The information won’t just sink in: Helping teachers provide technology-assisted data literacy instruction in social studies
May 30, 2023 at 8:00 am 9 comments
Last year, Tammy Shreiner and I published an article in the British Journal of Educational Technology, “The information won’t just sink in: Helping teachers provide technology-assisted data literacy instruction in social studies.” (I haven’t been able to blog much the last year while starting up PCAS, so please excuse my tardiness in sharing this story.) The journal version of the paper is here, and our final submitted version (not paywalled) is available here.
Tammy and I used this paper to describe what happened (mostly during the pandemic) as we continued to provide support to in-service/practicing social studies teachers to adopt data literacy instruction in their classes. Since this was a journal on educational technology, we mostly focused on two technologies:
- The OER Tammy created to support data literacy in social studies education — see link here.
- DV4L, the Data Visualization for Learning tool that we created explicitly for social studies teachers — see link here.
When we started collaborating together, we looked for a theoretical model could inform our work. The end goal was easy to describe: we wanted social studies teachers to teach data literacy. But it’s hard to measure progress towards that big, high-level goal. Teachers are teaching data literacy, or they’re not. How do you know if you’re getting closer to the goal? We structured our work and our evaluation around the Technology Acceptance Model (TAM). TAM suggests that adoption of a new technology boils down to two questions: (1) is the technology actually useful in solving a problem that users care about, and (2) is the technology usable by the users? Those were things that we could measure progress towards.
During the pandemic, we ran several on-line professional learning opportunities — a workshop where practicing teachers could try out the OER with some guidance (e.g., “Make sure you see this” and “Why don’t you try that?”), and kick the tires on a bunch of tools including DV4L. We gathered lots of data on those teachers, and Tammy did the hard work of analyzing those data over time. We made progress on TAM goals — our tools got more usable and more useful.
But we still got very little adoption. TAM didn’t work for us. Adoption didn’t increase as usability and usefulness increased.
Why not? That’s a really big question, and we barely touch on it in this paper. It’s now a couple of years since we wrote the BJET article, and I could now tick off a dozen bullet points of reasons why teachers do not adopt, despite a technology being both useful and usable. I’m not going to list them here, because there are other publications in the pipeline. Bahare Naimipour, the EER PhD student working on our project, is finishing a case study of some teachers who did adopt and how their beliefs about data literacy changed.
I can give you a big meta-reason which probably isn’t a surprise to most education researchers but might be a surprise to many computer scientists: It’s not all about (or even mostly about) the technology. I led the group that worked on DV4L, and I’ve been directing students who have been helping Tammy make the OER more usable and useful (including build new tools that we haven’t yet released). TAM matters, but the characteristics of the individual teachers and the context of the teacher’s classroom are critical factors that technology is unlikely to overcome.
This is work funded in part by our National Science Foundation grant, #DRL2030919
Entry filed under: Uncategorized. Tags: computing education research, social sciences, social studies, teachers.
9 Comments Add your own
Leave a comment
Trackback this post | Subscribe to the comments via RSS Feed
Computing Ed Research - Guzdial's Take 
1.
Glenn Boustead | May 30, 2023 at 9:00 am
“I could now tick off a dozen bullet points of reasons why teachers do not adopt, despite a technology being both useful and usable.” I have been teaching for 22 years in elementary schools. I am quite interested in the reasons you have come up with so far. I retired a year ago because I want to help figure out how to address this lack of adoption of data literacy tools and ideas. I do have 18 years experience in data sciences prior to teaching, so I spent 22 years being baffled by the lack of awareness of data in the school system (I don’t mean student data).
2.
Bob Gotwals | May 30, 2023 at 9:17 am
I’ve been a computational science educator at the high school level since 1987 (see “SuperQuest”). I just finished an NSF CT grant. The teachers said (of the modules we created to collect data): “The modules are great…just take out the computing part, and they’ll be perfect.” I could talk all day why teachers are not embracing computational science and related disciplines like data science.
3.
Mark Guzdial | May 30, 2023 at 10:04 am
I’ll be blogging later this summer about our new PCAS courses. When I was creating “Computing for Creative Expression,” I met with computational artists and asked them “So, how close is Media Computation to what you want?” The response was: “It’s great, just replace the code with art.”
4.
Ian Utting | May 30, 2023 at 9:30 am
The link to the non-paywalled version of the paper is broken. There’s an extraneous “\” (%5C) in it.
Should be: https://web.eecs.umich.edu/~mjguz/uploads/Shreiner-Guzdial-BJET-2022-Resubmit.pdf
5.
Mark Guzdial | May 30, 2023 at 10:02 am
Thank you, Ian! Fixed!
6.
chaikens | May 31, 2023 at 10:41 am
A key lesson and practice in mathematics is to make sure you and your audience are informed (appropriately for the background of the audience) explicitly and precisely what every word, symbol, quantity and diagram means–its mathematical type and units if relevant–even it feels pedantic or boring. I wonder if a lack of “mathematical literacy” which makes one inclined and comfortable about declaring, sticking to such given definitions, and using them to draw strong conclusions would cause teachers to be uncomfortable, if not unable, to explain in speech whatever qualitative features are apparent intuitively. For example, how routine is it to remind social studies students of the meaning slope and its constancy in connection to straightness, proportions and similar right triangles when explaining the plot linear data fit? I see hope from your finding of a significant growth in the number of teachers “confident in their abilities to find inaccuracies in maps and graphs” from your program. Weak mathematical discipline might also account for the lack of connectedness and definitive explanations of visual data presentations in textbooks. Other mathematical phenomena, like exponential growth, and showing how map projections might distort relative areas or angles or both, might also have been neglected to be explained and demonstrated in textbooks and teacher education. How do we assure that all students are taught what I was (I think) first taught in Boy Scouts, how to estimate a distance using a map?
.
7.
Mark Guzdial | May 31, 2023 at 11:38 am
We see slow reveal graphs as a way to support social studies teachers in making sense of the elements of the visualization — see https://slowrevealgraphs.com/ and Tammy’s website (which focuses on slow reveal graphs for critical perspectives in social studies education) https://sites.google.com/view/slowrevealforsocialstudies/home?authuser=0. We have a new tool that we’ve just created to help teachers create slow reveal graphs.
8.
chaikens | May 31, 2023 at 6:15 pm
Looks good! However, for graphs, the mathematician in me says to START with a qualitative explanation of the axes, then add the units, then the scale, and AFTER that show the graph. Or perhaps reveal and explain a data point or two (to indicate the y-data may vary with the x-data) after the axes and scale are revealed, before adding the whole graph. I wonder if it helps to ask students to identify the meaning and units of the axes. I hope the slow reveal software will accommodate revealing the axes and units first.
9.
Mark Guzdial | June 2, 2023 at 2:08 pm
The software can support on any component first. There’s a bunch of exploration going on in mathematics and social studies about the order of focus/reveal.