Review Article
Héctor Pérez-Montesdeoca, Daniel Rodriguez-Rodriguez, Aitana Fernández-Sogorb
CONT ED TECHNOLOGY, Volume 18, Issue 3, Article No: ep667
ABSTRACT
In recent years, the emergence of generative artificial intelligence (GenAI) has reshaped multiple domains of human knowledge, including education, giving rise to an emerging field of study that still lacks conceptual and empirical systematization—particularly at the secondary education level. Despite growing interest in exploring its pedagogical potential, existing studies remain fragmented, methodologically uneven, and often rooted in experimental or anecdotal contexts, which hinders the development of a robust evidence base regarding its actual impact on learning. In response to this situation, the present study conducts a systematic review of recent scientific literature with the aim of identifying the main uses of GenAI in secondary education and examining the improvements these uses bring to teaching and learning processes. The review follows the PRISMA protocol and includes a total of 33 studies selected based on explicit inclusion criteria, focusing on experiences involving generative tools. The findings reveal a diverse range of approaches to GenAI integration, with a predominance of applications in written production, STEM problem-solving, creative stimulation, and automated feedback—most of which are initiated by teachers and implemented in isolated or experimental settings. The review also identifies significant improvements in areas such as student motivation, autonomy, critical thinking, and digital competence. However, methodological limitations and gaps in pedagogical integration are also noted. These findings underscore the need to move towards more integrated and sustained pedagogical models and highlight the urgency of strengthening longitudinal and theoretically grounded research to gain deeper insights into the educational implications of this emerging technology.
Keywords: applications, benefits, educational technology, emerging technology, innovation
Research Article
Kerem Kilicer, Salih Bardakci, Ibrahim Arpaci
CONT ED TECHNOLOGY, Volume 9, Issue 3, pp. 225-245
ABSTRACT
For today’s societies trying to cope with the current globally increased competition, existence of individuals who can take risks, solve problems and adopt changes an innovation has gained more importance when compared to the past. This situation brings responsibility to educational institutions for increasing the number of innovative individuals and the qualifications of these individuals. Therefore, in the process of designing and developing any kind of in-class activities which will contribute to innovativeness, it is important to determine the technology usage characteristics that can be used to define individuals who have high levels of innovativeness. The purpose of the present study was to determine the variables related to technology which will be used to discriminate between individuals who have high and low levels of innovativeness. In the study, which was carried out using the causal-comparative design, a logistic regression model was formed by using technology-related variables, and which technology-related variables managed to predict high level of innovativeness was tested. In the logistic model, the technology budget (purchases, internet, and phone bills), technology ownership (smart phones, tablets, laptops, personal computers, internet, websites, blogs), technology renewal/update time (smart phones, computers), the number of utilized internet applications and internet usage habits were analyzed as predictors. The study was conducted with 244 university students from different class grades at a state university in Turkey. The results revealed that among the variables examined, only the variables of Internet usage habit, the number of Internet applications used, blog ownership and the money spent on technology use were significant predictors. In addition, the model in which these variables were used was found to classify high and low levels of innovativeness with accuracy of 71%. Implications are discussed.
Keywords: Emerging technology, Innovativeness, Technology usage habits, Preservice teachers