This study reviews 60 papers using a Likert scale and published between 2012 – 2021. Screening for literature review uses the PRISMA method. The data analysis technique was carried out through data extraction, then synthesized in a structured manner using the narrative method. To achieve credible research results at the stage of the data collection and data analysis process, a group discussion forum (FGD) was conducted. The findings show that only 10% of studies use a measurement scale with an even answer choice category (4, 6, 8, or 10 choices). In general, (90%) of research uses a measurement instrument that involves a Likert scale with odd response choices (5, 7, 9, or 11) and the most popular researchers use a Likert scale with a total response of 5 points. The use of a rating scale with an odd number of responses of more than five points (especially on a seven-point scale) is the most effective in terms of reliability and validity coefficients, but if the researcher wants to direct respondents to one side, then a scale with an even number of responses (six points) is possible. more suitable. The presence of response bias and central tendency bias can affect the validity and reliability of the use of the Likert scale instrument.

This research aims to examine the effect of coding education on the analytical thinking skills of gifted students. The participants are 18 students, 11 to 12 years old. An embedded experimental mixed design was used in the research. The data collection was carried out with the Analytical Thinking Skill Scale to determine the difference in the analytical thinking skills of the study group before and after the coding training; the Analytical Thinking Skill Observation Form to determine the analytical thinking skill levels during the implementation process; and the semi-structured interview form to get their opinions on the coding training. The data were analyzed with a pre-test-post-test quasi-experimental design, descriptive analysis, and content analysis. The results show that coding education developed the participants' analytical thinking skills. The difference in the analytical thinking skills of the study group was not statistically significant in terms of gender. According to the students' views on the coding education application process, there was an improvement in the sub-dimensions of sorting, classification, comparison, and evaluation in analytical thinking skills; coding education developed problem-solving and thinking skills, was useful, encouraged students to choose a profession, and was entertaining, as well as negative opinions such as being difficult, boring, and requiring a lack of time.

The purpose of the study is to explore the ways of involving university stakeholders specifically in updating educational services. It combined exploratory and observational research methods which relied on qualitative or quantitative data gathered through the researcher-designed and validated tools which were the empirical and methodological contributions to the previous research. The five most frequent choices that might encourage the stakeholders to donate or invest in an educational institution were as follows: a portfolio of the use of donations, investments, or grants, having a stake in the educational services of more than 7%, having access to budgeting and cost reporting, having a share in the institutions’ profit and being one of the decision-makers. The factors that discouraged investors from investing in education were as follows: distrust of the activity of the educational institutions in terms of addressing the stakeholders’ needs or interests, lack of engagement or cooperation, institutional and government-imposed barriers between them and the institutions, uncertainty concerning the efficiency of the institutions and inefficient use of the resources by the institutions. The initiative was complimentarily perceived by stakeholders in terms of collaboration and investment opportunities. It was also found beneficial by the sampled students.

The purpose of this study was to classify the active job behaviors of Generation Z (Gen Z, born after 1995) elementary school teachers and investigate relevant variables that significantly affect such a classification. A total of 375 Gen Z elementary school teachers who passed the National Elementary Teacher Qualification Test and had worked in elementary schools in South Korea participated in this study. The data collected identified the types of active job behaviors among Gen Z elementary school teachers using cross-tabulation through Latent Profile Analysis (LPA). A multinomial logistic regression analysis was conducted to identify the predictors that influence the types of active job behaviors of Gen Z elementary school teachers. The results were as follows: First, there are four types of active job behaviors of Gen Z elementary school teachers: Ideal, relational, non-participatory, and passive job performance types. Second, teacher efficacy, learning agility, organizational commitment, and principals’ transformational leadership influenced the types of active job behaviors of Gen Z elementary school teachers. The results offer insights into the human resource management of Gen Z elementary school teachers and have significant implications for improving the active job behavior of Gen Z elementary school teachers.