| Learning Outcomes |
PO |
MME |
| The students who succeeded in this course: |
|
|
| LO-1 |
Define digital transformation, digital technologies and experience management; gain basic knowledge about the applications of these topics in sport management. |
PO-10 Can use digital sports technologies and data analytics to assess and improve athletes' performance.
|
Examination
|
| LO-2 |
Explain the strategic role of digital transformation and experience management in sport management and gain basic knowledge about the effective planning, design and management of these processes. |
PO-10 Can use digital sports technologies and data analytics to assess and improve athletes' performance.
PO-14 Can utilize educational technologies to develop digital and innovative teaching models in sports sciences.
|
Examination
|
| LO-3 |
Analyze and solve problems/cases related to digital transformation and experience management in sport management. |
PO-10 Can use digital sports technologies and data analytics to assess and improve athletes' performance.
|
Examination
|
| LO-4 |
To be able to carry out an assignment and/or project related to digital transformation and experience management in sports management individually or as a team; to be able to analyze the results obtained. |
PO-3 Can effectively carry out data collection, analysis, and reporting processes related to sports sciences.
PO-10 Can use digital sports technologies and data analytics to assess and improve athletes' performance.
|
Examination
|
PO: Programme Outcomes
MME:Method of measurement & Evaluation |
| Course Contents |
| This course includes the fundamental concepts and strategies of digital transformation and experience management; digital business models and digital business processes; the introduction of digital technologies (in two phases); the planning and implementation of digital transformation; effective management of the transformation process; applications of digital transformation in sports management; the fundamentals of experience management and the design of effective experience strategies; applications of experience management in sports management; the ethical, social, and security dimensions of digital transformation and experience management; as well as a midterm exam and project presentations. |
| Weekly Course Content |
| Week |
Subject |
Learning Activities and Teaching Methods |
| 1 |
Digital transformation and experience management: Core concepts and strategies |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 2 |
Digital business models and their applications in sports management |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 3 |
Planning and managing digital business processes |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 4 |
Introduction to digital technologies: Big data and the Internet of Things |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 5 |
Introduction to digital technologies: Artificial intelligence and augmented reality |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 6 |
Planning and executing digital transformation processes |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 7 |
Applications of digital transformation in sports management |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 8 |
mid-term exam |
|
| 9 |
Fundamentals of experience management and effective experience design |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 10 |
Experience management applications in sports management |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 11 |
Ethical, social, and security aspects of digital transformation and experience management |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 12 |
Case analysis on digital transformation in sports management |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 13 |
Team or individual project work: Planning and execution |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 14 |
Project presentations and evaluation |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 15 |
General review and discussion |
Lecture and Discussion,
Applied Technology Introductions,
Case Analysis and Problem Solving,
Group Work and Project Development,
Technology Assisted Presentations |
| 16 |
final exam |
|
| Recommend Course Book / Supplementary Book/Reading |
| 1 |
Koç, H., & Çetin, E. (2022). Dijital çağda spor: Teknoloji, yapay zekâ ve veri analitiği. Spor Yayınevi ve Kitabevi. |
| Required Course instruments and materials |
| Computer, projector, and PowerPoint presentations,
AI-based performance analysis software (e.g., Catapult, Wimu, Stats Perform),
Athlete monitoring systems and sensor-based data collection devices,
Software tools for sports analytics, data mining, and machine learning (Python, R, Tableau, etc.),
Videos and case studies on digital sports applications and innovative AI solutions, |
