The AI Literacy Heptagon: A Structured Approach to AI Literacy in Higher Education

• URL: http://arxiv.org/abs/2509.18900v1
• Date: Tue, 23 Sep 2025 11:28:30 GMT
• Title: The AI Literacy Heptagon: A Structured Approach to AI Literacy in Higher Education
• Authors: Veronika Hackl, Alexandra Mueller, Maximilian Sailer,
• Abstract summary: The study aims to bridge the gap between theoretical AIL conceptualizations and the practical implementation in academic curricula.<n>Our analysis identifies seven central dimensions of AIL: technical, applicational, critical thinking, ethical, social, integrational, and legal.
• Score: 41.99844472131922
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The integrative literature review addresses the conceptualization and implementation of AI Literacy (AIL) in Higher Education (HE) by examining recent research literature. Through an analysis of publications (2021-2024), we explore (1) how AIL is defined and conceptualized in current research, particularly in HE, and how it can be delineated from related concepts such as Data Literacy, Media Literacy, and Computational Literacy; (2) how various definitions can be synthesized into a comprehensive working definition, and (3) how scientific insights can be effectively translated into educational practice. Our analysis identifies seven central dimensions of AIL: technical, applicational, critical thinking, ethical, social, integrational, and legal. These are synthesized in the AI Literacy Heptagon, deepening conceptual understanding and supporting the structured development of AIL in HE. The study aims to bridge the gap between theoretical AIL conceptualizations and the practical implementation in academic curricula.

Related papers

• Report on the Scoping Workshop on AI in Science Education Research 2025 [2.0613397238713778]
  Report summarizes the outcomes of a two-day international scoping workshop on the role of artificial intelligence (AI) in science education research.<n>As AI rapidly reshapes scientific practice, classroom learning, and research methods, the field faces both new opportunities and significant challenges.<n>Report concludes with actionable recommendations for training, infrastructure, and standards, along with guidance for funders, policymakers, professional organizations, and academic departments.
  arXiv  Detail & Related papers  (2025-11-18T10:23:22Z)
• A Structured Unplugged Approach for Foundational AI Literacy in Primary Education [7.495145157323768]
  We propose a structured teaching approach that fosters foundational AI literacy in primary students.<n>Our results indicate improvements in terminology understanding and usage, features description, logical reasoning, and evaluative skills.<n>The approach proved engaging, with students particularly enjoying activities that linked AI concepts to real-world reasoning.
  arXiv  Detail & Related papers  (2025-05-27T16:23:57Z)
• A Theory-driven Interpretation and Elaboration of Verification and Validation [49.97673761305336]
  This paper presents a formal theory of verification and validation (V&V) within systems engineering.<n>We develop precise definitions of verification and validation, articulating their roles in confirming and contextualizing knowledge about systems.
  arXiv  Detail & Related papers  (2025-04-11T17:58:07Z)
• Form-Substance Discrimination: Concept, Cognition, and Pedagogy [55.2480439325792]
  This paper examines form-substance discrimination as an essential learning outcome for curriculum development in higher education.<n>We propose practical strategies for fostering this ability through curriculum design, assessment practices, and explicit instruction.
  arXiv  Detail & Related papers  (2025-04-01T04:15:56Z)
• AI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative Review [3.5297361401370044]
  There is little consensus among researchers and practitioners on how to discuss and design AI literacy interventions.<n>This paper applies an integrative review method to examine empirical and theoretical AI literacy studies published since 2020.
  arXiv  Detail & Related papers  (2025-02-27T23:32:03Z)
• Towards Bidirectional Human-AI Alignment: A Systematic Review for Clarifications, Framework, and Future Directions [101.67121669727354]
  Recent advancements in AI have highlighted the importance of guiding AI systems towards the intended goals, ethical principles, and values of individuals and groups, a concept broadly recognized as alignment. The lack of clarified definitions and scopes of human-AI alignment poses a significant obstacle, hampering collaborative efforts across research domains to achieve this alignment. We introduce a systematic review of over 400 papers published between 2019 and January 2024, spanning multiple domains such as Human-Computer Interaction (HCI), Natural Language Processing (NLP), Machine Learning (ML)
  arXiv  Detail & Related papers  (2024-06-13T16:03:25Z)
• A Literature Review of Literature Reviews in Pattern Analysis and Machine Intelligence [51.26815896167173]
  We present a comprehensive tertiary analysis of PAMI reviews along three complementary dimensions.<n>Our analyses reveal distinctive organizational patterns as well as persistent gaps in current review practices.<n>Finally, our evaluation of state-of-the-art AI-generated reviews indicates encouraging advances in coherence and organization.
  arXiv  Detail & Related papers  (2024-02-20T11:28:50Z)
• Computational Argumentation and Cognition [0.3867363075280543]
  This paper stems from the 1st Workshop on Computational Argumentation and Cognition (COGNITAR) It argues that within the context of Human-Centric AI the use of theory and methods from Computational Argumentation for the study of Cognition can be a promising avenue to pursue. The paper presents the main problems and challenges in the area that would need to be addressed, both at the scientific level but also at the level of synthesis of ideas and approaches from the various disciplines involved.
  arXiv  Detail & Related papers  (2021-11-12T21:44:30Z)
• An interdisciplinary conceptual study of Artificial Intelligence (AI) for helping benefit-risk assessment practices: Towards a comprehensive qualification matrix of AI programs and devices (pre-print 2020) [55.41644538483948]
  This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence. The aim is to identify shared notions or discrepancies to consider for qualifying AI systems.
  arXiv  Detail & Related papers  (2021-05-07T12:01:31Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.