Case Study — Socializing App For Online Students

OnCampus — Socializing App For Online Students

Executive Summary

The main purpose of this Case Study is to build a mobile application to boost socializing between peers studying online who don’t experience physical contact by meeting each other on campus.

Methodology process

  1. User Research
  2. Analysing the context of the use
  3. Specifying the context of the use
  4. Designing the user interaction
  5. Prototyping an interactive system.
An exemplary user of OnCampus App — Malee

1. User Research

The first step in order to prepare the qualitative analysis of the context of use is to plan the observation and the interviews. Structuring the interview questionnaire coupled with choosing the right participants is the crucial part if we want to get valuable insights. Therefore, we have prepared digital documents to stay organised:


  1. Interview & observation template



The questionnaire was tested with a family member of one of us to assess the time needed for the interview and to test the tools and practice. The time taken for the questionnaire was 17 minutes, and adding a time buffer for technical set up we assessed the overall time for 30 minutes.

2. Analysing the context of the use

After performing 6 extensive interviews there was time for transcribing them and translating them to English if needed. Once we all did it, we began the interpretation of each interview unit (one sentence or sometimes one thought). The ‘coding’ describing the meaning of the sentence must have been contained in one-two words which later have been clustered to larger concepts and even larger categories.


A sample of the extracted codings can be seen on the pages below.

Reliability — Intra-Coders Agreement Rate

The coding activity has been performed twice with a 5–6 days gap between the two attempts so we could compare the outcomes from the first round and exclude coincidences. If the coding was conveying the same concept but it was structured with other words we have still counted it as a successfully repeating one. We also noticed that the more specific codings in the first round, the lower the intra-coders agreement rates. Also, the number of codes was smaller the second time and more specific as after going through multiple interviews and working with the data, the coders got a better grasp of relevant codes. Together, we managed to get a really good outcome of 0.84 which means that the coders were quite consistent.

Intra-coders agreement rate

Reliability — Inter-Coders Agreement Rate

Furthermore, an inter-coders agreement rate was performed. The main rule was to check if 2 out of 3 coders coded the same content in a similar way. Since the interviews were semi-structured with open questions, there was freedom to answer and coders set different focus on the content when coding. After counting the reliability this time we got 0.608 in agreement rate which means it is moderate and the codes are somewhat reproducible.

Inter-coders agreement rate

Reliability — Fleiss’ Kappa

Fleiss Kappa Reliability

Internal Validity

Then, we also checked the internal validity which included:

  1. Methods triangulation — The qualitative analysis included semi-structured interviews with open questions, including questions covering observational aspects, audio-recording, taking notes for additional comments and non-verbal behaviour, coding raw data (inter-& intra-coding), framework divided into codes, themes and categories, draw conclusions.
  2. Coders triangulation — We used a document template for transcriptions and codings and we coded all the interviews parallelly without influencing each other.

External Validity

Even though our focus group was small and diverse, they mentioned the same aspects and problems that are faced by first-year students who study online in an international program. The results can be used to power further studies in the future. Data analysis was meticulously done followed by finding themes and categories from the raw data vigorously. This detailed approach showed that external validity is given even with a small focus group.

External validity


Thanks to the clustering method and extracting the essential information we were able to create a framework of the main issues which may later help us identifying the underlying problem in online studies.

Framework 1/3
Framework 2/3
Framework 3/3 and Observations

3. Specifying the context of the use

Based on the previously mentioned methods — semi-structured interviews, observation, information clustering and framework creation we managed to specify the main issues in online studies.

Main problems

  • Keeping track of deadlines, meetings and classes.
  • No common student space to exchange experiences, discuss ideas or rant.
  • Lack of personal bonding and feeling isolated.

Personas and User Needs Statements

To better empathize with the potential app users, two personas have been defined.

Task Organization Model

The task organization model helped when defining the tasks which would be performed in the app. Meanwhile, two main app purposes were identified:

  • Interact with peers

Task Scenarios


User Flows

Staying organized

User Flow
User Flow

4. Designing the user interaction

When the structure of the app was defined, the next step was to design the wireframes. Figma was used to develop the low fidelity prototype with some of the layout displayed below:


5. Prototyping an interactive system.

After performing user testing, some major obstacles in task completion were identified and substituted with better solutions. In the next phase, the design system was created including:

On Campus App — Task 1

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