GMS 3102 - Kitchen Practices IV - Course Information

Basic Information

Course Code:

GMS 3102

Course Name:

Kitchen Practices IV

Language of Instruction:

English

Course Type:

Class

Course Level:

Bachelor

ECTS:

4.00

Instructor:

Doç. Dr. OĞUZ DOĞAN

Course Objectives

Students learn selection of suitable cooking technique, food preparation, effective recipe usage and mise-en-place in respect to timing throughout this course. Kitchen practices about stocks, bakery and basic cooking techniques are performed. The course provides information about how attentive and delicious food preparation and serving to real customers is conducted. The course covers the preparation and presentation of garde manger - hot cooking practices in details

Course Content

The content of this course is made up of the forthcoming culinary specifications and practices of Europe, Far East, Asia, and the America continents. The students are informed about the culinary culture and the cuisines of those geographical areas. The recipes belonging to those geographical areas of the world are taught theoretically and practically

Prerequisites / Corequisites

GMS 1005 Food Safety and Hygiene and GMS 1002 Introduction to Kitchen Practices

Course Books / Materials / Recommended Resources

None

Learning Outcomes

Code	Description
LO1	Apply various cooking techniques.
LO2	Apply garnish preparation techniques.
LO3	Apply different presentation techniques.
LO4	Create his/her own presentation style.
LO5	Prepare food items for cooking.

Weekly Course Content

Week	Content
1	Marinades, pan frying glaze
2	Galantine, the dishes which cooked in poaching technique
3	Bullions, stock reduction, vinaigrette dressing
4	Steaks with mushroom and sauce, foi grass
5	Sea foods with sauce
6	Vegetables with sauces
7	Midterm Exam
8	Steak Menu planning for 2 people
9	Seafood menu planning for 4 persons
10	Hors d’oeuvre preparation for 4 persons
11	Regional themed menu preparations
12	Special day themed menu preparation
13	Gard manger, Charcuterie
14	Final Project
15	End-of-Term Evaluation

Workload Calculation

Activity	Count	Duration (Hours)	Total
Attendance	15	4.00	60.00
Practice	15	4.00	60.00
Midterm Exam/Preparation	1	3.50	3.50
Final Exam/Preparation	1	3.50	3.50
Total Workload (Hours)			127
ECTS Credit (Workload / 25)			4

Assessment

#	Assessment Type	Contribution (%)
1	Midterm Exam	%40
2	Final Exam	%60
TOTAL		%100

PO - LO Matrix

PO \ LO	LO1	LO2	LO3	LO4	LO5
PO-1
PO-2
PO-3
PO-4
PO-5
PO-6
PO-7
PO-8
PO-9
PO-10
PO-11
PO-12
PO-13
PO-14

1

Low Contribution

2

Medium Contribution

3

High Contribution

Teaching and Learning Methods

#	Method Name	Description	Tools
1	Lecture (expository teaching), interactive discussion	Listening and taking notes.	Standard classroom technologies, multimedia tools (projector, computer, digital presentations)
2	Group Work	Students determine the slope and cross-sectional geometric characteristics of a parabolic irrigation canal on campus, plot the flow rate curve at different sections of the canal, and submit a report.	Land surveying instruments
3	Laboratory	Listening, note-taking, conceptual analysis, critical thinking, questioning, and participation in discussions.	Special equipment

Academic Integrity and Artificial Intelligence

Academic integrity is a fundamental principle of this course. Students are expected to produce original work in all assignments and academic activities. Plagiarism, fabrication or falsification of data, the use of others’ ideas, thoughts, or texts without proper citation, and presenting a work while concealing the contribution of others are considered ethical violations. Within the scope of this course, artificial intelligence tools may be used as supportive resources in the learning process. Such use requires responsibility and transparency. Artificial intelligence may be utilized for idea development, clarification of concepts, language editing, or technical support. However, content generated by artificial intelligence may not be copied and presented as the student’s own academic work. Any use of artificial intelligence must be clearly acknowledged, and the final work must reflect the student’s own ideas, reasoning, academic knowledge, and effort. Failure to disclose the use of artificial intelligence or the detection of ethical violations will be evaluated in accordance with the relevant university regulations.

Sustainable Development Goals