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Semelhante a Dreaming of Electric Sheep: CSU's vision for analytics-driven adaptive learning and teaching
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Dreaming of Electric Sheep: CSU's vision for analytics-driven adaptive learning and teaching
- 1. DIVISION OF STUDENT LEARNING Dreaming of Electric Sheep CSU’s Vision for Analytics-Driven Adaptive Learning and Teaching Simon Welsh Manager, Adaptive Learning & Teaching Services Division of Student Learning Charles Sturt University siwelsh@csu.edu.au http://www.csu.edu.au/division/student- learning/analytics-and-evaluations Assoc Prof Philip Uys Director, Learning Technologies Unit Division of Student Learning Charles Sturt University puys@csu.edu.au http://www.csu.edu.au/division/student- learning/home/technologies-for-learning-and-teaching
- 2. DIVISION OF STUDENT LEARNING Contents 1. Learning Analytics at CSU 2. The Adaptive Learning and Teaching Vision 3. The Organisational Arrangements
- 3. DIVISION OF STUDENT LEARNING 1. Learning Analytics at CSU • 2013: • Established a cross-institutional Learning Analytics Working Party • Developed a Learning Analytics Strategy • Appointed a Senior Learning Analytics Officer to lead implementation of Strategy • 2014: • Implemented “At Risk” analytics capability • Developed Model of Learning Analytics to guide implementation • Mapping of drivers of student success
- 4. DIVISION OF STUDENT LEARNING 1. Learning Analytics at CSU • 2015: • Implemented Blackboard Analytics • Established analytics Community of Practice • Developed Code of Practice and Policy Framework • Strategic development of the CSU data warehouse • New Distance Education Strategy and Online Learning Model
- 5. DIVISION OF STUDENT LEARNING 2. The Adaptive Learning and Teaching Vision Typical institutional approaches to Learning Analytics would not deliver the kind of personalised learning we sought: • Engagement defined in behavioural terms, more about management than learning • Over-reliance on inductive techniques, using simplistic metrics, when dealing with a complex process (learning) • “Lag” Feedback & the Boxer Response vs Adaptation During Learning • “Incompatibility” of certain learning designs • Ethical issues • Raising the floor vs raising the ceiling
- 6. DIVISION OF STUDENT LEARNING 2. The Adaptive Learning and Teaching Vision So, what’s our response? • Focus on the change not the input: Adaptive Learning and Teaching, as a pathway to personalised online learning • Recognise Learning Analytics as a learning design challenge to create representations of knowledge and embed analytics in formative feedback processes • Adaptation (of learning activities and feedback) during learning through analysis of knowledge representations and a students’ digital footprint • Need to go beyond current adaptive learning approaches and support a wider range of pedagogies
- 7. DIVISION OF STUDENT LEARNING 3. The Organisational Arrangements • Q: “Who does your Learning Analytics?” A: We all do • Developed the Adaptive Learning & Teaching Services team: • Focus on supporting personalised support, personalised learning and data- informed practice by building capability of people, as well as systems • Partner with academics on research and evaluation
- 8. DIVISION OF STUDENT LEARNING Thanks & Questions Simon Welsh Manager, Adaptive Learning & Teaching Services Division of Student Learning Charles Sturt University siwelsh@csu.edu.au http://www.csu.edu.au/division/student- learning/analytics-and-evaluations Assoc Prof Philip Uys Director, Learning Technologies Unit Division of Student Learning Charles Sturt University puys@csu.edu.au http://www.csu.edu.au/division/student- learning/home/technologies-for-learning-and-teaching