EXP: Exploratory study on the Adaptive Online Course and its implication on synergetic competency
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The Cyberlearning and Future Learning Technologies Program fundsefforts that support envisioning the future of learning technologiesand advance what we know about how people learn in technology-richenvironments. Cyberlearning Exploration (EXP) Projects explore theviability of new kinds of learning technologies by designing andbuilding new kinds of learning technologies and studying theirpossibilities for fostering learning and challenges to using themeffectively. Most online courseware helps teach facts and concepts,while a different type of online learning software called intelligenttutoring systems can effectively teach skills in a way that istailored to each learner. Unfortunately, these two tools are rarelyintegrated because of the expense and specialized expertise requiredto create intelligent tutors. This project will close this gap bybuilding and testing a new scalable technology that will allowteachers without years of specialized training to author adaptiveonline courses that combine the best of both these approaches. Thisscalable cyberlearning platform will provide students with effectiveonline instruction, provide learning engineers with an efficientauthoring environment to build adaptive online courses, and provideresearchers with a sharable corpus of big learning data that they canuse to develop and refine theories of how students learn in adaptiveonline-course learning environments.This project will build a web-browser-based authoring environment thatsupports the creation cognitive tutors and their seamless integrationinto online courses and will measure how well the resulting adaptiveonline courses promote facets of student learning such as synergeticcompetency and engagement. The central hypotheses are: (1) that theSimStudent technology -- a machine-learning agent that learnscognitive skills from demonstration -- can be a practical authoringtool for cognitive tutors that can be easily embedded into onlinecourses; (2) that this technology can represent a tight connectionbetween learners'' procedural competency and conceptual competency bycombining knowledge-tracing (a standard method used by existingcognitive tutors) and text-mining (data-mining latent skills fromtraditional online course instructions) into an innovativestudent-modeling technique; and (3) that adaptive online coursescreated with this technique can produce robust student learning bypromoting connections between their procedural and conceptualunderstanding (synergetic competency). As part of the overall researchprogram, the project will: (a) develop a genetic applicationprogramming interface (API) for an existing web-based authoringtechnology to build cognitive tutors for online course integration;(b) develop an adaptive instructional technology as a generic controlmechanism for adaptive online courses; (c) build new adaptive onlinecourses on Open edX and also convert an existing OLI course into anadaptive online course; (d) conduct in-vivo studies using the adaptiveonline courses to test their effectiveness; (e) test the efficacy ofthe proposed adaptive online courses in supporting students to achievethe aforementioned synergetic competency. Successful completion of theproject will yield the following expected outcomes: (i) a scalableonline course architecture with efficient authoring tools for buildingcognitive tutors and integrating them into online courses in order tomake those courses adaptive; (ii) a practical technique to identifyrelationships between procedural competency and conceptual competency;and (iii) an expanded theory of how students learn with the adaptiveonline course, and in particular of how students achieve robustlearning with synergetic competency.
