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Active learning is "a method of learning in which students are actively or experientially involved in the learning process and where there are different levels of active learning, depending on student involvement." [1] Bonwell & Eison (1991) states that "students participate [in active learning] when they are doing something besides passively ...
David A. Kolb's model is based on his experiential learning model, as explained in his book Experiential Learning. [13] Kolb's model outlines two related approaches toward grasping experience: Concrete Experience and Abstract Conceptualization, as well as two related approaches toward transforming experience: Reflective Observation and Active Experimentation.
Blended learning or hybrid learning, also known as technology-mediated instruction, web-enhanced instruction, or mixed-mode instruction, is an approach to education that combines online educational materials and opportunities for interaction online with physical place-based classroom methods. Blended learning requires the physical presence of ...
Experiential learning (ExL) is the process of learning through experience, and is more narrowly defined as "learning through reflection on doing". [1] Hands-on learning can be a form of experiential learning, but does not necessarily involve students reflecting on their product. [2][3][4] Experiential learning is distinct from rote or didactic ...
Machine learningand data mining. A standard Transformer architecture, showing on the left an encoder, and on the right a decoder. Note: it uses the pre-LN convention, which is different from the post-LN convention used in the original 2017 Transformer. A transformer is a deep learning architecture developed by researchers at Google and based on ...
Federated learning (also known as collaborative learning) is a sub-field of machine learning focusing on settings in which multiple entities (often referred to as clients) collaboratively train a model while ensuring that their data remains decentralized. [1] This stands in contrast to machine learning settings in which data is centrally stored ...
t. e. Multimodal learning, in the context of machine learning, is a type of deep learning using multiple modalities of data, such as text, audio, or images. In contrast, unimodal models can process only one type of data, such as text (typically represented as feature vectors) or images. Multimodal learning is different from combining unimodal ...
Microlearning refers to a set of compact e-learning modules that are designed to reduce learner fatigue. The modules can be educational, professional, or skill-based, and are usually designed to be less than 20 minutes long, with a single learning objective or topic. [1] The name originates from the Greek word 'micro' meaning 'small'.