Human Behavior in Military Contexts (2008) / Chapter Skim
Currently Skimming:
Technology-Based Training--Arthur C. Graesser and Brandon King
Technology-Based Training--Arthur C. Graesser and Brandon King
Pages 127-149
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From page 127... ...
The learning environments they confront are often limited or disappointing because the developers of the systems have not had sufficient training in cognitive science, pedagogy, behavioral sciences, and learning technologies. There is a shortage of trained professionals in these areas of 127
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From page 128... ...
For example, there has not been enough research on learning gains from serious games that afford active discovery learning in adults with low reading ability. In contrast, there is a wealth of research on learning gains from intelligent tutoring systems on algebra and physics that spans the gamut of learner characteristics, pedagogical mechanisms, and learning goals (Anderson, Corbett, Koedinger, and Pelletier, 1995; Corbett, 2001; VanLehn et al., 2002)
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From page 129... ...
The prominent ones associated with each genre of learning environment are discussed below. Examples of pedagogical mechanisms are mastery learning with presentation-test-feedback-branching; building on prerequisites; practice with problems and examples; multimedia learning; modeling-scaffolding fading; reciprocal training; problem-based learning and curricula; inquiry learning; and collaborative knowledge construction.
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From page 130... ...
One way of learning a complex system at a deep level is to build an advanced learning environment on the system with an authoring tool. Learning environments must be evaluated from the standpoint of learning gains, usage, engagement, and return on investment.
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From page 131... ...
There are few data on learning gains from various classes of learning environments, such as inquiry-based information retrieval, virtual environments with agents, serious games, and computer-supported collaborative learning: research is needed on them. Although learning gains are routinely reported in published studies, there are often incomplete data on use (attrition)
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From page 132... ...
The nature of the test format calls for additional research. Most multiple choice questions in actual courses, electronic learning facilities, and commercial test banks tap shallow rather than deep levels of comprehension (Ozuru, Graesser, Rowe, and Floyd, 2005; Wisher and Graesser, 2005)
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From page 133... ...
Other learning environment genres appear to be more appropriate for enhancing engagement, active application of knowledge and skills, and depth of mastery. Multimedia In a multimedia learning environment, material can be delivered in different presentation modes (verbal, pictorial)
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From page 134... ...
. Although some researchers have documented learning gains from animations, there is a persistent question of whether there is information equivalence between the simulation and control conditions in that research.
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Unfortunately, simulations and many other advanced learning environments tend to have complex content and interfaces that are unfamiliar to learners. Learners with low domain knowledge or computer expertise have trouble getting started and managing the human-computer interface.
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The processes of tracking knowledge (called user modeling) and adaptively responding to a learner ideally incorporate computational models in artificial intelligence and cognitive science, such as production systems, case-based reasoning, Bayes networks, theorem proving, and constraint satisfaction algorithms.
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From page 137... ...
. There are three major reasons for encouraging more research on developing and testing intelligent tutoring systems with tutorial dialogue in natural language.
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From page 138... ...
What has been rare in evaluations of these systems is performance in the context of learning environments. In one study on a learning environment on research ethics, the performance in terms of the accuracy of paragraphs returned in an inquiry, with 95 percent of the paragraphs judged relevant by the learners and 50 percent were judged informative (Graesser, Hu et al., 2004)
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From page 139... ...
, so the research is expensive and takes months or years for adequate evaluations. A pragmatic skeptic might ask how, when, or whether these broad-scale inquiry learning environments are relevant to military training.
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This direction requires integration of advances from computational linguistics, cognitive science, and artificial intelligence. Fourth, researchers can investigate alternative ways that agents can be responsive to learners as learners make contributions that vary in quality.
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The learner holds a dialogue in natural language, with speech recognition, and multiple agents. These award-winning virtual environments are major milestones and have involved major investments by the military.
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From page 142... ...
, but the scale of these distributed learning environments makes it very difficult to perform systematic evaluations. Social and behavioral scientists can improve these systems in several ways (Clark and Brennan, 1991; Dillenbourg and Traum, 2006; Looi, 2005; Mazur, 2004; Soller et al., 1998; Wang, 2005)
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From page 143... ...
Scaffolding would require a deep interpretation of a learner's contributions, including natural language, multimodal sensing, and a dynamic generation of computer actions. Modeling and testing the conditions under which interactive simulation with multimedia promotes deep learning. There typically are a large number of displays, media, controls, input channels, forms of feedback, icons with particular semiotic functions, and other interface features in interactive simulations.
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From page 144... ...
. Optimizing learning from examples using animated pedagogical agents.
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From page 145... ...
Interactive Learning Environments, 8, 111-127. Gagne, R.M.
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From page 146... ...
. Animated pedagogical agents: Face-to-face interaction in interactive learning environments.
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From page 147... ...
. Speech and language processing: An introduction to natural language processing, computational linguistics, and speech recognition.
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. Authoring tools for advanced tech nology learning environments: Towards cost-effective adaptive, interactive and intelligent educational software.
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From page 149... ...
. Question asking in advanced distributed learning environments.
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