ARTIFICIAL INTELLIGENCE AWARENESS
- Course
- APSC123 - ARTIFICIAL INTELLIGENCE AWARENESS
- Department
- Management Information Systems - English - Undergraduate
- Course Type
- Online Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 6
- T+P+L
- 0 + 0 + 3
- Course Coordinator(s)
- Asst. Prof. Dr. Kian JAZAYERI
- Prerequisite
- -
Course Description
This course provides an accessible and engaging introduction to Artificial Intelligence (AI), focusing on its core concepts, real-world applications, and broader impact on society. Students from all academic backgrounds will explore how AI shapes everyday life, with special attention to its role in education, language learning (such as platforms like Duolingo), and classroom assignments. The course highlights how AI agents are increasingly used in areas like tutoring, content generation, and personalized learning support. Through real-world examples and discussions, students will learn about the potential and limitations of AI, while also understanding key ethical issues such as fairness, privacy, and responsible use.
ARTIFICIAL INTELLIGENCE AWARENESS
Evaluation Tools (Active Term)
| Item | Type | Weight (%) |
|---|---|---|
| Final Exam | Final | 40 |
| Midterm Exam | Midterm | 30 |
| Homework 1 | Assignment | 15 |
| Homework 2 | Assignment | 15 |
| Total | 100 | |
Course outcomes
No course outcomes have been defined yet.
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | What is AI? (ANI vs AGI, Machine Learning, Data, Why Now?) |
| Week 2 | How AI Works in Practice (Machine Learning basics, examples, what AI can/can’t do) |
| Week 3 | Building AI Projects (workflow, selecting use cases, data importance) |
| Week 4 | Building AI in Organizations (AI strategy, roles in AI teams, pilot projects) |
| Week 5 | Generative AI Introduction (LLMs, image/audio/video generation, prompting) |
| Week 6 | Generative AI in Practice (software applications, RAG, fine-tuning, cost of AI) |
| Week 7 | Generative AI and Business (automation vs. augmentation, job task analysis) |
| Week 8 | Midterm Examination |
| Week 9 | AI and Society (AI hype, limitations, bias, adversarial attacks) |
| Week 10 | AI Ethics and Responsible AI |
| Week 11 | AI and Future of Work (jobs at risk, new opportunities, skills needed), The Future of AI (speculative futures, opportunities, risks, AGI debates) |
| Week 12 | AI in Daily Life (healthcare, education, governance, developing economies) |
| Week 13 | Policy and Regulation (global perspectives, EU AI Act, governance frameworks) |
| Week 14 | Philosophy of Artificial Intelligence |
| Week 15 | Final Exam |
Reference Books & Course Materials
- 01 Philip C. Jackson, Introduction to Artificial Intelligence, Third Edition, Dover Publications, 2019.
Learning Outcomes
- L01 Define fundamental AI concepts, distinguish ANI from AGI, and explain why AI is transforming industries. SOLO 3.3
- L02 Describe core AI capabilities and limitations, and identify tasks suitable for AI automation. SOLO 2.5
- L03 Explain how AI projects are structured and recognize AI’s role in business and organizational transformation. SOLO 3.3
- L04 Analyze how organizations adopt AI, identify roles in AI transformation, and evaluate its potential to augment or automate tasks across professions. SOLO 3.7
- L05 Explain generative AI concepts, differentiate between prompting, fine-tuning, and RAG, and illustrate common applications (text, image, audio). SOLO 3.7
- L06 Recognize AI’s limitations, sources of bias, and risks from adversarial manipulation, and discuss fairness, transparency, privacy, and responsible AI guidelines. SOLO 3.5
- L07 Assess AI’s impact on jobs, workforce transitions, and future skill requirements, and analyze its effects across sectors such as education, healthcare, and governance. SOLO 4.5
- L08 Explain different approaches to AI regulation, evaluate policy frameworks, and critically reflect on possible AI futures and their ethical and social implications. SOLO 4.75
- L09 Explaing and Asses AI Philosophy SOLO 4.5
Program Outcomes
- P01 1- make use of their professional training in language teaching and achieve effective classroom management,
- P02 2- carry out research on the development of their learners’ social, psychological and personal characteristics by using testing and evaluation techniques in accordance with ethical principles and then report their results.
- P03 3- conduct research using basic scientific research techniques with the aim to find solutions to problems that may be encountered in the field of Teaching English,
- P04 4- evaluate, apply and interpret concepts and scientific methods related to the field of teaching English
- P05 5- choose appropriate language teaching methods and techniques considering diverse learner characteristics stemming from their ages, learning styles, motivation and background knowledge,
- P06 6- prepare daily lesson plans appropriate to the things to teach and deliver effective lessons by using appropriate course materials and instructional technology,
- P07 7- choose appropriate materials available for use and/or develop their own course materials according to students’ level, interest and learning characteristics with the aim to use them in the teaching of language items (phonological, lexical, grammatical items and so on) and in the development of learners’ language skills (listening, speaking, reading and writing),
- P08 8- choose and use appropriate measurement tools and materials to asses and evaluate learners’ development and success,
- P09 9- explain the similarities and differences between first and second language acquisition theories, and relate these theories to language teaching theories and practices.
- P10 10- make use of principles, theories, approaches and techniques for the development and evaluation of educational programs.
- P11 11- explain the concepts of Theoretical Linguistics & Applied Linguistics and use their knowledge for the preparation of lesson plans appropriate to the characteristics of the target language,
- P12 12- use information and communication technology together with computer software required by the field,
- P13 13- describe the characteristics of different text types considering basic theories & approaches in translation and translate texts from English to Turkish and from Turkish to English,
- P14 14- define the basic concepts and principles of classical and modern literature, analyse and construct information, and then make use of their literary knowledge in language teaching,
- P15 15- use the target language to obtain and transmit information; communicate either orally or in writing.
- P16 16- identify and solve problems in their social environment with the awareness of social responsibility they have developed.
Po-Lo Matrix
| LO | P01 | P02 | P03 | P04 | P05 | P06 | P07 | P08 | P09 | P10 | P11 | P12 | P13 | P14 | P15 | P16 | Average |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| L01 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L02 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L03 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L04 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L05 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L06 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L07 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L08 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L09 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |