Search results
Results from the WOW.Com Content Network
The purpose of learning object metadata is to support the reusability of learning objects, to aid discoverability, and to facilitate their interoperability, usually in the context of online learning management systems (LMS). The IEEE 1484.12.1-2020 – Standard for Learning Object Metadata [1] is the latest revision of an internationally ...
The IEEE Transactions on Learning Technologies (TLT) is a peer-reviewed scientific journal covering advances in the development of technologies for supporting human learning. It was established in 2008 and is published by the IEEE Education Society. [1] The current editor-in-chief (since 2022) is Minjuan Wang of San Diego State University.
The blog articles are written pro bono by major educational writers who advocate for the paradigm shift to Deeper Learning as well as by a balance of school leaders, teachers, professional learning specialists and others who are incorporating deeper learning practices into their curricula, instruction, assessment and system change plans.
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.
Since curriculum learning only concerns the selection and ordering of training data, it can be combined with many other techniques in machine learning. The success of the method assumes that a model trained for an easier version of the problem can generalize to harder versions, so it can be seen as a form of transfer learning .
The following is a list of some of the types of information that may be included in a learning object and its metadata: General Course Descriptive Data, including: course identifiers, language of content (English, Spanish, etc.), subject area (Maths, Reading, etc.), descriptive text, descriptive keywords
IEEE Transactions on Neural Networks and Learning Systems is a monthly peer-reviewed scientific journal published by the IEEE Computational Intelligence Society. It covers the theory, design, and applications of neural networks and related learning systems. According to the Journal Citation Reports, the journal had a 2021 impact factor of 14. ...
Differentiated instruction and assessment, also known as differentiated learning or, in education, simply, differentiation, is a framework or philosophy for effective teaching that involves providing all students within their diverse classroom community of learners a range of different avenues for understanding new information (often in the same classroom) in terms of: acquiring content ...