Ethics, Big Data and Artificial Intelligence: Exploring Academic Works in the Educational Landscape

Big Data and Artificial Intelligence (AI) confer substantial advancements across diverse sectors of society, education included. However, it is imperative to extend the discourse surrounding these interventions to align with ethical research principles, data usage, and prevailing legislation. Consequently, this study endeavors to scrutinize scholarly literature spanning the interval between 2011 and 2022, concentrating on the ethical facets recommended for inquiries that meld big data and artificial intelligence within educational contexts. Employing a bibliographic research approach, the inquiry was conducted on the CAPES Periodicals Portal, utilizing descriptors such as “ethics,” “big data,” “artificial intelligence,” and “education.“ Out of a corpus of 84 articles, nine were incorporated into this research subsequent to the application of inclusion and exclusion criteria. These works encompass both empirical and theoretical contributions, interlinking big data and AI with educational settings. Researchers employ documentary sources, questionnaires, and their individual pedagogical experiences for data collection. Methodologically, these studies lean towards techniques such as descriptive content analysis, descriptive statistical analysis, confirmatory factor analysis, and textual data mining for data analysis. With regard to ethical principles spotlighted in the studies, salient themes include responsibility, transparency, reliability, and privacy. The outcomes suggest that crucial lacunae still exist, particularly concerning aspects like informed consent and other pivotal ethical protocols.