Art is one of the most powerful ways of expressing an individual's internal state, expectations and needs with an aesthetic attitude. Different materials can be used during the expression process including colour, line, sound, movement, word, object and so on. Although the materials used in these branches of art are different from each other, the path followed in the application process and the final results are the same “to reveal an aesthetic product”. In order for an artistic practice to mature and reach the beautiful one, the practitioner must have the art education discipline and acquire certain knowledge, skills and understanding of the art field concerned. The art of painting, which is one of the plastic arts, provides the ability to search for beauty through lines and colours on two dimensional surfaces, to create compositions and express the individual's self with this composition, also has its own beauty value criteria. From this point of view, it was aimed to determine the opinions of the prospective teachers studying in the Department of Painting Education in the study about the beauty criteria that should be in the picture. In this study, survey method which is one of the quantitative research methods was preferred. As a data collection tool, a five - point Likert - type scale was developed by the researchers, and 25 items were used. 110 prospective teachers from various grades participated in the study. The results of the research showed that the prospective teachers greatly contributed to the beauty criteria that should be in the picture.

This study examined the effect of Yunnan’s ethnic minority college students’ acculturation on their academic achievement under the risk of the Matthew effect. Additionally, the role played by learning motivation in the relationship between ethnic minority college students’ acculturation and academic achievement was explored. A total of 403 valid questionnaires were collected from four areas in Yunnan province, China. Consequently, the Acculturation Scale, Academic Achievement Scale, and Learning Motivation Scale were used for measurement materials. These items of scales were evaluated on a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). SPSS (statistical package for the social sciences) and AMOS (analysis of a moment structures) softwares were used for data analyses. In addition, items were analyzed through item analysis, confirmatory factor analysis, reliability analysis and regression analysis. These results indicated that ethnic minority college students with low acculturation and learning motivation or high acculturation and low learning motivation can become objects of the Matthew effect. However, this study also observed that in certain students, high acculturation and high learning motivation can prevent the Matthew effect. Thus, high acculturation is crucial for improving academic achievement in ethnic minority college students. A level of high learning motivation is a powerful moderator promoting the academic achievement of students with high acculturation.

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 analyzed the involvement of teachers, parents, and school committees in improving scientific attitudes in science learning using Rasch model analysis. A survey method was used in this quantitative study. Participants in the study were selected using a purposive sample of 174 teachers, parents, and school committees in Sleman and Kebumen Regencies, Indonesia. A questionnaire was used in data collection to determine the involvement of teachers, parents, and school committees in improving scientific attitudes toward science learning. The questionnaires were completed using a Likert scale of 1-4, and the data were then analyzed using the Rasch model. The result showed that all participants were the average logit items (+1.03 logit). The reliability was 0.89, indicating a positive response to improving students' scientific attitudes. The results of the Rasch model analysis suggested that the involvement of parents, teachers, and school committees in improving scientific attitudes differed according to their roles. Each instrument element was analyzed in more detail in the Rasch model. Participants' roles were reflected in the specific involvements of teachers in learning, parents at home with children, and school committees participating in school policy-making.

Social identity is an important social determinant of student outcomes such as mental health and well-being. Currently, no validated social identity measures exist for adolescents in secondary school settings. A new ‘Adolescent Social Identity’ measure was developed by adapting two social identity dimensions from a validated reputation enhancement scale. The Social Identity Measure comprises two scales of 10 items each to measure how adolescents think their peers view them (e.g., reputational status) in terms of their conforming and nonconforming behaviour (Self-perception of Public Self) and how adolescents would ideally like to be viewed (Ideal Public Self) by peers. Exploratory and confirmatory factor analyses were conducted along with assessments of reliability, validity, and measurement invariance. Conforming and Nonconforming subscales for both scales were shown to be reliable, valid, and invariant across age and gender groupings. There were significant but small differences in the latent means for gender.

Educational researchers, as well as researchers in other disciplines, often work with ordinal data, such as Likert item responses and test item scores. Critical questions arise when researchers attempt to implement statistical models to analyse ordinal data, given that many statistical techniques assume the data analysed to be continuous. Could ordinal data be treated as continuous data, that is, assuming the ordinal data to be continuous and then applying statistical techniques as if analysing continuous data? Why and why not? Focusing on structural equation models (SEMs), particularly confirmatory factor analysis (CFA), this article discusses an ongoing debate on the treatment of ordinal data and reports a short review on the practices of conducting and reporting SEMs, in the context of mathematics education research. The author reviewed 70 publications in mathematics education research that reported a study involving SEMs to analyse ordinal data, but less than half discussed how data were treated or guided readers through the analysis; it is therefore harder to repeat such an analysis and evaluate the results. This article invites methodological discussions on SEMs with ordinal variables in the practices of educational research. Subsequently, a standard for reporting SEMs with ordinal data is proposed, followed by an example. This standard contributes to educational research by enabling researchers (self and others) to evaluate SEMs reported. The example demonstrates, using real-life research data, how two different approaches for analysing ordinal data (as continuous or as a product of discretisation from some continuous distributions) can lead to results that disagree.