Analytics Model for Teacher Inquiry (AMTI): an eight-step circular model for analytics-informed teacher inquiry¶

Theory · All theories
Evidence · 6 claims (1 for, 5 mixed) · 1 study (1 design), q2 · 0 of 1 report an effect size · 6 claims rest on one study

Description¶

The AMTI is a process model guiding teachers through analytics-informed teacher inquiry in eight steps: motivation, purpose, inquiry questions, data needs, data collection, sense-making, interpretation, and decision-making. It was synthesized from existing teacher inquiry and data use models (Rolfe et al., Hansen & Wasson, Sergis & Sampson), splitting data interpretation into sense-making and interpretation "as suggested in Wise and Jung (2019)". It deliberately starts with "purpose" rather than problem identification, includes process, outcome, and student feedback data types, and was visualized as a circular diagram "to emphasize that TI could start at any step of the inquiry cycle". The model was refined across three DBR iterations with teachers and experts.

Design Implications¶

Context¶

Requirements¶

• Teachers need explanations and examples for each step, as the initial model was extended "with explanations and examples based on existing literature"

Constraints¶

• The model requires further testing with a larger, more versatile sample, per the authors' conclusion

Target Learners¶

• Practising primary and secondary school teachers

Target Learning Objectives¶

• Analytics-informed teacher inquiry into one's own teaching practice

Claims¶

• Two teacher-researchers using the AMTI in real classes found the collected data informative and useful, demonstrating the model's feasibility [+W]
• The sense-making and interpretation steps of teacher inquiry models proved confusing for teachers [~W]
• Teachers see high workload, habits, low-quality data and skills, and predisposition as the main constraints on data-informed analysis, and none regularly collect teaching data [~W]
• Teachers would engage in analytics-informed inquiry if they saw direct benefits for student outcomes and the process were a regular part of their work [~W]
• Teachers' motivation to analyze their teaching falls into four broad categories: self-analysis, understanding students, change, and problems [~W]
• Teachers pose inquiry questions mostly about their students, not their own teaching, indicating teaching data remains a novel concept [~W]

Related Theories¶

Examples¶

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Key Sources¶

• Saar, M., Rodríguez-Triana, M. J., & Prieto, L. P. (2022). Towards Data-Informed Teaching Practice: A Model for Integrating Analytics with Teacher Inquiry. Journal of Learning Analytics, 9(3), 88–103. https://doi.org/10.18608/jla.2022.7505