T T4 104 2022 Course Specification - uqu.edu.sa

(1)

T4 2022

Course Title:

Marketing data analysis

Course Code : MA3113 Program: Bachelor

Department:

Marketing

College:

College of Business

Institution:

Umm Al Qura University

Version:

2

Last Revision Date:

2/2/2023

Course Specification

T-104

2022

(2)

2

Table of Contents:

Content Page

A. General Information about the course 3

1. Teaching mode (

mark all that apply)

2. Contact Hours

(based on the academic semester)

3 B. Course Learning Outcomes (CLOs), Teaching Strategies and

Assessment Methods 5

C. Course Content 5

D. Student Assessment Activities 6

E. Learning Resources and Facilities 7

1. References and Learning Resources 7

2. Required Facilities and Equipment 7

F. Assessment of Course Qualit 7

F. Assessment of Course Quality

Assessment Areas/Issues Assessor Assessment Methods

Effectiveness of teaching

Chair, Students, External Stakeholders

Department and quality committee

Open discussions with the students

Anonymous surveys

Effectiveness of students assessment

Checking marking by the students themselves if it’s possible

Using the help of other members in reviewing the assignments/exams

7

(3)

3

Quality of learning resources

Review of course portfolios

Instructor assessment by students

The extent to which CLOs have been achieved

Course specifications are periodically reviewed at the departmental level.

Courses are updated periodically and compared to the benchmark standards.

Other

Assessor (Students, Faculty, Program Leaders, Peer Reviewer, Others (specify) Assessment Methods (Direct, Indirect)

(4)

4

A. General information about the course:

Course Identification

1. Credit hours:

3

2. Course type

a.

University

☐

College

☐

Department

☒

Track

☐

Others

☐ b. Required ☒ Elective☐

3. Level/year at which this course is offered: 7



4. Course general Description

To provide students with structured and comprehensive guide to marketing analysis.

 To monitor the marketing efforts and to predict the results through strategic models and metrics.

To help making a better decision and maximizing the effect of the resources

5. Pre-requirements for this course (if any):

Principles of statistics Advertising Management

Distribution Channel

6. Co- requirements for this course (if any):

7. Course Main Objective(s)

The main purpose of this course is to include some strategic models and metrics in order to provide actionable insight. The models, which are decision tools, such as spreadsheets which help in decision making. In addition to that, the metrics that are the key indicators to provide insights into business operations

1. Teaching mode (

mark all that apply)

No Mode of Instruction Contact Hours Percentage

1. Traditional classroom Yes 90

2. E-learning Yes 10

3.

Hybrid

 Traditional classroom

 E-learning 4. Distance learning

(5)

5

2. Contact Hours

(based on the academic semester)

No

Activity Contact Hours

1. Lectures 15

2. Laboratory/Studio 15

3. Field 4. Tutorial 5. Others (specify)

Total

30

(6)

6

B. Course Learning Outcomes (CLOs), Teaching Strategies and Assessment Methods

Code Course Learning Outcomes

Code of CLOs aligned with program

Teaching Strategies

Assessment Methods 1.0 Knowledge and understanding

1.1

Define the

fundamentals of Marketing data Analysis

K1 Lecture, group

discussions, case studies

Examinations, presentations

1.2

Define a research problem and know how to answer empirically

K2 Lecture, group

discussions, case studies

…

2.0 Skills

2.1

Use a software of data analysis ^S1

Lecture, group discussions, case studies

2.2

Use different techniques of data analysis

S2

Lecture, group discussions, case

studies Examinations,

presentations

…

3.0 Values, autonomy, and responsibility

3.1

Demonstrate the ability to work in a group

V1 Group discussions,

assignments, case studies

Group works, learning logs

3.2

Encourage

participation in the front of the class

V2 Group discussions,

assignments, case studies

Group discussions, assignments, case studies ...

C. Course Content

No List of Topics Contact Hours

1. 1 Introduction to marketing data analysis 3

2. 2 Descriptive statistics 3

3 Statistical inferences 3

4 Univariate tests 3

(7)

7

6 Linear regression analysis 3

7 Exploratory factor analysis 3

8 Cluster analysis 3

9 Multidimensional scaling techniques 3

10 Conjoint analysis 3

Total 30

D. Students Assessment Activities

No Assessment Activities *

Assessment timing (in week no)

Percentage of Total Assessment Score

1. Practical works 3, 6, 10 40

2. Quiz 7 10

3. Attendance and participation 2 to 10 10

... Final exam Exam period 40

*Assessment Activities (i.e., Written test, oral test, oral presentation, group project, essay, etc.)

(8)

8

E. Learning Resources and Facilities 1. References and Learning Resources

Essential References

Marketing Research with SPSS Wim Janssens

Katrien Wijnen

Prof Patrick De Pelsmacker, University of Antwerp, Belgium Patrick Van Kenhove, University of Ghent, 2008 Supportive References

Electronic Materials Other Learning Materials

2. Required Facilities and equipment

Items Resources

facilities

(Classrooms, laboratories, exhibition rooms, simulation rooms, etc.)

Lecture room capacity: 30 seats

Technology equipment

(projector, smart board, software) Data show Other equipment

(depending on the nature of the specialty)

Laboratories equipped with pc and SPSS softaware

F. Assessment of Course Quality

Assessment Areas/Issues Assessor Assessment Methods

Effectiveness of teaching

Open discussions with the students

Anonymous surveys

Effectiveness of students assessment

Checking marking by the students themselves if it’s possible

Using the help of other members in reviewing the assignments/exams

Quality of learning resources Chair, Students, External Stakeholders

Review of course portfolios

(9)

9

Assessment Areas/Issues Assessor Assessment Methods

Department and quality

committee Instructor assessment by students

The extent to which CLOs have been achieved

Course specifications are periodically reviewed at the departmental level.

Courses are updated periodically and compared to the benchmark standards.

Other

Assessor (Students, Faculty, Program Leaders, Peer Reviewer, Others (specify) Assessment Methods (Direct, Indirect)

Specification Approval Data

COUNCIL

/COMMITTEE

MARKETING DEPARTMENT

REFERENCE NO.

DATE

28/01/2023