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An authentic text is written by native speakers for native speakers, i.e. it was not written for language learners as part of a language learning program. Automaticity A learner’s ability to recover a word automatically, without straining to fetch it from memory.
For example, while one hour of standard e-learning can take 73 [2] to 220 [3] hours to develop, a PowerPoint to e-learning conversion can be estimated to take an average of 33 hours to develop. [3] The term "rapid learning" is also sometimes used as a synonym for "short-form" or "bite-size" learning.
Speed learning is a collection of methods of learning which attempt to attain higher rates of learning without unacceptable reduction of comprehension or retention. It is closely related to speed reading , but encompasses other methods of learning, such as observation , listening , conversation , questioning , and reflection .
[2] [3] [4] Experiential learning is distinct from rote or didactic learning, in which the learner plays a comparatively passive role. [5] It is related to, but not synonymous with, other forms of active learning such as action learning, adventure learning, free-choice learning, cooperative learning, service-learning, and situated learning. [6]
Learning is the process of acquiring new or modifying existing knowledge, behaviors, skills, values, or preferences based on instruction. See also: Category:Teaching Subcategories
Instructor-led training, [1] or ILT, is the practice of training and learning material between an instructor and learners, either individuals or groups. Instructors can also be referred to as a facilitator, who may be knowledgeable and experienced in the learning material, but can also be used more for their facilitation skills and ability to deliver material to learners.
Personalized learning refers to instruction in which the pace of learning and the instructional approach are optimized for the needs of each learner. Learning objectives, instructional approaches, and instructional content (and its sequencing) may all vary based on learner needs.
For example, learners learn better when they have a certain level of disequilibrium (frustration), but not enough to make the learner feel completely overwhelmed. [111] This has motivated affective computing to begin to produce and research creating intelligent tutoring systems that can interpret the affective process of an individual. [111]