Spyridon Aravantinos

Spyridon Aravantinos

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Spyridon Aravantinos has a total of 9 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Teachers' Artificial Intelligence Practices, Benefits, and Challenges

    by Spyridon Aravantinos, Konstantinos Lavidas, Stamatis Papadakis, Thanassis Karalis, Vassilis Komis

    Since the emergence of Artificial Intelligence (AI) in aspects of everyday life and its introduction into the educational sector, teachers from primary and secondary education level have been attempting to implement it into their practices, recognizing its benefits while also trying to address the challenges it presents. This systematic literature review followed the PRISMA guidelines with specific inclusion and exclusion criteria, analyzing 49 peer-reviewed empirical articles in English, published online by the end of 2024 from Scopus and Web of Science databases. The main objectives were to identify teachers' practices, the benefits and the challenges, as they were shaped by the integration of AI into their teaching, aiming to gather trends, update knowledge and understand how it can be useful for learning without posing any threat. The results identified key insights in areas such as AI literacy, personalization of learning, assessment and feedback, ethical and responsible use, human-AI collaboration, academic integrity, teachers' attitudes and perceptions, and continuous PD.

  • Top Cited Papers
    Open Access

    Teacher Education Students’ Practices, Benefits, and Challenges in the Use of Generative AI Tools in Higher Education

    by Stavros Athanassopoulos, Aggeliki Tzavara, Spyridon Aravantinos, Konstantinos Lavidas, Vassilis Komis, Stamatios Papadakis

    Despite the growing adoption of generative artificial intelligence (GenAI) tools in higher education, limited research has examined how future educators perceive and use these technologies in their academic practices. This study investigates the practices, perceived benefits, and challenges associated with the use of GenAI tools—such as ChatGPT—among undergraduate students enrolled in programs that confer teaching qualifications. Using a mixed-methods design, data were collected from 314 students from the Early Childhood Education, Philosophy, and Philology departments. The findings indicate that the majority of students use GenAI tools primarily for academic purposes, most commonly for information searching, data analysis, study advice, and exam preparation. Students reported several perceived benefits, including rapid access to information, time efficiency, improved comprehension of complex concepts, enhanced study organization, and support with assignments and research-related tasks such as summarizing or translating academic texts. At the same time, participants expressed notable concerns, particularly regarding over-reliance on AI, reduced personal effort, risks to academic integrity, diminished critical thinking, and weakened research skills. Additional challenges included misinformation, reduced creativity, improper use of AI-generated content, skill underdevelopment, and potential technological dependence. The study concludes that teacher education programs should systematically integrate AI literacy and responsible-use training to prepare future educators to address the pedagogical and ethical implications of GenAI in educational settings.


  • Top Cited Papers
    Open Access

    Artificial Intelligence in K-12 Education: A Systematic Review of Teachers’ Professional Development Needs for AI Integration

    by Spyridon Aravantinos, Konstantinos Lavidas, Vassilis Komis, Thanassis Karalis, Stamatios Papadakis

    Artificial intelligence (AI) is reshaping how learning environments are designed and experienced, offering new possibilities for personalization, creativity, and immersive engagement. This systematic review synthesizes 43 empirical studies (Scopus, Web of Science) to examine the training needs and practices of primary and secondary education teachers for effective AI integration and overall professional development (PD). Following PRISMA guidelines, the review gathers teachers’ needs and practices related to AI integration, identifying key themes including training practices, teachers’ perceptions and attitudes, ongoing PD programs, multi-level support, AI literacy, and ethical and responsible use. The findings show that technical training alone is not sufficient, and that successful integration of AI requires a combination of pedagogical knowledge, positive attitudes, organizational support, and continuous training. Based on empirical data, a four-level, process-oriented PD framework is proposed, which bridges research with educational practice and offers practical guidance for the design of AI training interventions. Limitations and future research are discussed.


  • Top Cited Papers
    Open Access

    Educational Approaches with AΙ in Primary School Settings: A Systematic Review of the Literature Available in Scopus

    by Spyridon Aravantinos, Konstantinos Lavidas, Iro Voulgari, Stamatios Papadakis, Thanassis Karalis, Vassilis Komis

    As artificial intelligence (AI) becomes increasingly prevalent, it has become a topic of interest in education. The use of AI in education poses complex issues, not only in terms of its impact on teaching and learning outcomes but also in terms of the ethical considerations regarding personal data and the individual needs of each student. Our study systematically analyzed empirical research on the use of AI in primary education, specifically for children aged 4–12 years old. We reviewed 35 articles indexed in SCOPUS, filtered them according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, analyzed them, and categorized the findings. The research focused on the studies’ objectives, learning content, learning outcomes, learning activities, and the pedagogy of activities or the AI tools. Our categorization resulted in three main categories of research objectives regarding the creation, implementation, and evaluation of AI tools and five categories for learning content: AI and ML (machine learning) concepts in STEM and STEAM, language learning, mathematics, arts, and various other subjects. The learning activities were split into four categories: apply, engage, interact, use; project-based learning with multiple activities; experience and practice; and students as tutors. The learning outcomes were split into three levels: cognitive, affective, and psychomotor. The pedagogy of AI tools falls into four categories: constructivism, experiential learning, AI-assisted learning, and project-based learning. The implications for teacher professional development are discussed.


  • Exploring the Role, Implementation, and Educational Implications of AI in Early Childhood Education

    by Iro Voulgari, Konstantinos Lavidas, Spyridon Aravantinos, Soultana Sypsa, Maria Sfyroera