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    From Know-It-Alls to Learn-It-Alls: Executive Development in the Era of Self-Refining Algorithms, Collaborative Filtering and Wearable Computing
    06 Jan 2020Working Paper Summaries

    From Know-It-Alls to Learn-It-Alls: Executive Development in the Era of Self-Refining Algorithms, Collaborative Filtering and Wearable Computing

    by Mihnea Moldoveanu and Das Narayandas
    Learning happens most reliably and efficiently when it is contextualized, personalized, and socialized. This is important for executive learning in particular and adult learning more generally. Innovators and educational designers can leverage technologies that enable sensing, interacting, computing, searching, and storing to produce learner-optimal experiences.
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    Author Abstract

    We examine the future of executive education on a technological and cultural landscape that is imminent but different to the one we are accustomed to. We show how the contextualization, socialization and personalization of learning—avowed but distal goals of current executive education programs—are made real by the integration of a suite of currently available technologies and ways of using them that bring learners together in dense and intimate learning networks (socialization), powered by semantic and social search technologies that adapt content to individual learners’ styles and preferences (personalization) and can be deployed in the setting of the learners’ own organizations (contextualization)—all of which serve to optimize the learning production function for both skill acquisition and skill transfer—the two charges that the new skills economy has laid out for any educational enterprise.

    Paper Information

    • Full Working Paper Text
    • Working Paper Publication Date: November 2019
    • HBS Working Paper Number: HBS Working Paper #20-061
    • Faculty Unit(s): General Management; Marketing
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    Das Narayandas
    Das Narayandas
    Edsel Bryant Ford Professor of Business Administration
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