Co-Lab: research and development of an online learning environment for collaborative scientific discovery learning

Joolingen, Wouter van; Jong, Ton de; Lazonder, Adrianus W.; Savelsbergh, E.R.; Manlove, Sarah

doi:10.1016/j.chb.2004.10.039

Cited by 263 publications

(168 citation statements)

References 27 publications

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“…Computer simulations have long been incorporated in these environments, and are increasingly being supplemented with opportunities for students to build computer models of the phenomena they are investigating via the simulation. As in authentic scientific inquiry, modeling is considered integral to the inquiry learning process in that students have to build models to express their understanding of the relation between variables (Van Joolingen et al 2005;White et al 1999). Students can check their understanding by running the model, and weighting its output against prior knowledge or the data from the simulation.…”

Section: Introductionmentioning

confidence: 99%

Validating and Optimizing the Effects of Model Progression in Simulation-Based Inquiry Learning

et al. 2011

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Model progression denotes the organization of the inquiry learning process in successive phases of increasing complexity. This study investigated the effectiveness of model progression in general, and explored the added value of either broadening or narrowing students' possibilities to change model progression phases. Results showed that high-school students in the 'standard' model progression condition (n = 19), who could enter subsequent phases at will, outperformed students from a control condition (n = 30) without model progression. The unrestricted condition (n = 22) had the additional option of returning to previous phases, whereas the restricted condition (n = 20) disallowed such downward progressions as well as upward progressions in case insufficient knowledge was acquired. Both variants were found to be more effective in terms of performance than the 'standard' form of model progression. However, as performance in all three model progression conditions was still rather weak, additional support is needed for students to reach full understanding of the learning content.

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Section: Introductionmentioning

confidence: 99%

Validating and Optimizing the Effects of Model Progression in Simulation-Based Inquiry Learning

et al. 2011

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“…In recent decades, discovery learning has moved away from the concept of pure discovery. For several years, discovery learning has relied on a more systematic approach adapted from theories of scientific discovery (Bruner 1961;van Joolingen et al 2005). This notion is referred to as scientific discovery learning (Klahr and Dunbar 1988;Klahr et al 1993).…”

mentioning

confidence: 99%

“…Learners are asked to infer the characteristics underlying the scenarios when they explore the principles, concepts, rules, and terms of simulated experiments (van Joolingen et al 2005). Learners are required to discover the model behind the simulation (de Jong et al 1994).…”

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confidence: 99%

How effective is instructional support for learning with computer simulations?

et al. 2012

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The study examined the effects of two different instructional interventions as support for scientific discovery learning using computer simulations. In two well-known categories of difficulty, data interpretation and self-regulation, instructional interventions for learning with computer simulations on the topic ''ecosystem water'' were developed and tested using a sample of 124 eighth graders in science classes. The results demonstrate the effectiveness of instructional support for domain-specific factual, conceptual, and procedural knowledge acquisition. Students who received either only instructional support for data interpretation or only for self-regulation achieved the highest learning outcomes. However, a combination of instructional support for data interpretation and self-regulation seemed detrimental for knowledge acquisition. Students who received instructional interventions for both data interpretation and self-regulation also showed the highest values of perceived cognitive load. High cognitive load could be a reason for why a combination of particular instructional interventions does not lead to the expected positive learning outcomes.

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“…Un ejemplo interesante que ilustra las valiosas posibilidades de las herramientas de modelización para la enseñanza de las ciencias se puede encontrar en el proyecto Co Lab (van Joolingen et al, 2005). Este proyecto europeo se ha centrado en el desarrollo y la evaluación de un entorno virtual para promover el aprendizaje de las ciencias de la naturaleza en los niveles superiores de enseñanza secundaria y en la universidad, a través de la realización de proyectos de investigación de forma colaborativa.…”

Section: Entornos Virtuales Modelización Y Enseñanza De Las Cienciasunclassified

Nuevas tecnologías y aprendizaje significativo de las ciencias

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Este trabajo pretende fomentar la reflexión sobre el potencial de la tecnología educativa para promover el aprendizaje significativo de las ciencias. Con este propósito se recurre a la literatura especializada, para mostrar algunos resultados de investigación sobre la aplicación de las TIC a la enseñanza de las ciencias (herramientas de adquisición de datos, programas de modelización, simulaciones, laboratorios virtuales…). El valor formativo de dichas aplicaciones se discute desde los actuales conocimientos acerca de cómo los individuos aprenden, mostrando el potencial de estos recursos para superar los obstáculos específicos asociados al aprendizaje efectivo de las ciencias (ideas previas, falta de contextos significativos, grado de abstracción de modelos y teorías…). No obstante, también se ofrece una visión crítica señalando riesgos y limitaciones.

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Co-Lab: research and development of an online learning environment for collaborative scientific discovery learning

Cited by 263 publications

References 27 publications

Validating and Optimizing the Effects of Model Progression in Simulation-Based Inquiry Learning

Validating and Optimizing the Effects of Model Progression in Simulation-Based Inquiry Learning

How effective is instructional support for learning with computer simulations?

Nuevas tecnologías y aprendizaje significativo de las ciencias

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