a battery of tests and is now used by a number of education institutions in Australia and overseas to help with their selection processes. We are also using it, along with a student’s academic record, to better select students into the Master of Teaching from next year.

TeacherSelector sees students complete a series of questionaires online, over a period of about one to one and a half hours. These questionnaires are based on what qualities we know excellent teachers have; factors like achievement, experience, motivation and personal attributes. The aim is to select people into teacher education programs who will suit the teaching profession.

After all, there’s more to being a great teacher than getting high academic scores. They also need relationship skills, communication skills and sensitivity to others. We know that previous academic achievement and experience as well as certain aspects of personality, can give us a pretty good picture of an individual’s future success in teacher education and their teaching career.

Using a Five Factor Model, we look at key personality traits, including emotional stability, conscientiousness, perseverance or grit, openness to views of others. We also ask open-ended questions about how individuals engage with others, apply themselves to tasks and manage emotion under stress when there are many competing demands on their time. This information can tell us a lot about an individual’s ability to self-regulate, their resilience, their communication style and other personal attributes.

There are also sections asking for transcripts of academic performance, but to complement this, TeacherSelector also measures general cognitive ability, including numerical, verbal and spatial reasoning. This is because general cognitive ability has been shown to be a good predictor of high performance as a beginner teacher.

Finally, the test also covers the individual’s motivation for, understanding of and experience with teaching, through a series of written responses; highly effective teachers are known to be passionate about teaching and learning, and show a deep understanding of their content area.

What we’re finding out

Our findings about TeacherSelector to date generally confirm what we already know, but we are also finding that candidates have a strong interest in using their individual results as as way to become a better teacher. They can identify their own strengths, as well as areas they would like to work on, and take proactive steps to address these, with the support of academic staff.

We are also interested in the predictive capacity of the tool and have embarked on longitudinal studies to establish which factors predict prolonged career engagement and service.

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