E-Learning-Inclusivo (Mashup)

Artificial intelligence (AI) is a daunting topic as there are so many issues with respect to its use in education. AI is also currently going through yet another period of extreme hype, currently being at the peak of inflated expectations, driven by developments in generative large language models such as ChatGPT and DALL-E. Anything written down in a textbook such as this is likely to be overtaken very quickly by new developments. Furthermore, at the time of writing, the lack of transparency and complexity of the underlying software that drives AI is a particular challenge. If you don’t know how something works, it is very difficult to control or manage it. For many AI developers, this is not a bug but a deliberate feature, but in education it is essential to understand the assumptions, biases and limitations of the software.

Via Canadian Vocational Association / Association canadienne de la formation professionnelle

This working paper undertakes a meta study on informal apprenticeship in developing countries. It compares the findings of country-level research conducted by the ILO and others in the past 15 years to shed more light on apprenticeship systems in the informal economy. It discusses the features and practices of informal apprenticeship systems, their responsiveness to rights at work, and the effectiveness of such systems along criteria such as dropouts, training quality, and transitions to employment. The analysis is complemented by a selected number of country case studies that describe and assess the policies and programmes that were introduced during past years to strengthen and upgrade apprenticeship systems in the informal economy. The findings aim to improve understanding of this complex, heterogenous, yet self-sustained training system in the informal economy for evidence-based discussions and policy dialogue between ILO constituents and beyond.

Via Canadian Vocational Association / Association canadienne de la formation professionnelle