AI-SUPPORTED MEASUREMENT AND EVALUATION PRACTICES IN EDUCATION

EDS444

Course Code: EDS444
Semester: -
Theory+Practice: 2 + 0
ECTS: 4

Course Type

Elective Course

Course Level

Bachelor's Degree

Year of Study

Semester

ECTS

Name of Lecturer(s)

Learning Outcomes

At the end of this course, the students;

Evaluates the questions produced by artificial intelligence from a psychometric point of view.
Evaluates open-ended question responses generated by AI and real raters and compares their results.
Interpret the results obtained by combining artificial intelligence and classical measurement methods.
Examines the limitations of artificial intelligence in measurement and evaluation processes.

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

Course Description

This course focuses on the effects of Artificial Intelligence on Assessment and Evaluation in Education. In the course, the transformative effect of Artificial Intelligence in assessment and evaluation, the use of Artificial Intelligence in assessment and evaluation, applications and the role of teachers in this context are examined. Ethical principles in the use of AI and responsible use of AI are discussed.

Course Contents

WEEK	TOPICS
1^st Week	Artificial Intelligence and Assessment in Education: Introduction and Basic Concepts
2^nd Week	The role of assessment and evaluation in teaching, concepts changing with AI, and teacher competencies
3^rd Week	Advantages and risks of using AI in Assessment and Evaluation
4^th Week	Comparison of Traditional Assessment and Evaluation with AI-supported Assessment and Evaluation
5^th Week	Automatic Item Generation: The role of large language models
6^th Week	Application Strategies for Automatic Item Generation
7^th Week	Automatic Scoring and Feedback Systems
8^th Week	Midterm exam
9^th Week	Application Strategies for Automatic Scoring and Feedback
10^th Week	The Complementary Role of Teachers in AI-Supported Measurement and Evaluation
11^th Week	Ethics, Data Privacy
12^th Week	Bias, Hallucination
13^th Week	Artificial Intelligence Tools Used in Measurement and Evaluation
14^th Week	Artificial Intelligence Tools Used in Measurement and Evaluation
15^th Week	Overview

Recommended or Required Reading

Planned Learning Activities and Teaching Methods

Lecture
Discussion
Questions/Answers

Assessment Methods and Criteria

	Quantity	Percentage (%)
Mid-term	1	20
Assignment	3	30
Total(%)		50
Contribution of In-term Studies to Overall Grade(%)		50
Contribution of Final Examination to Overall Grade(%)		50
Total(%)		100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Midterm exam	1	2	2
Preparation for Quiz
Individual or group work	14	3	42
Preparation for Final exam	1	12	12
Course hours	13	2	26
Preparation for Midterm exam	1	12	12
Laboratory (including preparation)
Final exam	1	2	2
Homework	3	8	24
Total Work Load			120
Total Work Load / 30 (h)			4
ECTS Credit of the Course			4

Language of Instruction

Turkish

Work Placement(s)

Programme Qualifications / Learning Outcomes

	LO1	LO2	LO3	LO4
K1
K2
K3	X	X	X	X
K4
K5
K6
K7
K8
K9
K10