PhD Seminar: Gloria Fernandez Nieto- Providing guidance in Multimodal Learning Analytics visual feedback interfaces for Collaborative Classrooms

PhD Candidate: Gloria Milena Fernandez Nieto

Abstract:

Feedback is a crucial aspect of classroom-based learning. Delivering high-quality feedback can help students to make well-informed decisions by understanding their learning goals, teacher’s pedagogical intentions, and their actual performance. However, providing actionable feedback is challenging, especially in large classes with many students or groups to follow up. One way to provide automated feedback is through learning analytics (LA) visual interfaces, in which digital traces and analytics outputs are shown to teachers and students. Yet, concerns about LA visual interfaces in terms of complexity, lack of guidance to communicate insights and lack of educationally meaningful impact have been highlighted in recent research. Besides, capturing, rendering visible and making sense of data about collocated activity in the classroom is even more complex and challenging than in fully computer-mediated settings. The present doctoral thesis aims to address the following research question: how to effectively communicate educationally meaningful insights to teachers and students to provoke reflection on teaching and learning in the collaborative classroom? This document presents the thesis proposal that includes: (i) literature review, (ii) motivation and identified gaps, (iii) thesis proposal, (iv) methodology to be followed, (v) current state of the project with the detailed plan to complete this research, and (vi) preliminary conclusions of this proposal.

This is a Stage 1 PhD seminar to mark the end of Year 1. All are welcome, and invited to share constructive feedback.

Bio:

Gloria Fernandez Nieto is a first year PhD student at University of Technology Sydney in the Connected Intelligence Centre. She is currently supervised by Professor Simon Buckingham Shum, PhD Kirsty Kitto and PhD Roberto Martinez. Her current research focuses on exploring alternatives of feedback to understand traces from data collected in the CSCL classroom to prompt reflection in teaching and learning practices. She also has focused her previous research on Learning Analytics, Technology Enhance Learning and Knowledge Management.