ARTIFICIAL INTELLIGENCE ENGINEERING
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
EDT5009	Human Performance Technology	Spring	3	0	3	12

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Dr. Öğr. Üyesi YAVUZ SAMUR
Recommended Optional Program Components:	None
Course Objectives:	The overall course objectives are: Examine basic concepts and principles of human performance technology Describe the models used in human performance technology. Examine the systematic approach to the analysis, design, development, implementation and evaluation of performance improvement interventions (performance support systems, job analysis/work design, personal development, human resource development, organizational communication, organizational design and development, financial systems)

Learning Outcomes

The students who have succeeded in this course;
1. to be able to discuss key concepts and terminology in human performance improvement
2. to be able to discuss the domain, origins, and key figures of human performance technology
3. to be able to distinguish between instructional technology and performance technology.
4. to be able to discuss the elements of selected human performance technology models.
5. to be able to explain a procedure for conducting a needs assessment and a cause analysis
6. to be able to examine the systematic approach to the analysis, design, development, implementation and evaluation of performance improvement interventions
7. to be able to discuss emerging trends in human performance technology
8. to be able to discuss selected strategies and tactics for performance improvement.

Course Content

Bu ders Insan Performans Teknolojisi alanina giriş niteliğindedir. İnsan performansı, insan performansı sistem modelleri ile ilgili temel kavram ve prensipleri ve insan performans modelleri ile ilgili problemleri inceler. Özellikle de bu derste performans geliştirme uygulamalarını (performans destek sistemleri, iş analizi, iş tasarımı, bireysel gelişim, insan kaynakları gelişimi, organizasyon iletişimi, organizasyon tasarımı ve gelişimi, finansal sistemler) derinlemesine analiz etme vurgulanmaktadır.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction and Overview
2)	What is Human Performance Technology?
3)	Human Performance Technology Models and Innovation
4)	Human Performance Technology Models
5)	Performance Analysis - Defining the problem or opportunity (Organization analysis, Environmental Analysis, Gap Analysis)
6)	Cause Analysis and Technology foresight and forecasting
7)	HPT Tools and Strategies
8)	Perspectives on HPT
9)	Teknoloji ve Öğrenme
10)	Shift from Training to Performance, Motivation, Performance Support Systems
11)	Design and manage HPT course project
12)	Technology Assessment
13)	Project Work & Project Presentations
14)	Project Presentations

Sources

Course Notes / Textbooks:	Van Tiem, D.M., Moseley, J.L. and Dessinger, J.C. (2004). Fundamentals of performance technology: A guide to improving people, process, and performance, Second Edition. Washington, DC: International Society for Performance Improvement. Pershing J. A. (Ed.). (2006). Handbook of human performance technology (3rd Ed.). San Francisco: JosseyBass.
References:	-

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	1	% 20
Project	1	% 45
Final	1	% 35
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 20
PERCENTAGE OF FINAL WORK		% 80
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Project	1	90	90
Quizzes	1	10	10
Final	1	50	50
Total Workload			192

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Have sufficient background in mathematics, science and artificial intelligence engineering.
2)	Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions.
3)	Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose.
4)	Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction.
5)	Select and use modern techniques and tools necessary for engineering applications.
6)	Design and conduct experiments, collect data, and analyse and interpret results.
7)	Work effectively both as an individual and as a multi-disciplinary team member.
8)	Access information via conducting literature research, using databases and other resources
9)	Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning.
10)	Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field.
11)	Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level.
12)	Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age.
13)	Have a sense of professional and ethical responsibility.
14)	Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices.