The purpose of this descriptive study was to apply 2nd order confirmatory factor analysis (CFA) and structural relationship models to identify the digital competency components essential to undergraduate students in Thai higher education institutions. The sample comprised 1,126 specialists in Information Technology, Computer Technology, Computer Education, Computer Science, and Computer Engineering working in public higher education instructions throughout the country. The selection was the result of multi-stage random sampling from 76 public higher education instructions that offer undergraduate education. The instrument was a questionnaire form on essential digital competency components for undergraduate students in higher education institutions. The question items employed a 7-point Likert scale and showed Cronbach's alpha values for the content validity and reliability at a range of.93-.97 per domain and .87-.99 per component. The data were analyzed using descriptive statistics for general data and 2nd Order CFA analysis. The findings revealed that from 24 observed variables, there were 7 competency components.: 1) Fundamental of digital ; 2) Accessing digital information; 3) Using digital information; 4) Creating digital information and media; 5) Communicating digital information; 6) Managing digital information; and 7) Evaluating digital information. The discovery from this study was substantially constructive for Thai higher education institutions as it could be used to design an essential digital competency framework of the 21st century.
The objective of this research was to develop a Problem-Based Learning (PBL) Model which used a cloud-based constructivist learning environment to enhance Thai undergraduate creative thinking and digital media skills. Initially using a mixed-methods approach, a five-step model was conceptualized. Thereafter, a panel of five academic experts gave input into the model’s design from which the model was expanded to include six related learning environments. The instrument used in the research was a problem-based assessment form. Data collection was carried out utilizing group chats and analyzed using descriptive statistics including the mean and standard deviation. The results of the study revealed that the initial model contained five steps including (1) <em>problem identification</em>, (2), <em>problem analysis</em>, (3) <em>research</em>, (4) <em>presentations</em>, and (5) <em>summary and evaluation</em>, which is integrated into the model’s additional six learning environment elements. These six learning environments were (1) <em>problem-based</em>, (2) <em>resources,</em> (3) <em>cognitive tools</em>, (4) <em>collaboration</em>, (5) <em>scaffolding</em>, and finally, (6) <em>coaching</em>. When applying the proposed model and related environments, there was a consensus from the experts that the model had excellent suitability and can be used as a model for teaching and learning at the bachelor's degree level.
The goals of this research were to analyse and develop a Hierarchical Linear Model (HLM) of appropriate Internet use behaviour of Thai student teachers. The sample group consisted of 1,800 student teachers studying for their bachelor’s degree at 30 Thai government educational institutions. The research tool used was a questionnaire with content validity and reliability at 0.83 – 0.92. Mean (¯(x )), standard deviation (S.D.), and HLM were used to analyse the data. The findings revealed that appropriate Internet use behaviour in Thai student teachers was at a high level. Additionally, the HLM for appropriate Internet use behaviour for Thai student teachers consisted of two levels of predictor variables. The first level was the student teacher level, in which six of the hypothesized nine predictor variables had statistical significance. Five had a positive effect, which included ability, affect, family situation, gender, and GPA, while one variable had a negative effect, which was income. The second level was the institutional level, which contained two predictor variables with statistical significance, friends and educational institution situation, with both having positive effects. Friends had a direct effect on behaviour at the educational institution level, while educational institution situation had an effect through ability.
The research used a hierarchical linear model to develop a model to study the variables of appropriate Internet use of 2,400 Thai high school students from 48 high schools. Furthermore, the groups were divided into one group of 1,200 students in science related programs, while the second group of 1,200 students were in a non-science related program. The data collection instrument was a reliability questionnaire which was determined to range between 0.75-0.97. Data were analysed using statistical averages, standard deviation, and analysis of hierarchical linear models (HLM). The research found that Thai high school students have appropriate Internet use behaviour at a very appropriate level, while the HLM of appropriate Internet use behaviour of students contained two predictive variables at both the student level and school level. These included the four student predictive variables of ability, characteristic, family, and student grade point average (GPA). At the school level in the HLM, there were two predictor variables including friends and schools, which had a direct influence and an indirect influence, respectively. There were also six capacity variables having both positive influence and statistical significance.
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