Songkram, Nutthakorn

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Unlocking the power of robots: enhancing computational thinking through innovative teaching methods
(2024-01-01)
Songkram, Noawanit
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Upapong, Supattraporn
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Ku, Heng Yu
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Aulpaijidkul, Narongpon
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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.
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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
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Aulpaijidkul, Narongpon
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Upapong, Supattraporn
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Osuwanan, Hathaiphat
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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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University lecturers’ perceptions on digital transformation and knowledge management for teaching innovation
(2026-01-01)
Songkram, Noawanit
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Shidiq, Galih Albarra
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Winarto
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Taweejamsup, Suphasit
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Songkram, Nutthakorn
This study used the qualitative design to investigate the perceptions of 33 university lecturers through semi-structured interviews and observations conducted after a professional development program in Indonesia. Thematic analysis discovered three interconnected dimensions shaping innovation in teaching: (1) supportive institutional environments that promote responsible behaviour, teamwork, and collaboration; (2) acquisition and application of new knowledge through digital tools and collegial learning; and (3) integration of technological innovation to improve teaching efficiency, creativity, and multidisciplinary engagement. The findings indicate that effective knowledge management enhances lecturers’ ability to adapt digital pedagogies, share expertise, and sustain innovation practices. The implications of this study include developing professional learning communities, improving digital literacy programs, and aligning institutional policies to support innovation in teaching. These insights extend global understanding of how universities in emerging contexts can strategically integrate technology and knowledge management to advance educational innovation.
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Potential of ChatGPT in academic research: exploring innovative thinking skills
(2025-01-01)
Songkram, Noawanit
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Chootongchai, Suparoek
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Keereerat, Chayakarn
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Songkram, Nutthakorn
Academics, scholars, and learners are increasingly turning to AI-based language models like ChatGPT for a variety of academic and non-academic applications including essay writing, speech creation, literature summarizing, and idea production. However, the use of ChatGPT in academic research has sparked debate and raised concerns about its influence on research and publishing. By offering an actual scenario and suggestions, this study intends to shed light on the practical implementation of ChatGPT in academic research. The dataset for this study includes 3,860 students from Thailand's basic and secondary school levels. The survey data gathered focuses on investigating innovative thinking skills. The findings suggest that ChatGPT might be a useful technique for generating first ideas in academic studies. However, it is crucial for researchers to exercise caution as they may encounter certain challenges during the process. As a result, while using ChatGPT in academic research, researchers must be aware of these issues and make educated judgments appropriately. Given the possible uses and ramifications of ChatGPT, the academic community must develop detailed protocols governing its usage in research and subsequent publishing. These rules will ensure the proper and ethical use of ChatGPT in the academic setting.

Songkram, Nutthakorn

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