This scoping review comprehensively explores how artificial intelligence (AI) is being incorporated into accounting education, examining the evolving educational setting and its potentially transformative impact on the development of future accounting professionals. Following the Arksey and O'Malley (2005) methodology and PRISMA-ScR guidelines (Tricco et al., 2018), this review synthesizes systematically a diverse set of academic literature to determine major trends, new opportunities, and long-standing challenges of integrating AI into accounting pedagogical practices. Key findings demonstrate AI's transformative potential in enhancing student engagement, fostering deeper learning, aligning educational curricula with contemporary industry demands, and improving teaching efficiency through innovative tools and techniques. However, substantial challenges persist, including faculty preparedness, the complexity of curriculum redesign, resistance to change, and critical ethical considerations surrounding the use of AI in education. These findings emphasize the multifaceted nature of integrating AI into accounting pedagogy. The review emphasizes the need for cooperation between academia, industry practitioners, and policymakers to develop adaptive, forward-thinking pedagogical strategies and establish robust ethical frameworks. These efforts are essential to improve learners with the skills and competencies required to thrive in a dynamic, technology-driven professional environment.

In primary and middle schools in China, banzhuren is the teacher responsible for managing and overseeing a specific class of students. The lower job satisfaction of banzhurens has been a longstanding issue. This study employs a quantitative method to investigate the impact of banzhurens' self-efficacy and burnout on their job satisfaction. A total of 624 primary school banzhurens from G City (in Henan province, China) participated in an online survey assessing their perceived job satisfaction, self-efficacy, and burnout. The data were analysed using structural equation modelling analysis. The results revealed that (a) banzhurens' burnout negatively influenced their self-efficacy and job satisfaction; (b) banzhurens' job satisfaction was positively influenced by self-efficacy; (c) banzhurens' self-efficacy could mediate the adverse effects of burnout on job satisfaction. Therefore, we suggest that banzhurens' job satisfaction can be enhanced by increasing their self-efficacy, particularly in terms of communication with leaders, and by reducing their burnout.

This study examines the transition challenges faced by students with learning disabilities (LD) from primary to secondary school, focusing on emotional, behavioral, and social aspects. Using a sample of 168 special education teachers, the study employs the Strengths and Difficulties Questionnaire (SDQ-Hel) to assess emotional symptoms, conduct problems, hyperactivity/inattention, peer relationship difficulties, and prosocial behavior before and after the COVID-19 pandemic. Statistical analyses, including t-tests and repeated measures ANOVA, reveal significant increases in emotional and behavioral challenges post-pandemic. Effect sizes (Cohen’s d) indicate moderate to strong impacts in key areas, with emotional symptoms (η² = .06) and hyperactivity/inattention (η² = .05) exhibiting notable changes. The findings highlight the necessity for targeted interventions, such as teacher training on emotional regulation strategies and structured transition programs. Implications for educators and policymakers include the implementation of inclusive practices and specialized transition support structures to mitigate these challenges and enhance the overall well-being of students with LD.

There are studies in the learning management literature examining the measure of system usage, but few explore how users apply the software tools to achieve specific work tasks, which in turn leads to perceived benefits. In the context of distance education, this study focuses on how Learning Management Systems (LMS) are fully used by faculty for their instructional needs. It extends existing research on LMS adoption by investigating how faculty members or instructors use the LMS tools for effective class teaching to achieve educational outcomes. Four usage patterns were identified: communication, content management, assessment, and class management. A model is presented to examine how these usage patterns interplay to achieve the perceived benefits. Data were collected from 544 instructors using LMS, such as Blackboard Learn, etc. Structural equation modeling using LISREL was employed to assess the research model. The results suggest that the usage for communication, content, and assessment activities positively impacts the usage for class management. In turn, the usage for class management influences the net benefits perceived by the instructors, and the usage for content also impacts perceived net benefits directly. These results provide practical guidelines for LMS developers’ design improvements and institutions’ policies, such as training instructors to fully utilize LMS features to achieve the maximum benefits of distance education.

Developing efficient and reliable tools for assessing early mathematical skills remains a critical priority in educational research. This study aimed to develop and validate a brief version of the Prueba Uruguaya de Matemática (Uruguayan Mathematics Test, PUMa), a digital tool to assess mathematical abilities in children aged 5 to 6. The original test included 144 items covering both symbolic (66%) and non-symbolic (34%) tasks, such as approximate number system, counting, numerical ordering (forward and backward), math fluency, composition and decomposition of numbers, and transcoding auditory-verbal stimuli into Arabic-visual symbols. Unlike most existing tools that require individual administration by trained professionals and lack cultural adaptation for Latin American contexts, PUMa is self-administered, culturally grounded, and suitable for large-scale assessments using tablets. Using a sample of 443 participants and applying parametric and non-parametric models within the framework of Item Response Theory (IRT), along with correlations with TEMA-3, preliminary evidence was generated showing that the brief version retained precision and validity. The resulting shortened tests included 69 and 73 items for the parametric and non-parametric versions, yielding a balanced representation of symbolic (56%) and non-symbolic (44%) tasks. Despite item reduction, ability scores remained highly correlated between original and brief versions (r > .90), and both brief versions demonstrated strong internal consistency (α = .94). PUMa improves upon existing assessments by combining cultural relevance, group-based digital administration, and real-time data collection, offering a scalable solution for early identification and intervention. These features support personalized educational strategies that foster cognitive and academic development from the earliest stages.

Students are among the most vulnerable populations during periods of crisis, including war, economic collapse, and pandemics. These events extend beyond academic disruption, significantly affecting students' emotional and social well-being. Mental health challenges such as anxiety, depression, and behavioural changes are commonly reported, particularly among youth living in conflict-affected areas or economically disadvantaged households. This review examines the consequences of crises on school-aged students across both local and global contexts. A structured search strategy was employed to retrieve peer-reviewed articles published between 2005 and 2024 from databases including PubMed, ERIC, Scopus, and Google Scholar. The selected studies were thematically categorized into three primary domains: pandemics, economic hardship, and war-related trauma. The review emphasizes the identification of common psychological outcomes, contributing factors, and resilience strategies implemented at the school and community levels. The findings highlight the urgent need for early interventions, trauma-informed pedagogical approaches, mental health support programs, coping strategies, and emotional regulation skills. By examining the interplay between crisis-induced stress and student support mechanisms, this review seeks to inform educators, policymakers, and practitioners in their efforts to foster resilience and promote academic recovery.

Student dropouts led to a squandering of the education budget. The education system and society are significantly affected, particularly in terms of potential development. To ensure vocational students graduate and secure satisfactory employment in line with the field of study. Implementing a comprehensive system that encompasses promoting, supporting, preventing, and resolving various student issues is essential. This system includes close, meticulous care and support, timely and appropriate interventions, enhancement of life skills, guidance, and holistic student development. This research found that the risk factors in the teaching and learning process account for 90.78 percent of the reasons scholarship students drop out of the education system; there are instances of absenteeism, inappropriate behavior, and a dislike for the teacher and the subject they are teaching. Additionally, the care and support system for vocational students at risk of dropping out consists of four components: Component 1: living care; Component 2: dropout protection; Component 3: counseling and advising; and Component 4: transfer to support. The empirical evaluation of the care and support system for students concluded that the overall assessment was highly suitable. The information should be utilized for planning and policymaking in educational institutions.

This study delved into Terry Borton’s reflective model and 7E instructional model to produce comprehensive and guided tools that fit as observation and reflective tools for enhancing learners’ engagement and outcomes in Mathematics lessons. The aim was to gather insights that can inform strategies to adapt Borton’s model to produce tools to be used to observe and analyse 7E model-based Mathematics lessons to contribute to improved student outcomes. Literature information was used to explore, analyse, and synthesise the study’s related existing theories and models to provide a deeper understanding of constraints and prompt question descriptors to produce 21st-century tools to observe and reflect on a Mathematics lesson. After comparing different prompt question descriptors from different literature and Borton’s model, concise descriptors were retained for educational purposes to be analysed, considering the 7E model phases, to produce the guided tools. As a result, two products. “Classroom Observation-Guided Tool”, which includes a guided tool table with a last column for the observer to write comments during class. This column is used to identify gaps in student engagement and learning practices across the 7E phases, which may have been misused. The “Post-Lesson Discussion Guided Tool”, to make a positive post-lesson discussion session, enabling teachers to identify areas for improvement in student engagement to achieve better outcomes next time. Other researchers can study the applicability of 21st-century observation and reflection-guided tools to other subjects, exploring their long-term impact on teacher professional development to improve overall student achievement across all school subjects.

Teachers’ self-efficacy in classroom management is essential to their professional identity and teaching quality. While contextual factors shape these beliefs, the role of pre-service teachers’ perceptions of teacher education courses in influencing self-efficacy through their classroom management beliefs remains underexplored. This study expands self-efficacy theory by proposing an integrated model in which beliefs serve as both a mediator and a moderator between course perceptions and classroom management self-efficacy, particularly in inclusive classrooms. It builds on previous evidence that pre-service teachers’ beliefs about proactive strategies partially mediate the relationship between their course perceptions and capability beliefs in proactive management practices. This leads to the proposal of a moderated mediation model to explore a more nuanced relationship by investigating whether pre-service teachers’ punishment-oriented classroom management beliefs alter the strength and direction of this partial mediation effect. Data collected online from 480 pre-service teachers enrolled in State University and National Colleges of Education in Sri Lanka, which were used in the previous study, were analyzed using SmartPLS4 structural equation modeling. The findings indicate that punishment-based beliefs negatively moderated the indirect partial effect of pre-service teachers’ perceptions of classroom management training on their self-efficacy for inclusive classroom management, mediated by preventative beliefs. This positive indirect effect was significant only when reactive punishment-based beliefs were at low to moderate levels. These findings suggest that an overreliance on reactive strategies diminishes the beneficial influence of teacher education on self-efficacy in implementing preventive measures for inclusive classroom management. The results emphasize the importance of fostering proactive beliefs through targeted training within initial teacher education programs, supported by dedicated engagement from teacher educators and policymakers.  

Analysis of student grades and demographic data to understand the effects of modality and Covid-19 on academic performance is important for universities to understand the impact these factors may have on course grades. This study analyzes all the 615,964 complete undergraduate student-course records from Kennesaw State University (KSU) spanning from 2015 to 2024 to examine the impact of course modality and the Covid-19 pandemic on academic performance. The population dataset includes student demographics (e.g., sex, age, ethnicity), prior GPA, and course characteristics (e.g., department, modality). Descriptive statistics and trend analyses were employed to evaluate grade outcomes across in-person, online, and hybrid modalities over the 9-year period. Results indicate a temporary increase in mean course grades during the Covid-19 period, followed by a return to the pre-pandemic upward trend. Hybrid courses consistently exhibited the highest mean grades throughout the study period. However, consistent patterns across modalities, demographics, and academic units suggest that these factors have limited influence on grade outcomes. These findings raise questions about the reliability of GPA and course grades as indicators of learning success across different instructional contexts and student populations.

This study applies explainable machine learning to identify which vocal attributes in a lecturer’s speech influence students’ views of a lecturer’s charisma, a key contributor to teaching quality. It further explores whether vocal qualities differ between male and female lecturers and how students of different genders respond to these differences, offering insights into voice-related factors that influence the impact of educators. Speech segments from YouTube videos featuring 200 native-English lecturers were evaluated by 900 students using charisma rating scales. A set of attributes related to three primary prosodic dimensions of voice - pitch, rhythm, and loudness - was computed. A random forest classifier was employed to predict the charisma level based on the speech attributes and to list and rank the attributes that contributed most to the prediction. The findings revealed prominent vocal attributes that achieved higher charisma scores in the students' ratings. Same-gender evaluations of charisma were mainly based on pitch, while cross-gender evaluations rely mostly on loudness or rhythm. The automated, interpretable method provides a reliable and efficient way to measure vocal charisma in academic lecturers. It can be adapted to examine additional individual factors that influence the perception of a lecturer’s charismatic presence. It may also be integrated into practice-based tools, designed to support instructors in improving their presentation skills. Our research bridges the fields of applied psychology and computer science to contribute to the development of educational technology.

Within the context of investigating belief systems, this work exemplifies a mixed-method approach. Two approaches are utilized to explore the philosophical, ontological, and epistemological assumptions that university students foster regarding the relationships between knowledge and reality. In the first step, written materials that elaborated on the matter at hand were subjected to content analysis with the assistance of Leximancer, a software that recognizes themes and concepts and turns textual data into concept maps that express networks of meaning. The second step involved conducting a cluster analysis on the data obtained from the questionnaire to identify distinct groups of participants who shared consistent epistemological viewpoints. The results obtained from the two approaches are in agreement and shed light on the prevalent epistemic inclination that favors a constructivist viewpoint. Discussion on the ramifications of the findings, as well as the methodological issues that are pertinent to the present illustration, is provided.

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.

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.