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Module

CEG8435 : Data collection and survey methods

  • Offered for Year: 2022/23
  • Module Leader(s): Professor Elisabetta Cherchi
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus
Semesters
Semester 2 Credit Value: 10
ECTS Credits: 5.0

Aims

The aim of the module is to make the student capable of collecting the relevant data for understanding, modelling and planning consumer’s behaviour. The module is built as part of the MSc in transport but most of the contents are not transport-specific and can be applied and hence be of interest for several disciplines in engineering (environment, water, energy, etc.), in economics (environmental, health, food, etc.), marketing etc.

The module is open and welcome students and professionals from any fields who are interested in learning how to collect data to study consumer’s behaviour.

The module covers general type of data and survey methods (traditionally used in transport and in other fields of engineering, economics, marketing, psychology), as well as recent techniques that make use of advanced technology (such as smartphone, virtual reality, etc.) to track movements or to study technologies not yet available (such as autonomous vehicles).

Students will learn a number of type of data used to study consumer’s behaviour and a variety of techniques to collect these data. Students will also learn how to use the appropriate type of data for each specific type of problem analysed.

The module includes also a brief RECAP of the sampling theory covered in the Transport Research Methods CEG8423 or other analogous modules (for students not in transport).


-The theoretical part is supported by an extensive empirical work where students have the possibility to practically build their own survey and experience collecting the data.

-The module also provides information on how to do a descriptive analysis of the data collected and how to write a report for policy makers or industrial clients.

Outline Of Syllabus

The themes of lectures delivered are (it does not correspond to the exact lecture schedule):

Basic Data and data Collection Methods:
-Introduction to consumer’s behaviour and information needs
-Types of data
-Types of surveys
-Survey protocol and sample size
-Survey data correction, expansion and validation

Qualitative data:
-Why and when qualitative data
-Forms of qualitative research: Focus groups, Metaplan, Expert opinion
-Survey protocol
-Data analysis

Cross-sectional and longitudinal data:
-Survey period
-Questionnaire design
-Sample size
-Types of surveys
-Data analysis

Stated Preference data:
-Survey process
-Introduction to Experimental Design Theory
-Orthogonal and Efficient Designs
-Comparison with contingent evaluation
-Sample size
-Introduction to common software to build experimental designs
-Data analysis

Attitudinal data:
-Introduction to the psychological/social theories
-Definition of the psychological/social constructs
-Questionnaire designs

New technology to collect data:
-Possible topics are (might change subject to lab availability): Smartphone, Social channels, Virtual Reality, Eye tracking
-Status of the art and potentiality

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion150:0050:00Group report of 3/4 students. Report will be evaluated.
Scheduled Learning And Teaching ActivitiesLecture41:004:00Computer practical’s included demo’s &sessions for completion of assessed work whilst under guidance
Scheduled Learning And Teaching ActivitiesLecture51:005:00PiP Lectures
Scheduled Learning And Teaching ActivitiesPractical12:002:00Q&A sessions - PiP
Scheduled Learning And Teaching ActivitiesPractical35:0015:00Exercises under the guidance of the lecturers - PiP
Guided Independent StudyIndependent study116:0016:00Project independent work
Scheduled Learning And Teaching ActivitiesModule talk42:008:00PiP Lectures
Total100:00
Teaching Rationale And Relationship

Teaching and learning of this module is done by a combination of lectures, computer demonstrations and practical work, guest lectures, coursework and reading materials. This is in line with the learning outcomes. Lectures, guest lectures and coursework are intended to provide the theoretical background, computer demonstrations allow students to learn the software and the codes to build the mathematical model. Practical work allows students to learn how to link the theory with the practice (how to use the theory in practice) and help developing problem solving skills. Reading materials helps developing critical, independent and innovative thinking.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Report2M60Report groupwork of 3-4 people that describes theoretical and practical work carried out to collect online data for problem assigned
Report2M40Each student will receive a question based on the group report and will write to short report addressing the question.
Assessment Rationale And Relationship

The form of examinations (group written report and individual short report addressing a specific question) are intended to test if students acquired the intended skills in terms of understanding and master the theory behind data collection and being able to apply the theory in practice. In particular:

(1)       Data collection involves major work that is typically performed in team. This is why the practical work and the report is a group work, though teams will be small (3-4 people) to make it easier for the students to organise the work.
(2)       The short report allows testing students’ ability to address specific questions related to the work done. The short reports are individuals, allowing also identifying the contribution of each student within the team.

Reading Lists

Timetable