Our proposal for a special issue in the British Journal for Technological Education (BJET) has been accepted!
The special issue is entitled “Technological Frameworks on Ethical and Trustworthy Learning Analytics”. It is focused on how we can leverage the latest research on Data Privacy and Ethics to build technological solutions and on how to integrate them into the design of Learning Analytics frameworks.
This is a cross-disciplinary issue so we are calling for LA practitioners, Data privacy and cybersecurity experts, Policy makers and Education providers to contribute with publications pertaining to the scope detailed below.
The link to the call in BJET can be found here.
Get in touch if you would like to contribute or if you just want to know more about the work we do.
Scope of the special issue
Technology has dramatically changed the way we learn with the proliferation of computers and connected devices in the learning environment to the rise of Massive Online Open Courses. The COVID-19 pandemic intensified this shift in 2020 with numerous education institutions digitising entire curriculums in record time. Many institutions are turning to Learning Analytics (LA) to help them improve the learning experience and outcome. Despite recent contributions there are still many challenges facing the field. LA relies on collecting, combining and sharing learning data. A process which raises ethical issues and data security and privacy concerns: from data ownership and stewardship, informed consent, privacy and security, trust and accountability, to fairness and equity in algorithmic LA solutions. Poorly implemented ethics and data privacy frameworks can negatively impact LA outcomes, reproducibility of results and in the long term undermine trust in the discipline.
Despite an abundance of research there are very few practical implementations of ethical LA frameworks in the Education Industry setting. This has been linked to a lack of proper technology infrastructure, knowledge of how to implement the frameworks and ability to scale the solutions. There is a clear gap between research and practice. Our aim with this special section is to bridge this gap by seeking expert opinions from relevant fields and improve communication and collaboration. We would like to focus the discussion on how to translate the latest and most innovative research in data privacy and security into practical tools and applications for an ethical and privacy aware LA.
We invite LA researchers, educators, technology providers, data privacy and cybersecurity experts as well as policy makers to contribute publications which may address, but are not limited to, one or more of the following topics:
- Privacy risk on learners’ data: assessment methodology, threat model analysis and mitigation strategies.
- Development of ethical and privacy aware LA algorithms: sensitivity of ML/AI algorithms to data privacy requirements, impact on fairness and equity, information leakage from ML/AI models and federated learning.
- Cross border data sharing and collaboration in LA within an ethical and privacy aware technology framework.
- Development and integration of data privacy tools in education.
- Data security in EdTech: challenges in online and offline learners’ data collection, processing, storage and transfer.
Submission and Inquiries
Interested authors are invited to submit an abstract first. The Abstract should demonstrate that the paper fits the special section focus, has a rigorous methodology, is innovative, makes a significant contribution to the field, is relevant to an international audience, and takes a critical approach. Full papers will undergo the standard reviewing process. Therefore, if based on your abstract, you are invited to submit a full paper, this invitation is just that and should not be taken as indication that the final paper will be accepted.
Abstracts should be around 250 words, clearly and concisely written, and generally include the following:
- An introduction of one or two sentences stating the research aims and educational context; e.g. undergraduate; high school; pre-school, or all levels.
- For empirical reports, a brief summary of the data collection methodology.
- A summary of the outcomes
- Concise conclusions and implications in two or three sentences. What new insights does this research provide? What is its unique and significant contribution to the field? How is it relevant for a diverse international audience?
Abstract submission emailed to the guest editors: August 30, 2021
Full paper submission: November 28th 2021
Last Article Acceptances: April 22nd 2022
Articles published online as soon as copyediting is completed.
Issue Publication July 2022.
- Dr. Srecko Joksimovic Research Fellow UniSA Education Futures University of South Australia srecko.Joksimovic@unisa.edu.au
- Dr. Thierry Rakotoarivelo Senior Research Scientist Data61, CSIRO Thierry.Rakotoarivelo@data61.csiro.au
- (Corresponding guest editor) Dr. Djazia Ladjal Senior Data Scientist Practera (EdTEch provider) Djazia@practera.com
- Dr. Chen Zhan Research Associate Centre for Change and Complexity in Learning, UniSA STEM University of South Australia Chen.Zhan@unisa.edu.au