1,694 research outputs found

    Internal and external scripts in computer-supported collaborative inquiry learning

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    We investigated how differently structured external scripts interact with learners’ internal scripts concerning individual knowledge acquisition in a Web-based collaborative inquiry learning environment. 90 students from two secondary schools participated. Two versions of an external collaboration script (high vs. low structured) supporting collaborative argumentation were embedded within a Web-based collaborative inquiry learning environment. Students’ internal scripts were classified as either high or low structured, establishing a 2x2-factorial design. Results suggest that the high structured external collaboration script supported the acquisition of domain-general knowledge of all learners regardless of their internal scripts. Learners’ internal scripts influenced the acquisition of domain-specific knowledge. Results are discussed concerning their theoretical relevance and practical implications for Web-based inquiry learning with collaboration scripts

    Supporting Collaborative Learning in Videoconferencing using Collaboration Scripts and Content Schemes

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    Studies have shown that videoconferences are an effective medium for facilitating communication between parties who are separated by distance. Furthermore, studies reveal that videoconferences are effective when used for distance learning, particularly due to their ability to facilitate complex collaborative learning tasks. However, as in face-to-face communication, learners benefit when they receive additional support for such learning tasks. This article provides an overview of two empirical studies to illustrate more general insights regarding some effective and less effective ways to support collaborative learning with videoconferencing. The focus is on content schemes as content-specific support and task-specific support as collaboration scripts. Based on the results of the two studies, conclusions can be drawn about support measures that promote learning. Conclusions can also be reached about the need for employing both content schemes and collaboration scripts to provide learners with the most benefit.Studien haben gezeigt, dass Videokonferenzen ein effektives Medium fĂŒr die verteilte Kommunikation sind. Ebenso zeigten erste Studien, dass sich Videokonferenzen auch in Telelernumgebungen einsetzen lassen, insbesondere weil sie komplexe kooperative Lernaufgaben ermöglichen. Lernende profitieren jedoch in solchen Lernaufgaben – Ă€hnlich wie face to face – von zusĂ€tzlicher UnterstĂŒtzung. In diesem Beitrag werden zwei empirische Studien dargestellt, die weiterfĂŒhrende Erkenntnisse hinsichtlich effektiver und weniger effektiver Arten der UnterstĂŒtzung kollaborativen Lernens in Videokonferenzen erbringen sollen. Der Schwerpunkt liegt dabei auf Wissensschemata als Methode inhaltlicher UnterstĂŒtzung, und aufgabenspezifischer UnterstĂŒtzung in Form von Kooperationsskripts. Ausgehend von den Ergebnissen dieser zwei Studien werden Folgerungen ĂŒber lernförderliche Merkmale der UnterstĂŒtzungsmaßnahmen formuliert. Befunde weisen auf die Notwendigkeit Wissensschemata und Kooperationsskripts kombiniert anzuwenden hin, um fĂŒr die Lernenden den grĂ¶ĂŸtmöglichen Nutzen zu erreichen

    Enhancing Free-text Interactions in a Communication Skills Learning Environment

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    Learning environments frequently use gamification to enhance user interactions.Virtual characters with whom players engage in simulated conversations often employ prescripted dialogues; however, free user inputs enable deeper immersion and higher-order cognition. In our learning environment, experts developed a scripted scenario as a sequence of potential actions, and we explore possibilities for enhancing interactions by enabling users to type free inputs that are matched to the pre-scripted statements using Natural Language Processing techniques. In this paper, we introduce a clustering mechanism that provides recommendations for fine-tuning the pre-scripted answers in order to better match user inputs
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