Session Information
Paper Session
Contribution
The ethics of technology has gained prominence in the field of educational technology, with transnational organizations such as the EU, UNESCO, and the OECD publishing guidelines on the adoption of artificial intelligence and data usage in education (Bosen et al., 2023; European Commission, 2022; Molina et al., 2024; OECD & Education International, 2023). However, thinking ethically does not necessarily translate into acting ethically (Morley et al., 2021).
In education, pre-service teachers and professionals face multiple challenges when attempting to apply an ethical approach to technology, often shaped by techno-enthusiastic discourses (Nemorin et al., 2023). Platformization and datafication have reconfigured educational priorities, directing attention toward user experience, productivity, and performance under narratives that normalize access to technology as synonymous with quality and inclusion (Rivera-Vargas et al., 2024).
Regulatory frameworks on technology ethics are frequently perceived as mere “compliance checklists” (Raffaghelli et al., 2023), reflecting limited critical engagement with the underlying infrastructures and interests (Hartong & Förschler, 2019). Additionally, when regulations are overly broad, they often lack concrete strategies for action or activism.
In response to these challenges, the ETH-TECH project (Anchoring the Ethics of Technology—AI and Data—into Practice) has emerged as a collaboration among researchers from Germany, Italy, Romania, and Spain. Its objective is to expand the understanding of ethics in educational technology and provide concrete tools for its application in initial teacher training. Beyond mere awareness-raising, ETH-TECH aims to articulate a practical and critical approach that moves beyond regulatory compliance, enabling educators to integrate ethical considerations into their professional practice.
Nevertheless, teaching ethics remains a contested issue, as it requires conceiving ethics as a situated process. In this context, reviewing teacher education curricula serves as a crucial starting point to assess the extent to which these issues are embedded within curricular design.
Syllabi function as public documents that provide a structured overview of course content and pedagogical approaches (Godwin et al., 2017; Stanny et al., 2014). A syllabus is not merely a structural blueprint of a subject but also reflects teaching methodologies and conceptualizations of learning (Palmer et al., 2016).
Research has shown that curricula influence students’ course selection (Kim et al., 2020) and have been conceptualized as contractual documents that regulate instruction and establish pedagogical standards, directly impacting the evolution of academic programs (Eberly et al., 2001). However, their organization and content vary significantly across countries and universities, leading to differences in how specific topics—such as ethics in educational technology—are addressed in teacher education.
Against this backdrop, this study examines the syllabi of education degree programs in Spanish universities, aiming to assess the extent to which ethics is integrated into the teaching of educational technology and artificial intelligence. This analysis seeks to identify gaps and opportunities to enhance teacher education from a critical perspective, aligning it with international ethical frameworks and contributing to the development of more responsible and reflective educational practices.
Method
This study conducted a documentary analysis of approximately 200 syllabi from over 60 Spanish universities. The primary objective was to examine how educational technologies and digital learning are taught in teacher education programs, with a particular focus on the methodologies used, the scientific literature referenced, and the presence of ethical and critical perspectives in these programs. The sample selection followed an institutional diversity criterion, including universities from Spain’s 17 Autonomous Communities and covering both public and private institutions. This approach provided a broad and representative overview of the national landscape, allowing for the identification of patterns and variations in how ethics is integrated into teacher education in the context of educational technology. Data collection involved systematically searching for and extracting syllabi from university websites. Once identified, each syllabus was analyzed in detail to examine its structure, content, and pedagogical approach. The information was then organized into a structured database, categorizing the content according to key areas of interest in this initial phase of the project: ethics, artificial intelligence, critical perspectives on educational technology, platformization of education, datafication of education, algorithmic education, and digital ethics. After the information was compiled and integrated into the database, a content analysis (Krippendorff, 2004) was conducted to identify trends, patterns, and gaps in the inclusion of ethics in teacher education syllabi. This analysis allowed for a systematic examination of the data, facilitating the classification and coding of key elements related to the teaching of digital technologies in teacher education. The application of this method provided a solid analytical framework for interpreting the preliminary findings and established clear criteria for subsequent phases of the study, which will further investigate the institutional and curricular dynamics shaping the role of ethics in educational technology.
Expected Outcomes
A preliminary analysis focused on identifying key terms reveals that the concept of ethics has a limited presence in the syllabi examined. Similarly, notions such as artificial intelligence (AI), critical perspectives in EdTech, platformization, and datafication appear only marginally or are entirely absent from most curricula reviewed. This absence suggests that discussions on the social, political, and ethical implications of technology in education have not yet been fully incorporated into teacher training at the curricular level. Additionally, the study indicates that the bibliographic references included in these syllabi tend to be outdated, with a predominance of sources published before 2021. This could point to a gap between recent research on ethics and educational technology and its integration into the preparation of future educators. However, these findings require further analysis to better understand the factors underlying these trends, considering elements such as national regulations, institutional dynamics, and pedagogical perspectives that shape curricular design in this field.
References
Bosen, L.-L., Morales, D., Roser-Chinchilla, J. F., Sabzalieva, E., Valentini, A., Vieira do Nascimento, D., & Yerovi, C. (2023). Harnessing the era of artificial intelligence in higher education: A primer for higher education stakeholders. UNESCO-IESALC. https://unesdoc.unesco.org/ark:/48223/pf0000386670?locale=en European Commission: Directorate-General for Education, Youth, Sport and Culture. (2022). Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for educators. Publications Office of the European Union. https://data.europa.eu/doi/10.2766/153756. Green, B. (2021). The contestation of tech ethics: A sociotechnical approach to ethics and technology in action [Preprint]. arXiv. http://arxiv.org/abs/2106.01784 Hartong, S., & Förschler, A. (2019). Opening the black box of data-based school monitoring: Data infrastructures, flows and practices in state education agencies. Big Data & Society, 6(1), 2053951719853311. https://doi.org/10.1177/2053951719853311 Krippendorff, K. (2018). Content analysis: An introduction to its methodology (3rd ed.). Sage. Molina, E., Cobo-Romaní, C., Pineda, J., & [Nombre de pila de Rovner] Rovner. (2024). Revolución de la IA en la educación: Lo que hay que saber. World Bank. https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099355206192434920/IDU18a4e03161fc3d14a691a4dc13642bc9e086a Morley, J., Elhalal, A., Garcia, F., Kinsey, L., Mökander, J., & Floridi, L. (2021). Ethics as a service: A pragmatic operationalisation of AI ethics. Minds and Machines, 31(2), 239–256. https://doi.org/10.1007/s11023-021-09563-w Nemorin, S., Vlachidis, A., Ayerakwa, H. M., & Andriotis, P. (2023). AI hyped? A horizon scan of discourse on artificial intelligence in education (AIED) and development. Learning, Media and Technology, 48(1), 38–51. https://doi.org/10.1080/17439884.2022.2095568 OECD, & Education International. (2023). Opportunities, guidelines and guardrails for effective and equitable use of AI in education. OECD Publishing. https://www.oecd.org/education/ceri/Opportunities,%20guidelines%20and%20guardrails%20for%20effective%20and%20equitable%20use%20of%20AI%20in%20education.pdf Raffaghelli, J. E., Romero Carbonell, M., & Romeu-Fontanillas, T. (2023). In my opinion, the TOS… Situating personal data literacy interventions. Information and Learning Sciences, ahead-of-print(ahead-of-print). https://doi.org/10.1108/ILS-06-2023-0086 Rivera-Vargas, P., Raffaghelli, J., & Miño-Puigcercós, R. (2024). Plataformas digitales comerciales en la educación pública: Desafíos emergentes sobre privacidad y protección de datos. Edutec. Revista Electrónica de Tecnología Educativa, 87, Article 87. https://doi.org/10.21556/edutec.2024.87.3063
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