SECTION I: GENERAL INFORMATION ABOUT THE COURSE

Course Code Course Name Year Semester Theoretical Practical Credit ECTS
LOJ5214 Tehlikeli Madde Taşımacılığı 2 Fall 3 0 3 6
Course Type : University Elective
Cycle: Associate      TQF-HE:5. Master`s Degree      QF-EHEA:Short Cycle      EQF-LLL:5. Master`s Degree
Language of Instruction: Turkish
Prerequisities and Co-requisities: N/A
Mode of Delivery:
Name of Coordinator: Instructor UMUT GENÇ
Dersin Öğretim Eleman(lar)ı: Instructor UMUT GENÇ
Dersin Kategorisi: Competency Development (University Elective)

SECTION II: INTRODUCTION TO THE COURSE

Course Objectives & Content

Course Objectives: The aim of the course is to ensure that students gain knowledge and awareness regarding safety, regulations, risk management, and environmental responsibility in the transportation of hazardous materials.
Course Content: This course covers the definition and classification of dangerous goods, national and international transport regulations (ADR, IMDG, RID, ICAO), packaging, labeling and marking rules, transport documents and documentation processes, responsibilities of persons and institutions involved in the transport chain, safety measures according to transport modes, emergency and accident management, environmental impacts, and sustainable transport practices.

Course Learning Outcomes (CLOs)

Course Learning Outcomes (CLOs) are those describing the knowledge, skills and competencies that students are expected to achieve upon successful completion of the course. In this context, Course Learning Outcomes defined for this course unit are as follows:
Knowledge (Described as Theoritical and/or Factual Knowledge.)
  1) 1) Explains the concept of dangerous goods and their importance in transportation. 2) Can classify dangerous goods and distinguish the characteristics of each class. 3) Identifies national and international transportation regulations (ADR, IMDG, RID, ICAO) and interprets their basic provisions. 4) Correctly applies the documents, labeling, and packaging rules used in the transportation of dangerous goods. 5) Analyzes the processes related to the transportation of dangerous goods in different modes of transport (road, sea, air, rail). 6) Explains the responsibilities and distribution of tasks among the parties in the transport chain. 7) Acquires basic knowledge and skills in risk analysis and safety plan preparation. 8) Evaluates emergency and accident management processes and develops solution proposals based on case studies. 9) Assesses the environmental impacts of dangerous goods transportation and can propose sustainable transportation approaches. 10) Develops awareness of acting in accordance with legal responsibilities and ethical principles in hazardous material transportation.
Skills (Describe as Cognitive and/or Practical Skills.)
Competences (Described as "Ability of the learner to apply knowledge and skills autonomously with responsibility", "Learning to learn"," Communication and social" and "Field specific" competences.)

Weekly Course Schedule

Week Subject
Materials Sharing *
Related Preparation Further Study
1) Definition, classification, and historical development of hazardous substances
2) Classification of dangerous goods, ADR, IMDG, IATA, and RID classes; UN numbers, packaging groups.
3) Vehicles Used in the Transport of Dangerous Goods
4) Authorities and responsibilities regarding the transport of hazardous materials, practices related to the handling of hazardous materials.
5) Packaging and labeling in the transport of dangerous goods, transport documents used in the transport of dangerous goods.
6) Risk management and occupational safety in hazardous material transportation.
7) Safety measures, equipment, and emergency response plans for the transport of hazardous materials.
8) MID TERM
9) Accidents and statistical data in the transport of hazardous materials.
10) Environmental impacts and sustainability in hazardous material transportation.
11) International regulations and agreements, national regulations and practices, vehicles used for transporting hazardous materials.
12) National and International Legislation, Safety Rules, and Operational Practices Regarding the Transport of Hazardous Waste
13) Inspection in the transport of dangerous goods, the role of the Dangerous Goods Safety Advisor (DGSA), and sanctions.
14) General evaluation and project presentations.
*These fields provides students with course materials for their pre- and further study before and after the course delivered.

Recommended or Required Reading & Other Learning Resources/Tools

Course Notes / Textbooks:
References:

DERS ÖĞRENME ÇIKTILARI - PROGRAM ÖĞRENME ÇIKTILARI İLİŞKİSİ

Contribution of The Course Unit To The Programme Learning Outcomes

Ders Öğrenme Çıktıları (DÖÇ)

1

Program Öğrenme Çıktıları (PÖÇ)
1) It explains fundamental concepts in mathematics, statistics, and probability; and applies this knowledge to data analysis, modeling, and interpretation of results.
2) It explains the principles of algorithm design and develops software for solving problems using at least one programming language.
3) It compares machine learning and data mining algorithms, selects the appropriate method, and applies it to real data.
4) Big data platforms utilize distributed systems and cloud computing architectures to perform data processing operations.
5) They apply natural language processing techniques to text data and develop basic NLP-based applications.
6) It analyzes different data sources, transforms them into meaningful outputs, and presents them using appropriate visualization tools.
7) It creates data-driven decision models using decision support systems.
8) It develops optimization models and produces solutions for industrial and sectoral problems.
9) In professional practice, we operate within the framework of ethical principles, data security, and social responsibility.
10) They keep up with current technological developments in their field, actively participate in teamwork, and develop a lifelong learning awareness.

SECTION III: RELATIONSHIP BETWEEN COURSE UNIT AND COURSE LEARNING OUTCOMES (CLOs)

Level of Contribution of the Course to PLOs

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Programme Learning Outcomes Contribution Level (from 1 to 5)
1) It explains fundamental concepts in mathematics, statistics, and probability; and applies this knowledge to data analysis, modeling, and interpretation of results.
2) It explains the principles of algorithm design and develops software for solving problems using at least one programming language.
3) It compares machine learning and data mining algorithms, selects the appropriate method, and applies it to real data.
4) Big data platforms utilize distributed systems and cloud computing architectures to perform data processing operations.
5) They apply natural language processing techniques to text data and develop basic NLP-based applications.
6) It analyzes different data sources, transforms them into meaningful outputs, and presents them using appropriate visualization tools.
7) It creates data-driven decision models using decision support systems.
8) It develops optimization models and produces solutions for industrial and sectoral problems.
9) In professional practice, we operate within the framework of ethical principles, data security, and social responsibility.
10) They keep up with current technological developments in their field, actively participate in teamwork, and develop a lifelong learning awareness.

SECTION IV: TEACHING-LEARNING & ASSESMENT-EVALUATION METHODS OF THE COURSE

Teaching & Learning Methods of the Course

(All teaching and learning methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)
Teaching and Learning Methods defined at the Programme Level
Teaching and Learning Methods Defined for the Course
Lectures
Case Study
Problem Solving
Views
Reading
Homework
Technical Visit
Questions Answers
Individual and Group Work
Role Playing-Animation-Improvisation
Active Participation in Class

Assessment & Evaluation Methods of the Course

(All assessment and evaluation methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)
Aassessment and evaluation Methods defined at the Programme Level
Assessment and Evaluation Methods defined for the Course
Midterm
Final Exam
Quiz
Homework Evaluation
Active Participation in Class

Contribution of Assesment & Evalution Activities to Final Grade of the Course

Measurement and Evaluation Methods # of practice per semester Level of Contribution
Quizzes 1 % 15.00
Midterms 1 % 35.00
Semester Final Exam 1 % 50.00
Total % 100
PERCENTAGE OF SEMESTER WORK % 50
PERCENTAGE OF FINAL WORK % 50
Total % 100

SECTION V: WORKLOAD & ECTS CREDITS ALLOCATED FOR THE COURSE

WORKLOAD OF TEACHING & LEARNING ACTIVITIES
Teaching & Learning Activities # of Activities per semester Duration (hour) Total Workload
Course 14 3 42
Laboratory 0 0 0
Application 0 0 0
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 0 0 0
Presentations / Seminar 0 0 0
Project 0 0 0
Homework Assignments 1 20 20
Total Workload of Teaching & Learning Activities - - 62
WORKLOAD OF ASSESMENT & EVALUATION ACTIVITIES
Assesment & Evaluation Activities # of Activities per semester Duration (hour) Total Workload
Quizzes 0 0 0
Midterms 1 40 40
Semester Final Exam 1 51 51
Total Workload of Assesment & Evaluation Activities - - 91
TOTAL WORKLOAD (Teaching & Learning + Assesment & Evaluation Activities) 153
ECTS CREDITS OF THE COURSE (Total Workload/25.5 h) 6