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Author: search.filters.author.Aulpaijidkul, Narongpon

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    Bridging the digital divide: tailoring learning platforms for the elderly based on learning styles and digital skills
    (2026-01-01)
    Songkram, Noawanit
    ;
    Aulpaijidkul, Narongpon
    ;
    Upapong, Supattraporn
    ;
    Osuwanan, Hathaiphat
    ;
    Thamsuwan, Pattarporn
    This study examines the relationship between learning styles and digital skills among older adults in Thailand to offer insights for the development of customized online learning platforms. A study was conducted on 706 participants aged between 60 and 78 years to evaluate their digital skills in four areas and learning styles according to Kolb’s model. Confirmatory factor analysis was performed to validate the four-factor model of digital skills. MANOVA results demonstrated significant variations in digital skills among learning styles, with convergers displaying superior proficiency in most areas. A matrix was created to outline the recommended functions of a learning platform with the objective of aligning pedagogical approaches with individual learning preferences and specific digital competencies. The results emphasized the significance of tailored methods in educating older adults on digital literacy and offered a framework for creating digital learning environments that are more comprehensive and efficient. This study intended to address the digital divide and improve the quality of life of older adults in a world that is increasingly becoming digital. Lastly, it posed implications for educational policy and practice.
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    Unlocking the power of robots: enhancing computational thinking through innovative teaching methods
    (2024-01-01)
    Songkram, Noawanit
    ;
    Upapong, Supattraporn
    ;
    Ku, Heng Yu
    ;
    Aulpaijidkul, Narongpon
    ;
    Chattunyakit, Sarun
    This research proposes the integration of robotic education and scenario-based learning (SBL) paradigm for teaching computational thinking (CT) to enhance the computational abilities of primary school students, based on digital innovation and a teaching assistant robot acceptance model. The sample group consisted of 532 primary school teachers and 33 first-grade students in Thailand. The study demonstrated that a causal model was consistent with the empirical data (Chi-square = 216.06, df = 262, p = 0.000, GFI = 0.98, AGFI = 0.95, RMR = 0.018, RMSEA = 0.000). The result found that “Facilitating Conditions’ have a positive effect on “Perceived Usefulness’ (β = 0.19), “Subjective Norm Conformance” influences “Perceived Usefulness’ (β = 0.49), “Perceived Ease of Use” influences “Perceived Usefulness’ (β = 0.26), “Perceived Usefulness’ influenced “Attitudes Toward Technology” (β = 0.12), “Attitudes Toward Technology” influenced “Behavioral Intention” (β = 0.88), and “The Facilitating Conditions’ had an inverse effect on “Behavioral Intention” (β = −0.16). Moreover, teaching assistant robots for primary school students were developed, which consist of: (1) characteristics and components of teaching assistant robots, namely the central processing unit, driving system, wheels, recognition part, display and sound section, power supply, etc. and (2) seven scenario-based learning activities designed to guide teachers, instructors, and educators to effectively implement a robot aimed at improving young students’ computational thinking abilities.