Mobile and Social Computing

University of Oulu
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Course overview

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ECTS Credits 5   cr
Language of instruction FI.

In English.


Spring, periods 3-4

Learning outcomes

1. Ability to implement mobile user interfaces

2. Ability to implement online social network applications

3. Ability to explain the fundamental concepts of context awareness

4. Ability to explain the fundamental concepts of online communities


Mobile interface design and implementation, mobile sensor acquisition, context awareness, social platforms, crowdsourcing, online communities, graph theory.

Mode of delivery

Face to face teaching  + independent work.

Learning activities and teaching methods

Lectures, exercises, and practical work. The course is passed with an approved practical work. The implementation is fully English.

Target group

Computer Science and Engineering students and other Students of the University of Oulu.

Prerequisites and co-requisites

Object oriented programming.

Recommended optional programme components

The course is an independent entity and does not require additional studies carried out at the same time.

Recommended or required reading

All necessary material will be provided by the instructor.

Assessment Methods and criteria

The assessment is project-based. Students have to complete individual assignments throughout the semester and a final pair-based project: build a mobile application, conduct or analysis of data. Passing criteria: the assignments and the project must be must be completed, receiving more than 50% of the available points.

Read more about assessment criteria at the University of Oulu webpage.


The course unit utilizes a numerical grading scale 1-5. In the numerical scale zero stands for a fail.

Person responsible Teixeira Ferreira Denzil
Work placements


Other information


Proficiency level

English B2 - C2

This course is designed to give students an overview of the mobile and social computing domain, conceptualize the fundamental aspects of this domain, and provide practical experience in building such applications. The course is aimed at masters and doctoral students. Upon completing the course the student is able to implement mobile user interfaces, implement online social network applications, explain the fundamental concepts of context awareness and online communities.


This course focuses on one of the core demands of industry today: deep understanding of mobile interaction, mobile computing constrains and mobile development. After this class, students will possess the:

- ability to design and prototype a mobile user interface taking into account usability aspects of interaction on smaller displays

- ability to explain and leverage the fundamental concepts of context awareness using smartphone hardware, software and human sensors

- ability to understand and implement from scratch a mobile application that leverages both usability and context to create engaging mobile experiences


Deliverables from last two years:

- 2016:

- 2017:


The course is composed of hybrid lectures (theory + in practice class exercise) and lab sessions for period 3, group project for period 4. 


The course is passed with an approved work in all deliverables. This course is taught only in English.


  • Denzil Ferreira
  • Aku Visuri (assistant)
  • Opoku Kennedy Asare (assistant)
  • Mohamed Aboeleinen (assistant)


Mobile computing

  • Mobile UI design: design principles, examples, tools, and mistakes to avoid.
  • Mobile sensor and data acquisition: data collection on Android.
  • Context awareness: context definition, tools and middleware.
  • Future cities, IoT and big-data applications.

Social computing

  • Online community studies: encouraging contribution, controlling behaviour.
  • Facebook applications: Facebook API, tools, examples.
  • Crowdsourcing: Mechanical Turk, tools, filters, examples.
  • Social data analysis: graph theory fundamentals, graph analysis.  


There are two options for passing this course.
== For attending students, there are no exams. The final grade is calculated as: 
- 20% lecture attendance. Skip 1, penalty 10%, skip 2, penalty 20% if no HW is submitted.
- 20% laboratory attendance. Skip 1, penalty 10%, skip 2, penalty 20% if no HW is submitted.
- 20% average lab exercises (LAB 1-6)*, done and submitted individually in class. If unable to complete, the student will have until the corresponding HW submission deadline to submit his LAB exercise.
- 40% team project *

== For non-attending students, there are 2 exams. The final grade is calculated as:
- 20% individual assessments (HW 1-6)*
- 20% midterm exam (end period 3) (1-5, 0 is fail/no show)
- 20% final exam (end period 4) (1-5, 0 is fail/no show)
- 40% team project *

*All LAB/HW, exams and project require a passing grade.

The team project is peer-evaluated (30% of the grade). The final grade is on a scale 1-5 on:
- 50% implementation and complexity
- 30% peer-assessment average
- 20% quality of video demo (max. 1-minute long)

The final grade is on the numerical scale 1 to 5, with 0 standing for fail. 


All material for this course is available in Google Classroom. This includes

  • Slides
  • Exercises
  • Templates for exercises and presentations

University of Oulu oulun.yliopisto(at)
Tel. +358 294 48 0000
Fax +358 8 553 4112
PL 8000
FI-90014 Oulun yliopisto