The DOI matches its Crossref record; 60 of the 63 references it cites were found in a registry or an index.
Student privacy self-management: implications for learning analytics
Abstract
Optimizing the harvesting and analysis of student data promises to clear the fog surrounding the key drivers of student success and retention, and provide potential for improved student success. At the same time, concerns are increasingly voiced around the extent to which individuals are routinely and progressively tracked as they engage online. The Internet, the very thing that promised to open up possibilities and to break down communication barriers, now threatens to narrow it again through the panopticon of mass surveillance.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“So-called “nudging” techniques direct students toward particular learning resources or to change their behaviors.90”
From Learning Analytics and the Academic Library: Professional Ethics Commitments at a Crossroads (2018) · cites this paper as [90]
In the citing paper
“In an analysis of the TACs of three providers of massive open online courses (MOOCs) namely Coursera, EdX, and FutureLearn, Prinsloo and Slade (2015) found several troubling gaps in both the providers' fiduciary duty to students and their consideration for the inherent privacy issues and resulting student vulnerability.”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“Though the intention of collecting and using student data arguably falls within the scope of the fiduciary duty of higher education, it is increasingly possible that student data may be also used inappropriately and unethically, further increasing the vulnerability of students (Prinsloo & Slade, 2015).”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“Individuals may adapt decisions regarding how much information they are prepared to share (and for what purpose) depending on the context.”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“In this context, HEIs are increasingly vulnerable and must optimize their use of data, in particular student data (Baker & Siemens, 2014;Gašević & Siemens, 2015;Prinsloo & Slade, 2015).”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“Prinsloo and Slade (2015) identified the following problems regarding the notion of informed consent: 1) the problem of scale; 2) the re-identification and the problem of aggregation; 3) the quality, accountability, and purpose of data; 4) the drawbacks in setting limitations for use; 5) the impact of the increasing openness and sharing of data; and 6) the problematics and understandings of user a”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“This study found that the length, font size, and number of headings used in these TACs would, in all probability, discourage engagement, so that users would accept the TACs without reading them.”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“There was no indication whether that use would include a depersonalization of the data.”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“Interestingly, while all three providers acknowledged that they used cookies to collect data, only one (FutureLearn) provided a list of cookies with clear descriptions of their function.”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“One MOOC provider explicitly stated that they may request information from third parties such as credit reference agencies.”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“One provider (EdX) alerted users that student posts are owned by EdX in perpetuity and could be used for whatever purposes EdX decides.”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“All three providers made it clear that disabling the cookies would disrupt the service, potentially to the extent that it would be rendered unusable.”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“All three providers stated clearly that all information provided by users would be collected and used.”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“Only one, FutureLearn, provided an opportunity (for a small fee) for users to request access to the data held by the company (in line with national data protection requirements).”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“In following Solove (2013), Prinsloo and Slade suggest that despite concerns about the effectiveness of regulation and legislation, we cannot altogether negate the role of substantive rules and hard boundaries”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“Interestingly, and of some concern, was the encouragement by FutureLearn for users to reveal personal details such as gender, location, and history in order to deepen the personal element in the learning.”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“None of the providers gave the option to opt out -indeed, users were alerted to the inability of their MOOC provider to ensure and guarantee that information shared would not be used by fellow users or made public because of security breaches.”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
In the citing paper
“Regarding the collected data, all three stated that it would be used to increase the efficiency of the platform and the structure of the learning experience.”
From Student Vulnerability, Agency and Learning Analytics: An Exploration (2016) · cites this paper as Prinsloo & Slade, 2015
Citations
Cites
Three Approaches to Qualitative Content Analysis
Hsieh, H.-F., & Shannon, S. E. (2005) · Qualitative Health Research · doi:10.1177/1049732305276687 · Cited by 44,601
The qualitative content analysis process
Elo, S., & Kyngäs, H. (2008) · Journal of Advanced Nursing · doi:10.1111/j.1365-2648.2007.04569.x · Cited by 22,617
Warren, S. D., & Brandeis, L. D. (1890) · University of Washington Press eBooks · doi:10.1515/9780295803661-014 · Cited by 4,092
Content analysis: Method, applications, and issues
Downe‐Wamboldt, B. (1992) · Health Care for Women International · doi:10.1080/07399339209516006 · Cited by 2,682
Penetrating the Fog: Analytics in Learning and Education.
Siemens, G., & Long, P. (2011) · Adelaide Research & Scholarship (AR&S) (University of Adelaide) · Cited by 1,752
Learning Analytics: The Emergence of a Discipline
Siemens, G. (2013) · American Behavioral Scientist · doi:10.1177/0002764213498851 · Cited by 1,284
Applications of Social Research Methods to Questions in Information and Library Science
(2016) · Libraries Unlimited eBooks · doi:10.5040/9798400613739 · Cited by 1,109
Learning Analytics: Ethical Issues and Dilemmas
Slade, S., & Prinsloo, P. (2013) · American Behavioral Scientist · doi:10.1177/0002764213479366 · Cited by 1,078
Self-citationAnalyzing brain networks with PCA and conditional Granger causality
Zhou, Z., Chen, Y., Ding, M., Wright, P. K., Lu, Z., & Liu, Y. (2008) · Human Brain Mapping · doi:10.1002/hbm.20661 · Cited by 994
Higher education and its communities: Interconnections, interdependencies and a research agenda
Jongbloed, B. W. A., Enders, J., & Salerno, C. (2008) · Higher Education · doi:10.1007/s10734-008-9128-2 · Cited by 965
Research works printed but not linked: 13
- Brandimarte L. Acquisti A. and Loewenstein G. 2013. Misplaced confidences: privacy and the control paradox. Social Psychological and Personality Science 4 (2013) 340--347. DOI: 10.1177/1948550612455931 · DOI · Paper page
- DeAngelis W. 2014. Academic deans codes of ethics and ... fiduciary duties? Journal for Academic Ethics 12 (2014) 209--225. DOI: 10.1007/s10805-014-9212-4 · DOI
- Eggers , D. 2013. The circle . Penguin , London, UK . Eggers, D. 2013. The circle. Penguin, London, UK.
- Elo S. and Kyngäs H. 2007. The qualitative content analysis process Journal of Advanced Nursing 62 (2007) 107--115. DOI: 10.1111/j.1365-2648.2007.04569.x. · DOI · Paper page
- Kharouf H. Sekhon H. and Roy S. K. 2014. The components of trustworthiness for higher education: a transnational perspective. Studies in Higher Education . DOI: 10.1080/03075079.2014.881352 · DOI
- Lee B. A. 2014. Student-faculty academic conflicts: emerging legal theories and judicial review. Mississippi Law Journal 83 (2014) 837--951. Lee B. A. 2014. Student-faculty academic conflicts: emerging legal theories and judicial review. Mississippi Law Journal 83 (2014) 837--951.
- Lincoln , Y. S. and Guba , E. G . 1985 . Naturalistic inquiry. London, UK: SAGE Publications. Lincoln, Y. S. and Guba, E. G. 1985. Naturalistic inquiry. London, UK: SAGE Publications.
- Lyon , D. (Ed.). 2006 . Theorising surveillance. The panopticon and beyond. Cullumpton, UK: Willan Publishing. Lyon, D. (Ed.). 2006. Theorising surveillance. The panopticon and beyond. Cullumpton, UK: Willan Publishing.
- Nissenbaum H. 2004. Privacy as contextual integrity. Washington Law Review 79 (2004) 119--158. Nissenbaum H. 2004. Privacy as contextual integrity. Washington Law Review 79 (2004) 119--158.
- Slade S. and Prinsloo P. 2013. Learning analytics: ethical issues and dilemmas. American Behavioral Scientist . DOI: 10.1177/0002764213479366 · DOI · Paper page
- Solove , D. J. 2004 The digital person . New York University Press , New York, NY . Solove, D. J. 2004 The digital person. New York University Press, New York, NY.
- Tene O and Polonetsky J. 2012. Big data for all: Privacy and user control in the age of analytics. Northwestern Journal of Technology and Intellectual Property 239 (2012) 1--36. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2149364 Tene O and Polonetsky J. 2012. Big data for all: Privacy and user control in the age of analytics. Northwestern Journal of Technology and Intellectual Property 239 (2012) 1--36. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2149364
- 10.2307/1321160 · DOI
Cited by
Sorted by citations
Utilising learning analytics to support study success in higher education: a systematic review
Ifenthaler, D., & Yau, J. Y.-K. (2020) · Educational Technology Research and Development · doi:10.1007/s11423-020-09788-z · Cited by 1,063
Drachsler, H., & Greller, W. (2016) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2883851.2883893 · Cited by 374
Student perceptions of privacy principles for learning analytics
Ifenthaler, D., & Schumacher, C. (2016) · Educational Technology Research and Development · doi:10.1007/s11423-016-9477-y · Cited by 314
Navigating the New Normal: Adapting Online and Distance Learning in the Post-Pandemic Era
Sato, S. N., Condés, E., Rubio-Zarapuz, A., Dalamitros, A. A., Sepulveda, R. A. Y., Tornero-Aguilera, J. F., & Clemente‐Suárez, V. J. (2023) · Education Sciences · doi:10.3390/educsci14010019 · Cited by 269
Jones, K. M. L., Asher, A., Goben, A. H., Perry, M. R., Salo, D., Briney, K. A., & Robertshaw, M. B. (2020) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24358 · Cited by 163
Student Vulnerability, Agency and Learning Analytics: An Exploration
Prinsloo, P., & Slade, S. (2016) · Journal of Learning Analytics · doi:10.18608/jla.2016.31.10 · Cited by 147
Self-citationFrom Data to Insights: A Layered Storytelling Approach for Multimodal Learning Analytics
Martinez-Maldonado, R., Echeverria, V., Fernandez Nieto, G., & Buckingham Shum, S. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376148 · Cited by 123
Willis, J. E., Slade, S., & Prinsloo, P. (2016) · Educational Technology Research and Development · doi:10.1007/s11423-016-9463-4 · Cited by 115
Self-citationPrivacy-Preserving Learning Analytics: Challenges and Techniques
Gürsoy, M. E., İnan, A., Nergiz, M. E., & Saygın, Y. (2016) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2016.2607747 · Cited by 113
Learning analytics at the intersections of student trust, disclosure and benefit
Slade, S., Prinsloo, P., & Khalil, M. (2019) · International Conference on Learning Analytics and Knowledge · doi:10.1145/3303772.3303796 · Cited by 116
Self-citationDrachsler, H., & Kalz, M. (2016) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12135 · Cited by 110
The SHEILA Framework: Informing Institutional Strategies and Policy Processes of Learning Analytics
Tsai, Y.-S., Moreno-Marcos, P. M., Jivet, I., Scheffel, M., Tammets, K., Kollom, K., & Gašević, D. (2018) · Journal of Learning Analytics · doi:10.18608/jla.2018.53.2 · Cited by 93
Students' privacy concerns in learning analytics: Model development
Mutimukwe, C., Viberg, O., Oberg, L., & Cerratto‐Pargman, T. (2022) · British Journal of Educational Technology · doi:10.1111/bjet.13234 · Cited by 90
Working Together in Learning Analytics Towards the Co-Creation of Value
Dollinger, M., Liu, D., Arthars, N., & Lodge, J. M. (2019) · Journal of Learning Analytics · doi:10.18608/jla.2019.62.2 · Cited by 101
Cerratto Pargman, T., & McGrath, C. (2021) · Journal of Learning Analytics · doi:10.18608/jla.2021.1 · Cited by 88
Lawson, C., Beer, C., Rossi, D. M., Moore, T., & Fleming, J. (2016) · Educational Technology Research and Development · doi:10.1007/s11423-016-9459-0 · Cited by 86
Understanding privacy and data protection issues in learning analytics using a systematic review
Liu, Q., & Khalil, M. (2023) · British Journal of Educational Technology · doi:10.1111/bjet.13388 · Cited by 113
Learning Analytics and the Academic Library: Professional Ethics Commitments at a Crossroads
Jones, K., & Salo, D. (2018) · College & Research Libraries · doi:10.5860/crl.79.3.304 · Cited by 85
The answer is (not only) technological: Considering student data privacy in learning analytics
Prinsloo, P., Slade, S., & Khalil, M. (2022) · British Journal of Educational Technology · doi:10.1111/bjet.13216 · Cited by 77
Self-citationPutting an ethical lens on learning analytics
West, D., Huijser, H., & Heath, D. (2016) · Educational Technology Research and Development · doi:10.1007/s11423-016-9464-3 · Cited by 77
It's My Data! Tensions Among Stakeholders of a Learning Analytics Dashboard
Sun, K., Mhaidli, A. H., Watel, S., Brooks, C. A., & Schaub, F. (2019) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300824 · Cited by 77
Brown, M., & Klein, C. (2020) · The Journal of Higher Education · doi:10.1080/00221546.2020.1770045 · Cited by 68
Learning analytics: A glance of evolution, status, and trends according to a proposed taxonomy
Peña‐Ayala, A. (2018) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1243 · Cited by 65
The Student Expectations of Learning Analytics Questionnaire
Whitelock‐Wainwright, A., Gašević, D., Tejeiro, R., Tsai, Y., & Bennett, K. (2019) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12366 · Cited by 63
Big Data, Higher Education and Learning Analytics: Beyond Justice, Towards an Ethics of Care
Prinsloo, P., & Slade, S. (2016) · Springer eBooks · doi:10.1007/978-3-319-06520-5_8 · Cited by 68
Self-citationStudent perceptions of their privacy in leaning analytics applications
Arnold, K. E., & Sclater, N. (2017) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3027385.3027392 · Cited by 56
Tsai, Y., Moreno-Marcos, P. M., Tammets, K., Kollom, K., & Gašević, D. (2018) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3170358.3170367 · Cited by 55
Learning Analytics Challenges to Overcome in Higher Education Institutions
Leitner, P., Ebner, M., & Ebner, M. (2019) · Springer eBooks · doi:10.1007/978-3-319-64792-0_6 · Cited by 54
Mobile learning analytics in higher education: usability testing and evaluation of an app prototype
Kuhnel, M., Seiler, L., Honal, A., & Ifenthaler, D. (2018) · Interactive Technology and Smart Education · doi:10.1108/itse-04-2018-0024 · Cited by 52
Hoel, T., & Chen, W. (2016) · Journal of Learning Analytics · doi:10.18608/jla.2016.31.9 · Cited by 47
Thoma, B., Warm, E. J., Hamstra, S. J., Cavalcanti, R. B., Pusic, M. V., Shaw, T. J., Verma, A., Frank, J. R., & Hauer, K. E. (2020) · Journal of Graduate Medical Education · doi:10.4300/jgme-d-19-00493.1 · Cited by 44
Amin, M. R. M., Ismail, I., & Sivakumaran, V. M. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.101308 · Cited by 85
Ethics and Privacy as Enablers of Learning Analytics
Gašević, D., Dawson, S., & Jovanović, J. (2016) · Journal of Learning Analytics · doi:10.18608/jla.2016.31.1 · Cited by 40
Learner Privacy in MOOCs and Virtual Education
Zeide, E., & Nissenbaum, H. F. (2018) · Theory and Research in Education · doi:10.1177/1477878518815340 · Cited by 39
Roberts, L. D., Chang, V., & Gibson, D. (2016) · Springer eBooks · doi:10.1007/978-3-319-06520-5_7 · Cited by 37
More Than Figures on Your Laptop: (Dis)trustful Implementation of Learning Analytics
Tsai, Y., Whitelock‐Wainwright, A., & Gašević, D. (2021) · Journal of Learning Analytics · doi:10.18608/jla.2021.7379 · Cited by 35
Digital analytics in professional work and learning
Edwards, R., & Fenwick, T. (2016) · Studies in Continuing Education · doi:10.1080/0158037x.2015.1074894 · Cited by 30
Thoma, B., Ellaway, R., & Chan, T. M. (2021) · Academic Medicine · doi:10.1097/acm.0000000000004092 · Cited by 30
Viberg, O., Kizilcec, R. F., Jivet, I., Martínez‐Monés, A., Oh, A. H., Mutimukwe, C., Hrastinski, S., & Scheffel, M. (2024) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2024.100416 · Cited by 41
Student data privacy in MOOCs: a sentiment analysis
Prinsloo, P., Slade, S., & Khalil, M. (2019) · Distance Education · doi:10.1080/01587919.2019.1632171 · Cited by 29
Self-citationWang, Q., Jing, S., & Goel, A. K. (2022) · Designing Interactive Systems Conference · doi:10.1145/3532106.3533534 · Cited by 35
Ethics in educational technology research: Informing participants on data sharing risks
Beardsley, M., Santos, P., Hernández‐Leo, D., & Michos, K. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12781 · Cited by 39
Protecting Privacy in AI-Enhanced Education
Ismail, I. A. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-0884-4.ch006 · Cited by 25
Advancing privacy in learning analytics using differential privacy
Liu, Q., Shakya, R., Khalil, M., & Jovanović, J. (2025) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3706468.3706493 · Cited by 30
Digital Colonialism: South Africa’s Education Transformation in the Shadow of Silicon ValleyPreprint
Kwet, M. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3496049 · Cited by 28
Lünich, M., Keller, B., & Marcinkowski, F. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100305 · Cited by 36
Digital Technology as Affordance and Barrier in Higher Education
Smale, M. A., & Regalado, M. (2016) · Springer eBooks · doi:10.1007/978-3-319-48908-7 · Cited by 23
User Consent in MOOCs – Micro, Meso, and Macro Perspectives
Khalil, M., Prinsloo, P., & Slade, S. (2018) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v19i5.3908 · Cited by 28
Self-citationInteligencia Artificial en la Educación Avances y Desafíos Multidisciplinarios.
Barahona-Martínez, G. E., Gallardo-Chiluisa, N. N., Caiza, Y. E. Q., Jiménez-Rivas, D. E., Caicedo-Basurto, R. L., Guanotuña-Yaulema, J. A., Flores-Cruz, P. L., & Hernández, D. M. G. (2024) · Editorial Grupo AEA eBooks · doi:10.55813/egaea.l.101 · Cited by 24
Developing a Multimodal Classroom Engagement Analysis Dashboard for Higher-Education
Sabuncuoğlu, A., & Sezgin, T. M. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3593240 · Cited by 20
Learning Analytics within Higher Education: Autonomy, Beneficence and Non-maleficence
O’Donoghue, K. (2022) · Journal of Academic Ethics · doi:10.1007/s10805-021-09444-y · Cited by 17
A Complete Validated Learning Analytics Framework
Tlili, A., Essalmi, F., Jemni, M., Kinshuk, K., & Chen, N. (2018) · International Journal of Information and Communication Technology Education · doi:10.4018/ijicte.2018040101 · Cited by 16
Digital Human Sciences: New Objects – New Approaches
(2021) · doi:10.16993/bbk · Cited by 17
Policy Matters: Expert Recommendations for Learning Analytics Policy
Scheffel, M., Tsai, Y.-S., Gašević, D., & Drachsler, H. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-29736-7_38 · Cited by 16
Educational Data Analytics for Teachers and School Leaders
Mougiakou, S., Vinatsella, D., Sampson, D. G., Papamitsiou, Z. K., Giannakos, M. N., & Ifenthaler, D. (2022) · Advances in analytics for learning and teaching · doi:10.1007/978-3-031-15266-5 · Cited by 25
Viberg, O., Mutimukwe, C., & Grönlund, Å. (2022) · Journal of Learning Analytics · doi:10.18608/jla.2022.7751 · Cited by 15
Developing a Strategic Approach to MOOCs
Ferguson, R., Eileen Scanlon, A., & Harris, L. (2016) · Journal of Interactive Media in Education · doi:10.5334/jime.439 · Cited by 15
Lee, H. H., & Gargroetzi, E. C. (2023) · Journal of Learning Analytics · doi:10.18608/jla.2023.7787 · Cited by 14
Virtuous Business Intelligence
McBride, N. K. (2015) · International Journal of Business Intelligence Research · doi:10.4018/ijbir.2015070101 · Cited by 14
Hakami, E., & Hernández‐Leo, D. (2020) · Repositori digital de la UPF (Universitat Pompeu Fabra) · Cited by 13
Prestigiacomo, R., Hadgraft, R. G., Hunter, J. L., Lockyer, L., Knight, S., van den Hoven, E., & Martínez‐Maldonado, R. (2020) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3375462.3375475 · Cited by 13
Chang, M. A., Tissenbaum, M., Philip, T. M., & D’Mello, S. K. (2025) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2025.100364 · Cited by 12
Understanding students’ effective use of data in the age of big data in higher education
Xing, W., & Wang, X. (2021) · Behaviour and Information Technology · doi:10.1080/0144929x.2021.1936176 · Cited by 16
Modeling Ethics: Approaches to Data Creep in Higher Education
Whitman, M. (2021) · Science and Engineering Ethics · doi:10.1007/s11948-021-00346-1 · Cited by 15
Pargman, T. C., & McGrath, C. (2021) · doi:10.16993/bbk.i · Cited by 12
Student Privacy and Learning Analytics
Francis, M. A., Avoseh, M. B. M., Card, K., Newland, L. A., & Streff, K. (2023) · Journal of Learning Analytics · doi:10.18608/jla.2023.7975 · Cited by 23
The unbearable lightness of consent
Khalil, M., Prinsloo, P., & Slade, S. (2018) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/3231644.3231659 · Cited by 11
Self-citationChallenging Assumptions in Learning Analytics
Dawson, S., Gašević, D., & Mirriahi, N. (2016) · Journal of Learning Analytics · doi:10.18608/jla.2015.23.1 · Cited by 10
van Haastrecht, M., Brinkhuis, M., & Spruit, M. (2024) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-64299-9_5 · Cited by 9
Students’ Perceptions of Learning Analytics for Mental Health Support: Qualitative Study
Freccero, A., Onwunle, M., Elliott, J., Podder, N., Oliveira, J. P. D., & Dewa, L. H. (2025) · JMIR Formative Research · doi:10.2196/70327 · Cited by 11
Merikko, J., Ng, K., Saqr, M., & Ihantola, P. (2022) · IEEE Access · doi:10.1109/access.2022.3207274 · Cited by 9
Curricular and Learning Analytics: A Big Data Perspective
Pinnell, C., Paulmani, G., Kumar, V., & Kinshuk, K. (2016) · Springer eBooks · doi:10.1007/978-3-319-06520-5_9 · Cited by 9
Radway, S., Quintanilla, K., Ludden, C., & Votipka, D. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642066 · Cited by 8
Velander, J., Otero, N., Pargman, T. C., & Milrad, M. (2021) · Advances in Analytics for Learning and Teaching · doi:10.1007/978-3-030-81222-5_15 · Cited by 8
Artificial intelligence for determining learning strategies in university students
García, Á. R. S., Olguín-Martínez, C. M., Lara, R. M. B., Echeagaray, T. I. S., Huerta-Mora, E. A., García, B. B. B., Barcia, L. A. C., & Moreira-Chóez, J. S. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1611189 · Cited by 7
The Impact of Student Opt-Out on Educational Predictive Models
Li, W., Brooks, C. A., & Schaub, F. (2019) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3303772.3303809 · Cited by 13
Krieter, P., Viertel, M., & Breiter, A. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-57717-9_14 · Cited by 7
Enabling Mobile and Wireless Technologies for Smart Cities: Part 2
Ahmed, E., Imran, M. A., Guizani, M., Rayes, A., Lloret, J., Han, G., & Guibène, W. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.7876850 · Cited by 7
A Complete Validated Learning Analytics Framework
Tlili, A., Essalmi, F., Jemni, M., Kinshuk, P., & Chen, N. (2019) · International Journal of Information and Communication Technology Education · doi:10.4018/ijicte.2019070104 · Cited by 7
Students' Information Privacy Concerns in Learning Analytics: Towards a Model DevelopmentPreprint
Mutimukwe, C., Twizeyimana, J. D., & Viberg, O. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.00068 · Cited by 7
Wilson, A. N., & Ross, J. (2024) · Studies in Higher Education · doi:10.1080/03075079.2024.2368264 · Cited by 6
Cisel, M. (2023) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v24i4.7265 · Cited by 7
Building capacity in institutional research: collaboration and complementarity?
Botha, J., Webber, K. L., Williams, J., & Woodfield, S. (2024) · Tertiary Education and Management · doi:10.1007/s11233-024-09139-0 · Cited by 4
Learning analytics and dental education; choices and challenges
Zijlstra‐Shaw, S., & Stokes, C. W. (2018) · European Journal Of Dental Education · doi:10.1111/eje.12370 · Cited by 4
Evaluation of the UNESCO Recommendation Concerning Open Educational Resources
Downes, S. (2020) · International Journal of Open Educational Resources · doi:10.18278/ijoer.3.2.4 · Cited by 4
Li, X. V., Rosson, M. B., & Robert, J. (2022) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/3491140.3528271 · Cited by 4
McNicol, T., Carthouser, B., Bongiovanni, I., & Abeysooriya, S. (2023) · Information Technology and People · doi:10.1108/itp-12-2022-0971 · Cited by 4
Surveillance Imaginaries: Learning from Participatory Speculative Fiction
Wilson, A. N., & Ross, J. (2023) · Surveillance & Society · doi:10.24908/ss.v21i3.16025 · Cited by 6
Analytics in Authentic Learning
Kumar, V., Kinshuk, K., Pinnell, C., & Paulmani, G. (2017) · Lecture notes in educational technology · doi:10.1007/978-981-10-5930-8_6 · Cited by 4
Trustworthy Learning Analytics for Smart Learning Ecosystems
Svetec, B., & Divjak, B. (2025) · Interaction design & architecture(s)/ID&A Interaction design & architecture(s) · doi:10.55612/s-5002-064-002sp · Cited by 3
Exploring the Role of Paradata in Digitally Supported Qualitative Co-Research
Rainey, J., Macfarlane, S., Puussaar, A., Vlachokyriakos, V., Burrows, R., Smeddinck, J. D., Briggs, P., & Montague, K. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3502103 · Cited by 4
The online educational model and drivers for online learning
Achebo, N., Adeola, O., & Idemudia, E. C. (2019) · International Journal of Business Information Systems · doi:10.1504/ijbis.2019.10024675 · Cited by 3
Ethics in Predictive Learning Analytics
Joseph‐Richard, P., & Uhomoibhi, J. O. (2021) · Advances in educational technologies and instructional design book series · doi:10.4018/978-1-7998-7103-3.ch004 · Cited by 3
Foster, C. (2025) · Perspectives Policy and Practice in Higher Education · doi:10.1080/13603108.2025.2556195 · Cited by 2
Student Vulnerability And Agency In Networked, Digital Learning
Prinsloo, P., & Slade, S. (2016) · Open Research Online - ORO (The Open University) · Cited by 2
Self-citationPrinsloo, P., & Slade, S. (2016) · IGI Global eBooks · doi:10.4018/978-1-4666-9840-6.ch079 · Cited by 2
Self-citationRecommendations for Technology in Higher Education
Smale, M. A., & Regalado, M. (2016) · Springer eBooks · doi:10.1007/978-3-319-48908-7_5 · Cited by 2
‹Da habe ich es dann einfach ausgeschaltet›
Viertel, M., Krieter, P., & Breiter, A. (2021) · MedienPädagogik Zeitschrift für Theorie und Praxis der Medienbildung · doi:10.21240/mpaed/44/2021.10.26.x · Cited by 2
Postdigital Learning Analytics
Scott, H. (2025) · Springer eBooks · doi:10.1007/978-3-031-35469-4_87-1 · Cited by 1
Young, C. (2017) · Arrow@dit (Dublin Institute of Technology)
Metadata
- Authors
- Prinsloo, P., & Slade, S.
- Affiliations
- University of South Africa (ZA)
- The Open University (GB)
- Venue
- Proceedings of the Fifth International Conference on Learning Analytics And Knowledge
- Publisher
- ACM
- Published
- 2015-03-16
- Pages
- 83-92
- OpenAlex
- W2142141517
- Cited by
- 119
- References
- 63
- Citations by year
- 2026: 8 · 2025: 10 · 2024: 9 · 2023: 11 · 2022: 9 · 2021: 11 · 2020: 10 · 2019: 13 · 2018: 10 · 2017: 6 · 2016: 20 · 2015: 2
- FWCI
- 46.19
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Learning Analytics and Knowledge (LAK) (publishedVersion)
- Open Research Online (The Open University) (acceptedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Law › Data Privacy and Cybersecurity
- Keywords
- student privacy, self-management, student data, online tracking, mass surveillance, panopticon, student success, student retention, data harvesting, higher education
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
