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Assessing creative problem-solving competencies in primary school educators: A confirmatory factor analysis approach
(2025-01-01)
Charoentham, Mai
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Kantathanawat, Thiyaporn
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Pimdee, Paitoon
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Teerasoonthontai, Krittameth
This study aimed to examine and analyze the second-order confirmatory factor structure of creative problem-solving for primary school teachers. The sample consisted of 150 teachers and educational supervisors from the Office of the Basic Education Commission, selected through multi-stage random sampling. The data collection tool was a creative problem-solving questionnaire evaluated for item-objective congruence (IOC) values between 0.60 and 1.00, with discriminant power ranging from 0.68 to 0.88 and reliability coefficients between 0.77 and 0.92. Data were analyzed using means, standard deviations, and second-order confirmatory factor analysis (CFA). The results revealed that teachers and educational supervisors had a high level of agreement on creative problem-solving in general and for each component. The second-order CFA creative problem-solving model demonstrated a good fit with the empirical data and consisted of five components and 15 indicators. The components, ranked by weight from highest to lowest, were Truth Discovery (TD), reflecting the emphasis teachers place on understanding the nature and context of problems. This was followed by Knowledge Creation (KC), which highlights the importance of applying knowledge to real-world challenges, and Problem Identification (PI). Idea Generation (IG) and Solution Discovery (SD) received slightly lower scores, though still within the high range. This suggests that while teachers value these components, they may require further development in fostering innovation and evaluating solutions critically.
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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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Enhancing Project-based Learning (PBL) in Cloud Education Models for Word Software Courses
(2023-01-01)
Tang, Shi
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Petsangsri, Sirirat
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Ratana-Olarn, Thanin
This research aimed to conduct a comprehensive needs analysis to gauge the needs of both students and educators concerning Project-Based Learning (PBL) in the context of a Cloud Education Model for Word Software Courses. The primary objectives encompassed the assessment of students' receptiveness towards PBL adoption and the evaluation of instructors' levels of enthusiasm for embracing the PBL instructional model. The study emphasized establishing a synergistic understanding between educators and learners regarding the seamless integration of PBL within the Cloud Education framework. Significantly, the research sought to innovatively develop and put together PBL within the Cloud Education milieu, discerning disparities in software proficiency and computational thinking between students exposed to PBL through Cloud Education and their counterparts experiencing traditional instructional methodologies.
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Development of Project-Based Learning (PBL) in Cloud Education Model to Enhance the Application Ability and Computational Thinking for Undergraduate Students
(2023-01-01)
Tang, Shi
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Ratana-Olarn, Thanin
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Petsangsri, Sirirat
This research investigated the Development of Project-Based Learning (PBL) in Cloud Education Model to Enhance the Application Ability and Computational Thinking Undergraduate Students with the core objectives, to study the needs of students and teachers towards the teaching approach based on Project-Based Learning (PBL) in Cloud Education in Word Software Application, to design Project-Based Learning (PBL) in Cloud Education model 3, and to compare Word Software Application ability and computational thinking between students who learn in Project-Based Learning (PBL) in Cloud Education model and students who learn in Traditional Teaching Method. Qualitative and Quantitative both methods were used in the current study. As the research population, from a pool of 165 students, a total of 100 students majoring in accounting from the 2022 cohort of Nanning University was randomly selected along with five lecturers from the "College Computer Foundation" course. Questionnaire was used for collecting data from students while a focus group interview was adopted for collecting in-depth data from focus group teachers. The result of study brought to surface that students expect a classroom atmosphere with higher participation, more active classroom, and stronger interactivity thereby promoting course learning and achieving course goals. The revised teaching model emphasizes active learning, practical application, and the cultivation of computational thinking, aiming to provide a richer and more effective educational experience. The revision process involves multiple steps such as project design, group task allocation, plan formulation, exploration and cooperation, work production, achievement exchange, summary and evaluation, and the use of cloud education platforms to support teaching and learning activities. This process fully reflects the importance of continuously optimizing and improving educational models to adapt to the constantly changing learning environment and needs.
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An Integrated Design-Based Learning Management Model to Promote Thai Undergraduate Computational Thinking Skills and Programming Proficiency
(2022-01-01)
Prommun, Phattharapol
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Kantathanawat, Thiyaporn
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Pimdee, Paitoon
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Sukkamart, Thanate
The study applied concepts of computational thinking, waterfall programming, and design-based learning management (DBLM) combined with a participatory action research (PAR) methodology to obtain an integrated learning management model (LMM) designed as a base to promote computational thinking skills (CTS) and programming proficiency. The study used three groups consisting of 21 volunteer computer education undergraduate students, three teachers, and three computer studies graduates from the Computer Studies Department of the Faculty of Education at Dhonburi Rajabhat University in Thailand. To verify the model, nine educational experts conducted an assessment of the proposed model, and determined that the evaluation standards were overall at a high level (x= 4.23, SD = 0.44), with the experts feeling that the integration of the DBLM computational thinking framework, the Waterfall programming conceptual framework, and the PAR meeting the study's stated objectives at the highest level (x= 4.56, SD = 0.53). The proposed model is best undertaken in five week sessions of five hours each using five exercises per week. Activity effectiveness is best measured by taking notes, worksheets, and practicing the learned skills. In conducting this research, there may be obstacles from learners who may withdraw during research due to personal activities or becoming discouraged in learning activities based on a five-week schedule, preventing them from participating every time.
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A Game to Promote Safe Use of Online Media with Mixed Reality Technology
(2022-01-01)
Tannitisataporn, Ganokpan
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Nuatongdee, Chanoknet
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Jamsri, Pornsuree
Currently, online media is widely used and accessible to all ages. Careless use of cooperativeness in online media, however, can allow vulnerabilities that lawbreakers exploit. Learning as much as possible about media also requires users to be engaged and not bored. So, to avoid boring players while learning we offer a mixed reality (MR) technology stimulating game named Catcher. Catcher is a story game whereby players investigate accurate facts from varied evidence in 5 different game levels. By giving a hint of the non-player character (NPC) at the story’s beginning, the player finds clues to add more information toward the conclusion of the complete story. Testing Catcher showed the game can improve systematic thinking skills by 40% and media learning by 64%. By choosing MR technology players can connect directly with the game system. This allows them to effectively learn while having safe fun without being bored.
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Protobot: An Educational Game for Algorithmic Thinking
(2022-01-01)
Lertlapnon, Thanachote
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Lueangrungudom, Naruebes
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Vittayakorn, Sirion
Algorithm has been heavily used to provide a comfort life for us: from finding the best route in Google map to biometrics authentication on your phone. The significant of algorithm defines Computational thinking (CT) as one of the 21st Century skills. Although CT has been integrated into the education in the past years, many students still struggle with CT concept due to the complication of the topic and limited learning methods provided in school environment. To provide alternative learning approach for algorithmic thinking, we propose a game-base learning system called Protobot. Protobot requires students to apply their CT knowledge, especially the algorithmic thinking to solve problems in the gameplay. The experimental results demonstrate that Protobot fosters the algorithmic thinking skill of the players as well as provides the amusement during the gameplay.

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