Module Catalogue 2024/25

Pre Requisite Comment

N/A

Co Requisite Comment

N/A

Aims

The aim of the module is to make the student capable of collecting the relevant data for understanding, the individual and the performance and operation of the transport system and related sectors.

The module covers general type of data and survey methods (traditionally used in transport and in other fields of engineering, economics, marketing, psychology). The module also introduces the students to real-world data collection from sources such as traffic management centres, smart cities (Urban Observatory) and trials/demonstrations of new techniques or technologies.

Students will learn a number of type of data used to study behaviour, attitudes, acceptance and operation in the real world to support trials, demonstrations and living labs and their evaluation.

Understand the need for data to provide evidence to evaluate a scheme or how transport is operating to inform business cases, safety cases and operation of transport systems and services.

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 aim of the module is to make the student capable of collecting the relevant data for understanding, the individual and the performance and operation of the transport system and related sectors.

The module covers general type of data and survey methods (traditionally used in transport and in other fields of engineering, economics, marketing, psychology). The module also introduces the students to real-world data collection from sources such as traffic management centers, smart cities (Urban Observatory) and trials/demonstrations of new techniques or technologies.

Students will learn a number of type of data used to study behavior, attitudes, acceptance and operation in the real world to support trials, demonstrations and living labs and their evaluation.

Understand the need for data to provide evidence to evaluate a scheme or how transport is operating to inform business cases, safety cases and operation of transport systems and services.

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

Intended Knowledge Outcomes

At the end of the module a student will be able to:

-Understand the link between the type of data and the specific problem to study, i.e. pros and cons (their strengths and weaknesses) of each type of data (M2, M3, M5, M8)
-Understand the link between the type of data and theory or the technology behind each specific type of data. (M1, M2, M3, M4, M8, M9)
-Collect each type of data, including identifying the appropriate type of survey and/or data collection methods (M4, M5, M6, M9, M10, M15)
- Experience of collecting data and its analysis (M8, M9, M10, M11, M12, M13)
- Experience from real-world data collection, (M11, M12, M13)
-Critically review data collected by others to assess their quality and appropriateness for the specific problem studied.(M6, M7, M14, M15)
- Construct and draft evaluation reports (M14, M15, M16, M17, M18)

Intended Skill Outcomes

At the end of the module a student will have the following skills (with AHEP4 maping):

-Understand the link between the type of data and the specific problem to study, i.e. pros and cons (their strengths and weaknesses) of each type of data (M2, M3, M5, M8)
-Understand the link between the type of data and theory or the technology behind each specific type of data. (M1, M2, M3, M4, M8, M9)
-Collect each type of data, including identifying the appropriate type of survey and/or data collection methods (M4, M5, M6, M9, M10, M15)
- Experience of collecting data and its analysis (M8, M9, M10, M11, M12, M13)
- Experience from real-world data collection, (M11, M12, M13)
-Critically review data collected by others to assess their quality and appropriateness for the specific problem studied.(M6, M7, M14, M15)
- Construct and draft evaluation reports (M14, M15, M16, M17, M18)

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 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.

General Notes

N/A