{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T03:44:48Z","timestamp":1779162288694,"version":"3.51.4"},"reference-count":0,"publisher":"Society for Learning Analytics Research","issue":"1","license":[{"start":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T00:00:00Z","timestamp":1774828800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Learning Analytics"],"abstract":"<jats:p>The rise of generative artificial intelligence (GenAI) and accelerated globalization have necessitated a fundamental recalibration of higher education to prioritize domain-agnostic, 21st-century professional competencies. While institutional commitment to these skills is high, their systematic integration into the curriculum and evaluation remains fragmented, highlighting a critical gap between traditional academic success metrics and demonstrated workforce readiness. This special issue presents five complementary studies that investigate how the intersection of learning analytics (LA) and GenAI can bridge the gap between institutional rhetoric and demonstrated professional readiness. The contributions collectively advance a research agenda across four dimensions: 1) benchmarking large language models (LLMs) for curricular-competency alignment using reasoning-based prompting, 2) the iterative design of Socratic-style GenAI chatbots to scaffold self-regulated learning, 3) the application of psychometric modelling and Latent Profile Analysis to quantify 21st-century professional competencies, and 4) institutional governance and adoption of curriculum analytics. Collectively, these studies advocate for an epistemological shift toward process-sensitive assessments that move beyond static, episodic indicators toward dynamic, longitudinal representations of learner capability. We conclude by outlining the sociotechnical infrastructure, including robust governance and interdisciplinary collaboration, required to responsibly transition these AI-driven innovations from research prototypes to sustainable enterprise infrastructure, ensuring that analytics serve the evolving needs of students, educators, and professional bodies.<\/jats:p>","DOI":"10.18608\/jla.2026.9743","type":"journal-article","created":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T22:51:27Z","timestamp":1774911087000},"page":"1-6","source":"Crossref","is-referenced-by-count":2,"title":["Advancing 21st-Century Professional Competencies with Learning Analytics in the Age of Generative AI"],"prefix":"10.18608","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2437-6892","authenticated-orcid":false,"given":"Abhinava","family":"Barthakur","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8543-3774","authenticated-orcid":false,"given":"Olga","family":"Viberg","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6283-5546","authenticated-orcid":false,"given":"Ren\u00e9 F.","family":"Kizilcec","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3051-3232","authenticated-orcid":false,"given":"Ryan S.","family":"Baker","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2435-2193","authenticated-orcid":false,"given":"Shane","family":"Dawson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7859","published-online":{"date-parts":[[2026,3,30]]},"container-title":["Journal of Learning Analytics"],"original-title":[],"link":[{"URL":"https:\/\/learning-analytics.info\/index.php\/JLA\/article\/download\/9743\/7973","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/learning-analytics.info\/index.php\/JLA\/article\/download\/9743\/7973","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T22:51:27Z","timestamp":1774911087000},"score":1,"resource":{"primary":{"URL":"https:\/\/learning-analytics.info\/index.php\/JLA\/article\/view\/9743"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,30]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,3,30]]}},"URL":"https:\/\/doi.org\/10.18608\/jla.2026.9743","relation":{},"ISSN":["1929-7750"],"issn-type":[{"value":"1929-7750","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,30]]}}}