Ethical issues in learning analytics: a review of the field

Tzimas, Dimitrios; Demetriadis, Stavros

doi:10.1007/s11423-021-09977-4

Cited by 60 publications

(49 citation statements)

References 91 publications

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“…Privacy, by nature, could be defined as “the right to be left alone”, which underscores the right of having personal information being protected (Muller, 2020 ). This digital revolution in education, particularly the use of AI and learning analytics in the field of education, entails a massive amount of personal data generated, captured, and analyzed to optimize learning experiences (Tzimas & Demetriadis, 2021 ; Pardo & Siemens, 2014 ). The personal data of teachers and learners may run the risk of privacy breaches.…”

Section: Ethical Principles For Artificial Intelligence In Education ...mentioning

confidence: 99%

Ethical principles for artificial intelligence in education

et al. 2022

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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.

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Section: Ethical Principles For Artificial Intelligence In Education ...mentioning

confidence: 99%

Ethical principles for artificial intelligence in education

et al. 2022

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“…Although some authors put emphasis on data ethics, the majority fail to make note of it (Ifenthaler & Tracey, 2016). A recent review of the ethical issues in learning analytics (Tzimas & Demetriadis, 2021) demonstrate the shortage of empirical evidence-based guidelines on educational data analytics ethics and highlight the need to establish codes of practices to monitor and evaluate the respective ethics policies, so that trusted partners may use educational data analytics responsibly to improve teaching and learning. In order for IDs and eTUTs to understand and critically think about the larger issues regarding EDL, they must have an understanding and awareness of the ethics surrounding data (Ifenthaler & Tracey, 2016).…”

Section: Environmental Scan Of Existing Edl Competence Framework and Coursesmentioning

confidence: 99%

Towards an educational data literacy framework: enhancing the profiles of instructional designers and e-tutors of online and blended courses with new competences

Papamitsiou

Filippakis

Poulou

et al. 2021

Smart Learn. Environ.

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In the era of digitalization of learning and teaching processes, Educational Data Literacy (EDL) is highly valued and is becoming essential. EDL is conceptualized as the ability to collect, manage, analyse, comprehend, interpret, and act upon educational data in an ethical, meaningful, and critical manner. The professionals in the field of digitally supported education, i.e., Instructional Designers (IDs) and e-Tutors (eTUTs) of online and blended courses, need to be ready to inform their decisions with educational data, and face the upcoming data-related challenges; they need to update and enhance their profiles with relevant competences. This paper proposes a framework for EDL competence profiles of IDs/eTUTs and evaluates the proposal with the participation of worldwide professionals (N = 210) with experience in digitally supported education. The evaluation aims at validating the proposal and assesses (a) the current EDL-readiness of IDs/eTUTs; and (b) the extent to which the framework captures and describes the essential EDL competences. The findings indicate that professionals are not EDL-competent yet, but the proposed dimensions and related competences are offering a solid approach to support EDL development.

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“…Öğrenme analitiklerinin tüm dünyadaki eğitim kurumlarının stratejik planlarını yapmak için kullandıkları kritik bir araç olarak görülmesi ile birlikte gizlilik, güvenlik ve etik gibi konular, üzerinde tartışılan önemli başlıklar haline gelmiştir [2]. Kurumların bir yandan öğrencilerin mahremiyetini bağlı bulundukları yasalar gereğince koruması bir yandan da kişiselleştirilmiş bir temelde öğretme ve öğrenmeyi destekleme amaçlarına ulaşmak için gerekli tüm verileri toplaması arasında bir denge kurması gerekmektedir [33,34]. ÖYS'ler, MOOC'lar, wikiler, arama motorları, sosyal medya kullanımı gibi pek çok kaynaktan elde edilen veriler öğrenme analitiği olarak kullanılabilmektedir.…”

Section: Güvenli̇k Standartlaşma Ve Eti̇k (Security Standarts and Ethical Issues)unclassified

E-Öğrenme Ortamları ve Öğrenme Analitikleri

Somyürek

Güyer

Atasoy

et al. 2021

Bilişim Teknolojileri Dergisi

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Özet-2020 yılı Horizon raporunda da vurgulandığı üzere, son yıllarda etkili öğrenme ortamları tasarlamak için ele alınan kavramlardan biri de öğrenme analitikleridir. Öğretim teknolojileri alanında, öğrenme analitiklerinin 10 yıllık bir geçmişi olmasına rağmen henüz gelişiminin erken aşamalarında olduğu düşünülmektedir. Öğrenme analitiklerinin kullanılabilmesi için eğitim bilimleri, istatistik, matematik, makine öğrenmesi ve yazılım geliştirme gibi disiplinler arası pek çok bilgi ve beceriye ihtiyaç duyulmaktadır. Bu çalışmanın amacı, öğrenme analitiklerinin e-öğrenme ortamları açısından potansiyelini ortaya koyarak öğretim tasarımcıları ve uygulayıcılar tarafından daha fazla tanınmasını sağlamaktır. Bu bağlamda, öğrenme analitiklerinin kapsamı, uygulama alanları ve aşamaları açıklanmaktadır. Ayrıca, öğrenme analitiklerinde kullanılan göstergeler, veri kaynakları, araç ve sistemler sunulmaktadır. Öğrenme analitiği süreç modeli ile öğrenme analitiği sunan öğrenme panellerinin kullanımı özetlenmektedir. Son olarak, bu konudaki güvenlik, etik ve standartlaşma kavramları ile ilgili çalışmalardaki sınırlıklar tartışılmaktadır.

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Ethical issues in learning analytics: a review of the field

Cited by 60 publications

References 91 publications

Ethical principles for artificial intelligence in education

Ethical principles for artificial intelligence in education

Towards an educational data literacy framework: enhancing the profiles of instructional designers and e-tutors of online and blended courses with new competences

E-Öğrenme Ortamları ve Öğrenme Analitikleri

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