A revised application of cognitive presence automatic classifiers for MOOCs: a new set of indicators revealed? | International Journal of Educational Technology in Higher Education | Full Text

Automatic analysis of the myriad discussion messages in large online courses can support effective educator-learner interaction at scale. Robust classifiers are an essential foundation for the use of automatic analysis of cognitive presence in practice. This study reports on the application of a revised machine learning approach, which was originally developed from traditional, small-scale, for-credit, online courses, to automatically identify the phases of cognitive presence in the discussions from a Philosophy Massive Open Online Course (MOOC). The classifier performed slightly better on the MOOC discussions than similar previous studies have found. A new set of indicators to identify cognitive presence was revealed in the MOOC discussions, unlike those in the traditional courses. This study also cross-validated the classifier using MOOC discussion data from three other disciplines: Medicine, Education, and Humanities. Our results suggest that the cognitive classifier trained using MOOC data in only one discipline cannot yet be applied to other disciplines with sufficient accuracy.
— Read on educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-022-00353-7

We need to transform education for this generation to be prepared for the future – World Education Blog

In 2015, the international community declared that universal primary completion, the unattained education goal of past decades, was not going to be ambitious enough for the 2030 Agenda. It would not even be sufficient if all youth completed secondary school, a new target aimed to set the bar higher. Instead, all children and adolescents would also need to achieve a minimum proficiency level in reading and mathematics if they were to be prepared for the future.
— Read on world-education-blog.org/2022/09/15/we-need-to-transform-education-for-this-generation-to-be-prepared-for-the-future/

AI Isn’t Ready to Make Unsupervised Decisions

AI has progressed to compete with the best of the human brain in many areas, often with stunning accuracy, quality, and speed. But can AI introduce the more subjective experiences, feelings, and empathy that makes our world a better place to live and work, without cold, calculating judgment? Hopefully, but that remains to be seen. The bottom line is, AI is based on algorithms that responds to models and data, and often misses the big picture and most times can’t analyze the decision with reasoning behind it. It isn’t ready to assume human qualities that emphasize empathy, ethics, and morality.
— Read on hbr.org/2022/09/ai-isnt-ready-to-make-unsupervised-decisions