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Viewing: TTM 731 : Decision Models and Applications in Textile and Apparel Management

Last approved: Tue, 13 Mar 2018 08:00:15 GMT

Last edit: Wed, 07 Mar 2018 16:14:16 GMT

Catalog Pages referencing this course
Change Type
Major
TTM (Textile Technology Management)
731
032573
Dual-Level Course
Cross-listed Course
No
Decision Models and Applications in Textile and Apparel Management
Textile and Apparel Management
College of Textiles
Textile and Apparel Management (18TAM)
Term Offering
Spring Only
Offered Every Year
Fall 2018
Previously taught as Special Topics?
Yes
4
 
Course Prefix/NumberSemester/Term OfferedEnrollment
TTM 791Spring 201714
TTM 791Spring 201613
TTM 791Spring 20155
TTM 791Spring 20146
Course Delivery
Face-to-Face (On Campus)

Grading Method
Graded/Audit
3
16
Contact Hours
(Per Week)
Component TypeContact Hours
Lecture3
Course Attribute(s)


If your course includes any of the following competencies, check all that apply.
University Competencies

Course Is Repeatable for Credit
No
 
 
Dr. Lori Rothenberg
Associate Professor
assoc

Open when course_delivery = campus OR course_delivery = blended OR course_delivery = flip
Enrollment ComponentPer SemesterPer SectionMultiple Sections?Comments
Lecture1515NoN/A
Open when course_delivery = distance OR course_delivery = online OR course_delivery = remote


Is the course required or an elective for a Curriculum?
Yes
SIS Program CodeProgram TitleRequired or Elective?
TTMTextile Technology ManagementRequired
This course provides students with an overview of data decision models used in the textile and apparel industry, along with skills to apply them in real-world decision processes. Published academic papers and case studies will augment the teaching and learning in international trade, supply chains, manufacturing processes, quality, marketing, retail and distribution.

The course has been offered under TTM 791 for 4 years. It needs a permanent course number.


No

Is this a GEP Course?
GEP Categories

Humanities Open when gep_category = HUM
Each course in the Humanities category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Mathematical Sciences Open when gep_category = MATH
Each course in the Mathematial Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

Natural Sciences Open when gep_category = NATSCI
Each course in the Natural Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

Social Sciences Open when gep_category = SOCSCI
Each course in the Social Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Interdisciplinary Perspectives Open when gep_category = INTERDISC
Each course in the Interdisciplinary Perspectives category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

Visual & Performing Arts Open when gep_category = VPA
Each course in the Visual and Performing Arts category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Health and Exercise Studies Open when gep_category = HES
Each course in the Health and Exercise Studies category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
&
 

 
 

 
 

 
 

Global Knowledge Open when gep_category = GLOBAL
Each course in the Global Knowledge category of the General Education Program will provide instruction and guidance that help students to achieve objective #1 plus at least one of objectives 2, 3, and 4:
 
 

 
 

 
Please complete at least 1 of the following student objectives.
 

 
 

 
 

 
 

 
 

 
 

US Diversity Open when gep_category = USDIV
Each course in the US Diversity category of the General Education Program will provide instruction and guidance that help students to achieve at least 2 of the following objectives:
Please complete at least 2 of the following student objectives.
 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

Requisites and Scheduling
 
a. If seats are restricted, describe the restrictions being applied.
 

 
b. Is this restriction listed in the course catalog description for the course?
 

 
List all course pre-requisites, co-requisites, and restrictive statements (ex: Jr standing; Chemistry majors only). If none, state none.
 

 
List any discipline specific background or skills that a student is expected to have prior to taking this course. If none, state none. (ex: ability to analyze historical text; prepare a lesson plan)
 

Additional Information
Complete the following 3 questions or attach a syllabus that includes this information. If a 400-level or dual level course, a syllabus is required.
 
Title and author of any required text or publications.
 

 
Major topics to be covered and required readings including laboratory and studio topics.
 

 
List any required field trips, out of class activities, and/or guest speakers.
 

The faculty will be teaching this course as a part of their normal workload. Faculty will need seminal and recent works in decision making models in the textile and apparel industry. In addition, faculty will need the appropriate statistical and decision making software.

To provide students with the tools necessary for most of the management decisions required in the FTAR supply chain complex.


To help students develop the ability to conduct research on a FTAR topic by applying existing data decision making models.


To build student proficiency to critically evaluate academic literature and avoid the common pitfalls of research or data decision processes.


To develop student abilities to understand the values and limitations of quantitative decision models


Student Learning Outcomes

Students will be able to describe and apply the tools used in management decisions in the FTAR complex.


Students will be able to complete a research study on a FTAR topic by applying the appropriate data decision making model.


Students will be able to synthesize the findings from their respective research studies and communicate the results.


Students will be able to critically evaluate management research articles that employ data decision making models.


Evaluation MethodWeighting/Points for EachDetails
Exam25Exam
presentation10Presentation of Final Research Paper in mock conference setting
Discussion10Discussion Leadership
Participation15Oral and written contributions in class
Written Assignment25Final Research Paper
Written Assignment15Review Report - review classmate's research paper using real journal paper review rubric
TopicTime Devoted to Each TopicActivity
Big Data1 course periodLecture
Question and Answer
Alternative Competing Hypotheses1 course periodDiscussion Leadership
Lecture
Case Study Analysis
Psychometrics1 course periodDiscussion Leadership
Lecture
Statistical Examples
Consumer Decision Making1 course periodDiscussion Leadership
Lecture
Construction of Conjoint Study
Time Series1 course periodDiscussion Leadership
Lecture
Problem Solving
Data Visualization1 course periodDiscussion Leadership
Lecture
Hands-on use of IBM Watson Analytics or equivalent
Analytics for Social Media1 course periodDiscussion Leadership
Lecture
Hands-on use of IBM Watson Analytics for Social Media or equivalent
Predictive Models1 course periodDiscussion Leadership
Lecture
Hands-on use of IBM Watson Analytics or equivalent
Data Visualization and Prediction1 course periodDiscussion Leadership
Lecture
Hands-on use of IBM Watson Analytics or equivalent
Text Mining1 course periodDiscussion Leadership
Lecture
Hands-on use of Text Mining software
Individual Consultations1 course periodFinalizing conference presentations
Finalizing Discussant Remarks
Optimization Decisions1 course periodDiscussion Leadership
Lecture
Hand-on use of DOE software
Data Management1 course periodDiscussion Leadership
Lecture
Mock Conference Session1 course periodOpening Session Keynote Speaker
Paper Presentations
Discussants Remarks
Discussion Leadership
Mock Conference Session1 course periodPaper Presentations
Discussants Remarks
Discussion Leadership
Closing Session Keynote Speaker
mlnosbis 12/20/2017:
1) In prereq field, enter the academic plan (18TTMPHD) as a requisite as directed in the help bubble.
2) The course description on the CIM form should match that on the syllabus.
3) Indicate (on the syllabus) what the necessary software is, and how students may obtain it if they do not use a university computer.

cohen 1/18/2018:
1. This is a 700-level course and so Credit Only grading is not an option. Please make that clear on the syllabus.
2. On the syllabus under Late Assignments, there is a comment that discussions and presentations not ready on the scheduled day will be assigned a grade of 'C'. Is it possible to receive a grade lower than C in those circumstances? If so, I would suggest pointing that out on the syllabus.

ABGS Reviewer Comments 2/12/2018:
- Previous comments have been addressed.
- No concerns.
yxu11 (Mon, 06 Nov 2017 18:36:06 GMT): Rollback: Please update per comments provided from the last TTM Steering committee meeting. When done, please resubmit. Thanks. ----Yingjiao
smichie (Fri, 01 Dec 2017 17:43:49 GMT): Rollback: Lori - On the submitted syllabus, the section that starts with Exam is an incomplete sentence. Can you finish it. Also, the Assessment distribution in the syllabus and the html are different. Can you correct this? Thanks -- Steve
Key: 13788