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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS ÖEP 5141 THE USE OF ARTIFICIAL INTELLIGENCE TOOLS IN SPECIAL EDUCATION ELECTIVE 3 0 0 8

Offered By

Special Education

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSISTANT PROFESSOR FÜSUN ÜNAL

Offered to

Special Education

Course Objective

The aim of this course is to enable prospective teachers and professionals in the field of special education to recognize the opportunities offered by artificial intelligence technologies, use them ethically, and apply them effectively in the education of individuals with special needs. The course will address the features of AI tools, their integration into classroom practices, and their role in assessment processes.

Learning Outcomes of the Course Unit

1   Identify the main AI tools used in special education. 2   Explain the role of AI technologies in special education. 3   Analyze the ethical and legal aspects of using AI in education. 4   Design an AI-supported instructional activity for individuals with special needs. 5   Evaluate the contribution of AI to assessment processes in special education. 6   Follow and critically evaluate current research related to AI in education.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to the Course and AI Concepts 2 Applications of Artificial Intelligence in Education 3 Overview of Technology Use in Special Education 4 AI Tools: Introduction and Classification 5 AI-Supported Instructional Materials and Interaction 6 Ethical and Legal Aspects 7 MidTerm Exam 8 Data Collection with Artificial Intelligence Tools 9 Data Collection with Artificial Intelligence Tools 10 AI-Supported Design of Individualized Educational Plans 11 Review of Current Research Studies 12 Review of Current Research Studies 13 Review of Current Research Studies 14 Review of Current Research Studies 15 Final Exam 16 Final Exam

Recomended or Required Reading

Kaya, A. (2024). Özel Eğitim ve Yapay Zeka. Ankara: Vize Yayıncılık.

Planned Learning Activities and Teaching Methods

Lecture, Discussion, Question & Answer, Case Study

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTEG MIDTERM GRADE 2 FCG FINAL COURSE GRADE 3 FCG FINAL COURSE GRADE MTEG * 0.40 + FCG * 0.60 4 RST RESIT 5 FCGR FINAL COURSE GRADE (RESIT) MTEG * 0.40 + RST * 0.60

Further Notes About Assessment Methods

None

Assessment Criteria

Midterm Exam, Final Exam, condition exam

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Preparations before/after weekly lectures 14 6 84 Preparation for midterm exam 1 30 30 Preparation for final exam 1 40 40 Final 1 2 2 Midterm 1 2 2 TOTAL WORKLOAD (hours) 200

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 LO.1 5 5 5 5 5 5 5 LO.2 5 5 5 5 5 5 5 LO.3 5 5 5 5 5 5 5 LO.4 5 5 5 5 5 5 5 LO.5 5 5 5 5 5 5 5 LO.6 5 5 5 5 5 5 5