🏷️ ethics
35 pages tagged with ethics(26 articles, 9 concepts)
📄 The AI Literacy Heptagon: A Structured Approach to AI Literacy in Higher Education
> **Synthesis:** Hackl, Müller, and Sailer (2026) present the AI Literacy Heptagon, a structured seven-dimensional framework for AI literacy (AIL) in higher education, developed through an integrative…
📄 Human Autonomy and Sense of Agency in Human-Robot Interaction: A Systematic Literature Review
> **Synthesis:** Glawe, Schmeckel, Brauner, and Ziefle (2025) systematically review empirical studies on human autonomy and sense of agency in human-robot interaction (HRI), aiming to bridge the gap b…
📄 Knowledge-Based Design Requirements for Generative Social Robots in Higher Education
> **Synthesis:** Vonschallen, Oberle, Schmiedel, and Eyssel (2026) adopt a knowledge-based design perspective to investigate what information tutoring-oriented generative social robots (GSRs) require …
🏷️ Learner Agency
> **Learner agency** — the capacity of learners to act intentionally, make choices, and exercise control over their own learning. In AI in education, agency is a central concern because AI tools can b…
2026-08-13 · agency, self-regulated-learning, motivation, student-experience, human-ai-collaboration
🏷️ AI Governance
> **AI governance** — the frameworks, policies, institutional structures, and norms that guide the responsible design, deployment, and use of artificial intelligence in education. Governance spans for…
🏷️ Social-Emotional Learning
> **Social-emotional learning (SEL)** — the process of developing the competencies that enable individuals to synchronize thoughts, emotions, and actions to foster positive interactions with oneself a…
2026-08-13 · ai-literacy, affective-computing, well-being, teacher-ai-competency, student-experience
🏷️ Well-Being
> **Well-being** — the positive state of being mentally, physically, and socially healthy, encompassing emotional, psychological, and social dimensions. In AI in education, well-being has become a cen…
📄 Technology, Education and Critical Media Literacy: Potential, Challenges, and Opportunities
> **Synthesis:** Based on expert interviews and a survey of 141 university students in Communication and Education programs, this study finds that while technology offers real opportunities for teachi…
📄 "It is a temptation to get it to do the work…" Student Experiences of Navigating the Generative AI Landscape in UK Higher Education: A Cross-Institutional Survey with International Comparison
> **Synthesis:** The StudentXGenAI Project surveyed more than 7,000 students across 7 UK institutions (September–December 2025) on GenAI use in their studies, comparing findings with a companion Austr…
📄 HAIML: A Human-Centered AI Metacognitive Learning Model — A Framework for Human Agency and Reflective Learning in the Age of Artificial Intelligence
> **Synthesis:** HAIML is a human-centered framework for learning in AI-supported environments that preserves human agency, metacognitive awareness, ethical reasoning, and personal responsibility. Gro…
2026-08-12 · metacognition, self-regulated-learning, human-in-the-loop, ai-literacy, cognitive-offloading
📄 Artificial Intelligence in UK Higher Educational Policy and Institutional Decision Making
> **Synthesis:** This systematic literature review examines how AI is positioned in UK higher-education policy and its influence on institutional pedagogical decision making, finding that AI integrati…
📄 Generative AI in Higher Education: A Systematic Review of Opportunities, Challenges, and Pedagogical Innovations (2022–2025)
> **Synthesis:** This PRISMA-guided systematic review synthesizes 125 peer-reviewed studies (2022–2025) on generative AI in higher education, documenting exponential adoption (92% student usage by 202…
📄 Human-Centric Artificial Intelligence Pedagogy (HCAP) framework developed from TPACK through integration of artificial intelligence literacy and competency
> **Synthesis:** Chiu (2026) proposes the Human-Centric AI Pedagogy (HCAP) framework, an evolution of the Technological Pedagogical Content Knowledge (TPACK) model designed for the generative AI era. …
📄 Metacognitive AI literacy: going beyond the AI skills gap agenda
> **Synthesis:** Shapiro, Souto-Otero, and Watermeyer (2026) argue that conventional AI literacy frameworks anchored in functional skills acquisition fail to address the fundamental epistemological ch…
📄 The (im)possibility of AI literacy
> **Synthesis:** Pangrazio (2026) offers a critical editorial questioning whether AI literacy is a meaningful or even achievable goal. Tracing the history of literacy from its elite origins through ma…
📄 Exploring interfaces and implications for integrating social-emotional competencies into AI literacy for education: a narrative review
> **Synthesis:** Palmquist, Sigurdardottir, and Myhre (2025) conduct a narrative literature review examining the intersection of AI literacy and social-emotional competencies (SEC) in education, propo…
📄 Teaching Intro AI When the Tools Can Do the Homework: A Course Redesign and a Student Bill of Rights
> **Synthesis:** This experience report describes the redesign of an introductory AI course at the University of Washington Bothell in response to LLMs being able to complete most assignments. The red…
🏷️ Educational AI Policy
> **Educational AI policy** — the formal and informal rules governing AI use in educational institutions, from national legislation to classroom guidelines. Policy research in the wiki spans instituti…
🏷️ Pedagogical Safety
> **Pedagogical safety** — the design principle that AI education systems must protect learners from harm, including inappropriate content, unsafe advice, biased treatment, and manipulative interactio…
🏷️ Privacy in AI Education
> **Privacy** — the protection of student data, identity, and autonomy in AI-augmented learning environments. Privacy concerns intensify as AI systems collect increasingly granular behavioral data for…
🏷️ AI Regulation in Education
> **AI regulation** — the laws, policies, and governance frameworks that control how AI is developed and deployed in educational settings. Regulation in the wiki spans government policy, institutional…
📄 Mapping the Emerging Curriculum for AI-Assisted Software Engineering via Syllabus Analysis
> **Synthesis:** This paper analyses 23 publicly available syllabi from upper-division, credit-bearing university courses that teach AI-assisted software development. The study identifies common curri…
📄 AI Literacy for Legal Translation: Developing Digital Resilience
> **Synthesis:** Proposes a four-component AI literacy framework for legal translation professionals: conceptual AI knowledge, technical operational skills, critical evaluation competencies, and ethic…
📄 When AI Wears Many Hats: The Role of Generative Artificial Intelligence in Marketing Education
> **When AI Wears Many Hats: The Role of Generative Artificial Intelligence in Marketing Education** — Uses multipronged analysis (syllabi review, educator survey, qualitative interviews) and Role The…
📄 Beyond Compliance: A Proposed Framework for Ethical Governance of Student Data in Learning Analytics
> **Beyond Compliance: A Proposed Framework for Ethical Governance of Student Data in Learning Analytics** — Proposes LEAGUE framework (Lawfulness, Equity, Agency, Governance, Utility, Ethics by Desig…
📄 The care-full craft of feedback in an age of generative AI
A conceptual/position paper arguing that feedback in an age of GenAI must be understood as **"matters of care"** — ethical, relational practices rather than information transmission. It builds on a te…
📄 Sycophantic AI makes human interaction feel more effortful and less satisfying over time
> Ibrahim, Hafner, Cheng, Lee, Anselmetti, Willer, Rocher & Yang (2026) provide large longitudinal experimental evidence (N = 3,075; 12,766 conversations; three-week census-representative U.S. sample)…
📄 A Longitudinal Analysis of Public Discourse on AI Ethics in Education Using Twitter Data
**Akriti Bagale, Nafisa Mehjabin, Ali Unlu, Aditya Johri, et al. (2026)** - George Mason University; University of Virginia. arXiv preprint. Bagale, A., Mehjabin, N., Unlu, A., Johri, A., et al. (2026…
🏷️ Bias Mitigation
> **Bias mitigation** in educational AI requires auditing models across the pipeline: [[gender-bias-transfer-llm-writing]], [[ai-scoring-language-bias-physics]], [[llm-cultural-relevance-k12]], and [[…
📄 Engagement Intensity as a Learner-Modeling Signal for Adaptive AI Ethics Instruction
> Engagement intensity during AI ethics instruction serves as an effective learner-modeling signal for adaptive instruction; prior LLM experience influences engagement patterns.…
📄 The Environmental Cost of LLMs in AIED: Reporting and Practices
> **Sabrina C. Eimler, Lukas Erle, Daniel Flood, Aditi Haiman, Luca Häckert, André Helgert, Lachlan McGinness, Büsra Yapici**…
📄 Beyond Tool Adoption: A Practical Five-Stage Developmental Continuum for AI Literacy in Higher Education
Proposes a five-stage developmental continuum (Not Engaged, Uncritical Use, Informed Use, Critical Evaluation, Improvement) for AI literacy at NC State; the continuum doubles as a diagnostic tool for …
📄 Cost-of-Ethics Crisis: Beliefs, Decisions, and Justifications in the Job Searches of Computer Science Students in Canada and the United States
This study examines the disconnect between **ethics education** and real-world decision-making among 129 computer science students and recent graduates during their job searches. Despite receiving con…
📄 Educational LLM Alignment
> Hardy & Kim (2026) identify a **cascading proxy** problem in AI-for-education evaluation: > The gap between what LLMs are *capable* of and what actually *benefits learners* — benchmark performance, …
📄 Robotics and Artificial Intelligence in Education: Transformations, Challenges, and Future Directions
> **Synthesis:** White & Wu (2026) critically examine the integration of AI and robotics into education, arguing that while transformative potential exists at all levels, effective integration require…