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  1. AU="Liying Xia"
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  1. Artikel ; Online: A Proposed Taxonomy of Teaching Models in STEM Education

    Baichang Zhong / Xiaofan Liu / Liying Xia / Wang Sun

    SAGE Open, Vol

    Robotics as an Example

    2022  Band 12

    Abstract: Many countries and regions have reached a consensus to promote science, technology, engineering, and mathematics (STEM) education in the past decade. A body of studies have demonstrated that the design and organization of interdisciplinary teaching ... ...

    Abstract Many countries and regions have reached a consensus to promote science, technology, engineering, and mathematics (STEM) education in the past decade. A body of studies have demonstrated that the design and organization of interdisciplinary teaching activities are important for the effective implementation of STEM education. So far, however, little attention has been paid to the taxonomy of teaching models in STEM education. This paper aims to propose a taxonomy based on the dimensions of learning outcomes (i.e., product-oriented and knowledge-oriented) and teaching process (i.e., forward teaching model and reverse teaching model) in STEM education. Through the intersection of the above two dimensions, four teaching models in STEM education have emerged, including project-based learning (PBL), reverse engineering (RE), scientific inquiry (SI), and troubleshooting/debugging (T/D). In addition, four cases are introduced to explain how these four teaching models operate in STEM education. The implications of this work for future research are also discussed. It is promising that the study will be valuable to enrich the current research, and shed light on the theory and practice of STEM education.
    Schlagwörter History of scholarship and learning. The humanities ; AZ20-999 ; Social Sciences ; H
    Thema/Rubrik (Code) 370
    Sprache Englisch
    Erscheinungsdatum 2022-05-01T00:00:00Z
    Verlag SAGE Publishing
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  2. Artikel ; Online: Is There a Digital Divide Between Urban Students and Migrant Students in China?

    Baizhang Zhong / Fenghui Zhu / Liying Xia

    SAGE Open, Vol

    2021  Band 11

    Abstract: The digital divide is an important issue that has been addressed in the world for several decades. However, little attention has been paid to the special population that emerged in cities of developing countries: rural migrant workers. Previous studies ... ...

    Abstract The digital divide is an important issue that has been addressed in the world for several decades. However, little attention has been paid to the special population that emerged in cities of developing countries: rural migrant workers. Previous studies have shown that family background is a potential determinant of digital inequality among schoolchildren. The study aims to explore whether the disadvantaged conditions of rural migrant workers have an impact on their children (i.e., migrant students). A questionnaire survey and multivariate analysis of variance (MANOVA) were conducted to examine the digital divide in information and communication technology (ICT) access, ICT usage, and ICT skill between urban and migrant students. We draw upon 1,230 fifth and eighth grade students from six urban public schools in China. Results indicate that all the indicators of the digital divide are statistically non-significant between the two groups, and the predictor of parental education level is invalid to an extent. Additional analyses suggest that providing equal opportunities like Chinese government for disadvantaged migrant students to enroll in urban public schools would reduce the digital divide between migrant students and urban students.
    Schlagwörter History of scholarship and learning. The humanities ; AZ20-999 ; Social Sciences ; H
    Thema/Rubrik (Code) 028
    Sprache Englisch
    Erscheinungsdatum 2021-05-01T00:00:00Z
    Verlag SAGE Publishing
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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