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Abstract Students' physical and digital lives are increasingly entangled. It is difficult to separate students' digital well‐being from their offline well‐being given that artificial intelligence increasingly shapes both. Within the context of education's fiduciary and moral duty to ensure safe, appropriate and effective digital learning spaces for students, the continuing merger between artificial intelligence and learning analytics not only opens up many opportunities for more responsive teaching and learning but also raises concerns, specifically for previously disadvantaged and vulnerable students. While digital well‐being is a well‐established research focus, it is not clear how AI‐Powered Educational Decision Support Systems (AI‐EDSS) might impact on the inherent, situational and pathogenic vulnerability of students. In this conceptual paper, we map the digital well‐being of previously disadvantaged and vulnerable students in four overlapping fields, namely (1) digital well‐being research; (2) digital well‐being research in education; (3) digital well‐being research in learning analytics; and (4) digital well‐being in AI‐informed educational contexts. With this as the basis, we engage with six domains from the IEEE standard 7010–2020 — IEEE Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well‐Being and provide pointers for safeguarding and enhancing disadvantaged and vulnerable student digital well‐being in AI‐EDSS. Practitioner notes What is already known about this topic Digital well‐being research is a well‐established focus referring to the impact of digital engagement on human well‐being. Digital well‐being is effectively inseparable from general well‐being as it is increasingly difficult to disentangle our online and offline lives and, as such, inherently intersectional. Artificial Intelligence shows promise for enhancing human digital well‐being, but there are concerns about issues such as privacy, bias, transparency, fairness and accountability. The notion of ‘vulnerable individuals’ includes individuals who were previously disadvantaged, and those with inherent, situational and/or pathogenic vulnerabilities. While current advances in AI‐EDSS may support identification of digital wellness, proxies for digital wellness should be used with care. What this study contributes An overview of digital well‐being research with specific reference how it may impact on vulnerable students. Illustrates specific vulnerabilities in five domains from the IEEE standard 7010–2020 — IEEE Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well‐Being selected for their significance in online learning environments. Pointers for the design and implementation of fair, ethical, accountable, and transparent AI‐EDSS with specific reference to vulnerable students. Implications for practice and/or policy Fairness, equity, transparency and accountability in AI‐EDSS affect all students but may have a greater (positive or negative) impact on vulnerable students. A critically informed understanding of the nature of students' vulnerability—whether as inherent, situational and/or pathogenic, as well as temporal/permanent aspects—is crucial. Since AI‐EDSS can exacerbate existing vulnerabilities resulting in pathogenic vulnerability, care is needed when designing AI‐EDSS.
Prinsloo et al. (Tue,) studied this question.