332 research outputs found

    An Evolutionary Upgrade of Cognitive Load Theory: Using the Human Motor System and Collaboration to Support the Learning of Complex Cognitive Tasks

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    Cognitive load theory is intended to provide instructional strategies derived from experimental, cognitive load effects. Each effect is based on our knowledge of human cognitive architecture, primarily the limited capacity and duration of a human working memory. These limitations are ameliorated by changes in long-term memory associated with learning. Initially, cognitive load theory's view of human cognitive architecture was assumed to apply to all categories of information. Based on Geary's (Educational Psychologist 43, 179-195 2008; 2011) evolutionary account of educational psychology, this interpretation of human cognitive architecture requires amendment. Working memory limitations may be critical only when acquiring novel information based on culturally important knowledge that we have not specifically evolved to acquire. Cultural knowledge is known as biologically secondary information. Working memory limitations may have reduced significance when acquiring novel

    Assessing the Role of Computer Simulation in Chemistry Learning

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    Simulation and Computation make a versatile teaching strategy, and may be an important way to motivate students and lecturers to achieve meaningful learning. Indeed, this work refers to a study whose main objective is to set the influence that a teaching approach based on the use of computer simulation would have on students’ learning, compared to the one in use today. This work involved the participation of two classes of 11th grade at a Secondary School in Lisbon, Portugal, where the main goal is to teach a specific topic to an untried student’s group. With regard to the simulation environment, it will be grounded on a Proof Theoretical approach to Knowledge Representation and Reasoning, which caters for the handling of incomplete, unknown or even self-contradictory information or knowledge

    Collaboration scripts - a conceptual analysis

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    This article presents a conceptual analysis of collaboration scripts used in face-to-face and computer-mediated collaborative learning. Collaboration scripts are scaffolds that aim to improve collaboration through structuring the interactive processes between two or more learning partners. Collaboration scripts consist of at least five components: (a) learning objectives, (b) type of activities, (c) sequencing, (d) role distribution, and (e) type of representation. These components serve as a basis for comparing prototypical collaboration script approaches for face-to-face vs. computer-mediated learning. As our analysis reveals, collaboration scripts for face-to-face learning often focus on supporting collaborators in engaging in activities that are specifically related to individual knowledge acquisition. Scripts for computer-mediated collaboration are typically concerned with facilitating communicative-coordinative processes that occur among group members. The two lines of research can be consolidated to facilitate the design of collaboration scripts, which both support participation and coordination, as well as induce learning activities closely related to individual knowledge acquisition and metacognition. In addition, research on collaboration scripts needs to consider the learners’ internal collaboration scripts as a further determinant of collaboration behavior. The article closes with the presentation of a conceptual framework incorporating both external and internal collaboration scripts

    On the ability of virtual agents to decrease cognitive load: an experimental study

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    When attempting to solve a problem, humans call upon cognitive resources. These resources are limited, and the degree of their utilisation is described as cognitive load. While the number of parameters to be taken into account and to be processed by modern-day knowledge workers increases, their cognitive resources do not. Research shows that too high a load can increase stress and failure rates and decrease the work satisfaction and performance of employees. It is thus in the interest of organisations to reduce the cognitive load of their employees and keep it at a moderate level. One way to achieve this may be the application of virtual assistants (VAs), software programs, that can be addressed via voice or text commands and respond to the users’ input. This study uses a laboratory experiment with N = 91 participants comparing two groups in their ability to solve a task. One group was able to make use of a VA while the other could not. Besides task performance, the cognitive load of the participants was measured. Results show that (a) cognitive load is negatively related to task performance, (b) the group using the VA performed better at the task and (c) the group using the VA had a lower cognitive load. These findings show that VAs are a viable way to support employees and can increase their performance. It adds to the growing field of IS research on VAs by expanding the field for the concept of cognitive load

    Quality specifications in postgraduate medical e-learning: an integrative literature review leading to a postgraduate medical e-learning model

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    BACKGROUND: E-learning is driving major shifts in medical education. Prioritizing learning theories and quality models improves the success of e-learning programs. Although many e-learning quality standards are available, few are focused on postgraduate medical education. METHODS: We conducted an integrative review of the current postgraduate medical e-learning literature to identify quality specifications. The literature was thematically organized into a working model. RESULTS: Unique quality specifications (n = 72) were consolidated and re-organized into a six-domain model that we called the Postgraduate Medical E-learning Model (Postgraduate ME Model). This model was partially based on the ISO-19796 standard, and drew on cognitive load multimedia principles. The domains of the model are preparation, software design and system specifications, communication, content, assessment, and maintenance. CONCLUSION: This review clarified the current state of postgraduate medical e-learning standards and specifications. It also synthesized these specifications into a single working model. To validate our findings, the next-steps include testing the Postgraduate ME Model in controlled e-learning settings
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