The traditional method of delivering lectures in secondary-level biology remains associated with low learner engagement, particularly when the curriculum is heavy, making active learning difficult. The flipped classroom strategy, which uses digital media to deliver instruction before class while class time is allocated to investigation activities, has been adopted as one of the most preferred educational reform strategies. The study used a quasi-experimental, non-equivalent pre-test-post-test control group design, involving 94 students (48 in the experimental group and 46 in the control group) over 12 weeks from two intact secondary school classes. Results of an independent-samples t-test showed statistically significant differences in favor of the flipped classroom on all measures of engagement, including behavioral engagement (t(92) = 6.04, p < .001, d = 1.25), emotional engagement (t(92) = 4.43, p < .001, d = 0.91), and cognitive engagement (t(92) = 4.13, p < .001, d = 0.85). Biology achievement gains were also significantly greater among participants in the experimental condition (t(92) = 5.34, p < .001, d = 1.10). ANCOVA also showed significant between-group differences on all outcomes while controlling for pre-test scores. Qualitative data revealed that learners appreciated autonomy, cooperative problem-solving, and quick feedback; however, they initially experienced some technology anxiety. The flipped classroom model can positively impact student engagement and academic success in secondary biology classes. Thus, implementing constructivist pedagogies with technology in secondary science education can be supported if the proper infrastructure is in place.
Egbosimba Chinazom Irene, Luo Gongbo, Eneze Florence Ego et al.· International journal of res...· 0 citations
The Higher Education sector is being revolutionized by AI, with machine learning, natural language processing and generative AI applications. Yet, with the fast pace of technological evolution, both the possibilities and threats of AI incorporation have been spread out. This study includes an integrated multimethod systematic review and bibliometric analysis of the dual landscape of AI in higher education. Following PRISMA 2020 guidelines, systematic searches of Web of Science (n=1,631), PubMed (n=1,349), and Scopus (n=1,439) yielded 4,419 records (2021-2025). Following screening for duplication and eligibility, 110 studies (85 high and 25 medium quality) were included for thematic synthesis. A concurrent bibliometric analysis of 1,227 documents in Scopus was performed to depict author citation networks, keyword co-occurrence, and bibliographic coupling by source and country, using VOSviewer. The study identified Jiao, Ouyang, and Zheng as the most cited authors; the most frequently used keywords are 'ChatGPT' (173 times) since late 2022. Academic support, automated grading, teacher development, perceived usefulness, personalization of learning, and prediction of performance. The perceived ease of use, 24/7 access to technology, administrative efficiency; and academic integrity, data issues, integration barriers, technological limitations, equity concerns. And attitudinal barriers were identified as opportunity and challenge domains, respectively, during the thematic synthesis process. This study offers a dual landscape framework which means that there are no opportunities without challenges, and no challenges without opportunities. It delivers an evidence-based typology for institutional AI strategy, and priority areas for policy intervention, practically. The methodologically, it shows the usefulness of the combination of bibliometric and systematic review for complete literature synthesis. This research aims to explore the opportunities and challenges in integrating AI into higher education, based on a systematic review and bibliometric analysis of relevant literature.
C. Kidega, Aciro Can Lucy, Egbosimba Chinazom Irene et al.· Educational Point· 0 citations
