This article presents a review of research comparing the effectiveness of individual learning environments with collaborative learning environments. In reviewing the literature, it was determined that there is no clear and unequivocal picture of how, when, and why the effectiveness of these two approaches to learning differ, a result which may be due to differing complexities of the learning tasks used in the research and the concomitant load imposed on the learner's cognitive system. Based upon cognitive load theory, it is argued that learning by an individual becomes less effective and efficient than learning by a group of individuals as task complexity increases. Dividing the processing of information across individuals is useful when the cognitive load is high because it allows information to be divided across a larger reservoir of cognitive capacity. Although such division requires that information be recombined and that processing be coordinated, under high load conditions, these costs are minimal compared to the gain achieved by this division of labor. In contrast, under low load conditions, an individual can adequately carry out the required processing activities, and the costs of recombination and coordination are relatively more substantial. Implications of these ideas for research and practice of collaborative learning are discussed.Keywords Collaborative learning . Cognitive load . Task complexity . Brain science Contemporary learning paradigms argue for the facilitation of lifelong learning in collaborative as opposed to individual environments. This is based upon the premise that the collaboration process will include discussion, argumentation, and reflection upon the task at hand, thus leading to deeper processing of the information and richer and more

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. Intern. J. Comput.-Support. Collab. Learn (2018) 13:213-233 https://doi

The effects of individual versus group learning (in triads) on efficiency of retention and transfer test performance in the domain of biology (heredity) among 70 high-school students were investigated. Applying cognitive load theory, the limitations of the working memory capacity at the individual level were considered an important reason to assign complex learning tasks to groups rather than to individuals. It was hypothesized that groups will have more processing capacity available for relating the information elements to each other and by doing so for constructing higher quality cognitive schemata than individuals if the high cognitive load imposed by complex learning tasks could be shared among group members. In contrast, it was expected that individuals who learn from carrying out the same complex tasks would need all available processing capacity for remembering the interrelated information elements, and, consequently, would not be able to allocate resources to working with them. This interaction hypothesis was confirmed by the data on efficiency of retention and transfer test performance; there was a favorable relationship between mental effort and retention test performance for the individual learners as opposed to a favorable relationship between transfer test performance and mental effort for the students who learned in groups. Collaborative learning models are based on the premise that certain types of learning are best achieved interactively rather than through a one-way transmission process (Johnston, James, Lye, & McDonald, 2000;Littleton & Häkkinen, 1999;Slavin, 1983Slavin, , 1995Veerman & Veldhuis-Diermanse, 2001;Weigel, 2002). Although collaborative learning is emerging as a promising educational approach, research on its effects on learning has been highly inconclusive (Kester & Paas, 2005). We believe that these inconclusive results have, among other things, been caused by a lack of attention to the structures constituting human cognitive architecture (Sweller, 1988;Sweller, Van Merriënboer, & Paas, 1998) when designing collaborative learning environments.Research stressing the potential of collaborative learning shows that collaborative learning environments can stimulate and/or enable learners to engage in activities that are valuable for learning. Activities such as self-directed learning, negotiating meaning (Beers, Boshuizen, & Kirschner, 2007;Kirschner, Beers, Boshuizen, & Gijselaers, 2008), verbalizing explanations, justifications and reflections, giving mutual support (Van Boxtel, Van der Linden, & Kanselaar, 2000), and developing arguments about complex problems or propositions (Munneke, Andriessen, Kanselaar, & Kirschner, 2007) have been found to facilitate the learning process. Collaborative learning has also been shown to help learners retain the learned information longer (Morgan, Whorton, & Gunsalus, 2000) and to foster their higher-order skills more than in more traditional lecture-based learning environments (Sloffer, Dueber, & Duffy, 1999). It is important to note that...

This study investigated the differential effects of learning task complexity on both learning process and outcome efficiency of 83 individual and group learners in the domain of biology.Based upon cognitive load theory, it was expected that for high-complexity tasks, group members would learn in a more efficient way than individual learners, while for low-complexity tasks, individual learning would be more efficient. This interaction hypothesis was confirmed, supporting our premise that the learning efficiency of group members and individuals is determined by a trade-off between the group's advantage of dividing information processing amongst the collective working memories of the group members and its disadvantage in terms of associated costs of information communication and action coordination. Memory EffectAlthough collaborative learning is a popular and widely used educational approach, research on its effects on learning has been inconclusive (Kester & Paas, 2005). Research stressing the potential of collaborative learning shows that collaborative learning environments can stimulate and enable learners to engage in activities that are valuable for learning (Beers, Boshuizen, & Kirschner, 2007;P. A. Kirschner, Beers, Boshuizen, & Gijselaers, 2008;Munneke, Andriessen, Kanselaar, & Kirschner, 2007). However, looking at the studies showing mixed and even negative findings regarding the learning process (e.g., Gregor & Cuskelly 1994;Heath, 1998), group forming, and group dynamics (e.g., Hughes & Hewson 1998;Taha & Caldwell, 1993), collaborative learning environments seem to be no guarantee for positive learning outcomes (Soller, 2001).In a review of research comparing the effectiveness of individual learning approaches to collaborative learning approaches, F. Kirschner, Paas, and Kirschner (2009a) argued that one possible cause for these inconclusive results may be that the structures constituting cognitive architecture have not been systematically considered when designing and carrying out research on collaborative learning (see also, P. A. Kirschner, Sweller, & Clark, 2006). Specifically, the differing complexities of learning tasks used and the concomitant load imposed by these tasks on the learner's cognitive architecture could be an important factor affecting the efficiency of individual and group learning, which is defined here as the amount of mental effort invested by a learner to reach a certain level of performance; high efficiency is associated with a relatively high test performance in combination with a relatively low mental-effort investment. In contrast, low efficiency is associated with a relatively low test performance in combination with a relatively high mental-effort investment. Task Complexity and Collaborative Learning Efficiency 4Two recent studies investigated the efficiency of individual versus group learning as a function of task complexity (i.e., determined by the number of elements in a learning task and the interaction between those elements; Sweller & Chandler, 1994). In a ...