The study developed and standardized an Inventory for measuring Students’ Integration into University Academic Culture named Inventory for Students’ Integration into University Academic Culture (ISIUAC). The increase in dropout rates, substance use, cultism and other deviant behaviours in Nigerian universities makes it necessary for one to ask the extent to which university students are integrated into the university academic culture. This necessitates the development of standardized instrument for the assessment of students’ integration into university academic culture. The Study employed an instrumentation design in which a five point scale inventory were developed and standardized. An initial draft of 60 item instrument was developed and standardized. After corrections a 58 item instrument emerged and was administered to 500 University students. The data collected were subjected to factor analysis. The result from factor analysis showed that 27 items loaded well on three factors with minimum loading of 035.  The 27 items were administered to 1,000 students to establish norms. The norm for the entire instrument was 105.19, the norms of male and female students were 100.96 and 109.21 respectively.  Cronbach alpha statistics was used to establish the reliability of the instrument, its result shows an internal consistency of 0.926 for the 27 items. Hypotheses were tested using t-test statistics; the result shows that there is a significant difference between the norms of male and female students. The manual of the ISIUAC shows the administration and scoring procedure of the inventory and its psychometric properties. The instrument ISIUAC is recommended therefore for assessing students’ integration into the university academic culture.

This study aims to conduct validity and reliability analysis of Organizational Structure Scale-University version (OSS-U) that enables us to determine organizational structures of universities. The scale was developed based on the Axiomatic Theory by Hage, literature review and expert opinions. The sample of the study consisted of a total of 655 faculty members working at state universities in Turkey. Psychometric features of the scale were tested with three different models. The content validity of the suggested models was tested with Lawshe Analysis; the construct validity with Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) while the reliability was tested with Cronbach alpha which is a measure of internal consistency. As a result of the analyses conducted, all of these three models were determined to be valid and reliable with the relevant sample. It was also revealed that OSS-U can be used as model 1 in which nine dimensions (number of occupational specialties, professional training, professional activities, participation in decisions, hierarchy of authority, standardization, professional latitude, difference in rewards and difference in status) describe one single concept (University Structure), or model 2 in which four subscales (Complexity Scale, Centralization Scale, Formalization Scale and Stratification Scale) are independent pieces of an umbrella term (University Structure) or model 3, as a combination of these two models (model 1 + model 2), where combined subscales that have dimensions in itself describe a hypernym (University).

Studies have acknowledged computational thinking (CT) as an efficient approach for problem-solving particularly required in digital workplaces. This research aims to identify indicators for a holistic CT assessment instrument for undergraduate students. A three-round fuzzy Delphi study has been conducted to gain comprehensive opinions and consensus from undergraduate lecturers of computer science disciplines and experts from the information technology industry. In round 1, the experts judged a set of predefined indicators describing CT skills and attitudes identified from the literature, while rounds 2 and 3 focused on variables selection. The consensus was achieved on holistic CT, and the indicators are teamwork, communication, spiritual intelligence, generalization, problem-solving, algorithmic thinking, evaluation, abstraction, decomposition, and debugging. Results demonstrate the importance of attitudes in the process of solving a problem and suggest higher education institutions to consider holistic CT in preparing qualified future graduates. Many CT studies focused only on the skills of CT. This study outlines the assessment indicators that consider both CT skills and attitudes, particularly at the undergraduate level.

University attempts to respond to globalization to build international trust by conducting internationalization as the bridge of their selected strategies. The efforts needed to build international trust are promotion strategies. This study aims to elaborate the effective promotion strategies in Jenderal Soedirman University, Indonesia. The data were collected by some deep interviews, observation, and documentation. The result shows that the promotion strategies includes, first, the university’s direction to be recognized globally by a strong vision, international accreditation for its study programs, and being the center of special studies. Second, the university publicizes the university’s programs, activities, excellence, and uniqueness through printed or online media, foreign institutions, and individuals. Third, the university initiates international collaborations with foreign universities and institutions by building good interpersonal communication, forming teams for international collaborations, initiating activities to build trust among individuals, and getting involved in international events. Last, the university offers scholarships for foreign students to increase inbound students.

The purpose of the research was to identify whether the English language e-classes that are automated and delivered through the Smart Sender platform influence the students’ attendance and procrastination rates, their motivation, time management skills, cognitive processing speed, and satisfaction. The study used qualitative and quantitative methods to monitor students’ attendance and procrastination rates, motivation and engagement, time management skills, thinking speed, and satisfaction. The questionnaire on learning motivation, engagement, and competence, the time management skills test, the mental speed test, and the course satisfaction questionnaire were used to collect data. The focus group discussion questionnaire was used to obtain verbal feedback for the participants. The Smart Sender platform proved effective as an instructional tool for teaching the English Language to students majoring in Philology, International Business, and Law. The automated delivery of the English language e-classes was effective in addressing the issues of dropouts and procrastination in distance learning through automation of the lesson delivery based on the ‘push’ factor. It increased students’ motivation, improves time management skills, and satisfaction. The quantitative findings showed that the students experienced a positive change in attendance, motivation and learning engagement, time management skills, and thinking speed due to the intervention. The students perceived the automated delivery-based approach to language teaching positively. They reported that the delivery approach content met the participants’ expectations and needs. Focus group discussion revealed that the intervention changed their learning behaviour and strategies which were considered the improvements of the quality learning outcomes.

In this research, the influence of the Coronavirus disease (COVID-19) pandemic on 9th grade students’ mathematics achievement is analyzed through quantitative and qualitative methods. A posttest only with control group design was used to compare the mathematics marks of 9th grade students from the previous school year (before the pandemic, control group) and the current school year (during the pandemic, experimental group). Seventy-three students from a public high school in Spain attending class on alternate days participated in the study. Three focus group sessions were held with students, and five semi-structured interviews were conducted—two with teachers and three with students’ families. Results show statistically significant differences in students’ mathematics achievement, with students enrolled in 9th grade the previous (pre-pandemic) year outscoring their peers currently enrolled in 9th grade (during the pandemic) by 22.17%. An overall negative effect size of Hedge’s g = -1.11 was reported. Although significant statistical differences between groups were reported for both male and female students, the effect was 42.31% larger for male students (Hedge’s g = -1.11) than for females (Hedge’s g = -0.78). The qualitative information supported the quantitative results. Changes in educational settings, students’ lack of motivation, monotony, and students’ level of responsibility were qualitatively reported as factors that may explain this phenomenon. The main conclusion of this study is that the COVID-19 pandemic may be significantly and negatively affecting 9th grade students’ mathematics achievement.

Modern technology is necessary and important for improving the quality of education. While machine learning algorithms to support students remain limited. Thus, it is necessary to inspire educational scholars and educational technologists. This research therefore has three main targets: to educate the holistic context of rural education management, to study the relationship of continuing education at the upper secondary level, and to construct an appropriate education program prediction model for high school students in a rural school. The data for research is the academic achievement data of 1,859 students from Manchasuksa School at Mancha Khiri District, Khon Kaen Province, Thailand, during the academic year 2015-2020. Research tools are separated into 2 sections. The first section is a basic statistical analysis step, it composes of frequency analysis, percentage analysis, mean analysis, and standard deviation analysis. Another section is the data mining analysis phase, which consists of discretization technique, XGBoost classification technique (Decision Tree, Gradient Boosted Trees, and Random Forest), confusion matrix performance analysis, and cross-validation performance analysis. At the end, the research results found that the reasonable distribution level of student achievement consisted of four clusters classified by academic achievement. All four clusters were modeled on predicting academic achievement for the next generation of students. In addition, there are four success models in this research. For future research, the researcher aims to develop an application to facilitate instruction for learners by integrating prediction models into the mobile application to promote the utilization of modern technology.

This paper investigates the viewpoints and perspectives of 179 undergraduate students engaged in a co-creation project regarding their anticipated progress, exploring, simultaneously, the affecting factors. The students attended the physics course in the Department of Industrial Design and Production Engineering at the University of West Attica, Greece. The investigation is implemented through a questionnaire that appraises the students' co-creation expectations in association with collected demographic data via twenty-two close-ended questions (Q1-Q22). Several statistical data sets are presented, including descriptive and correlation statistics and principal component and exploratory factor analyses. The majority of the replies are provided by male participants in their first year of study, with an average age of between 18 and 19. The correlation coefficient between the questions ranges from -.04 to.73, with the maximum occurring between the questions Q19 and Q20. Factor analysis justified by KMO (.862) and Bartlett’s sphericity (1749.843, p= .000) tests indicates five principal components within the following factors determining the undergraduate co-creation activities: responsible behaviour, feedback, helping, tolerance, and personal interaction. The above findings may contribute to the implementation of students’ co-creation as they are valuable tools for the design and pre-requisites for a successful implementation.