Learning analytics and higher education: a proposed model for establishing informed consent mechanisms to promote student privacy and autonomy

@article{Jones2019LearningAA,
  title={Learning analytics and higher education: a proposed model for establishing informed consent mechanisms to promote student privacy and autonomy},
  author={Kyle M. L. Jones},
  journal={International Journal of Educational Technology in Higher Education},
  year={2019},
  volume={16},
  pages={1-22}
}
  • Kyle M. L. Jones
  • Published 1 December 2019
  • Computer Science
  • International Journal of Educational Technology in Higher Education
By tracking, aggregating, and analyzing student profiles along with students’ digital and analog behaviors captured in information systems, universities are beginning to open the black box of education using learning analytics technologies. However, the increase in and usage of sensitive and personal student data present unique privacy concerns. I argue that privacy-as-control of personal information is autonomy promoting, and that students should be informed about these information flows and… 

Students' Information Privacy Concerns in Learning Analytics: Towards a Model Development

A theoretical model is proposed to understand the IPC of students in relation to LA and explores the concept of IPC as a central construct between its two antecedents: perceived privacy vulnerability and perceived privacy control, and its consequences, trusting beliefs and self-disclosure behavior.

A measurement of faculty views on the meaning and value of student privacy

Learning analytics tools are becoming commonplace in educational technologies, but extant student privacy issues remain largely unresolved. It is unknown whether faculty care about student privacy

‘We’re Being Tracked at All Times’: Student Perspectives of Their Privacy in Relation to Learning Analytics in Higher Education

Higher education institutions are continuing to develop their capacity for learning analytics (LA), which is a socio-technical data mining and analytic practice. Institutions rarely inform their

"We're being tracked at all times": Student perspectives of their privacy in relation to learning analytics in higher education

Findings demonstrate that students lacked awareness of educational data mining and analytic practices, as well as the data on which they rely, and institutions must balance their desire to implement LA with their obligation to educate students about their analytic practices.

Sins of omission: Critical informatics perspectives on privacy in e‐learning systems in higher education

The COVID‐19 pandemic emptied classrooms across the globe and pushed administrators, students, educators, and parents into an uneasy alliance with online learning systems already committing serious

Do They Even Care? Measuring Instructor Value of Student Privacy in the Context of Learning Analytics

Learning analytics tools are becoming commonplace in educational technologies, but extant student privacy issues remain largely unresolved. It is unknown whether or not faculty care about student

Learning Analytics as a Service for Empowered Learners: From Data Subjects to Controllers

This work questions whether sincere consent is possible in the higher education setting, and shows how it might be possible to recognise the autonomy of the learner by providing LA as a service, rather than an intervention, which could indicate a paradigm shift towards the learners as empowered demander.

Be Careful What You Wish For! Learning Analytics and the Emergence of Data-Driven Practices in Higher Education

With the growing digitalization of the education sector, the availability of significant amounts of data, “big data,” creates possibilities for the use of artificial intelligence technologies to gain

Modeling Ethics: Approaches to Data Creep in Higher Education.

This work examines data ethics, from a larger institutional model to everyday enactments related to data creep, and proposes a remodeling of ethics that draws on recent works on data, justice, and refusal to pose generative questions for rethinking ethics in institutional contexts.

Learning Analytics for Educational Innovation: A Systematic Mapping Study of Early Indicators and Success Factors

A Learning Analytics Educational Process Innovation (LAEPI) model is proposed that leverages the ever-increasing amount of data that are recorded and stored about different learning activities or digital footprints of users within the educational domain to provide a method that proves to be useful towards maintaining continuous improvement and monitoring of different educational platforms.

References

SHOWING 1-10 OF 139 REFERENCES

Student privacy in learning analytics: An information ethics perspective

There are five crucial questions about student privacy that must be addressed in order to ensure that whatever the laudable goals and gains of learning analytics, they are commensurate with respecting students' privacy and associated rights, including (but not limited to) autonomy interests.

Student perceptions of privacy principles for learning analytics

It is concluded that all stakeholders need to be equally involved when learning analytics systems are implemented at higher education institutions and privacy principles are considered.

An elephant in the learning analytics room: the obligation to act

The moral and legal basis for the obligation to act is explored on the analyses of student data and how that obligation unfolds in two open distance education providers from the perspective of those in immediate contact with students and their learning journeys - the tutors or adjunct faculty.

Ethical and privacy principles for learning analytics

A set of principles is identified to narrow the scope of the discussion and point to pragmatic approaches to help design and research learning experiences where important ethical and privacy issues are considered.

Contemporary Privacy Theory Contributions to Learning Analytics

An overview of privacy is provided and the potential contribution contemporary privacy theories can make to learning analytics is considered, reflecting on the suitability of these theories towards the advancement of learning analytics.

Developing a Code of Practice for Learning Analytics

This paper outlines the extensive research and consultation activities which have been carried out to produce a document which covers the concerns of institutions and, critically, the students they serve.

Ethical oversight of student data in learning analytics: a typology derived from a cross-continental, cross-institutional perspective

The growth of learning analytics as a means to improve student learning outcomes means that student data is being collected, analyzed, and applied in previously unforeseen ways. As the use of this

Intentional Learning: The Need for Explicit Informed Consent in Higher Education

The idea of informed consent, if not the language and underlying logic, is increasingly taken for granted by patients, research sub jects, clients, and even consumers who wish to conduct themselves

Student Attitudes toward Learning Analytics in Higher Education: “The Fitbit Version of the Learning World”

Higher education students' knowledge, attitudes, and concerns about big data and learning analytics are explored through four focus groups, highlighting the need to engage students in the decision making process about learning analytics.

Harnessing ICT potential: The adoption and analysis of ICT systems for enhancing the student learning experience

– This paper aims to examine how effective higher education institutions have been in harnessing the data capture mechanisms from their student information systems, learning management systems and
...