This conceptual paper proposes a framework explaining how critical pedagogy can foster students’ sense of belonging, essential for their meaningful learning. This paper argues that a sense of belonging in classrooms is a multidimensional construct that promotes physical engagement, emotional connectedness, and intellectual investment in the learning process. It further explains how, by implementing critical pedagogy, teachers can provide students with a positive experience that fosters a sense of belonging; without it, students feel alienated and unrecognized. Drawing on Freirean principles, the paper identifies five pedagogical pathways through which critical pedagogy promotes classroom belonging: dialogue, collaboration, problem-posing, shared authority, and student voice. These pathways foster respectful relationships, a sense of learning community, purpose, ownership of learning, and recognition of students’ identities, experiences, and perspectives. Together, these pathways provide a conceptual framework for understanding how critical pedagogy creates classroom conditions in which students experience belonging and, consequently, engage more meaningfully in learning. The paper concludes with implications for teachers and teacher educators seeking to design classrooms that intentionally cultivate belonging as a foundation for meaningful learning.
Higher education is undergoing a revolution due to the fast-developing generative artificial intelligence (AI) solutions, including ChatGPT, Whisper, and DALL E. This review will capture a synthesis of evidence-based articles published in the period 2020 onwards aimed at establishing the impact of generating AI on the learning capabilities of students, learning engagement and motivation, cognitive development, and performance in academic learning among higher education institutions. The search was done logically utilizing databases including Scopus, Web of Science, and Google Scholar. Peer-reviewed empirical studies on generative AI use in classroom situations were the target of inclusion criteria. The selection and screening process followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement framework which led to 12 empirical studies being included. Emotional well-being, AI literacy, and discipline specialization were determined as key moderators of effectiveness. The study revealed more productivity and less anxiety amongst students. However, issues of academic integrity, over-dependency, and correctness of content were prevalent. Students and teachers both expressed the importance of policies and support for the use of ethical AI. In conclusion, generative AI has great potential to change the learning experiences by improving engagement, personalization, and accessibility.
This study examined the utility of Brief Experimental Analysis (BEA) as an efficient, data-driven method for identifying effective reading comprehension strategies for high school students with significant reading difficulties. Three ninth-grade students at risk of failing a social studies course participated in a multielement single-case design comparing three reciprocal teaching strategies (i.e., generating questions, summarizing, predicting) against a control condition. Reading passages and comprehension assessments were drawn directly from course textbooks to enhance ecological validity. Results indicated that BEA successfully differentiated effective strategies across participants. Summarizing and generating questions consistently produced the highest comprehension outcomes for two students, while all three strategies improved performance for the third student, with predicting yielding the strongest effect. Across participants, strategy-based conditions generally outperformed the control condition. Transfer effects, measured using MAZE assessments, showed meaningful gains in reading comprehension, with two students demonstrating strong improvement and one showing moderate progress. Growth rates exceeded typical norms, suggesting educationally significant change within a relatively brief intervention period. Overall, findings support BEA as a practical tool for rapidly identifying individualized reading comprehension interventions at the high school level. Despite limitations related to small sample size and limited exposure to conditions, the study contributes evidence that structured, strategy-based interventions embedded in authentic academic materials can meaningfully improve comprehension for struggling adolescent readers.
This single-case experimental study examined the effectiveness of the Sound Partners reading intervention, delivered by a high school student tutor, for a seven-year-old female student with a specific learning disability (SLD) in reading. The intervention was implemented during a university-based summer reading program using an ABA (baseline–intervention–follow-up) design. Outcome measures included letter-sound fluency, decodable word fluency, and nonsense word fluency, assessed using FastBridge earlyReading and Sound Partners Mastery Tests. Over a 15-day intervention period, the participant received daily, 25-minute, one-on-one sessions focused on foundational reading skills such as phonemic awareness, phonics, and decoding. Results indicated substantial improvements in all measured domains: letter-sound fluency increased from 34 (baseline) to 53 (intervention) to 66.7 (follow-up) correct responses per minute; decodable word fluency rose from 23.7 to 36.5 to 48.7; nonsense word fluency improved from 8.7 to 20.1 to 26.7 correct responses per minute. Improved Rate Difference (IRD) values demonstrated moderate to large intervention effects. Procedural fidelity was 99.5% and interscorer agreement reached 100%, confirming reliable implementation and assessment. The study highlights the potential for high school student tutors to deliver structured, evidence-based reading interventions with strong fidelity, resulting in significant gains for students with SLD. Limitations include the single-subject design and lack of long-term follow-up. Future research should replicate these findings with larger samples and investigate sustained outcomes. Sound Partners offers an accessible, effective intervention for schools seeking to improve early literacy among students with reading disabilities.
The rapid advancement of artificial intelligence (AI) is fundamentally transforming the global workforce, challenging the relevance and effectiveness of traditional higher education models. This paper argues that the long-standing academic major, rooted in rigid disciplinary boundaries and slow to adapt, is increasingly misaligned with the demands of a dynamic, AI-driven world. In response, we propose a shift toward modular, AI-centric learning paths as a more flexible, personalized, and future-ready alternative. Through a critical examination of the limitations of the current system - including inflexibility, siloed knowledge, skill mismatches, and lack of lifelong learning support - we highlight the urgent need for educational reform. We then present a compelling case for modular learning, emphasizing its ability to foster interdisciplinary thinking, embed AI literacy across all fields, and support the development of transferable, in - demand skills. This model empowers students to build customized, stackable credentials aligned with evolving career opportunities. The paper concludes with a comprehensive set of recommendations for implementing this transformation, including faculty development, industry collaboration, updated accreditation standards, and the integration of AI - powered learning technologies. By embracing modular, AI-integrated education, institutions can better prepare graduates for the complexities of the 21st-century workforce and ensure higher education remains relevant, inclusive, and responsive in the age of AI.
