In Project 1, we learned about quantitative and qualitative data analysis. The assignment was to set a research topic associated with learning design, distribute a survey to collect data and consolidate the result with visualized data in a video presentation. 

Over the courses last year, my interest in accessibility grew, and I kept thinking about what it means to create accessible and inclusive learning environments. As a first-generation immigrant and woman of color, I’m keenly aware of exclusive systems that are hard to reach for the intersectional population. So, I selected to explore applying data analytics to increase the inclusivity of courses.

Background

According to a research article on 2023 Data on Higher Learning & Corporate Training, the author concluded that online learning in higher education and corporations is here to stay and grow (Bouchrika, 2023). As an avid MOOC learner, I tried multiple platforms and noticed that many existing online courses set high stakes for learners. One of them seems that the courses take it for granted for learners to participate in academic discussions in English even though it is a non-native language for many learners. While high-quality courses open doors for the global learning population with a low fee or even free of charge, most are delivered solely in English. As common knowledge, we know that English is one of the most commonly used languages. But how universal is it? 

Research topic and question: The online course offered solely in English is the first barrier for people who live in countries with low regional ranks on the English Proficiency Index. If the language barrier is lowered or removed by localization, will the online course become more attractive for non-native English speakers?

The audience of the research: Client (An international organization offering online courses in English)

Target learners: Adult, non-native English speakers who have taken online courses recently.

Survey: Five quantitative and three qualitative questions that generate actionable data.

Method: I created surveys in Google Forms and distributed them through social media platforms.

Process

1. Select a micro-level research topic, invent the audience of the research, and target learners. Create a survey to collect quantitative data. 

2. Distribute the survey to collect data. Perform descriptive statistical analysis.

3. Visualize data. I learned some use of Tableau Public, but the collected data requires simple visualization, so I used functions in Google Sheets.

4. Map out the process of creating a video presentation. Have a rough draft on incorporating visualized info and data.

5. Write scripts with all of the assignment requirements.

6. Record and edit voiceover with Audacity.

7. Find the presentation template and lay out the slides.

8. Create slides with highlighted information and visualized data.

9. Export the presentation as .mp4 into Premiere Pro.

10. Edit the video to match the timing of the voiceover with screen freezes.

11. Upload the video and add captions and transcripts on YouTube.

Challenges & Solution

To keep the animation in PowerPoint, I needed to download it as an mp4 file, which required me to adjust the timing of the voiceover in Adobe Premiere Pro. Instead, I could simplify the process by recording a voiceover in a PowerPoint presentation and publishing a video directly.

    In the end

The data exists everywhere. The process was a pursuit of clarification and interpretation called analysis. The assignments required articulating the purpose and focusing on what I aimed to validate from the collected data. The data should point toward revealing answers and actionable solutions. To collect such usable data, the survey questions should be considered well enough to capture the evidence of the hypothesis and not to impose bias and misguide respondents.