A Case Study Of Knowledge Management Factors And Information Technology In Government Funded Universities In Thailand

The objective of this research is to study and analyze the components of knowledge management, principles, concept and theory on the learning format of knowledge management in government funded universities in Thailand in order to determine the knowledge management factors through an information technology system. From the analysis of the knowledge management factors, it is determined that essential knowledge management factors have 11 components and that the components for information technology system have 12 components. Regarding the opinion of evaluation experts, it is concluded that the components analyzed can be divided into preliminary and necessary components of the knowledge management for government funded universities of Thailand

Increasing Programming Self-Efficacy (PSE) Through a Problem-Based Gamification Digital Learning Ecosystem (DLE) Model

The researchers initially undertook a systematic literature review concerning problem-based learning (PBL), gamification, digital learning ecosystems (DLE), and programming self-efficacy (PSE). Using recent studies and papers from Google Scholar, a preliminary gamified and DLE model was proposed to help Thai students PSE. Further analysis was conducted on gamification mechanics, dynamics, and aesthetics (MDA). After an assessment by nine educational experts using four educational assessment tools from the Joint Committee on Standards for Educational Evaluation (JCSEE) of the proposed seven-step A3S3R (advise, assign, analyze, search, synthesize, summarize, and report) DLE Management Model, the model’s suitability was judged to be ‘very high’ (mean = 4.40, SD = 0.59). Consequently, the development of this learning management model will result in learners recognizing their abilities better in programming and having better programming skills. It can also potentially increase students’ critical and analytical thinking skills and computational thinking and allow them to apply new knowledge or skills to new situations. Finally, researchers can develop new practical learning styles for use in teaching and learning

Development of an Online Active Learning Model Using the Theory of Multiple Intelligence to Encourage Thai Undergraduate Student Analytical Thinking Skills

This research aim was to create an online active learning (OAL) model using Multiple Intelligence Theory (MIT) to promote Thai undergraduate analytical thinking skills (ATS). Eight experts assisted with their expertise in the model’s development and five for the model’s final assessment. The research tools used consisted of an interview form and a model assessment form. The results showed that the PPICE learning model consisted of nine elements and five steps. The five steps were preparation and problem determination (Step 1), problem analysis (Step 2), study and collect relevant information to practice thinking (Step 3), conclusion and presentations (Step 4), lesson summary and evaluation (Step 5). The expert's assessment of the PPICE Model revealed that overall the model was at its 'best' level (mean = 4.63, SD = .048). Moreover, the experts judged the model's nine components as the 'best' (mean = 4.74, SD = 0.38), with measurement and evaluation second (mean = 4.70, SD = 0.45), and teaching and learning activity processes third (mean = 4.66, SD = 0.48)

A blended learning model with IoT-based technology

In 2021, the COVID-19 pandemic is still not over. Thailand is the one that is facing the second wave of new coronavirus. Schools and universities were closed, and faculties need to mostly teach with Online pedagogy, including the graduate students' courses. This study proposes to focus on the Ubiquitous area of the Blended Learning model with IoT-based to solve a problem of graduate students and their advisors by the qualitative focus-group technique. The mobile application draft was synthesized and designed to track and monitor graduate students' research activities on smartphones by built-in sensors. They should stay active along while researching the advisor’s assignments on their smartphone. Non-active periods are implied when several behaviors are detected. Virtualize dashboards are processed to report the total active learning period of students for the advisor's evaluation.Moreover, students can continually monitor their self-efficacy to improve the online learning process. Besides, this study proposes to confirm the model’s quality by twelve experts with the questionnaire. The results show average scores of Propriety, Utility, Feasibility, and Accuracy standard are 4.32, 4.41, 4.37, and 4.21, respectively. Therefore, the Blended Learning model's overall qualities with IoT-based smartphones are extremely high and proper to implement.</p

Blended Learning Model with IoT-based by Smartphone

In 2021, the COVID-19 pandemic is still not over. Thailand is the one that is facing the second wave of new coronavirus. Schools and universities were closed, and faculties need to mostly teach with Online pedagogy, including the graduate students' courses. This study proposes to focus on the Ubiquitous area of the Blended Learning model with IoT-based to solve a problem of graduate students and their advisors by the qualitative focus-group technique. The mobile application draft was synthesized and designed to track and monitor graduate students' research activities on smartphones by built-in sensors. They should stay active along while researching the advisor’s assignments on their smartphone. Non-active periods are implied when several behaviors are detected. Virtualize dashboards are processed to report the total active learning period of students for the advisor's evaluation.Moreover, students can continually monitor their self-efficacy to improve the online learning process. Besides, this study proposes to confirm the model’s quality by twelve experts with the questionnaire. The results show average scores of Propriety, Utility, Feasibility, and Accuracy standard are 4.32, 4.41, 4.37, and 4.21, respectively. Therefore, the Blended Learning model's overall qualities with IoT-based smartphones are extremely high and proper to implement

A Thai Junior High School Students’ 21st Century Information Literacy, Media Literacy, and ICT Literacy Skills Factor Analysis

As Thailand moves through the 21st Century, the education system and resultant labour force must be prepared for the rapid changes in Thailand’s society, culture, politics, economy, and technologies. Previously, the 21st century framework has identified crucial elements to their future success as information literacy, media literacy, and information and communication technology (ICT) literacy skills. Given this priority, by use of multistage clustering sampling, 600 Thai junior high school students were selected, from which a five-level, 73-item Likert type agreement scale questionnaire was used to collect data from October 2017 to December 2017. The analysis of the student’s skills in information literacy, media literacy, and ICT literacy was conducted with the use of SPSS Version 24 and mean (¯(x )), standard deviation (S.D.), the Kaiser-Meyer-Olkin (KMO) test, and Bartlett's test of sphericity for analysis. Furthermore, a second-order confirmatory factor analysis was undertaken in which AMOS Version 24 software was used. Based on the second order CFA, it was found that the Information, Media and Technology Skills (IMTS) model was composed of three components that corresponded to the empirical data, with the most important element being ICT literacy, followed by media literacy, and finally, information literacy