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The Early Years Learning Framework (commonly known as EYLF), [1] together with the National Quality Standard (or NQS), [2] forms the policies around early childhood education in Australia. In January 2023 the Australian Education ministers approved proposed changes and endorsed the use of Version 2 of the EYLF under the National Quality ...
A key difference between the two frameworks include how EYLF focuses on children from birth to five years of age, while VEYLDF extends to eight years. [3] [4] Both frameworks share the same five learning and development outcomes, with the VEYLDF linking to the first three year levels of the Victorian curriculum F-10 (Foundation - year 10). [5]
The VCAA is responsible for the Victorian Early Learning and Development Framework (VELDF) and the Victorian Curriculum. The Victorian Curriculum F–10 sets out a single, coherent and comprehensive set of content descriptions and associated achievement standards to enable teachers to plan, monitor, assess and report on the learning achievement of every student.
The OER movement was motivated from work by researchers who pointed out that class size and learning outcomes had no established connection. Here, Daniel Barwick's work is the most often-cited example. [16] [17] Within the OER movement, the Wikiversity was founded in 2006 and the first open course on the platform was organised in 2007.
The Youth Outcome Questionnaire is a collection of questions designed to collect data regarding the effectiveness of youth therapies. [1] The Y-OQ is a parent report measure of treatment progress for children and adolescents (ages 4–17) receiving mental health interventions.
In South Korea, there were accounted to be 2.517 million people with disabilities in total, or roughly 5.0% of the population, in 2018. When compared to Koreans without disabilities, people with disabilities spent an average of 56.5 days in medical facilities, which was 2.6 more than the national average. 34.9% of the entire workforce was ...
Situated learning has also been examined in SL, to determine how the design and social dynamics of the virtual world support and constrain various types of learning. [206] The paper, "The future for (second) life and learning", published in the British Journal of Educational Technology , examines the potential of Second Life to further ...
Integrating advanced machine learning algorithms including deep learning into IoT devices is an active research area to make smart objects closer to reality. Moreover, it is possible to get the most value out of IoT deployments through analyzing IoT data, extracting hidden information, and predicting control decisions.