Search results
Results from the WOW.Com Content Network
Chen, Y. & Willits, F. (1998). A path analysis of the concepts in Moore's theory of transactional distance in a videoconferencing learning environment. Journal of Distance Education, 13 (2), 51-65. Chen, Y.J. 2001a. Transactional distance in World Wide Web learning environments. Innovations in Education and Teaching International (UK), 38(4 ...
Student teams-achievement divisions (STAD) is a Cooperative learning strategy in which small groups of learners with different levels of ability work together to accomplish a shared learning goal. [1] It was devised by Robert Slavin and his associates at Johns Hopkins University.
Spaced retrieval practice – trying to recover long-term memories quickly and accurately – is the subject of a different line of research but also shows that spaced practice (for example, taking a practice test every month) is more effective than massed practice. The significance of Spaced Learning may prove important in different ways:
The principle of graduated interval recall is based on the concept of distributed learning, where the learner is presented the information to be learned with gradual increases in the length of time between presentation. It uses the idea that learning can be optimized with a schedule of practice. [19]
Authentic Learning (Scale IV, consisting of 5 items), (e.g. I work on assignments that deal with real-world information). Active Learning (Scale V, consisting of 3 items), (e.g. I explore my own strategies for learning). Student Autonomy (Scale VI, consisting of 5 items), (e.g. I play an important role in my learning.
Community members learn through both instruction-based learning and group discourse. Finally, multiple dimensions facilitate the long-term management of support and the ability for synchronous interactions. [2] To some, a VCoP is a misnomer because the original concept of a CoP was based around situated learning in a co-located
Educational research refers to the systematic collection and analysis of evidence and data related to the field of education. Research may involve a variety of methods [1] [2] [3] and various aspects of education including student learning, interaction, teaching methods, teacher training, and classroom dynamics.
Temporal difference (TD) learning refers to a class of model-free reinforcement learning methods which learn by bootstrapping from the current estimate of the value function. These methods sample from the environment, like Monte Carlo methods , and perform updates based on current estimates, like dynamic programming methods.