I created this narrated video presentation (“digital poster”) in 2020 to summarize some of the original research I conducted for my master’s thesis. It’s intended for an audience of professors, experts, and advanced learners in the field of psychology. The conference guidelines provided the slide design and prohibited the use of slide animations. Scroll below the video for an analysis of what I liked about this presentation versus what I would do differently next time.
If you’re using a screen reader, I recommend downloading a PDF of the slides separately by clicking here instead.
Slide #1 Analysis
Pros: I like the content of this slide and how I used superscript numbers to put necessary in-text citations into the footnote, reducing the amount of text on the slide. I used italics and arrows to indicate the definitions of keywords that readers might not be familiar with. This helps to break up the monotony of a slide full of text.
I used EmbedPress to embed a PDF of this particular slide onto this webpage (instead of a screenshot) to make it accessible for individuals with screen readers to follow along my analysis.
Cons: The line height on this slide in very thin to fit all of the text onto it, so this slide violates Web Content Accessibility Guidelines. WCAG 2.22 requires 150% line height within paragraphs (and an additional 150% gap between paragraphs or bullet points). Readers can only edit the line height on the raw PowerPoint slides; they cannot edit the video or PDF slides. Thus, the text on this slide (and most of the slides in this presentation) can be very difficult to understand for readers with certain cognitive or visual disabilities.
Normally, I would’ve spread the information onto multiple slides to avoid this problem, but the conference limited posters to a max of 5 slides.
Slide #3 Analysis
I’m focusing on the data visualization on this slide; see above for an analysis of the text itself.
Pros: This bar graph fulfills my #1 priority with data visualizations: an intuitively accurate representation of the magnitude (or range) of the data. The program I used to create this graph, SPSS, automatically zooms in to the “relevant range” of the y-axis. (In this graph, that would be about 1.5 to 3.) However, this misrepresents the magnitude of the differences between conditions, and would like a casual reader to assume these differences were much bigger than in reality. I made the y-axis start at absolute 0 as an easy fix to make these experimental result more intuitive to laypeople.
This graph is also completely accessible to colorblind readers. The three colors I used to distinguish between types of traits are visually distinct for individuals with colorblindness and complete color vision, as each hue and brightness is unique. (As an additional assurance of legibility, each type of trait has its own pattern overlaid on the bar. Helpfully, SPSS does this automatically.)
Cons: What exactly the y-axis and each type of trait represents is unclear without listening to the audio narration. Ideally, a reader should be able to look at this graph in isolation and understand it.