Akademik Dersler - Tanıtım

Course Title	Code	Compulsory/Elective	Laboratory + Practice	ECTS
Mobile Learning	UZE572	II. SEMESTER	3+0	6.0

Language of Instruction	Türkçe
Course Type	Elective Courses
Course Instructor(s)	PROF. DR. NİLGÜN ÖZDAMAR
Mode of Delivery	Face to face
Prerequisites	There is no prerequisite or co-requisite for this course.
Courses Recomended	It is recommended that students who take/will take this course also take \\\"Development of e-Learning Materials\\\".
Recommended Reading List	Garzón, J. (2025). Mobile learning significantly enhances student learning gains: A meta-analysis of empirical studies. Computers & Education.Yu, C., Zhang, Y., & Li, H. (2025). Artificial intelligence-based mobile learning recommendation system for personalized learning. Scientific Reports.Tan, L. Y., Wong, S. L., & Lee, K. W. (2025). Artificial intelligence–enabled adaptive learning platforms in education. Computers and Education: Artificial Intelligence.Hayadi, B. H., Siregar, R., & Nugroho, A. (2025). Determinants of student engagement and behavioral intention towards mobile learning platforms. Contemporary Educational Technology.Kukulska-Hulme, A., Norris, L., & Donohue, J. (2025). Generative AI and mobile learning in higher education. International Journal of Interactive Mobile Technologies.
Assessment methods and criteria	Students are expected to actively participate in the lectures throughout the semester and activities to be set up every week. In addition homework and a term project will be designed.
Work Placement	There is no internship/application activity in this course.
Catalog Content	Introduction to mobile learning; key concepts and development of mobile learning; mobile learning ecosystem and mobile technologies; design principles for mobile learning; user experience in mobile learning environments; mobile learning applications in education; mobile learning content design; interaction and collaboration in mobile learning environments; assessment and evaluation methods in mobile learning; augmented reality and artificial intelligence–supported mobile learning applications; data analytics and learning analytics in mobile learning; the future of mobile learning and innovative approaches; development, presentation and evaluation of mobile learning p