Keyword: AI

ABSTRACT: This study examines the experiences of nine secondary content teachers who report high self-efficacy in working with English learners (ELs) in mainstream classrooms. As the number of ELs in US schools grows, many content area teachers feel unprepared to support these students effectively. Grounded in the theoretical frameworks of culturally responsive pedagogy and teacher self-efficacy, this phenomenological study focuses on mathematics, science, and social studies teachers in Florida public schools. The research employs in-depth, semi-structured interviews to explore teachers’ perceptions and lived experiences. Significant themes that emerged from the analysis include (a) undercover advocacy, (b) ethic of care, and (c) leveraging student achievement data. A common thread woven through all narratives was the integration of students’ native languages through translation and translanguaging practices while leading with empathy. Participants created more equitable learning environments for ELs in mainstream classrooms through multifaceted, often covert, advocacy efforts. Implications for teacher preparation programs and school districts are discussed, including professional development initiatives to cultivate teachers’ asset-based ideologies toward ELs and improve their pedagogical practices. Recommendations for state and national policymakers include modifications to ESOL certification requirements. This research informs efforts to foster mainstream teacher preparedness and efficacy in working with linguistically diverse student populations.

ABSTRACT: This study investigates artificial intelligence (AI) psychological empowerment in education, examining how AI tools enhance students’ sense of competence, autonomy, and engagement beyond the effects of material empowerment (e.g., task performance
improvements). Using a quasi-experimental design, we compared Chinese domestic students in China and Chinese international students in Australia to assess whether AI psychological empowerment is both tangible and more impactful than material empowerment. We highlight several nuanced ways AI fosters personal growth and self-perception. Our findings reveal that, while AI material empowerment is beneficial, psychological empowerment has a stronger influence on motivation and self-perception, particularly for international students compared to local students, despite both groups completing the same English writing task. These results suggest that AI’s role in education extends beyond traditional material support, offering transformative psychological empowerment that enhances students’ confidence in academic contexts. This empowerment reasonably translates into greater personal adaptability and, ultimately, personal growth. The study contributes to the growing literature on AI in education, providing insights for scholars, educators, and policymakers seeking to leverage AI for holistic student development. Notably, generative AI (GAI) emerges as a critical tool for cultural and linguistic adaptation, particularly for immigrant students navigating foreign academic systems. Furthermore, the psychological empowerment effects of GAI appear to be context-dependent, with stronger impacts observed in students facing greater cultural or linguistic barriers. These findings emphasize AI’s potential to foster personal growth and resilience across diverse learning contexts. Finally, we recommend that educational policies and practices be tailored to leverage GAI for immigrant populations, paving the way for more equitable educational opportunities.

ABSTRACT: Sustainable and equitable development requires comprehensive and collaborative initiatives that avoid and remedy environmental harms and remove and alleviate poverty-contributing factors. This review article presents a promising way forward for universities to engage in sustainable development challenges that build on South-North collaboration and the interests, dedication, energy, and contributions of today’s youth. First, we introduce critical dimensions of the contemporary global challenge of sustainable development along with their interconnected features. We next review the crucial sustainable development Higher-Education roles and gaps of tertiary education institutions along with encouraging educational approaches. Then, we set forth three innovative initiatives that, implemented collectively, promise to address prevailing shortcomings in the ways that universities currently approach these challenges. The linked initiatives are (1) transnational competence curricula and preparation, (2) South-North Higher Education Consortia, and (3) a Global Challenges Corps staffed by a transnational cadre of higher education graduates and professionals. These proposals are accompanied by a detailed evaluation framework. The world’s institutions of higher learning are strategically positioned to distinguish and address current and upcoming challenges of sustainable development. In combination, our three proposed initiatives offer tertiary-level institutions a breakthrough approach for preparing current and future students interested in gaining valuable sustainability problem-solving skills. By embracing the institutional change pathways elaborated here, forward-looking universities will move to a far stronger position from which to provide tomorrow’s students with valuable skills and experiences for tackling forthcoming glocal socio-ecological challenges.

ABSTRACT: The study aims to explore Strategies for restrainingClassroomDisruptive BehaviorAmong Public Secondary Schools Students in Ekiti State. Specifically, it sought to examine the types of disruptive behaviors, problems encountered by the schools, and strategies to be adopted to curb disruptive behaviors perpetuated by students in the classroom during teaching and learning. Three research questions guided the study. The study adopted a descriptive research design and utilized a quantitative approach. A sample of 100 respondents involving principals and teachers was used through purposive sampling. Strategies for Restraining Students’ Disruptive Behaviors in Public Secondary Schools served as an instrument. Data collected were analyzed using mean and standard deviation. The analysis revealed that (1) lateness to school, irregular class attendance, fighting with each other within and outside the school, refusal to do assignments given by teachers, non-participation in-class activities, use of abusive language against one another, and operating phones during class hours were disruptive behaviors perpetrated by students. (2) The school encountered several problems such as bullying of teachers and management by the punished students, and teachers get discouraged going back to class, which causes more stress for teachers as they become detracted from academic routine. (3) The use of classroom management, allowing students to have easy access to the teachers, promptness of teachers to the discharge of their tasks of teaching profession, ensuring of appropriate seating arrangement by teachers, attentiveness of the teachers to both reported and unreported cases in class, regular checking of children by parents in schools, and maintenance of small and well-controlled
class size were strategies to be adopted to curb disruptive behaviors among public secondary schools students in Ekiti state.

ABSTRACT: This paper introduces a quality-based conceptual framework for planning and conducting research and developmental projects within the knowledge co-production continuum. This paper uses a longitudinal self-study methodology to analyze six case studies over a decade and identify comparative and cumulative trends. The analysis shows the importance of inputs, processes, and outputs in knowledge co-production and reveals intangible benefits such as deep engagement and capacity strengthening relationships. This paper also demonstrates how diverse teams can effectively convert tacit knowledge into explicit knowledge through knowledge co-production. This paper adopts an innovative approach of cross-linking cases along a timeline to provide insights into comparative and cumulative trends and suggests future research directions to explore the interconnections among the framework’s components. This paper argues that the careful design of inputs and processes is essential for successful knowledge co-production outcomes and that the proposed framework can be applied to address complex developmental issues. This paper contributes a novel conceptual framework and a unique cross-linking approach, offering a comprehensive and practical tool for researchers and practitioners.

ABSTRACT: ver the past decade, the growth in generative artificial intelligence (GenAI) is reshaping and changing how we interact, learn, and work and is likely to bring ongoing change in the future. However, current educational understandings, frameworks, and models concerning digital technologies and digital literacies are remaining relatively static and hierarchical and do not adequately accommodate GenAI’s unique learning capabilities, creative potential, and agency. In this conceptual article, we use critical dialogic inquiry and employ ecological thinking using the notion of symbiosis and posthuman perspectives to explore and speculate about the nature of GenAI and its potential impact on educators and learners. We offer a new way of conceptualizing human relationships with GenAI, which we call “symbi(AI)tic understandings.” Symbi(AI)tic understandings acknowledge the evolving and contextual relationships between partners: from balanced mutualism to one-sided commensalism to potentially harmful parasitism. Thus, we position human–GenAI relationships as part of change futures in which there are complex associations between technology and human endeavor. These understandings aim to foster more nuanced ways of being with and thinking about technology: ways which are vital for educators and learners as they transition into an era of education with AI.

ABSTRACT: This article shares what Swedish preschool teachers are working with in the field of early childhood education for sustainable development (ESD) as emerged in talks with their children, aged two to five years. The tasks carried out as the basis for the present
analyses were informal child talks about a topic related to sustainability that the teachers and children had worked with in practice. The teachers themselves chose what content to talk about. The 200 teachers participated in the Swedish research and development program Sustainable Preschool. The aim of the present study was to make visible the content of teacher-child talks about sustainable development in early childhood education. The research question is as follows: What content areas do teachers communicate about with children 2–5 years of age related to ESD? The teacher-child talks were initiated by the teachers, but through the use of interpretative content analysis the children’s voices were also made visible. The main result is narratives about the content, the most common topics being recycling, growing plants and animals, areas which have long been common topics in Swedish preschools. For many preschools, however, the talks show an integration of transformative and transactional perspectives in how the content was handled together with the children. ESD in early education in Sweden is no longer dominated by the environmental dimension, as earlier content studies have shown; a new common content relates to the UN Sustainable Development Goal 4.7 regarding sustainable lifestyles and human rights, and sustainability is a long process, founded in empowerment, action competence, and changed policy.

ABSTRACT: Contemporary advances in generative AI technology have sparked considerable interest regarding its application in language education. This article explores the innovative impact that AI-powered linguistic educational tools may have, such as customized learning journeys, dynamic content, and individualized feedback mechanisms, which collectively have the potential to enhance language acquisition. At the same time, it is important to recognize the constraints associated with such technologies. Concern about maintaining precision and genuineness within AI-crafted language texts is an issue in the literature. There is also caution about AI’s current inclination to standardize language expression and to propagate limited cultural narratives, alongside the risks of overreliance on technology which may diminish analytical thought and inventiveness. This article examines the ethical considerations involving generative AI, such as the authenticity of creative work and the ownership of intellectual output. Emphasizing the necessity for clarity and conscientiousness in the application of AI, this conceptual article outlines the opportunities, limitations, and ethical concerns associated with generative AI in language instruction. This article advocates for a well-rounded strategy that
leverages the positive aspects of generative AI within language education, while also addressing possible drawbacks and championing an ethical and equitable approach to language learning in the emerging AI-centric digital landscape. A model for forging thinking in this new research and practice space is offered to synthesize many of the possibilities of generative AI in language education.

ABSTRACT: When teachers are confident in their ability to teach mathematics and science, it can inspire students to have confidence in their own abilities. Students are more likely to engage with and enjoy these subjects when they see their teacher’s interest and belief in the material. This study aimed at exploring teachers’ confidence of teaching mathematics and science as result of continuous professional development by the African Institute for Mathematical Science (AIMS Rwanda) through its Teacher Training Program (AIMS-TTP). It employed an ex post facto research design targeting 351 secondary school teachers. The findings revealed a positive and significant relationship (p < 0.05) between AIMS-TTP interventions and teachers’ confidence to teach mathematics and science. Besides, linear regression model indicated that the dependent variable Teachers’ Confidence to teach mathematics and science was regressed on predicting variables of improved capacity to plan, adapting teaching to the level of learners, Information Communication Technology (ICT) integrated in teaching and learning; learning from peers; addressing cross-cutting issues; effective implementation of the competence-based curriculum; and the application of bloom’s taxonomy. The independent variables significantly predict teachers’ confidence of teaching mathematics and science, F (7, 326) = 183.843, p < 0.001, which indicates that the factors under study have a significant impact on teachers’ confidence of teaching mathematics and science. Moreover, the findings (Adjusted R2 = 0.822, F (8, 342) = 197.055, p = 0.000 p < 0.05) indicated that 82.2% of the variance in improved teachers’ attitude in teaching mathematics and science evidences a significant influence on the total variance. Our research suggests that policymakers should consider developing and endorsing training on innovative teaching and learning methods to boost teachers’ confidence and attitude when it comes to instructing mathematics and science at basic levels. Trainings should also be extended to Technical Secondary School STEM teachers.

ABSTRACT: In the rapidly evolving landscape of English composition education, the integration of AI writing tools like ChatGPT and Claude 2.0 has marked a significant shift in pedagogical practices. A mixed-method study conducted in Fall 2023 across three sections, including one English Composition I and two English Composition II courses, provides insightful revelations. The study, comprising 28 student respondents, delved into the impact of AI tools through surveys, analysis of writing artifacts, and a best practices guide developed by an honors student. Initially, the study observed a notable anxiety and mistrust among students regarding the use of AI in writing. However, this apprehension gradually subsided as students increasingly integrated these tools into their writing processes, indicating a shift from skepticism to practical application. The analysis of writing artifacts, particularly early drafts, revealed distinct patterns of AI tool usage, differentiating between students utilizing the tools effectively and those attempting to shortcut the writing process. The final papers, while not overtly indicating AI usage, demonstrated nuanced integration of AI in iterative and recursive tasks like refining arguments and developing ideas at the paragraph level. This suggests a trend toward a hybrid model of writing instruction, where traditional methods are complemented by strategic use of emergent technologies. The study underscores the importance of revised instructional strategies that blend conventional writing techniques with guidance on effective and ethical AI tool usage. It highlights the potential of AI tools in supporting the writing process while also cautioning against over-reliance. The findings of this study offer valuable insights for educators and institutions aiming to develop a balanced and effective hybrid writing instruction model, catering to the needs of contemporary English composition classrooms while maintaining academic integrity.