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Data driven instruction is the core business of teachers’ work, enabling teachers with a process of practice that targets instruction to meet the needs of all students. Consisting of a cyclical set of stages, teachers collect, collate and analyse student data to inform planning. Throughout the cycle, teachers participate in critical reflection to consider their teaching practice and the impact of their teaching on student learning. In doing so, teachers have a mechanism by which their teaching can undergo continuous improvement for the benefit of all students.

The coursework focuses upon the implementation of a data driven instruction cycle through the Graduate Teacher Performance Assessment (GTPA). The course requires pre-service teachers to gather evidence of the teacher they are becoming and evaluate the impact this has upon their learners as well as justifying their repertoire of teaching practices.

This course contains a 25-day placement and is the final Professional Experience Placement within the following contexts:

BEED program, the placement is in a school setting (in the nominated primary curriculum specialisation area) from Prep to Year 3 with preservice teachers observing at least one lesson in Yr 4 - Yr 6) for exposure to upper primary.

BPED program, the placement is in a school setting (in the nominated primary curriculum specialisation area) from Prep to Year 6.

BSED program, the placement is in a school setting from Year 7 to Year 12 which is guided by, but not limited to, the preservice teachers nominated teaching areas.

Students need to pass the competency Assessment in this Course and reach a total passing Mark of 50% to be awarded a passing Grade in this course. Failure of the Professional Experience component will result in a fail grade for the course, regardless of the graded mark. Full details of the Professional Experience particulars can be found on the Professional Experience website and in the Professional Experience Book.

On successful completion of this course preservice teachers should be able to:

1. use a variety of student data and evidence to establish students’ readiness for learning and plan teaching and learning sequences connected to official curriculum documentation and the explicit teaching of literacy and numeracy (APST 1.1, 1.2, 1.3, 1.5, 2.1, 2.2, 2.3, 2.4*, 2.5, 2.6, 3.1, 3.2, 3.4, 3.6, 3.7*, 4.1, 4.3, 4.4, 4.5, 5.1, 5.2, 5.4, 7.1, 7.2, 7.3*);
2. employ a range of suitably challenging and engaging teaching and learning strategies for inclusive and differentiated instruction using ongoing data collection and analysis (APST 1.1, 1.2, 1.3, 1.4*, 1.5, 1.6*, 2.1, 2.2, 2.3, 2.4*, 2.5, 2.6, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 4.1, 4.2, 4.3, 4.5, 5.1, 5.2, 5.4, 7.1);
3. use assessment tools and moderation processes to assess student learning, make standards based judgements and provide feedback to students (APST 1.1, 1.2, 1.3, 1.4*, 1.5, 1.6*, 2.1, 2.3, 3.2, 3.6, 4.1, 4.4, 5.1, 5.2, 5.3, 5.4, 5.5, 6.3, 7.1, 7.2);
4. reflect on practice, drawing on relevant theory, at all stages of data driven instruction cycle to improve future teaching and learning (APST 1.2, 1.5, 2.1, 2.3, 3.6, 3.7*, 5.4, 5.5, 6.2*, 6.3, 6.4, 7.3*);
5. appraise and discuss the impact of teaching and learning on student outcomes drawing on relevant theory, enacted practice and evidence collected (APST 1.1, 1.2, 3.6, 4.4, 5.4, 6.1*, 6.2*, 6.4, 7.4).