-
CSS Zen Garden: The Beauty of CSS Design
-
The use of MOOC as a means of creating a collaborative learning environment in a blended CLIL course
-
(16) Collaborative Learning in a MOOC Environment | Request PDF
-
Machine Learning Applications in E-Learning: Bias, Risks and Mitigation
- Personalized and adaptive learning has the ability to change learning content or the mode of delivery on the fly and to provide real-time feedback to learners
- Personalized learning paths:
- Personalized learning paths are either pregenerated based on job roles, org charts, competencies required, etc., or can be changed dynamically based on learners’ progress, interest or some other criteria.
- Chatbots:
- intelligent tutoring system, that present a learning concept with a series of conversations
- pinpoint a certain learning pattern, such as significant spikes in course failings, so instructors can intervene before it is too late.
- Performance indicator
- Prediction could be too prescriptive
- Preferences are largely context dependent
- There is usually not enough data to make useful recommendations.
- Machine learning and big data analysis cannot sufficiently replace instructor observations and feedback from learners, peers and managers
- Adaptive learning is costly and time consuming to build
- granularity is an issue
- Will you adapt at the curriculum level, course level or module level? Per activity or scenario? A content system requires constant updating and monitoring, especially with multiple pathways.
- A focus on good instructional design and interaction principles is sufficient.
- Algorithm black box
- researchers in AI and machine learning say that algorithms used by organizations can be opaque and discriminatory.
- One notion to counter algorithm black box is advocating the use of explainable AI. Essentially, XAI programs enable users to understand and provide input on the decision-making process to improve algorithmic accountability.
- Trust
- ownership and governance of data is often ill-defined or not defined at all
- huge amount of personal data.
- What happens when the prediction goes wrong? Should you make recommendations to learners who don’t want them? Who owns those data?
-
-
Turning ‘Google Maps for Education’ From Metaphor to Reality | EdSurge News
Saturday, September 29, 2018
Weekly Sporto bookmarks (weekly)
Subscribe to:
Post Comments (Atom)
No comments:
Post a Comment