Libbrecht, PaulHoeppner, KristinaRebholz, SandraMueller, WolfgangKiesler, NatalieSchulz, Sandra2024-10-212024-10-212024https://dl.gi.de/handle/20.500.12116/45052The practice of students creating ePortfolios has been experienced as an effective means of students proving their individual knowledge and competencies by creating digital works that can be shared. This practice has been used for decades and has allowed many students to create study-relevant work and document these in E-Portfolios. Teachers, recruitment actors and fellow learners have enjoyed the possibility to perceive the learning and the relevant knowledge by reviewing E-Portfolios. Artificial intelligence empowers the reviewers of the work by providing powerful techniques that inform the many dimensions of the texts and can support the review and the creation of additional learning evidence. The Workshop ‘E-Portfolios Evolution Powered by Language Analysis’ has surfed this wave and provided a panorama of current techniques of employing machine-learning and large language model technology that support the pedagogical practice of e-portfolios to demonstrate student learning activity.enE-PortfoliosNatural Language ProcessingAssessmentFeedbackText10.18420/delfi2024-ws-36