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Moveable Älıpbi: The Montessori Method for Robot-Assisted Alphabet Learning

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Social Robotics (ICSR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13818))

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Abstract

The Montessori method is well-known for its child-centered and hands-on learning approach for early literacy development. This study is the first to apply the Montessori method in robot-assisted language learning (RALL). We developed an alphabet learning system that consists of a Moveable alphabet, a tablet, and a social robot. We conducted a between-subjects experiment with 89 Kazakh children aged 6–11 that learned the Kazakh Latin alphabet either with a Montessori-human (MH) or a Montessori-robot (MR) teacher. We examined the effects of the learning method on children’s learning gains and emotional outcomes across these two conditions. Our results suggest that in the Montessori learning environment the MH teacher was significantly more effective in providing early literacy support than the MR teacher. The emotional states were mixed between grades, but the children in the MR condition felt happier than those in the MH condition in Grades 1 (ages 6–7) and 4 (ages 10–11). This exploratory study suggests testing the method’s effectiveness in long-term child-robot interactions, with varied learning tasks over time.

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Acknowledgment

The Nazarbayev University Collaborative Research Program grants 091019CRP2107 and OPCRP2022002 provided funding for this work.

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Authors and Affiliations

  1. Department of Robotics and Mechatronics, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan

    Aida Zhanatkyzy, Zhansaule Telisheva, Arna Aimysheva & Anara Sandygulova

  2. Graduate School of Education, Nazarbayev University, Astana, Kazakhstan

    Aida Amirova & Nurziya Oralbayeva

Authors
  1. Aida Zhanatkyzy
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  2. Zhansaule Telisheva
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  3. Aida Amirova
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  4. Nurziya Oralbayeva
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  5. Arna Aimysheva
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  6. Anara Sandygulova
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Corresponding author

Correspondence to Anara Sandygulova .

Editor information

Editors and Affiliations

  1. University of Florence, Florence, Italy

    Filippo Cavallo

  2. Qatar University, Doha, Qatar

    John-John Cabibihan

  3. University of Florence, Florence, Italy

    Laura Fiorini

  4. University of Florence, Florence, Italy

    Alessandra Sorrentino

  5. Wichita State University, Wichita, KS, USA

    Hongsheng He

  6. Qingdao University, Qingdao, China

    Xiaorui Liu

  7. National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan

    Yoshio Matsumoto

  8. National University of Singapore, Singapore, Singapore

    Shuzhi Sam Ge

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Zhanatkyzy, A., Telisheva, Z., Amirova, A., Oralbayeva, N., Aimysheva, A., Sandygulova, A. (2022). Moveable Älıpbi: The Montessori Method for Robot-Assisted Alphabet Learning. In: Cavallo, F., et al. Social Robotics. ICSR 2022. Lecture Notes in Computer Science(), vol 13818. Springer, Cham. https://doi.org/10.1007/978-3-031-24670-8_11

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  • DOI: https://doi.org/10.1007/978-3-031-24670-8_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-24669-2

  • Online ISBN: 978-3-031-24670-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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