Poster: Privacy and identity management in Learning Anlayticsprocesses with Blockchain
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This thesis examines the fragility of student data privacy and management in learning analytics, highlighting the risks of data misuse and fragmentation. It proposes using blockchain technology to enhance data security, allow students to govern their own data, and ensure compliance with privacy policies. The research aims to foster trust in learning analytics by integrating technological solutions that address privacy concerns and certify the integrity of student data.
Poster: Privacy and identity management in Learning Anlayticsprocesses with Blockchain
- 1. Privacy and identity management in LearningAnlaytics processes with Blockchain Amo. D.,García-Peñalvo, F.J.,Alier, M., Fonseca, D.,Casañ, M.J. UniversitatLa Salle BCN– RamónLlull, Universidad de Salamanca,UniversitatPolitècnicadeCatalunya The collection of students’ sensible data raises adverse reactions againstLearningAnalyticsthat decreasesthe confidencein its adoption. Thelaws and policiesthat surroundthe use of educationaldata are not enough to ensure privacy, security, validity, integrity and reliability of students data. This problem has been detected through literature review and canbe solvedif a technologicallayer of automated checking rules is addedabovethese policies. Theaim of this thesis is to research about an emerging technology such as Blockchain to preserve the identity of students and securetheir data. In a first stage a systematic literature review will be conducted in order to set the context of the research. Afterwards, and through the scientific method, we will developa Blockchainbasedsolution to automate rules and constraints with the aim to let students the governanceof their data and to ensure data privacyandsecurity. Solution Blockchain Context and motivation that drives the dissertation research The motivation arises from the concerns of certain aspects about learning analytics in regard totrust,integrity andprivacyof the data collected with the aim to extend, standardize and accept their use in educational environments. LearningAnalytics Different investigationsshow the possibilitiesof improving the educational context through the use of educationaldata analysis. This analysisaims to avoiddropouts,failuresandincreaseopportunities for successandlearning. Thesepositivefacts doesnot leaveindifferent to potential beneficiaries. Fragilityin data privacy It is found that there is a distrust in the use of Learning Analysis. It is uncertain how education technology companiesare using students data, who is really being benefited,how this will affect to students in a short or long term future and which level of privacy or security its being appliedto securestudents data. Dataprinciples andpolicyframeworks The data generatedby the students is scattered and in the hands of other entities, accordingto the tools usedin the learningprocess. Thishighlightsa highly fragile environment in terms of the ethics of privacyand the identity of students,andthat hasto do with the expositionto any entity that collect educationalinteractions. No one can assurethat the information contained in the logsis reliableandat the sametime is not sharedwith others. The previous situation depicts a serious problem of fragility in terms of certification,privacyandidentity of students: • There is a clear fragmentation of educationaldata. The more tools are usedthe more dispersedstudent’s data andthe lesscontrol overprivacy. It is manifesteda low data protection. • The data is freely accessedby third parties and even shared, where students areclearlyidentified. • Thereis no control over the data. Anyonewho hasaccessto the data can modify it at their convenience. Consequently,no one canensurethat the stored data is the original. • There is no certification process. Anyone can certify some studies that the student has not attended in the schoolor can present some studies in which hehasnot attended. Abstract There is a clear disposition to set policy frameworks to ensure data protection legality and preservestudents data privacy. Despitethe efforts to set guidelinesand rules to assure students rights there are worrying lacks that allow data leaks, hacks or transfer between companiesas a businessmodel. It is necessarya layerof control policiesandtechnologythat: • Certify that the transaction between the student and the tool is valid andimmutable. • Givethe student the power to decidewho will act andin what way with their own data. Technological solution for technological problems This thesis focuses its efforts on solving aspects related to data privacy and the management of student identities. As said, the reason is its relevance to foster a strong confidence in this scientific element and, finally, the adoption, integration and use of analysis of learning data in formal institutions in a natural way. To increasethe trust in Learning Analytics it can be used technological approachesfor the managementof student identity andthe privacyof the data collected. Theprivacyof the data and the preservationof the identity of the students are those that we consider most important to work on. This will help to establish a minimum confidence before its possible integration andnormalizationin the educationalinstitutions. Otheraspects suchas the locationof storage,the ownershipof the data and its possible use are also important to take into account when adopting a Learning Analysisapproach. The stack ofBlockchaintechnologies is a new paradigm with a chance to provide a technological solution to the Learning Analytics ethics and trust problems and other problems related to identity in education and training. We foresee that the process of inquiry described in thedata principles and policy frameworkscan be implemented and enforced using theBlockchain andSmart Contractsas follows: The data and metadata about the learning activities of a student can be secured cryptographically using the Blockchainand the safeguard ofSmart Contracts. Acknowledgements With the support ofSecretariad’Universitatsi Recercadel Departamentd’Empresai Coneixementde la GeneralitatdeCatalunyawith the help of 2017 SGR 934 GRETEL. sensitivedata students interactions LearningAnalytics blockchain business tool university/ school Filters Policies Principles