868 research outputs found
Facebook as learning platform: Argumentation superhighway or dead-end street?
Facebook and other Social Network Sites are often seen by educators as multifunctional platforms that can be used for teaching, learning and/or the facilitation of both. One such strand is making use of them as tools/platforms for using and learning through argumentation and discussion. Research on whether this ‘promise’ is actually achieved – also the research reported on in this Special Issue – does not unequivocally answer the question of whether this is a good idea. This article as one of the two closing articles of this Special Issue discusses Social Networking Sites in general and Facebook specifically with respect to how they are ‘normally’ used by their members as well as with respect to their social and technical features. Then, in light of this, it discusses the learning results of the four studies. It concludes with a short discussion of whether they are capable of meeting the promise that many think they can
When a paradigm becomes a paradogma
Every science, every scientific discipline, operates under one or more paradigms; a world view that
underlies the theories and methodologies of the discipline. Sometimes a discipline’s paradigms complement or supplement each other while at other times they may contradict or even exclude each other. While paradigms are strong and have longevity, they are also fluid, relative and changeable and can even ‘die’. An anathema of the sciences, scientific disciplines and the process of carrying out science (or as Derek Hodson1 calls it: ‘doing science’) is the dogma. In contrast to a paradigm, a dogma is a set of principles or a doctrine prescribed by an authority as incontrovertibly true. Dogmata are possibly most often found in religion, forming the core principles that must be
upheld by all believers of a religion. As such, dogmata are also strong and have longevity, but are
static, immutable and almost unchangeable except by divine decree. This editorial discusses a recent case which I and some colleagues encountered where a highly reputable scientific journal’s editorial decision was not based on the article’s quality (e.g., weak theory, bad methodology, improper statistics, . . .) or misuse of a scientific paradigm (e.g., a methodology that does not fit the paradigm used), but rather on a dogma (i.e., the author questioned something that one of the executive editors found to be incontrovertibly true). In other words, a rejection based on a paradigm that has reached the status of a dogma; a paradogma
Do we need teachers as designers of technology enhanced learning?
In this special issue, five teams of researchers discuss different aspects of the teacher as designer of technology enhanced learning situations. This final contribution critically discusses if and how teachers as designers of technology enhanced learning might (not) be feasible or even desirable. The premise underlying this critical view is that technology enhanced learning should not be seen as ‘special’ in comparison to other forms of learning in the teacher’s arsenal. Both practicing professionals and institutions for teacher education must understand and embrace the role of design in professional competencies if technology enhanced learning is ever to be fully integrated into teaching and learning processes.2017-01-0
Epistemology or pedagogy:That is the question
A child is not a little adult, nor a learner a little scientist. Children’s concepts differ in structure and meaning from those of adults. Both Vygotsky (children have different kinds of concepts from adults; they don’t have true concepts until puberty) and Piaget (there are shifts between major periods which can be interpreted as changes in representational formats and processes that operate on them) would argue that there are fundamental changes in mental machinery from childhood to adulthood. As such, how to learn or be taught in a domain is quite different from how to perform or ‘do’ in a domain (i.e., learning science vs. doing science). The epistemology of most sciences, for example, is often based upon experimentation and discovery and, since this is so, experimentation and discovery should be a part of any curriculum aimed at ‘producing’ future scientists. But this does not mean that experimentation and discovery should also be the basis for curriculum organization and learning environment designing. Modern curriculum developers and reformers who often refer to themselves as constructivists tend to confuse the epistemological basis of a domain (i.e., how knowledge is acquired and the accepted validation procedures of that knowledge in a domain) with the psychological and pedagogic bases for teaching in that domain (i.e., strategies of instruction or a style of instruction). In other words, they fail to distinguish between learning and doing and thus overlook the fact that students are not miniature experts practicing something, but rather that they are novices learning about something
Individual and group-based learning from complex cognitive tasks: Effects on retention and transfer efficiency
Kirschner, F., Paas, F., & Kirschner, P. (2009). Individual and group-based learning from complex cognitive tasks: Effects on retention and transfer efficiency. Computers in Human Behavior, 25, 306-314.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
Superiority of collaborative learning with complex tasks: A research note on an alternative affective explanation
Kirschner, F., Paas, F., & Kirschner, P. A. (2011). Superiority of collaborative learning with complex tasks: A research note on an alternative affective explanation. Computers in Human Behavior, 27(1), 53-57. doi:10.1016/j.chb.2010.05.012Kirschner, Paas, and Kirschner (2009c) used the theoretical framework of cognitive load to explain why the learning of a group of collaborating individuals was more efficient than that of individuals learning alone with high-complexity tasks but not with low-complexity tasks. The authors argued that collaboration circumvented the limitations of an individual’s working memory by creating an expanded cognitive capacity and by allowing for the distribution of
cognitive load among group members. Inspired by research on efficacy, this study explored an alternative affective explanation of the results. By measuring the amount of mental effort learners expected to invest in working on a learning task before actually carrying out the task, this study showed that learners who had to collaboratively solve a high-complexity problem expected to invest less mental effort than learners who had to solve the problem alone. When confronted with low-complexity tasks, the expected amount of mental effort did not differ
Task complexity as a driver for collaborative learning efficiency: The collective working-memory effect
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
Task complexity as a driver for collaborative learning efficiency: The collective working-memory effect
Kirschner, F., Paas, F., & Kirschner, P. A. (2011). Task complexity as a driver for collaborative learning efficiency: The collective working-memory effect. Applied Cognitive Psychology, 25, 615–624. doi: 10.1002/acp.1730.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
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