COURSE UNIT TITLE

Offered By

BUSINESS ADMINISTRATION

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ENGIN BAĞIŞ ÖZTÜRK

Offered to

BUSINESS ADMINISTRATION

Course Objective

Digital Applications in HR is a new way of understanding HR functions and HR's impact. Through the digital transformation, tasks of HR professionals become digitalized and evidence based. To cope with the new demands in the HR field and increase decision-making quality, learners of HR need to upskill themselves with new techniques and methodologies, such as process and design thinking in HR and analytical techniques on people-data. Therefore, Digital Applications in HR will help learners to gain theoretical and practical understanding of data and technology to advance employee performance and wellbeing.

Learning Outcomes of the Course Unit

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Recomended or Required Reading

The following book is recommended to understand the key terms:
Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction machines: the simple economics of artificial intelligence. Harvard Business Press.

Other readings throughout the course will be provided by the instructor.

Planned Learning Activities and Teaching Methods

Preparation: Students should read the materials and analyze datasets that are provided to them. Materials and datasets will be provided by the lecturer.
During Course: Lecturing, lab practices, case studies

Assessment Methods

Further Notes About Assessment Methods

Explanations related to the assessment methods:

Quiz:
Two quizzes are planned as part of the quizzes. Each quiz can be taken multiple times, and only the quiz with the highest score will be recorded in the system. The purpose of these online quizzes is to accelerate the learning curve of the students.

Active Participation:
During our course, students are expected to take the floor, criticize certain topics, and comment on the ideas of other students. In certain weeks, students' suggestions for code for data analysis will also be considered as active participation. Each contribution to the in-class discussion will be monitored and graded.

Term Project:
The term project is related to digital transformation in HR of a company dealing with global expansion, new business model or new technologies. The project will consist of four parts: understanding the goal, technology selection, implementation strategy, and change management. Each part within the project will be evaluated with its own unique features, expectations related to each one of them will be explained in class.
Term projects will be evaluated with a scale ranging from 1-5: weak, fair, good, very good, and excellent. Weak (0-39%): Does not meet expectations due to missing content, plagiarism, lack of effort, or significant errors in the plan, analysis. Fair (40-59%): Meets some expectations but needs improvement in understanding, plan development, analysis depth. Good (60-79%): Meets all expectations with a satisfactory level of understanding, a clear plan with some execution details, an adequate analysis. Very Good (80-89%): Demonstrates strong understanding and critical thinking, exceeding most expectations with a well-defined plan, effective implementation, insightful analysis. Excellent (90-100%): Exceeds all expectations in all areas, demonstrating exceptional understanding, a well-developed and executed plan, insightful analysis.

Presentation:
This refers to the presentation of the term project. It will be evaluated based on professionalism, communication, and impact. Presentations will be evaluated with a scale ranging from 1-5: weak, fair, good, very good, and excellent. Weak (0-39%): Unorganized, unprofessional formatting, unclear writing, ineffective delivery. Fair (40-59%): Disorganized, unprofessional formatting, unclear writing, distracting delivery. Good (60-79%): Organized, appropriate formatting, clear writing, acceptable delivery. Very Good (80-89%): Well-organized, professional formatting, clear writing, confident delivery. Excellent (90-100%): Flawless organization, professional formatting, clear and concise writing, engaging delivery.

Assessment Criteria

1. Students will conduct text data analysis.
2. Students will prepare a digital tranformation plan.
3. Students will visualize important points in the data.
4. Students will draw workflows of HR projects.
5. Students will identify issues in data analytics.

Language of Instruction

English

Course Policies and Rules

1. Attending at least 70 percent of lectures is mandatory
2. Plagiarism of any type will result in disciplinary action.
3. Students are expected to participate actively in class discussions.

Contact Details for the Lecturer(s)

Associate Professor Engin Bağış Öztürk, engin.ozturk[at]deu.edu.tr

Office Hours

As a general rule, please send an e-mail before stopping by the office. (Room No: 131/A)
Office hours will be announced in class by the instructor.

Work Placement(s)

None

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes