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Year/Semester of Study | 2 / Fall Semester | ||||
Level of Course | 2nd Cycle Degree Programme | ||||
Type of Course | Compulsory | ||||
Department | EĞİTİMDE YAPAY ZEKA TEKNOLOJİLERİ(TEZLİ YÜKSEK LİSANS ÖNERİLEN) | ||||
Pre-requisities and Co-requisites | None | ||||
Mode of Delivery | Face to Face | ||||
Teaching Period | 14 Weeks | ||||
Name of Lecturer | ŞEYHMUS AYDOĞDU (saydogdu@nevsehir.edu.tr) | ||||
Name of Lecturer(s) | |||||
Language of Instruction | Turkish | ||||
Work Placement(s) | None | ||||
Objectives of the Course | |||||
To ensure that the thesis is prepared in coordination with the student. |
Learning Outcomes | PO | MME | |
The students who succeeded in this course: | |||
LO-1 | Comprehends the processes for preparing the thesis. |
PO-1 Has theoretical and practical knowledge about artificial intelligence technologies in education and develops an attitude to use this knowledge responsibly. PO-2 Designs and develops creative, original and innovative technology-supported learning environments to enhance learning. PO-3 He/She effectively uses the knowledge she has gained by following national and international research and innovations in artificial intelligence technologies in education in her professional and academic life through her theoretical and practical studies. PO-4 Designs learning-teaching environments appropriate for individual differences by effectively using existing resources and methods and techniques related to the teaching profession and artificial intelligence technologies in education, and acts with ethical sensitivity in these environments. PO-5 Has scientific and analytical thinking skills. PO-6 Plans and conducts scientific studies using research methods and techniques, independently or as a member of a team. PO-7 Develops and applies data collection tools in scientific research and analyzes the collected data with statistical methods. PO-8 Evaluates studies on artificial intelligence technologies in education with a critical perspective, taking into account ethical values. PO-9 He/she integrates different disciplines with artificial intelligence technologies in education and exhibits an open attitude towards collaboration. PO-10 Design and develop artificial intelligence based applications in educational environments. PO-11 Uses artificial intelligence technologies effectively, consciously and responsibly in learning and teaching environments. PO-12 Uses machine learning, deep learning and big data analytics methods effectively and practically in educational contexts. |
Presentation |
LO-2 | Prepares master's thesis. |
PO-1 Has theoretical and practical knowledge about artificial intelligence technologies in education and develops an attitude to use this knowledge responsibly. PO-2 Designs and develops creative, original and innovative technology-supported learning environments to enhance learning. PO-3 He/She effectively uses the knowledge she has gained by following national and international research and innovations in artificial intelligence technologies in education in her professional and academic life through her theoretical and practical studies. PO-4 Designs learning-teaching environments appropriate for individual differences by effectively using existing resources and methods and techniques related to the teaching profession and artificial intelligence technologies in education, and acts with ethical sensitivity in these environments. PO-5 Has scientific and analytical thinking skills. PO-6 Plans and conducts scientific studies using research methods and techniques, independently or as a member of a team. PO-7 Develops and applies data collection tools in scientific research and analyzes the collected data with statistical methods. PO-8 Evaluates studies on artificial intelligence technologies in education with a critical perspective, taking into account ethical values. PO-9 He/she integrates different disciplines with artificial intelligence technologies in education and exhibits an open attitude towards collaboration. PO-10 Design and develop artificial intelligence based applications in educational environments. PO-11 Uses artificial intelligence technologies effectively, consciously and responsibly in learning and teaching environments. PO-12 Uses machine learning, deep learning and big data analytics methods effectively and practically in educational contexts. |
Presentation |
PO: Programme Outcomes MME:Method of measurement & Evaluation |
Course Contents | ||
This course includes the acquisition of skills to transform the master's thesis work into a product and the processes for preparing the thesis in coordination with the student. | ||
Weekly Course Content | ||
Week | Subject | Learning Activities and Teaching Methods |
1 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
2 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
3 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
4 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
5 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
6 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
7 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
8 | mid-term exam | |
9 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
10 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
11 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
12 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
13 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
14 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
15 | To gain the skills to turn the master thesis study into a product | Discussion Method Method of Narration Question and Answer |
16 | final exam | |
Recommend Course Book / Supplementary Book/Reading | ||
Required Course instruments and materials | ||
Printed and electronic resources related to the thesis subject, computer |
Assessment Methods | |||
Type of Assessment | Week | Hours | Weight(%) |
mid-term exam | |||
Other assessment methods | |||
1.Oral Examination | |||
2.Quiz | |||
3.Laboratory exam | |||
4.Presentation | |||
5.Report | 16 | 1 | 100 |
6.Workshop | |||
7.Performance Project | |||
8.Term Paper | |||
9.Project | |||
final exam |
Student Work Load | |||
Type of Work | Weekly Hours | Number of Weeks | Work Load |
Weekly Course Hours (Theoretical+Practice) | 1 | 14 | 14 |
Outside Class | |||
a) Reading | 12 | 14 | 168 |
b) Search in internet/Library | 14 | 14 | 196 |
c) Performance Project | 10 | 14 | 140 |
d) Prepare a workshop/Presentation/Report | 15 | 14 | 210 |
e) Term paper/Project | 0 | ||
Oral Examination | 0 | ||
Quiz | 0 | ||
Laboratory exam | 0 | ||
Own study for mid-term exam | 0 | ||
mid-term exam | 0 | ||
Own study for final exam | 0 | ||
final exam | 0 | ||
0 | |||
0 | |||
Total work load; | 728 |