Learning Analytics and Impact on Personalized Student Learning - Srabine Kuhlmane; Dragany Grasevic; Ryany S. Bakery; Gseoff Scotte; Giarge Siemens (Journal of Teaching and Learning, 2025)
This study explores the role of Learning Analytics (LA) in advancing personalized learning within educational institutions in Germany. Employing a qualitative approach, the research adopts a case study design to delve into the experiences of teachers, students, and education administrators in implementing LA. Data were collected through in-depth interviews and focus group discussions with participants who have direct engagement with LA in educational contexts. The findings demonstrate that Learning Analytics empowers educators to create highly personalized learning experiences, addressing the unique needs of individual students, while also providing learners with prompt and meaningful feedback. Nonetheless, the study identifies critical challenges, including inadequate teacher training in leveraging data effectively and persistent concerns surrounding the privacy and security of student data. Despite these hurdles, the integration of LA has proven to enhance the overall learning experience and supports the development of a more responsive and adaptive curriculum. To unlock the full potential of Learning Analytics, the study recommends the establishment of comprehensive policies focused on enhancing teacher training, integrating advanced technology, and ensuring transparency and ethical practices in data usage within educational settings.