[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119010-en":3,"doc-seo-119010-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119010,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","Technology-Enhanced Learning, Data Sharing, and Machine Learning Challenges in South African Education","This paper examines the governance challenges of data sharing for machine learning education research (MLER) in South African education contexts. Machine learning can improve student success and reveal where additional support is needed, yet effective implementation depends on access to high-quality data. The study emphasizes difficulties arising from inconsistent data-sharing policies across institutions and organizations, which hinders standardizing data-sharing practices. It offers perspectives for policymakers to address these barriers so South African researchers can advance innovations and better support inclusive, equitable education outcomes.","education sciences  \nArticle  \nTechnology-Enhanced Learning, Data Sharing, and Machine Learning Challenges in South African Education  \nHerkulaas MvE Combrink *, Vukosi Marivate  and Baphumelele Masikisiki  \nCitation: Combrink, H.M.; Marivate, V.; Masikisiki, B. Technology-Enhanced Learning, Data Sharing, and Machine Learning Challenges in South African Education. Educ. Sci. 2023, 13, 438 . [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)educsci13050438  \nAcademic Editor: Peter Williams  \nReceived: 14 February 2023  \nRevised: 18 March 2023  \nAccepted: 5 April 2023  \nPublished: 24 April 2023  \nCopyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \nDepartment of Computer Science, University of Pretoria, Pretoria 0028, South Africa  \n* [Correspondence: u29191051@tuks.co.za](Correspondence: u29191051@tuks.co.za)  \nAbstract: The objective of this paper was to scope the challenges associated with data-sharing governance for machine learning applications in education research (MLER) within the South African context. Machine learning applications have the potential to assist student success and identify areas where students require additional support. However, the implementation of these applications depends on the availability of quality data. This paper highlights the challenges in data-sharing policies across institutions and organisations that make it difficult to standardise data-sharing practices for MLER. This poses a challenge for South African researchers in the MLER space who wish to advance and innovate. The paper proposes viewpoints that policymakers must consider to overcome these challenges of data-sharing practices, ultimately allowing South African researchers to leverage the benefits of machine learning applications in education effectively. By addressing these challenges, South African institutions and organisations can improve educational outcomes and work toward the goal of inclusive and equitable education.  \nKeywords: data-sharing governance; machine learning education research; challenges; innovation; South African context  \n1. Introduction  \nMachine-learning-based research relies heavily on the availability of data. In the event that there is no access to relevant data or there is a small dataset, this type of research can be delayed or produce poorly performing and unreliable models due to the lack of relevant data. The importance of data sharing for machine-learning-based research has led to an acceleration in machine-learning implementation and higher accuracy [1] .  \nUnfortunately, data access is not always a straightforward process, because every country and the academic institutions within these countries are governed by policies and regulations that are implemented differently. For example, in Europe, the General Data Protection Regulation (GDPR) has been questioned by a number of researchers, especially in the biomedical domain [2] . They have stipulated that consent for data and bio-sample sharing generates confusion and uncertainty and creates conflicts between the regulations and research ethics [2–5] . This is because, for biological data, understanding the context of each biological entity; their circumstances; and (in the case of human participants) their demography, gender, lifestyle, diet, and general behaviour is important [4] . Asa result, some researchers are reluctant to share data because of legal fears and social sanctions in combination with the threat of huge penalties as a consequence of violating the GDPR [6] . In South Africa, protection legislations such as the Protection of Personal Information Act (POPIA) and ethical policies are in place [7] . POPIA re","cbCaiaQLb619VFpg","https://ap.wps.com/l/cbCaiaQLb619VFpg","pdf",1232012,1,12,"English","en",105,"# Introduction\n## Data availability and research reliability\n## Policy and regulatory barriers to data sharing\n## South Africa’s governance context (POPIA and ethics)","[{\"question\":\"Why does machine learning education research depend on data availability?\",\"answer\":\"Machine-learning-based research relies on access to relevant datasets; without access or with small datasets, studies can be delayed or produce poorly performing, unreliable models.\"},{\"question\":\"What main challenge do institutions face when sharing data for MLER?\",\"answer\":\"Differences in policies and regulations across countries and organizations make data access and sharing complex, and inconsistent data-sharing governance makes it hard to standardize practices for MLER.\"},{\"question\":\"How do data protection regulations in South Africa affect data sharing?\",\"answer\":\"South Africa’s POPIA and ethical policies protect personal information, but concerns exist about whether POPIA restrictions and research ethics practices limit distribution and sharing, potentially delaying MLER implementation.\"}]","Technology-Enhanced Learning, Data Sharing, and Machine Learning Challenges in South African Education | PDF",1785721852,30,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"technology-enhanced-learning-data-sharing-and-machine-learning-challenges-in-south-african-education","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/technology-enhanced-learning-data-sharing-and-machine-learning-challenges-in-south-african-education/119010/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04","2026-08-03",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"Why does machine learning education research depend on data availability?","Question",{"text":76,"@type":77},"Machine-learning-based research relies on access to relevant datasets; without access or with small datasets, studies can be delayed or produce poorly performing, unreliable models.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What main challenge do institutions face when sharing data for MLER?",{"text":81,"@type":77},"Differences in policies and regulations across countries and organizations make data access and sharing complex, and inconsistent data-sharing governance makes it hard to standardize practices for MLER.",{"name":83,"@type":74,"acceptedAnswer":84},"How do data protection regulations in South Africa affect data sharing?",{"text":85,"@type":77},"South Africa’s POPIA and ethical policies protect personal information, but concerns exist about whether POPIA restrictions and research ethics practices limit distribution and sharing, potentially delaying MLER implementation.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":29,"slug":122},"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":107,"slug":138},19,"General","general"]