These days, many schools are reviewing their curricula, and Science, Technology, Engineering, Arts, and Mathematics (STEAM) education is one area where these changes are being applied. Because STEAM education integrates five subjects, it requires an approach in which teachers from these subjects work collaboratively. However, applying traditional assessment methods in STEAM education is challenging, as it requires teachers to jointly decide on appropriate assessment strategies. At present, no clear framework exists to support this process. This study examined the potential of the ordinal priority approach (OPA), a recently introduced method for multi-criteria decision-making, to facilitate teachers’ collaborative selection of assessment methods for STEAM education. It further explored the extent to which subject differences affect collaboration by comparing the decision-making of two groups: a homogeneous group (teachers of the same subject) and a heterogeneous group (teachers of different subjects). Pre- and post-questionnaires were administered to both groups to determine how the OPA can assist teachers in jointly developing a STEAM assessment method. Analyses of the responses identified differences in each group’s consensus-building process. The study revealed three key contributions of OPA to teacher collaboration in STEAM education: 1) it ensures that teachers from diverse subjects have their opinions considered; 2) its transparent decision-making process helps mitigate distrust during discussions; and 3) it promotes fair decision-making, unaffected by social power differences within the group. Based on these findings, OPA appears effective in converging diverse expert opinions through a clear decision-making process.

In recent years, significant developments have occurred in AI-based chatbots that have been effectively deployed in the educational field. However, given the novelty of this technology, descriptive analyses remain scarce. Although many review studies have focused on the effectiveness of chatbots, they generally present broad results, and only a few have addressed the impact of this technology on learning outcomes. The present study examines the educational implications of AI chatbots on various learning outcomes through a post hoc analysis conducted in accordance with PRISMA principles. It aims to aggregate and analyze findings from studies that examined the use of chatbots and their impact on specific learning outcomes. A total of 26 studies were selected from a pool of 6,721 published between 2021 and 2024 and indexed in the Scopus and Web of Science databases. Data analysis was conducted using the Newcastle-Ottawa Scale (NOS) for Education. The results revealed that AI-chatbot technology has a positive influence on several learning outcomes, including academic achievement, motivation, self-assessment, engagement in learning, self-efficacy, and language learning, among others. The studies also detailed the methodologies and tools employed in these investigations. The study also offers insights into how intelligent chatbots can be leveraged to enhance various learning outcomes.

Family routines and practices are recognized as critical determinants of child development. Despite extensive research on the socio-emotional benefits of family routines for school readiness in various contexts, there remains limited empirical evidence directly linking these routines to academic performance. This is because a lot of existing literature has focused on younger children below 8 years. This study sought to address this gap by examining the role of family routines on academic performance among middle school students in informal settlements. The study involved 351 middle school students and their parents from informal settlements in Nairobi, Kenya. Family routines were assessed using a structured questionnaire adapted from the Family Routine Inventory (FRI) scale. Academic performance data were obtained from the most recent school examinations of each participating student across five subjects (English, Kiswahili, Mathematics, Science, and Social Studies) as percentage scores. Results show that routines related to basic needs provision were the strongest predictors of academic performance, followed by academic monitoring routines. Emotional support routines moderately contributed to academic outcomes, while routines related to family outings and bonding had a limited impact. The study recommends further exploration of context-specific family routines using longitudinal designs to identify long-term impacts.

Vocational education plays a pivotal role in nurturing talent and supporting national development. However, challenges such as outdated talent development concepts, insufficient teacher training, and a lack of attention to soft skills cultivation from both schools and students have hindered the comprehensive development of secondary vocational students. This study aims to explore the direct effect of perceived teachers’ transformational leadership on the soft skills of 324 secondary vocational students in China and to examine the mediating role of students’ self-efficacy in this relationship. Using Structural Equation Modeling (SEM), the results show that teachers’ transformational leadership has a significant positive effect on students’ soft skills (β = 0.33, p < .01). Moreover, self-efficacy partially mediates this relationship (indirect effect β = 0.07, p < .05), accounting for 22.6% of the total effect. These findings suggest that teachers’ inspirational motivation, individualized consideration, and intellectual stimulation directly foster students’ communication, teamwork, and problem-solving skills, while also indirectly strengthening them by enhancing students’ confidence. Practically, the study underscores the need for teacher training in transformational leadership and for policy initiatives that integrate soft skills into vocational curricula.