Learner Experience at the Intersection of Two Dynamics: Artificial Intelligence and User Experience


Ersoy M., Aydın B.

17. ULUSLARARASI BİLGİSAYAR VE ÖĞRETİM TEKNOLOJİLERİ SEMPOZYUMU, Kastamonu, Türkiye, 3 - 05 Ekim 2024, ss.7

  • Yayın Türü: Bildiri / Özet Bildiri
  • Basıldığı Şehir: Kastamonu
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.7
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

User Experience (UX) design focuses on enhancing users' experiences throughout digital platform interactions, whereas Learner Experience Design (LXD) is a vital area of study that attempts to provide more efficient learning experiences. Artificial Intelligence (AI) technologies offer plenty of opportunities to enhance learners' experiences by customizing them to their individual requirements, hence increasing efficiency and personalization. Is it possible for the convergence of these two dynamic and fast evolving domains to amplify this capacity? This study seeks to investigate the convergence and future possibilities of two rapidly evolving domains, namely UX and AI technologies. This study investigates the ways in which future learning environments can be influenced at this point of junction, and the possible advantages of these technologies as indicated by the relevant literature. This research aims to find the possibilities of collaboration by analyzing existing studies that explore the intersection of the two domains through a comprehensive examination of the literature. It explores the new solutions that arise from the integration of different domains in terms of learning experiences. The data collected from the literature review will be examined using the content analysis method, focusing on the identified themes. The literature review will be analyzed based on the following sub-themes: personalized content recommendations, adaptive interface dynamically; automatic analysis and testing of user behavior. Additionally, it includes visual detection and instant feedback aides, as well as automatic accessibility controls and navigations. This study highlights the potential of AI-enabled products for individuals with various disabilities who require particular assistance. To enhance LXD in learning platforms, alternative support and measurement systems, such as emotion detection and gesture analysis, can be utilized. This is particularly important due to the limits of measuring tools that rely on self-report. The importance of instant feedback, which is an important argument in learning processes, is important in terms of providing critical suggestions accompanied by literature data to explore the potential of proactive support systems in user experience design. After completion, this research is anticipated to offer crucial recommendations for various phases of user experience design processes, a pivotal component in enhancing learning environments. The study is anticipated to make a valuable contribution to the advancement of novel methodologies in the user experience design process for upcoming educational settings.