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Beyond Machine Learning: Capturing Cause-and-Effect Relationships

Irving Wladawsky-Berger

Deep learning is a powerful statistical technique for classifying patterns using large training data sets and multi-layer AI neural networks. Machine learning is a statistical modelling technique, like data mining and business analytics , which finds and correlates patterns between inputs and outputs without necessarily capturing their cause-and-effect relationships. Why are there such universal human activity patterns?

Shaping (As Opposed to Stumbling Into It!) – The Future of Online Learning and Training

Stephen Downes: Half an Hour

Shaping (As Opposed to Stumbling Into It!) – The Future of Online Learning and Training Stephen Murgatroyd, PhD, Chief Innovation Officer Contact North | Contact Nord These are summary notes of the talk, taken by me, “I’m here because I’m old….

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Ethical Codes and Learning Analytics

Stephen Downes: Half an Hour

Abstract The growth and development of learning analytics has placed a range of new capacities into the hands of educational institutions. The ethics of learning analytics will therefore need to be developed on criteria specific to education. 2019) Ethical Codes As Standards of Conduct While ethics commonly applies to people in general, there is a specific class of ethics that applies to people by virtue of their membership in a professional group. Neelakantan, 2019).

Reflections on the Later Stages of Our Careers

Irving Wladawsky-Berger

In particular, the essay explains why in July of 2019 at the age of 55, he concluded that it was time to resign his decades-long position as president of the prestigious American Enterprise Institute (AEI) to join the faculty of the Harvard Kennedy School.

Educational Research in Learning Technology

Stephen Downes: Half an Hour

Decades of technological innovation in education have shown precious little in the way of educational gains and, more than anything else, have taught us that we need to be sceptical from the outset. Unfortunately, ‘the vast array of literature involving learning technology evaluation makes it challenging to acquire an accurate sense of the different aspects of learning that are evaluated, and the possible approaches that can be used to evaluate them’ (Lai & Bower, 2019).