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By Jayne Baayens MAPS
Senior school psychologist, Swan Education District, WA

Psychologists and other student services providers in schools are commonly faced with the challenge of managing large numbers of referrals and heavy caseloads. Referrals often occur at the point of crisis and demand immediate attention, while forward planning and early intervention are seemingly impossible. In one outer Perth metropolitan school, a backlog of referrals to the school psychologist and waiting lists of up to ten weeks demanded an alternative approach.

Teacher ratings of at-risk students

In 2006, the part time appointment of a Learning Support Coordinator provided the human resource necessary to trial a multidisciplinary approach to identifying at-risk students as implemented by Marilyn Campbell (2003) in primary schools, in a high school (years 7-12) setting. Using a rating scale that had been developed and used in a primary school on the same campus, teachers were asked to rate students for behaviour, attendance, learning difficulties, health issues and social/emotional concerns, as well as providing anecdotal comments. Home room teachers of years 7 and 8, and core subject teachers of years 9 and 10 were asked to provide ratings to year coordinators, while year 11 and 12 teachers reported to either the year coordinator or the VET coordinator depending on which course the students were taking. Teachers and coordinators were then given the opportunity to discuss the students in their class or year group with members of the Students at Educational Risk team that included the Learning Support Coordinator, Student Services Coordinator and school psychologist. The purpose of these meetings was to gain consistency in data collection, provide the opportunity for two-way sharing of information and to clarify teachers’ anecdotal comments. Teachers were provided with teacher relief if they chose not to use their own non-teaching time.

Ranking and matching process

After the teacher meetings, ratings were entered onto an Excel spreadsheet and matched to existing records such as suspension data, attendance registers, literacy and numeracy test results, and psychological and health records. Modifications were made to the ratings if required. Students in each year group were then ranked from most severe to least severely at-risk based on their teacher ratings. Students who were already matched to existing resources or programs in the school were identified, while those newly identified as being at-risk through the rankings were allocated a case manager. This ranking and matching process showed at a glance how resources were being utilised within the school, and whether there were students with a high level of need who were not being directed to appropriate resources.

Catalyst for system level change

Analysis of the group data produced some interesting results and provided concrete evidence for directing system level change within the school. Where teachers had under-identified the number of students with literacy difficulties, the school psychologist was able to discuss the nature and management of learning difficulties with individual class teachers. Analysis of behavioural data – which indicated frequent but mostly low-level disturbance – confirmed earlier findings of the leadership group reviewing the school’s behaviour management policy. Analysis of attendance issues confirmed the need for a review of attendance policy and procedures across the school. The area in greatest need of intervention and resource allocation was the social and emotional wellbeing of students. Teachers’ anecdotal comments were used to identify target students and types of interventions required.

Whilst the initial process of data collection was time consuming, the results were well worth the effort. By commenting on all students in their care, teachers were able to identify students whose risks levels in each category were low, but in combination were at higher risk. For teachers it helped to clarify who in the school had primary case management responsibility for individual students and also helped to define specialists' roles and referral processes. The flow-on effect was a dramatic reduction in the number of referrals to the school psychologist and a shift in the focus of the psychologist’s workload from individual to whole school level.

Despite the many positive outcomes from this profiling process, inconsistencies between the results and published research findings on the relationship between behaviour and learning difficulties prompted the school psychologist to question the reliability of the rating scale. A review highlighted the need for consistency between ratings in each category and a revised scale was developed for implementation in the second semester.

The author can be contacted on jjhogan@bigpond.com.

Reference

Campbell, M. (2003). An innovative multidisciplinary approach to identifying at-risk students in primary schools. Australian Journal of Guidance and Counselling, 13(2), 159-166.