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37 ta ish

Ish: Adaptive recommendation of student-created micro-lessons based on learning style and knowledge-level modeling

  1. A Web-based Instrument to Initialize Learning Style: An Interactive Questionnaire Instrument

    Doniyorbek Ahmadaliev, Chen Xiaohui, Murodjon Abduvohidov

    MaqolaLearning Styles and Cognitive DifferencesInternational Journal of Emerging Technologies in Learning (iJET)20183 iqtibos
    ABI

  2. The Adaptive Web

    Kitob20073 iqtibos
    ABI

  3. Hypertext: An Introduction and Survey

    Conklin

    Maqola19873 iqtibos
    ABI

  4. Evaluating Bayesian networks’ precision for detecting students’ learning styles

    Patricio García Báez, Analı́a Amandi, Silvia Schiaffino +1

    Maqola20052 iqtibos
    ABI

  5. Learning and Teaching Styles In Foreign and Second Language Education

    Richard M. Felder, Eunice Ribeiro Henriques

    Maqola19952 iqtibos
    ABI

  6. A genetic algorithm approach to recognise students' learning styles

    Virginia Yannibelli, Daniela Godoy, Analı́a Amandi

    Maqola20062 iqtibos
    ABI

  7. Prediction of Learner’s Profile based on Learning Styles in Adaptive E-learning System

    Sucheta V. Kolekar, Radhika M. Pai, M. M. Manohara Pai

    Maqola20172 iqtibos
    ABI

  8. Using the HOT-fit model to predict the determinants of E-learning readiness in higher education: a developing Country’s perspective

    Marva Mirabolghasemi, Sahar Hosseinikhah Choshaly, Noorminshah A. Iahad

    Maqola20192 iqtibos
    ABI

  9. The adequacy of UTAUT-3 in interpreting academician’s adoption to e-Learning in higher education environments

    Asanka Gunasinghe, Junainah Abd Hamid, Ali Khatibi +1

    Maqola20192 iqtibos
    ABI

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