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Human-computer interaction in foreign language learning applications: Applied linguistics viewpoint of mobile learning

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F21%3A50018069" target="_blank" >RIV/62690094:18450/21:50018069 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://www.sciencedirect.com/science/article/pii/S1877050921007729?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1877050921007729?via%3Dihub</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.procs.2021.03.123" target="_blank" >10.1016/j.procs.2021.03.123</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Human-computer interaction in foreign language learning applications: Applied linguistics viewpoint of mobile learning

  • Popis výsledku v původním jazyce

    The current development in mobile learning has seen an unprecedented rise in the last decade and, moreover, the present pandemic situation has speeded up the process of eLearning implementation even in areas that were still rather reluctant in this respect. The paper attempts to provide the results and analysis of the subjective satisfaction of the users of these foreign language learning apps. Qualitative research was conducted at the Faculty of Informatics and Management of the University of Hradec Kralove, the Czech Republic, as a qualitative study through a set of guided interviews with students/users. The respondents (n=18) were the students of information science and data science of the university; therefore, their opinion can prove to be very useful as they are well informed and they also represented the youngest generation, i.e. Millennials, who may have rather different needs from the previous generations, and these needs are, naturally, reflected in their use of technology. The tested apps belong to the most popular and most downloaded free apps for foreign language learning currently available in the iOS and Android markets. The findings of the research clearly show that the main concern of the users of the apps was the lack of AI utilization and old-fashioned interface of the apps despite the fact that they are relatively new. Another major concern was the old-fashioned design, and regarding human-computer interaction in these apps, the lack of machine learning and deep learning strategies.

  • Název v anglickém jazyce

    Human-computer interaction in foreign language learning applications: Applied linguistics viewpoint of mobile learning

  • Popis výsledku anglicky

    The current development in mobile learning has seen an unprecedented rise in the last decade and, moreover, the present pandemic situation has speeded up the process of eLearning implementation even in areas that were still rather reluctant in this respect. The paper attempts to provide the results and analysis of the subjective satisfaction of the users of these foreign language learning apps. Qualitative research was conducted at the Faculty of Informatics and Management of the University of Hradec Kralove, the Czech Republic, as a qualitative study through a set of guided interviews with students/users. The respondents (n=18) were the students of information science and data science of the university; therefore, their opinion can prove to be very useful as they are well informed and they also represented the youngest generation, i.e. Millennials, who may have rather different needs from the previous generations, and these needs are, naturally, reflected in their use of technology. The tested apps belong to the most popular and most downloaded free apps for foreign language learning currently available in the iOS and Android markets. The findings of the research clearly show that the main concern of the users of the apps was the lack of AI utilization and old-fashioned interface of the apps despite the fact that they are relatively new. Another major concern was the old-fashioned design, and regarding human-computer interaction in these apps, the lack of machine learning and deep learning strategies.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

    60203 - Linguistics

Návaznosti výsledku

  • Projekt

  • Návaznosti

    S - Specificky vyzkum na vysokych skolach

Ostatní

  • Rok uplatnění

    2021

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    Procedia Computer Science

  • ISBN

  • ISSN

    1877-0509

  • e-ISSN

  • Počet stran výsledku

    7

  • Strana od-do

    92-98

  • Název nakladatele

    Elsevier

  • Místo vydání

    Amsterdam

  • Místo konání akce

    Warsaw, Poland

  • Datum konání akce

    23. 3. 2021

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku