Teaching Plan Information

Presentation

Research methodologies in humanities & science covers the major considerations and tasks involved in conducting scientific research. It provides criteria of scientific rigor to reach new knowledge.

Associated skills

-Communication skills in the context of research
-Selection of the techniques and methods that can be applied to different types of research work
-Analysis and synthesis
-Team work
-Independent work
-Data analysis and Statistics
- Programming

Learning outcomes

During this course the students will learn the basics of research methods through reading, reflection, discussion, and practical exercises. Students will be empowered to develop critical thinking skills by learning how to identify a problem or question, gather data, opinions, and arguments, analyze and evaluate data, identify assumptions, establish significance, make a decision/reach a conclusion, and communicate it to other researchers in oral and written forms.

Sustainable Development Goals

4 Quality Education

5 Gender Equality

Prerequisites

Basic Python (notebooks) Programming or MATLAB

Contents

The course is distributed in 10 sessions. Two sessions will provide a theoretical background on research methods (including epistemological background, ethics, information sources, technical writing). Five lessons will focus on experimental design, statistics and the application of data science techniques. Two sessions will be devoted to practical work on a research project using Python or MATLAB. During the last session, the students will present the results of the research project executed along the course.

Teaching Methods

The course consists of 10 lectures of 2,5 hours. The participation of the students during the sessions will be encouraged through agile exercises, discussions and Q&A. Students will require to design and execute a research project in groups, submit assignments and complete a final exam.

Evaluation

Assignments (25% over the total score)
Exam (30% over the total score)
Project, including deliveries, a short paper and a presentation (45% over the total score)

Bibliography and information resources

Recommended bibliography includes:

Hugh Coolican (2019) Research Methods and Statistics in Psychology Publisher: Hodder Arnold; ISBN-10: 0340812583 

McKennie, W. (2017) Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython 1st Edition O'Reilly Media. ISBN-10:1449319793

More information resources will be recommended during the course.

Teaching Plan Information

Presentation

Research methodologies in humanities & science covers the major considerations and tasks involved in conducting scientific research. It provides criteria of scientific rigor to reach new knowledge.

Associated skills

-Communication skills in the context of research
-Selection of the techniques and methods that can be applied to different types of research work
-Analysis and synthesis
-Team work
-Independent work
-Data analysis and Statistics
- Programming

Learning outcomes

During this course the students will learn the basics of research methods through reading, reflection, discussion, and practical exercises. Students will be empowered to develop critical thinking skills by learning how to identify a problem or question, gather data, opinions, and arguments, analyze and evaluate data, identify assumptions, establish significance, make a decision/reach a conclusion, and communicate it to other researchers in oral and written forms.

Sustainable Development Goals

4 Quality Education

5 Gender Equality

Prerequisites

Basic Python (notebooks) Programming or MATLAB

Contents

The course is distributed in 10 sessions. Two sessions will provide a theoretical background on research methods (including epistemological background, ethics, information sources, technical writing). Five lessons will focus on experimental design, statistics and the application of data science techniques. Two sessions will be devoted to practical work on a research project using Python or MATLAB. During the last session, the students will present the results of the research project executed along the course.

Teaching Methods

The course consists of 10 lectures of 2,5 hours. The participation of the students during the sessions will be encouraged through agile exercises, discussions and Q&A. Students will require to design and execute a research project in groups, submit assignments and complete a final exam.

Evaluation

Assignments (25% over the total score)
Exam (30% over the total score)
Project, including deliveries, a short paper and a presentation (45% over the total score)

Bibliography and information resources

Recommended bibliography includes:

Hugh Coolican (2019) Research Methods and Statistics in Psychology Publisher: Hodder Arnold; ISBN-10: 0340812583 

McKennie, W. (2017) Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython 1st Edition O'Reilly Media. ISBN-10:1449319793

More information resources will be recommended during the course.