Machine Learning Feedback

Artificial Intelligence and machine learning is widely used to support individuals in industries where performance improvements increase productivity but can it bridge the cultural and diversity of learners. Artificial Intelligence is becoming evident in the teaching and learning of students across the globe and is used in business and sporting contexts. Despite this, the concept is yet to be widely applied to personalization and increasing student engagement and learning. This poster envisions an approach to one learner group, teachers in training. This pilot study applies a critical realism philosophy to explore if teacher activities and actions can be classified to inform algorithms that will result in automated feedback on performance. A case study approach is proposed. The broad nature of teaching requires a considered approach to find a case for examination. The classification process is described and the selection of micro skills as a focus case for this study is presented. An initial classification structure is presented and described with the proposed methodology for future examinatio