The Attraction-Selection-Attrition (ASA) model is a prominent framework for supporting employee retention, stating that organisations attract, select, and retain people who share their values. However, the ASA model only extends to the end of the recruitment stage and lacks clarity on how to assist newcomers in the assimilation process when they first join the organisation. This research proposed a refinement of the ASA paradigm by incorporating the assimilation process of new hires into the new school culture and environment. This study employed a qualitative research approach by interviewing ten participants about the retention process from high teacher retention international schools in Malaysia. Thematic data analysis revealed a new paradigm, 'Attraction-Selection-Onboarding-Retention (ASOR), ' designed to increase teacher retention in international schools. The ASOR model could assist school administrators and human resource managers working in a related setting in properly engaging the workforce to increase teacher retention. This would benefit school sustainability, performance and the local community's economy.

The world eagerly anticipates advancements in AI technologies, with substantial ongoing research on the potential AI applications in the domain of education. The study aims to analyse publications about the possibilities of artificial intelligence (AI) within higher education, emphasising their bibliometric properties. The data was collected from the Scopus database, uncovering 775 publications on the subject of study from 2000 to 2022, using various keywords. Upon analysis, it was found that the frequency of publications in the study area has risen from 3 in 2000 to 314 in 2022. China and the United States emerged as the most influential countries regarding publications in this area. The findings revealed that “Education and Information Technologies” and the “International Journal of Emerging Technologies in Learning” were the most frequently published journals. “S. Slade” and “P. Prinsloo” received the most citations, making them highly effective researchers. The co-authorship network primarily comprised the United States, Saudi Arabia, the United Kingdom, and China. The emerging themes included machine learning, convolutional neural networks, curriculum, and higher education systems are co-occurred with AI. The continuous expansion of potential AI technologies in higher education calls for increased global collaboration based on shared democratic principles, reaping mutual advantages.

Given the insufficient involvement of business investments in adult education, this study focused on the factors that motivate managers and entrepreneurs to invest in continuing education. For this purpose, we conducted a systematic literature review of studies referenced in Scopus and Web of Science since 2015. The factors for training were classified into four levels: personal, organizational, industry-related, and national. The results indicated that the inside firm-related determinants are the most studied and essential. A consensus emerged in the relevant literature on the positive impact of a supportive workplace culture, a learning orientation, formalized human resource development practices, and employee voice. The long-term orientation of managers and the perception of employees’ flexibility and adaptability to change also play a role. The study highlights the increasing pressure from regulations and market competition, as well as the (in)capability of universities to provide training tailored to the specific needs of companies. Although institutional factors appeared to predominate, economic considerations also influence training decisions; the latter means that the two underlying theories – institutional theory and human capital theory – complement each other when explaining employers' incentives to invest in training.

Critical thinking is a skill that enables individuals to keep pace with changes and enhances crucial competencies for contemporary competitiveness. Many researchers have studied learning management approaches to develop students' critical thinking, resulting in a substantial body of knowledge but lacking clear systematic summaries. The researchers aimed to (a) examine the effect sizes and research characteristics influencing students' critical thinking, and (b) compare the effect sizes of learning management approaches after adjusting with propensity score matching from 108 graduate research published between 2002 and 2021. Data were collected using research characteristics recording forms and research quality assessment questionnaires. Effect sizes were calculated using Glass's method and analyzed through random effect, fixed effect, and regression meta-analysis. Findings revealed that (a) research on developing learning management approaches influences students' critical thinking at a high level (d ̅ = 1.669), with nine research characteristics, including the field of publication, courses, total duration, teacher learning process, learning media, measurement and evaluation, research design, research statistics, and research quality, statistically significantly influencing students' critical thinking, and (b) after adjustment, inquiry-based learning significantly influences students' critical thinking. Recommendations for developing students' critical thinking include learning activities that encourage problem exploration, expanding thinking through collaborative analysis, and applying diverse media and activity sheets tailored to context suitability.
 

Analytical thinking is crucial for developing problem-solving, decision-making, and higher-order thinking skills. Many researchers have consistently developed learning management models to enhance students' analytical thinking, resulting in extensive knowledge but lacking clear systematic summaries. This study aims to: (a) explore the effect sizes and research characteristics influencing students' analytical thinking, and (b) compare the effect sizes of learning management models after adjusting for propensity score matching. In exploring 131 graduate research papers published between 2002 and 2021, the research utilized forms for recording research characteristics and questionnaires for assessing research quality for data collection. Effect sizes were calculated using Glass's method, while data analysis employed random effects, fixed effects, and regression meta-analysis methods. The findings indicate that (a) research on learning management models significantly impacts students' analytical thinking at a high level (d̅ = 1.428). Seven research characteristics, including year of publication, field of research, level, duration per plan, learning management process, measurement and evaluation, and research quality, statistically influence students' analytical thinking, and (b) after propensity score matching, learning through techniques such as KWL, KWL-plus, Six Thinking Hats, 4MAT, and Mind Mapping had the highest influence on students' analytical thinking. Recommendations for developing students' analytical thinking involve creating a learning management process that fosters understanding, systematic practical training, expanding thinking through collaborative exchanges, and assessments using learning materials and tests to stimulate increased analytical thinking.