The main thrust of the study was to explore the third-year English student’s sentiments on the application of the artificial intelligence (AI)-integrated paraphrasing tools. Specifically, it aimed to investigate the benefits and drawbacks brought by AI paraphrasing tools towards the writing skills of the students. The investigation utilized a semi-structured interviews with an open-ended questionnaire using an audio-video recorder. The data gathered were interpreted using the Thematic Analysis of Braun and Clarke. The study was carried out at one of the campuses of a state university located at Candijay, Bohol, Philippines. Using the Purposive sampling technique, twelve (12) respondents provided information on the research endeavor. The findings revealed that students had a positive opinion of AI-integrated paraphrase tools: they saw them as helpful resources that significantly improve their academic writing process; it includes plagiarism reduction, efficiency, and timesaving, and aids in rephrasing text. The findings also revealed the risks and issues of using AI-integrated paraphrasing tools, such as Prone to plagiarism, automated suggestions dependency, and loss of original meaning and context. With that, the students showed how they deal with those risks and issues, including as responsible users and thorough editing and reviewing. In accordance with the study, students are encouraged not to rely excessively on AI-integrated paraphrase tools, even though they can improve their writing abilities. This research emphasizes that students play a pivotal role in ensuring the appropriateness of texts generated by AI-integrated paraphrasing tools by mastering the art of proper paraphrasing.

This study explores the relationship between language competence and intercultural communicative competence (ICC) among English as a Foreign Language (EFL) learners through a mixed-methods approach. A sample of 196 Chinese EFL learners was divided into three proficiency groups (low, intermediate, and high), with data collected through Likert-scale questionnaires and semi-structured interviews involving 16 participants. Quantitative analysis revealed that higher language proficiency is linked to improved overall ICC scores and its specific dimensions. The Kruskal-Wallis H test confirmed significant differences in overall ICC, attitude, and skill across proficiency levels, with attitude showing the strongest effect. Spearman's correlation analysis demonstrated small but significant positive correlations between English proficiency and overall ICC, attitude, and skill. Qualitative findings further enriched the quantitative results, emphasizing the foundational and catalytic role of language competence in enhancing ICC and its dimensions. However, participants acknowledged that language competence alone is insufficient for fully successful intercultural interactions. This study expands Byram’s model by offering detailed insights into the intricate relationship between language competence and various ICC dimensions. The study recommends that to fully cultivate ICC, it is essential to integrate the development of language competence into instructional practices.

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.

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.

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.

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.

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.

The introduction of evolution in post-apartheid South Africa in 2008 presented significant challenges for teachers, due to both their own and their students' faith-based biases. This study investigates South African teachers' attitudes and understanding of evolution, utilizing Lemkian sociocultural theory and Vygotskian ZPD scaffolding. A mixed-methods approach was employed, including a Likert-scale questionnaire from 91 life science teachers and qualitative insights from open-ended questions. Results reveal a lack of enthusiasm for teaching evolution, influenced by personal religious beliefs and doubts about its scientific validity. Teachers often call for equal representation of evolution and creationism in classrooms. The preparation of teachers must address the stagnant discussion of evolution, while the life sciences curriculum emphasizes the Nature of Science, scientific literacy, and connections between science and society is compromised.

Team-based learning (TBL) is a popular form of collaborative learning designed to increase student engagement and motivate students to learn. A growing body of research, particularly in the health sciences, has demonstrated that TBL has positive impacts on student performance and classroom dynamics. However, much less is known about the student outcomes associated with TBL courses in undergraduate science, technology, engineering, and mathematics (STEM) education, fields in which active learning is especially important for student success and retention. To address this gap, we conducted a systematic review of the student outcomes associated with TBL in undergraduate STEM education. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method, we identified 55 empirical and qualitative research articles published between 2005 and 2024 that reported on TBL implementation practices and student outcomes. Importantly, we found that most studies described increased student performance and improved measures of classroom dynamics when TBL was compared to lecture-based teaching approaches. These findings provide further evidence that TBL is an effective instructional method and suggest that TBL can be implemented successfully across a wide range of student populations and undergraduate STEM disciplines.