Every year, across the globe, hundreds of thousands of people apply for places on teacher-training courses. Some will go on to do a great job, inspiring their pupils and providing the kind of education that we all want for our children. Others will not do so well, finding it hard to handle the complexities presented by a classroom of demanding children.
But how do we tell the two groups apart? How do we identify and select the most suitable candidates? That’s the question being addressed in a pioneering five-year study, the Teacher Selection Project, led by Professor Rob Klassen, Chair of York’s Psychology in Education Research Centre.
“Everyone knows from their own experience that the best teachers aren’t just the smartest people,” says Professor Klassen. “They have something else – it might be empathy or the way they communicate, but these non-cognitive attributes are much harder to pin down.”
Interviews
At the moment, selection panels try to get a sense of each candidate’s characteristics by using a range of techniques including interviews, group activities, personal statements, references and generic personality tests.
“The problem,” explains Professor Klassen, “is that none of these methods is very systematic, evidence-based or reliable. People want useful selection tools that are evidence-based and that are designed for education settings – unlike many of the commercial personality tests that are out there.”
It was to meet this growing need that the Teacher Selection Project was devised by Professor Klassen, supported by a grant of £1million from the European Research Council. In the early stages of the project, the team worked with Professor Paula Mountford, Director of Initial Teacher Training (ITT) at York.
Their next step was to talk to teachers.
Judgement
“We ran focus groups and interviews with teachers to ask what attributes are really important for someone starting out in the profession,” says Professor Klassen. “This helped us identify three main clusters of attributes: reliance and adaptability; organisation and planning; and empathy and communication. We have also asked current teachers about challenging situations they have encountered or seen other new teachers encounter, where they have had to make a critical decision or judgement.”
Professor Klassen’s team built on this research and existing educational theory to create selection tools based on Situational Judgement Test (SJT) methods. The idea, as Professor Klassen explains, is simple: “The SJT is an expansion of the age-old interview question: what should you do if…? We present the candidates with different classroom scenarios based on the real-world examples suggested in our focus groups and we ask them to make a judgement about what to do.
“The advantage of an SJT over an interview is that we can ask that kind of question 30 or more times in quick succession, and that gives us much more information to base our decisions on. The outcome is in a more standardised form so that we can have a straight comparison between candidates.”
https://www.youtube.com/watch?v=yXrEfwHMKyE
Watch this video to find out more about Professor Rob Klassen's research into teacher selection
The team has now started trialling the SJT alongside existing selection processes to see how closely its results correlate with decisions made by selection panels. Successful candidates are being monitored as they progress through their training and into the classroom to see how well they actually go on to perform.
“It’s in everyone’s interests to make sure the candidates selected for training choose to stay in the classroom,” says Professor Klassen, “and that’s one of the outcomes we are measuring in the study. We are testing the effectiveness of the SJTs by looking at how candidates get on in their training programmes but also how they do in the longer term – at least in the first five years. Do they stay in the profession and how well do they do?”
Evidence base
The overall aim of the project is to develop the SJT into a proven, evidence-based teacher selection tool that can be used alongside other selection methods to ensure the best candidates for the job. The scientific aim is to better predict teacher behaviour, and to build understanding about what makes a teacher effective in the classroom.
Professor Klassen, who came to York from the University of Alberta in Canada in 2012, has worked with his team to adapt the SJT for different countries and cultures. As well as their work with teacher training programmes in England, Northern Ireland, and Scotland, the team is collaborating with partners in Lithuania, Finland and Australia and there’s interest from the ministries of education in Oman and Saudi Arabia. They are also working with researchers in School of Arts and Creative Technologies on possible video-based and virtual reality applications for the work.
“There’s a real international need for this kind of tool,” says Professor Klassen. “If we can improve selection and lower attrition rates, then our research has the potential to improve educational quality on a larger scale.”
The text of this article is licensed under a Creative Commons Licence. You're free to republish it, as long as you link back to this page and credit us.
