Veranstaltungsprogramm

<p>This contribution examines participation as co‑creation within an interdisciplinary research project focused on the participatory design of GenAI-supported Social‑Emotional Learning (SEL) micro‑learning interventions in Higher Education. The study is theoretically grounded in critical participation theory, which conceptualizes participation as a redistribution of epistemic and decision‑making power rather than as learner engagement or consultative involvement (Arnstein, 1969), as well as in sociocultural perspectives that frame learning as situated participation in socially organized practices (Hickey &amp; Zuiker, 2005; Wenger, 1998).<br />Participation as co‑creation is operationalized through a multi‑phase participatory design process. In the first phase, learners contribute as co‑constructors of SEL priorities through a student‑centered needs assessment that combines qualitative and quantitative methods. Drawing on co‑design theory, participants are treated as experts of their lived experiences, and their contributions directly inform the identification and contextualization of core SEL competencies rather than merely validating predefined curricular frameworks (Sanders &amp; Stappers, 2008). By embedding learner perspectives at the level of conceptual framework formation, this approach explicitly seeks to move beyond tokenistic forms of participation.<br />In the second phase, interdisciplinary co‑design workshops translate learner‑generated insights into a structured SEL framework aligned with curricular learning outcomes and micro‑learning pedagogies. Informed by students‑as‑partners approaches in Higher Education, these workshops function as sites of negotiated meaning‑making across disciplinary and professional boundaries, supporting shared ownership of both pedagogical goals and design decisions (Bovill et al., 2011).<br />Within this participatory architecture, Generative Artificial Intelligence (GenAI) is positioned as a teacher‑facing adaptive design infrastructure rather than as a tool for direct student interaction. Informed by human‑centered perspectives on AI in education (Luckin, 2017), GenAI supports educators in responding dynamically to learner needs by analyzing patterns of learner progression and achievement, generating adaptive content variations, and iteratively refining micro‑learning pathways. Although students are not asked to directly interact with GenAI along their learning journey, its integration enables continuous feedback loops through which learner trajectories inform ongoing content design and refinement. <br />The expected outcomes include a theoretically grounded framework for operationalizing participation as co‑creation in SEL design, empirical insights into teacher‑mediated GenAI‑supported adaptation, and a critical reflection on the opportunities and limitations of participatory educational design through AI‑enabled infrastructures.</p>