Profile
Name : Anne
Email : annemachinda@gmail.com
Github : https://github.com/Lukong123
Location : Cameroon (UTC +1)
Typical working hours : Between 8 am and 4 pm UTC +1
Synopsis
The Multilingual Wikipedia Editor Survey internship project aims to gain a comprehensive understanding of individuals who contribute to Wikipedia by editing and using translation across multiple language versions.
The goal of this project is to get a better understanding of those who use translation and editing across multiple language versions of Wikipedia. Understanding their motivations, goals, and challenges in a way that informs product development to support their efforts.
Mentor : @MRaishWMF
Timeline
Week 4:
Documentation and Deployment:
Create comprehensive documentation for the tool, including installation instructions, usage guidelines, and troubleshooting tips.
Prepare the tool for deployment on the Portuguese Wikipedia.
Collaborate with the community to announce and promote the availability of the tool.
Monitor the tool's usage and gather feedback for further improvements.
| Period | Task |
|---|---|
| December 4 to December 15 | Community bonding period. Familiarization with the community. Get more acquainted with the project objectives, goals, and requirements.Understanding the various groups we will be working on and any new tool. Conduct background research on survey methodologies, best practices, and reviewing relevant literature. Collaborate with mentor and or necessary groups to define survey objectives, identify target audience, and draft survey questions. Seek feedback on the survey design from mentor and or necessary group. Incorporate feedback and make necessary revisions to the survey design. |
Submit bi-weekly report |
| December 18 to December 29 | Develop a plan for collecting survey responses, considering factors such as target audience reach, platform selection, ethical considerations etc. Conduct a pilot survey to evaluate the survey's clarity, effectiveness, and identify any potential improvements. Launch the survey and begin collecting responses from the target audience. Regularly monitoring survey responses, ensuring data integrity and addressing any issues that arise.Submit bi-weekly report. |
| January 2 to January 12 | Creating a comprehensive plan for analyzing the collected survey data, including the selection of appropriate statistical methods and data visualization techniques. Clean and organize the survey data where needed to ensure accuracy and consistency. Perform quantitative and quantitative analysis on the survey data(where applicable) to derive meaningful insights and identify trends. Document the analysis process, and methodologies used, and come up with a comprehensive report. Submit Biweekly report |
| January 15 to January 26 26 | Interpret the analyzed data to derive key insights and meaningful conclusions. Writing the research report, ensuring clarity, coherence, and proper organization of findings. Create visual representations, such as charts, graphs, and diagrams, to enhance the presentation of survey results. Seek feedback from the mentor and/or group members on the initial draft of the research report. Submit bi-weekly report |
| January 29 | Phase I evaluation |
| January 30 to February 8 | Incorporate feedback received and refine the research report accordingly. Generate actionable recommendations based on the survey insights and findings. Complete the final version of the research report and ensure all necessary sections, visuals, and references are included. Submit bi-weekly report. |
| February 9 | Phase II evaluation |
| February 12 to February 22 | Incorporate feedback received and refine the research report accordingly. Generate actionable recommendations based on the survey insights and findings. Complete the final version of the research report and ensure all necessary sections, visuals, and references are included. Submit bi-weekly report. |
| February 26 to March 1 | Create a presentation summarizing the research findings, insights, and recommendations. |
Deliver the presentation to the mentor and/or other groups, highlighting the key findings and recommendations. Reflect on the internship experience, document lessons learned, and prepare any necessary project documentation and final internship report. Obtain feedback from the mentor and the community|
Deliverables
- Comprehensive analysis of survey responses: The end product of the project will involve conducting a thorough analysis of the survey data collected from multilingual Wikipedia editors. This analysis will include examining and interpreting the responses to gain insights into the motivations, goals, and challenges faced by these editors.
- Research report: A detailed research report will be compiled, summarizing the findings from the survey analysis. The report will provide an overview of the key findings, trends, and themes derived from the data.
- Insights for product development: The research findings will help identify areas where product interventions can be implemented to support the work of multilingual editors.
Phase I evaluation
- Cleaning Data
- Interpreting and analyzing data
Phase II evaluation
- Create a presentation summarizing the research findings, insights, and recommendations.
- Deliver the presentation to the mentor and/or other groups, highlighting the key findings and recommendations.
- Document Internship process. Reflect on the internship experience, document lessons learned, and prepare any necessary project documentation and final internship report.
Final evaluation
Participation
- Work on google docs or any other tool which might be specified along the way.
- Online on Zulip in my working hours ( 8am to 4 pm UTC +1)
- Available through gmail during known working hours
- Communication on tasks will be through commenting on subtasks to the project created on Phabricator.
- Weekly reports will be published in my meta wiki user page
About me
I am currently a Master's Student at the University of Bamenda in the field of Computer Engineering. I have a strong inclination towards technology and a deep appreciation for open-source projects. I share interests in fields such as Software Engineering, Data Science etc
What particularly excites me about this project is the opportunity to contribute to the analysis of data. Not just the analysis part, but also because the prospect of utilizing this analyzed data to enhance product development and improve the experiences of multilingual editors will consequently help the population who look up to the organization.
I have acquired experience collaborating within teams like GDSC(Google Developer Student Club) co-lead and co team member, Technovation Girls Mentor etc.
Being in school, I have being opportuned to have and validate courses on Data Analysis, Data Analysis and Mining, Machine Learning which provided me with relevant knowledge understand and analyse data.
I have examined community surveys to support the project demonstration for both international competition and personal project.
Microtasks completed