From Cognitive Load Theory to Collaborative Cognitive Load Theory
By Paul A. Kirschner, John Sweller, Femke C. Kirschner, Jimmy Zambrano Ramírez. International Journal of Computer-Supported Collaborative Learning, 2018
483 citations recorded by the source corpus.
Cognitive load theory has traditionally been associated with individual learning. Based on evolutionary educational psychology and our knowledge of human cognition, particularly the relations between working memory and long-term memory, the theory has been used to generate a variety of instructional effects. Though these instructional effects also influence the efficiency and effectiveness of collaborative learning, be it computer supported or face-to-face, they are often not considered either when designing collaborative learning situations/environments or researching collaborative learning. One reason for this omission is that cognitive load theory has only sporadically concerned itself with certain particulars of collaborative learning such as the concept of a collective working memory when collaborating along with issues associated with transactive activities and their concomitant costs which are inherent to collaboration. We illustrate how and why cognitive load theory, by adding these concepts, can throw light on collaborative learning and generate principles specific to the design and study of collaborative learning.
Subfields: Artificial Intelligence, Developmental and Educational Psychology, Experimental and Cognitive Psychology
View Paper: https://www.semanticscholar.org/paper/a7dacb4598eb77ea3d84dc2c2c2603de49d6acd9
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In Artificial Intelligence
In Developmental and Educational Psychology
In Experimental and Cognitive Psychology
Citations in the corpus
- The impact of augmented reality on cognitive load and performance: A systematic review (2021, background): “This so-called collaborative cognitive load theory (CCLT) is also important for multimedia learning considering computer-supported collaborative learning (CSCL; Janssen & Kirschner, 2020; Kirschner et al., 2018) and mixed reality learning environments (Johnson-Glenberg et al., 2014).”