Human-centred learning analytics and AI in education: A systematic literature review

Computers and Education Artificial Intelligence, Год журнала: 2024, Номер 6, С. 100215 - 100215

Опубликована: Март 13, 2024

The rapid expansion of Learning Analytics (LA) and Artificial Intelligence in Education (AIED) offers new scalable, data-intensive systems but raises concerns about data privacy agency. Excluding stakeholders—like students teachers—from the design process can potentially lead to mistrust inadequately aligned tools. Despite a shift towards human-centred recent LA AIED research, there remain gaps our understanding importance human control, safety, reliability, trustworthiness implementation these systems. We conducted systematic literature review explore gaps. analysed 108 papers provide insights i) current state LA/AIED research; ii) extent which educational stakeholders have contributed systems; iii) balance between control computer automation such iv) reliability been considered literature. Results indicate some consideration system design, limited end-user involvement actual design. Based on findings, we recommend: 1) carefully balancing stakeholders' designing deploying throughout all phases 2) actively involving target end-users, especially students, delineate automation, 3) exploring as principles future

Язык: Английский

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Aligning and comparing values of ChatGPT and human as learning facilitators: A value‐sensitive design approach

British Journal of Educational Technology, Год журнала: 2025, Номер unknown

Опубликована: Янв. 15, 2025

Ethical considerations have become a central topic in education since artificial intelligence (AI) brought both great innovation and challenges to educational practices systems. Values influence what we believe is morally right guide how behave ethically different situations. However, there limited empirical research on improving the alignment between values embedded technology prioritised by learners. Using approach of value‐sensitive design (VSD), this study conducted an investigation explore: (1) ethical learners regarding facilitators were characterised online learning environment, (2) specific features ChatGPT human experts as embody these (3) value tensions occur environment. In order address questions, designed comparative experiment about writing revision facilitated ChatGPT‐4 expert. We semi‐structured interviews with 59 their experiences feelings after completing experiment. The results showed that responsiveness, social comfort, autonomy, freedom from bias privacy during learning. Compared expert, facilitator presented tirelessness, friendliness support for independent decision‐making embodying comfort autonomy. struggled interpret learners' intentions emotions posed risks information leakage, thereby presenting deficiency responsiveness privacy. Value arose within groups other stakeholders, including developers researchers. These emerged conflicting pragmatic Our findings highlight importance enhancing environments. strategies achieving include developing AI, leveraging strengths AI tools values, expanding VSD methodology AI's entire life cycle. Practitioner notes What already known has been demonstrated various advantages, but its use also brings challenges, particularly aligning Value‐sensitive (VSD) helps improve embedding stakeholders into design. environments remain under investigation. paper adds investigate characteristics learners, compare embodied experts, identify potential tension values. found shown advantages compared misalignment still not only learner such Implications practice and/or policy Educational should embed stakeholders' enhance seek balance Educators actively utilise powerful tool maximise Researchers consider methods cycle accommodate dynamism.

Язык: Английский

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Toward Asset-based Instruction and Assessment in Artificial Intelligence in Education

International Journal of Artificial Intelligence in Education, Год журнала: 2024, Номер unknown

Опубликована: Янв. 16, 2024

Язык: Английский

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Human‐Centred Learning Analytics: 2019–24

British Journal of Educational Technology, Год журнала: 2024, Номер 55(3), С. 755 - 768

Опубликована: Фев. 26, 2024

Abstract Human‐Centred Learning Analytics (HCLA) has emerged in the last 5 years as an active sub‐topic within Analytics, drawing primarily on theories and methods of Human‐Computer Interaction (HCI). HCLA researchers practitioners are adopting adapting HCI theories/methods to meet challenge meaningfully engaging educational stakeholders LA design process, evaluating systems use researching sociotechnical factors influencing successes failures. This editorial introduces contributions papers this special section, reflects more broadly field's emergence over five years, considers known gaps indicates new opportunities that may open next years.

Язык: Английский

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Learning about AI ethics from cases: a scoping review of AI incident repositories and cases

AI and Ethics, Год журнала: 2025, Номер unknown

Опубликована: Янв. 9, 2025

Abstract Cases provide a practical resource for learning regarding the uses and challenges of AI applications. give insight into how principles values are implicated in real contexts, trade-offs different perspectives held these the—sometimes hidden—relationships between cases, relationships that may support analogical reasoning across contexts. We aim to (1) an approach structuring ethics cases (2) investigate existing case repository structures. motivate scoping review through conceptual analysis desirable features. The sought retrieve repositories, (sometimes known as observatories, catalogues, galleries, or incident databases), their expression concepts. identify n = 14 extracting schema used each, this metadata can express ethical find most repositories focus on harm-indicators, with some indicating positive impacts, but little explicit reference concepts; subset (n 4) includes no structural elements addressing concepts impacts. extract from total 2000) education 100). These grouped by topic, structured content provided implications one sub-theme, offering qualitative insights coverage. Our empirical exemplify model (shorthanded Ethics-case-CPR), while highlighting gaps both specific examples cases.

Язык: Английский

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Value‐sensitive design of chatbots in environmental education: Supporting identity, connectedness, well‐being and sustainability

British Journal of Educational Technology, Год журнала: 2025, Номер unknown

Опубликована: Янв. 15, 2025

While offering the potential to support learning interactions, emerging AI applications like Large Language Models (LLMs) come with ethical concerns. Grounding technology design in human values can address ethics and ensure adoption. To this end, we apply Value‐Sensitive Design—involving empirical, conceptual technical investigations—to centre development evaluation of LLM‐based chatbots within a high school environmental science curriculum. Representing multiple perspectives expertise, help students refine their causal models climate change's impact on local marine ecosystems, communities individuals. We first perform an empirical investigation leveraging participatory explore that motivate educators engage chatbots. Then, conceptualize emerge from by grounding them research design, values, human‐AI interactions education. Findings illuminate considerations for students' identity development, well‐being, human–chatbot relationships sustainability. further map onto principles illustrate how these guide Our demonstrates conduct contextual, value‐sensitive inquiries emergent technologies educational settings. Practitioner notes What is already known about topic Generative artificial intelligence (GenAI) not only learning, but also raise concerns such as transparency, trust accountability. Value‐sensitive (VSD) presents systematic approach centring design. paper adds VSD education identify central supporting learning. investigations several stages GenAI development: conceptualization, evaluation. Implications practice and/or policy Identity human–AI sustainability are key designing Using stakeholders' generate metrics promote adoption engagement.

Язык: Английский

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Lessons Learnt from a Multimodal Learning Analytics Deployment In-the-Wild

ACM Transactions on Computer-Human Interaction, Год журнала: 2023, Номер 31(1), С. 1 - 41

Опубликована: Сен. 6, 2023

Multimodal Learning Analytics (MMLA) innovations make use of rapidly evolving sensing and artificial intelligence algorithms to collect rich data about learning activities that unfold in physical spaces. The analysis these is opening exciting new avenues for both studying supporting learning. Yet, practical logistical challenges commonly appear while deploying MMLA “in-the-wild”. These can span from technical issues related enhancing the space with capabilities, increased complexity teachers’ tasks. practicalities have been rarely investigated. This article addresses this gap by presenting a set lessons learnt 2-year human-centred in-the-wild study conducted 399 students 17 educators context nursing education. were synthesised into topics (i) technological/physical aspects deployment; (ii) multimodal interfaces; (iii) design process; (iv) participation, ethics privacy; (v) sustainability deployment.

Язык: Английский

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SLADE: A Method for Designing Human-Centred Learning Analytics Systems

Опубликована: Март 5, 2024

There is a growing interest in creating Learning Analytics (LA) systems that incorporate student perspectives. Yet, many LA still lean towards technology-centric approach, potentially overlooking human values and the necessity of oversight automation. Although some recent studies have adopted human-centred design stance, there limited research on establishing safe, reliable, trustworthy during early stages design. Drawing from newly proposed framework for artificial intelligence, we introduce SLADE, method ideating identifying features balance control computer We illustrate SLADE's application designing to support collaborative learning healthcare. Twenty-one third-year students participated sessions through four steps: i) challenges corresponding systems; ii) prioritising these iii) automation features; iv) refining emphasising safety, reliability, trustworthiness. Our results demonstrate potential assist researchers designers in: 1) aligning authentic with both divergent ideation convergent prioritisation; 2) understanding students' perspectives personal agency delegation teachers; 3) fostering discussions about trustworthiness solutions.

Язык: Английский

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Advancing equity and inclusion in educational practices with AI‐powered educational decision support systems (AI‐EDSS)

British Journal of Educational Technology, Год журнала: 2024, Номер 55(5), С. 1974 - 1981

Опубликована: Июль 10, 2024

Abstract A key goal of educational institutions around the world is to provide inclusive, equitable quality education and lifelong learning opportunities for all learners. Achieving this requires contextualized approaches accommodate diverse global values promote that best meet needs goals learners as individuals members different communities. Advances in analytics (LA), natural language processes (NLP), artificial intelligence (AI), especially generative AI technologies, offer potential aid decision making by supporting analytic insights personalized recommendations. However, these technologies also raise serious risks reinforcing or exacerbating existing inequalities; dangers arise from multiple factors including biases represented training datasets, technologies' abilities take autonomous decisions, tool development do not centre concerns historically marginalized groups. To ensure Educational Decision Support Systems (EDSS), particularly AI‐powered ones, are equipped equity, they must be created evaluated holistically, considering their both targeted systemic impacts on learners, Adopting a socio‐technical cultural perspective crucial designing, deploying, evaluating AI‐EDSS truly advance equity inclusion. This editorial introduces contributions five papers special section advancing inclusion practices with AI‐EDSS. These focus (i) review large models (LLMs) applications offers practical guidelines evaluation (ii) techniques mitigate disparities across countries languages LLMs representation educationally relevant knowledge, (iii) implementing intersectionality‐aware machine education, (iv) introducing LA dashboard aims institutional equality, diversity, inclusion, (v) vulnerable student digital well‐being Together, underscore importance an interdisciplinary approach developing utilizing only foster more inclusive landscape worldwide but reveal critical need broader contextualization incorporates questions what kinds decisions being used support, purposes, whose prioritized process.

Язык: Английский

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Value‐sensitive design in the praxis of instructional design: A view of designers in situ

British Journal of Educational Technology, Год журнала: 2025, Номер unknown

Опубликована: Фев. 10, 2025

Abstract Philosophical stances and design frameworks, such as value‐sensitive design, manifest in praxis through enacting specific approaches employing a variety of methods by the designers. Although it could overlap with other frameworks Instructional Design Technology (IDT) field, remains largely unexplored topic instructional for several reasons. As focuses on different stakeholders their values, recognizing contested issue universal we report this paper our empirical work that sought to describe values designers hold/express relation online courses. In study, communicated while discussing philosophies how they manifested designing human‐computer interactions promote authentic learning. Through theoretical lens provide detailed account designers' well showcase artefacts. investigation contribute ongoing discussion generate implications research education. These evolution field. Practitioner notes What is already known about (VSD), methods. VSD overlaps field manifests terms/frameworks. design. Designers' philosophies, judgements play significant role practice, are driving force behind enactment philosophical VSD. The IDT has not sufficiently addressed designer carrying out work. adds Detailed accounts care toward learners support learning environments. Specific examples designed artefacts qualify be designs. A contribution level expertise overall capacity evoke strong judgements. focusing themselves. Implications practice and/or policy scholars need focus more professional characters ethical orientations—as true guarantors design—and less prescriptive models. educators curricula developing so can aware examine them, cultivate and, most importantly, develop successful To able subscribe, enact even criticize expand designerly VSD, students mindset early journey. Designers have own nurture them new help become

Язык: Английский

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