=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 Lusophone technological wishlist, in the lusophone Wiki context, is a survey that intends to understand which are the technological innovations and the tools and platforms that could be modified to improve user experience, that is, to identify and prioritize the most basic needs of the community of editors, readers and researchers of the Wikimedia projects in Portuguese, so they have a more productive and pleasant experience.
The list's objective is to integrate the Portuguese-speaking communities in a strategic and collaborative process that acts towards research and identification of technological bottlenecks in the lusophone projects that prevent or hinder the entry and permanence of new and veteran editors, readers and researchers of the Wikimedia projects in Portuguese.
**Mentor** :
=Timeline=
| **Period** | **Task** |
|------------ |-----------|
|December 4 to December 09|**Community bonding period**. Familiarization with the community. Get more acquainted with the clarification, project objectives, goals, and requirements. Starting with project 9: Editting tutorial Videos for the mobile version. Research and planning, familiarizing myself with the Wikipedia mobile application, mobile editing features of Wikipedia and Wikimedia Commons. Identify the most common tasks and challenges faced by newcomers while editing on the mobile version. Research existing video tutorials and resources available for mobile editing. Based on the research, create an outline of the key topics and tasks that should be covered in the video tutorials. Prioritize the topics based on their importance and relevance to newcomers. Develop scripts for the video tutorials, ensuring clear and concise instructions for each task.Break down the content into logical sections for each video.
Week 2:
Video Recording:
Set up a screen recording software or use a mobile device to capture the editing process.
Follow the scripts and demonstrate the step-by-step instructions for each task.
Ensure the video quality is clear and the instructions are easy to follow.
Video Editing:
Edit the recorded footage to remove any mistakes or unnecessary content.
Add visual elements such as text overlays, annotations, or highlights to emphasize important points.
Enhance the overall visual and audio quality of the videos.
Finalize and Publish:
Review the edited videos to ensure they meet the desired quality standards.
Export the videos in a suitable format and resolution for online viewing.
Upload the videos to a suitable platform, such as YouTube or a dedicated tutorial section on Wikipedia/Wikimedia Commons.
Create accompanying descriptions or documentation for each video tutorial.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 [[ https://meta.wikimedia.org/wiki/User:Anne237 | 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**
- https://docs.google.com/document/d/12viWQSJ4H8kOkGnTthq1z9vpK2xhLVNM-OfPDp2vl5Q/edit?usp=sharing
- https://github.com/Lukong123/lusophone-technological-wishlist/tree/main/Task2