195.029 Research Methods in Computer Science Canceled
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2014S, VU, 2.0h, 3.0EC

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise

Aim of course

This course is divided into two parts:

The first part of the course provides a basic understanding of qualitative methods, and how to critically apply these in computer science for the purposes of design and evaluation of technology. By the end of this part students will:

  • Understand the relative strengths and philosophical positioning of qualitative and quantitative research methods in relation to technology;
  • understand the advantages, disadvantages and basic techniques of qualitative research methods, and associated theories as relevant;
  • be able to critically choose, apply and reflect on the use of methods in practice;
  • be able to analyse user data and derive insights for design;
  • understand if and how qualitative methods might apply to their particular research questions.
In the second part of the course, basic methods for the collecting of data using complex survey designs, methods for pre-processing the data as well as methods for the estimation of indicators from complex surveys are in main focus (~"from data to indicators"). For applications, data from official statistics, from geosciences, from clinical studies and data from the social and economic sciences in general are used. The methods are applied on these data with the help of the software environment R.

Subject of course

First part of the course (Prof. Fitzpatrick):

This class will be highly interactive and will use a mixed methods approach involving small group work and learning by doing and reflecting:

  • reviewing literature and identifying key themes/approaches
  • in-class presentations, discussions and reflections
  • in-class exercises using a running 'small' group project throughout the semester

Content will focus on understanding and applying qualitative user research methods that contribute to a better understanding of people and their use contexts.

  1. What are qualitative methods and what value do they offer
  2. Core qualitative user research skills
       - Data collection/user study: Observation, Interview;
       - Data analysis: using an adapted grounded theory /thematic analysis approach
  3. Additional qualitative methods and theories: This will be decided on, specific to the needs and interests of the class participants
Second part of the course (Prof. Templ):
 
In this lecture, basic methods for the collecting of data using complex survey designs, methods for pre-processing the data as well as methods for the estimation of indicators from complex surveys are in main focus (~"from data to indicators")
For applications, data from official statistics, from geosciences, from clinical studies and data from the social and economic sciences in general are used. The methods are applied on these data with the help of the software environment R.

The content of the lecture is as follows:
1. collection of data:
        - CAPI, CATI, online, retrospective, ...
        - addresses/registers/online resources/sampling frames/cost aspects
2. Complex Sampling Designs, 
        - stratified, multiple stage designs
        - sample size issues
3. Pre-processing
        - editing
        - imputation (estimation of missing or erroneous information)
4. Calibration and Estimation
        - non-resonse calibration
        - weighted estimation
5. Evaluation:
        - variance estimation, bias
        -  comparing methods through simulation
        - resampling methods
6. Dealing with non-random samples:
        - retrospecive studies
        - response propensity models
7. Data fushion
        - record linkage
        - statistical matching
8. Practical appliations with R (+ brief introduction to R)
 

Additional information

This is a fundamental course of Vienna PhD School of Informatics It will be held by Prof. Fitzpatric and Dr. Templ.

This course is offered to all PhD students of the Faculty of Informatics.

 
ECTS breakdown for each part:

- 12 hrs - in-class blocked sessions
- 12 hrs - readings and exercises between classes
- 13.5 hrs - assignment

Lecturers

Institute

Examination modalities

First part of the course:

  • 50% of the grade based on a portfolio (details of content to be decided)
  • other 50% to be announced

Second parf of the course:

  • practical work which is done as homework and short discussion about the results/code/application during the oral exam. 
  • oral or written exam about the subject matters from the lecture.

 

Course registration

Begin End Deregistration end
03.02.2014 00:00 06.06.2014 00:00 06.06.2014 00:00

Registration modalities

Please register in TISS.

Curricula

Study CodeObligationSemesterPrecon.Info
PhD Vienna PhD School of Informatics Not specified

Literature

Lecture notes and slides are given by the lecturers in class

Miscellaneous

  • Attendance Required!

Language

English