| MATHEMATICS (TURKISH, PHD) | |||||
| PhD | TR-NQF-HE: Level 8 | QF-EHEA: Third Cycle | EQF-LLL: Level 8 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| CET2111 | Recent Practices in Educational Technologies | Fall | 2 | 0 | 2 | 4 |
| The course opens with the approval of the Department at the beginning of each semester |
| Language of instruction: | En |
| Type of course: | Departmental Elective |
| Course Level: | |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Dr. Öğr. Üyesi YAVUZ SAMUR |
| Course Objectives: | The aim of this course is to make students aware of current technologies in educational technologies and to be aware of how these technologies can be transferred to learning environments. |
|
The students who have succeeded in this course; Performs analysis knowing the properties of big data. Knows different cloud computing systems. Integrates new technologies into learning environments. Recognizes the tools used in educational technology and makes a distinction as to which vehicles can be used in which situations. |
| The internet of things; augmented reality; virtual learning; wearable technologies; 360 degree videos; adaptive learning environments; intelligent systems; massive open online courses; learning analytics; big data. |
| Week | Subject | Related Preparation | |
| 1) | Meeting and introduction of course | ||
| 2) | Overview of current applications in educational technologies | ||
| 3) | The internet of things | ||
| 4) | Augmented reality | ||
| 5) | Virtual learning | ||
| 6) | Wearable technologies | ||
| 7) | Mid-term exam | ||
| 8) | 360 degree videos | ||
| 9) | Adaptive learning environments | ||
| 10) | Intelligent systems | ||
| 11) | Massive open online courses (MOOCs, xMOOCs, cMOOCs) | ||
| 12) | Öğrenme analitikleri | ||
| 13) | Cloud computing systems and big data | ||
| 14) | Presentations | ||
| Course Notes: | Ders Kitapları: Gündüz, M. Z., & Daş, R. (2018). Nesnelerin interneti: Gelişimi, bileşenleri ve uygulama alanları. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 24(2), 327-335. Özsevgeç, T., & Eroğlu, B. (2017). İnsan ve makine etkileşimi: Artırılmış gerçeklik ve uygulama örnekleri. Pegem Atıf İndeksi, 413-438. Öztürk, A. (2017). Yükseköğretimde büyük veri ve öğrenme analitikleri: güncel teori ve uygulamalar. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 3(1), 218-228. Yengin, D., & Bayrak, T. (2018). Sanal gerçeklik (1. Baskı). Derin Yayınları, İstanbul. |
| References: | YOK |
| Semester Requirements | Number of Activities | Level of Contribution |
| Attendance | 14 | % 5 |
| Laboratory | % 0 | |
| Application | % 0 | |
| Field Work | % 0 | |
| Special Course Internship (Work Placement) | % 0 | |
| Quizzes | % 0 | |
| Homework Assignments | 2 | % 20 |
| Presentation | 1 | % 15 |
| Project | 1 | % 40 |
| Seminar | % 0 | |
| Midterms | % 0 | |
| Preliminary Jury | % 0 | |
| Final | 1 | % 20 |
| Paper Submission | % 0 | |
| Jury | % 0 | |
| Bütünleme | % 0 | |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 40 | |
| PERCENTAGE OF FINAL WORK | % 60 | |
| Total | % 100 | |
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 2 | 28 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Special Course Internship (Work Placement) | 0 | 0 | 0 |
| Field Work | 0 | 0 | 0 |
| Study Hours Out of Class | 0 | 0 | 0 |
| Presentations / Seminar | 1 | 5 | 5 |
| Project | 1 | 40 | 40 |
| Homework Assignments | 2 | 1 | 2 |
| Quizzes | 0 | 0 | 0 |
| Preliminary Jury | 0 | 0 | 0 |
| Midterms | 0 | 0 | 0 |
| Paper Submission | 0 | 0 | 0 |
| Jury | 0 | 0 | 0 |
| Final | 1 | 20 | 20 |
| Total Workload | 95 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution |