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Post Conference Workshops

Workshop A

9:00 AM - 9:00 AM Utilising Big Data in Higher Education to Derive Insights and Adapt Curriculum

David Gibson, Director of Learning Futures and UNESCO Chair of Data Science in Higher Education Learning and Teaching, Curtin University
One of the promises of big data in higher education is to enable a new level of evidence-based research into learning and instruction and make it possible to gain highly detailed insight into student performance and their learning trajectories as required for personalizing and adapting curriculum as well as assessment.

This workshop will help participants understand more about data science and how educators, researchers and institutions are enabling computational approaches all across higher education. For example, how data analytics are being used to meet challenges in research, to support the journey of a learner from pre-university experiences, to marketing and recruitment, to enable personalized learning, adaptive curriculum and assessment resources, to create more effective teaching, to extend engagement with students to post-university life-long learning.

  • A brief history of data science and big data research
  • Foundations and challenges of learning analytics
  • Methods for educational big data analytics
  • Setting up your own learning analytics project

David Gibson

Director of Learning Futures and UNESCO Chair of Data Science in Higher Education Learning and Teaching
Curtin University

Workshop B

11:30 AM - 11:30 AM Students-Centred Learning Analytics Program: A Cost-Effective Approach and the Critical Success Factors

William Yeoh, Director, IBM Centre of Excellence in Business Analytics, Deakin University
Implementing a students-centred learning analytics program is a resource-consuming task. Why make it even more challenging? In this workshop William will help you to audit your students-centred learning analytics program. He will discuss a case university that adopted Watson Analytics approach, as well as the critical success factors for developing a cost effective students-centred learning analytics program.

  • Utilising IBM’s Watsons Analytics to derive meaningful insights at a low cost
  • Using the non-parametric statistical approach and multiple regression analysis to investigate the effect of periodic due dates on online quizzes and its correlation with students’ final examination performance
  • Understanding how time control plays a critical role within the online mastery learning

William Yeoh

Director, IBM Centre of Excellence in Business Analytics
Deakin University

Workshop C

This interactive workshop session invites participants to work together to consider how data literacy impacts on learning analytics, both for practitioners and for end users. Learning analytics outcomes can be targeted at a wide range of end users, some of whom will be young students and many of whom are not data specialists.

  • Establishing a clear learning analytics vision within your educational institution and how to communicate this across all key stakeholders
  • Having a framework in place to ensure transparency and open communication with students as to what their data is being used for
  • How to derive meaningful insights from data to influence feedback and improve the learning experience

Fernando Padro

Acting Director, Learning and Teaching Services
University of Southern Queensland

Workshop D

5:00 PM - 5:00 PM Key Steps to Creating and Implementing a Learning Analytics Policy

Dragan Gasevic , Professor and Chair in Learning Analytics and Informatics, The University of Edinburgh
The analysis of data collected from user interactions with educational and information technology has attracted much attention as a promising approach for advancing our understanding of the learning process. This promise motivated the emergence of the new field learning analytics and mobilized the education sector to embrace the use of data for decision-making. This talk will first introduce the field of learning analytics and touch on lessons learned from some well-known case studies. The talk will then identify critical challenges that require immediate attention in order for learning analytics to make a sustainable impact on research and practice of learning and teaching. The talk will conclude in discussing a set of milestones selected as critical for the maturation of the field of learning analytics.

  • Understanding learning analytics through the lens of international case studies
  • Key challenges faced when employing a learning centered analytics strategy
  • Understanding that learning analytics is about learning and that computational aspects of learning analytics need to be integrated deeply with educational research and practice

Dragan Gasevic

Professor and Chair in Learning Analytics and Informatics
The University of Edinburgh