KB7067 - Engineering Management Data Analysis

Active learning sessions will allow you to engage with and appraise specialist knowledge and assist you in exploring and critiquing key concepts and topics within the module. Sessions will involve a combination of content delivery and practical learning exercises to enable you to apply your learning to complex and authentic engineering problems.?A problem-solving focused curriculum will allow you to explore and analyse solutions to complex challenges in relevant subject areas. Learning activities will enable the facilitation of creative thinking approaches to solve open-ended engineering problems.

During your active learning sessions, academic support will be available to facilitate your exploration of the problem-solving activities. Formative feedback will be provided by the module team, including answering student queries and providing guidance concerning the module such as assessments and your academic progress. The electronic learning platform (eLP) provides a comprehensive resource for integrated learning incorporating learning materials and reading lists that will facilitate directed and self-directed learning. Contact with academic tutors and your peers outside formal teaching hours is encouraged through dedicated ‘office hours’, discussion boards and messaging systems within the eLP. Professional support staff, such as Ask4Help, provide the first point of contact for a range of queries, including, for example, those concerning assessment submission, late submission/extensions, and other administrative issues.

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

You will be able to:

Knowledge & Understanding:
MLO1. Apply a comprehensive knowledge of mathematics, statistics, natural science and engineering principles to the solution of complex problems. Much of the knowledge will be at the forefront of the particular subject of study and informed by a critical awareness of new developments and the wider context of engineering (M1)
MLO2, Select and critically evaluate technical literature and other sources of information to solve complex problems (M4)
MLO3, Apply knowledge of engineering management principles, commercial context, project and change management, and relevant legal matters including intellectual property rights (M15)

Intellectual / Professional skills & abilities:

MLO4. Select and apply appropriate data analysis skills, aided by computational techniques to help solving complex problems, discussing the limitations of the techniques employed.
(M3)

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
MLO5, Formulate and analyse complex problems to reach substantiated conclusions. This will involve evaluating available data using first principles of mathematics, statistics, natural science and engineering principles, and using engineering judgment to work with information that may be uncertain or incomplete, discussing the limitations of the techniques employed (M2)

Formative Assessments


Academic staff on the module will assess you in a formative manner to help build your confidence and highlight any improvements required to meet the MLOs.



Your formative feedback will be given to you either verbally by academic staff on the module during formally scheduled teaching sessions or using the eLP. Your formative feedback aims to help you learn and prepare for the submission of your summative assessment.

Summative Assessment



Component 1. Coursework 001 (30%)
This component includes tasks such as technical literature research and analytical modelling work on the core subject in a written report (2500 words or equivalent). It will assess MLOs 2 and 3


Component 2. Coursework 002 (70%)
This component requires students to conduct a set of research tasks and complete with a technical report (3500 words or equivalent) which will assess MLOs 1, 4 and 5.


Feedback will be provided electronically through the eLP within 20 working days of the date of submission.

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This module provides the students with in-depth knowledge of data analysis with a focus on engineering management through theoretical models that can be implemented on commercially available computer software tools. The module extends data analysis to incorporate modelling of engineering problems involving uncertainty involving multiple criteria considerations. The technical aspects of data analysis and the probabilistic modelling of problems supports the making of defensible decisions involving techno-economic, ethical, societal and other engineering management criteria.