ArticleEducation and information technologies2023
Ethical principles for artificial intelligence in education.
Article in Education and information technologies, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
57 citing papers in PubMed, 3 syntheses or guidelines pooled it, 917 citations in OpenAlex.
- Quality assurance in generative AI-mediated education: a bibliometric and scoping review.Frontiers in artificial intelligence · 2026Pooled it
- Investigating the use of generative AI policies among ASPPH member schools and programs of public health.Frontiers in public health · 2026Pooled it
- Advancements in artificial intelligence transforming medical education: a comprehensive overview.Medical education online · 2025Pooled it
- Designing, implementing, and evaluating a gamification approach in childbirth training for midwifery students using computer and mobile application.BMC medical education · 2025Trial
- Truth, tone, and trust: integrating an AI exercise to foster responsible science communication in a graduate biomedical science course.Journal of microbiology & biology education · 2026Article
- Mapping Current Use of Artificial Intelligence in Pharmacology Education via a Scoping Review.Pharmacology research & perspectives · 2026Article
- Turkish adaptation of the Artificial Intelligence Self-Efficacy Scale (AISES) and its role in prospective teachers' intentions to use AI in classroom practices.BMC psychology · 2026Article
- From Foundation to Intelligence Integration: The Synergistic Associations of ICT and AI Support with Pre-Service Teachers' TPACK Development.Behavioral sciences (Basel, Switzerland) · 2026Article
- Development and validation of the student readiness and anxiety scale for AI-assisted biology teaching (SRAS-AIBT).Scientific reports · 2026Article
- A privacy preserving synthetic learner dataset for learning analytics in technology enhanced higher education.Scientific reports · 2026Article
- Artificial Intelligence in Veterinary Education: Preparing the Workforce for Clinical Applications in Diagnostics and Animal Health.Veterinary sciences · 2026Review
- School Principals' Perspectives and Leadership Styles for Digital Transformation: A Q-Methodology Study.Behavioral sciences (Basel, Switzerland) · 2026Article
- Toward Smart VR Education in Media Production: Integrating AI into Human-Centered and Interactive Learning Systems.Biomimetics (Basel, Switzerland) · 2026Review
- Article
- Article
- Psychometric validation of the Turkish Brief General AI Self-Efficacy Scale: examining its role in AI anxiety, acceptance, and demographic predictors.Frontiers in psychology · 2026Article
- AI and higher education: teachers' perceptions of students' ethical tensions in online pedagogical methods.Frontiers in psychology · 2026Article
- EduFairBench: reproducible evaluation of large language models for educational assessment.Frontiers in artificial intelligence · 2026Article
- Exploring university physical education teachers' artificial intelligence use intention profiles: a Q-methodology study.Frontiers in psychology · 2026Article
- Artificial intelligence in college students' mental health education: opportunities, challenges, and strategic responses.Frontiers in psychology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The advancement of artificial intelligence in education (AIED) has the potential to transform the educational landscape and influence the role of all involved stakeholders. In recent years, the applications of AIED have been gradually adopted to progress our understanding of students' learning and enhance learning performance and experience. However, the adoption of AIED has led to increasing ethical risks and concerns regarding several aspects such as personal data and learner autonomy. Despite the recent announcement of guidelines for ethical and trustworthy AIED, the debate revolves around the key principles underpinning ethical AIED. This paper aims to explore whether there is a global consensus on ethical AIED by mapping and analyzing international organizations' current policies and guidelines. In this paper, we first introduce the opportunities offered by AI in education and potential ethical issues. Then, thematic analysis was conducted to conceptualize and establish a set of ethical principles by examining and synthesizing relevant ethical policies and guidelines for AIED. We discuss each principle and associated implications for relevant educational stakeholders, including students, teachers, technology developers, policymakers, and institutional decision-makers. The proposed set of ethical principles is expected to serve as a framework to inform and guide educational stakeholders in the development and deployment of ethical and trustworthy AIED as well as catalyze future development of related impact studies in the field.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.