Exploring General Morphological Analysis and Providing Personalized Recommendations to Stimulate Creativity with ReaderBench

Daniela Stamati, Maria-Dorinela Sirbu, Mihai Dascalu, Stefan Trausan-Matu

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

    Abstract

    Computer Supported Collaborative Learning (CSCL) has gained a steadily increasing role as it helps students to better comprehend through its synergistic effect, mediated by technology. In line with CSCL learning paradigm, our approach is centered on creativity stimulation which is facilitated by a deeper understanding of the dialog. This paper introduces new extended views for our ReaderBench framework, as well as a novel recommendations engine. Our General Morphological Analysis (GMA) implementation is based on the keywords extraction mechanism provided by ReaderBench, alongside with the similar concepts inferred using the lexicalized ontology WordNet, Latent Semantic Analysis (LSA), and Latent Dirichlet Analysis (LDA) semantic models. We also include a comprehensive case study to detail the new processing workflows that integrate voices (i.e., participants' points of view), keywords identification, and text cohesion in order to recommend personalized learning resources.
    Original languageEnglish
    Title of host publicationChallenges and Solutions in Smart Learning
    Subtitle of host publicationLecture Notes in Educational Technolog
    EditorsM. Chang, E. Popescu , Kinshuk, N.-S. Chen, M. Jemni, R. Huang , J. M. Spector
    Place of PublicationSingapore
    PublisherSpringer Singapore
    Pages41-50
    Number of pages10
    ISBN (Electronic)9789811087431
    ISBN (Print)9789811087424
    DOIs
    Publication statusPublished - 2018

    Publication series

    SeriesLecture Notes in Educational Technology

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    Keywords

    • Creativity stimulation
    • General Morphological Analysis
    • Dialogism
    • Semantic models
    • Personalized recommendations of learning resources
    • ReaderBench framework

    Cite this

    Stamati, D., Sirbu, M-D., Dascalu, M., & Trausan-Matu, S. (2018). Exploring General Morphological Analysis and Providing Personalized Recommendations to Stimulate Creativity with ReaderBench. In M. Chang, E. Popescu , Kinshuk, N-S. Chen, M. Jemni, R. Huang , & J. M. Spector (Eds.), Challenges and Solutions in Smart Learning: Lecture Notes in Educational Technolog (pp. 41-50). Singapore: Springer Singapore. Lecture Notes in Educational Technology https://doi.org/10.1007/978-981-10-8743-1_7