SMUA4300 Advanced Research Methods Emneplan

Much of the work in students´ scientific or practical work both during their studies and later in their professional life will require a good understanding of research methods and analysis tools and techniques. This course will provide the knowledge and skills necessary for planning and conducting engineering research, for processing data and for analysing results, with special focus upon the most common statistical techniques and data-driven computational techniques as some of the most common tools used in these areas.

Grade scale AF.

In accordance with the regulations governing studies and examinations at OsloMet - Oslo Metropolitan University, a student receiving a grade of "F" on a master's thesis is permitted to submit a new or revised master's thesis once. However, it is important to note that submitting a new or revised master's thesis within the same program is not allowed if the original submission received a grade of AE.

No formal requirements over and above the admission requirements.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge:

The student has advanced knowledge of:

• research methods, especially in engineering research
• statistical and analytical techniques, including knowledge of the most common libraries and tools used in statistical analysis and visualisation of the results
• designing experiments, preparing data and interpreting analysis results
• how relevant statistical and computational techniques relate to each other and where they are used

Skills:

The student has:

• required skills in setting up sound experiments, hypotheses and research questions, and in finding and preparing relevant data
• required skills in identifying which statistical and analytical techniques are to be used and how and where they should be used
• hands-on experience with some of the most common computational techniques and libraries as well as related tools for statistical analysis
• hands-on experience with relevant tools for use in analyses

General competence:

The student:

• has broad overview of the computational tools and techniques used in analysis and engineering research, including statistical techniques and techniques related to data science and machine learning
• has an overview of the terminology related to statistical analysis and data science.
• is able to design experiments for successful engineering research, analyses and critical interpretation of results
• can extend his/her knowledge and skills in programming/scripting, analysing, managing and visualizing data

This course features 3 optional preparatory weeks and 9 weeks of lectures that provide both theoretical and practical content and hands-on experience. The students will be given one mandatory project task to work in groups during the semester.

The preparatory weeks are optional and is for supporting the students who need to build up or renew Python/R programming skills, also using tools like Notebooks for presenting with embedded code. Notebooks will be used widely in lectures, exercises and in the mandatory project.

Students are required to complete one mandatory project assignment in allocated time and get it approved. Students who fail to meet the coursework requirements can be given up to one re-submission opportunity. (more details in Canvas).

After completing the master's thesis, the student is expected to gain several skills, defined in terms of knowledge, skills and general competence, that go beyond the realm of academic expertise and are highly transferable to various professional contexts.

Knowledge:

The student:

• has specialized knowledge in the topic of the master's thesis.
• has in-depth knowledge of theories and methods of relevance to the topic of the master's thesis.
• has knowledge of new solutions, technologies or processes in the field.

Skills:

The student:

• is capable of analyzing and taking a critical approach to different sources of information and using them to structure and formulate argumentation in the field.
• is capable of analyzing existing theories, methods and standardized solutions and of working independently on practical and theoretical problem-solving.
• is capable of using relevant methods for research and development work in an independent manner.
• is capable of carrying out an independent, delimited research or development project under supervision and in accordance with applicable research ethical standards.

General Competence :

The student:

• is capable of applying his/her knowledge and skills to new fields for the purpose of carrying out advanced tasks and projects.
• is capable of communicating extensive independent work and masters the forms of expression used in the field.
• is capable of communicating on issues, analyzes and solutions in the field of structural engineering and building technology, both with specialists and with the general public.
• is capable of contributing to new ideas and innovation processes.

The master's thesis is an independent piece of work planned and carried out by a student or a group of students (max 2). The student is responsible for conducting and managing his/her own master's thesis, including contact with the supervisor. The master's thesis shall take the form of a dissertation of a scientific nature (eg monograph, research paper, etc.) or project work (eg startup, software, digital or physical objects, etc.), original and specially created for this purpose, and an oral presentation.

If the master's thesis is conducted in cooperation with an external partner, the student(s) shall be assigned an external supervisor in addition to their internal supervisor and shall sign an agreement with the internal supervisor (contract provided on canvas) and external partner (agreements provided here: Student agreements |. Rights and duties - Student - minside (oslomet.no) .

There is no teaching offered in this course.

None

The master's thesis consists of a:

(1) A dissertation of a scientific nature (eg monograph, research paper, etc.). It should not exceed 100 pages including appendices (master thesis's template provided on canvas).

Or

(2) A project work (eg startup, software, digital or physical objects, etc.) original and specially created for this purpose. A written report, not exceeding 40 pages including appendices, should be submitted along with the project work. (master thesis's template provided on canvas)

duck

(3) An oral presentation and examination. The student will be informed about the time and place of the presentation on canvas.

The dissertation/report should be written and presented in English. It is necessary to provide an abstract in both English and Norwegian.

Students must be awarded en E or better on their disertation/project work to be permited to give the presentation.The dissertation/project work and the oral presentation will be assessed as a whole, but if there is doubt about the grading of the dissertation/project work, the grade can be adjusted up or down by one grade on the basis of the oral presentation and answers to pertaining questioning. After having reached mutual agreement, the examiners will provide the grade within 6 weeks after the submission deadline. Students have the right to an explanation for the determination of their grade. If the grade is changed as a result of re-assessment, the student must take the oral presentation and examination again. This oral presentation and examination grade cannot be appealed.

All aids are permitted.