How do you determine when a data visualization requires a deeper, more scaffolded approach for student comprehension?
How do you determine when a data visualization requires a deeper, more scaffolded approach for student comprehension?
If the data has more highly academic language for the X Axis or Y Axis, I will provide definitions for my MLL students. Similar to DBQ Online, guiding questions are helpful for students as well.
If there is complex wording or sometimes even if the verbage is not complex I may provide meanings so that everyone knows what, exactly, they are seeing. I believe I shared last week that I didn't realize my students did not know the word "casualty" so that became a teachable moment.
Recently, I realized that students were misinterpreting one of our DBQ charts. Through this experience, I will ensure that any chart that looks similar to that will have scaffolds starting in the beginning of the year.
Recently, I realized that students were misinterpreting one of our DBQ charts. Through this experience, I will ensure that any chart that looks similar to that will have scaffolds starting in the beginning of the year.
I work with MLs and always go over the basic features of a graph or map before I ask them to analyze it. Some of the students may understand better than others, but reviewing the axes, titles, and data source as a class ensures that everyone is set up for success later. Like Robert, I'll also cover critical vocabulary words that the students may not be familiar with. Once all of these basics have been covered, I am more confident that my students are better prepared to interpret and analyze the data for themselves. It also limits the number of questions I receive related to reading the data and allows me the time to answer the deeper questions about the data itself.
Usually if the type of graph or visual is different than we will break it down together. I also find that if the visual relies on the key, many of my students forgets the key exists. They need a lot of reminders to look at it and the visual as a whole. They tend to focus on just the main shape instead.
I think if the data is comparing multiple items than it is important to use a more scaffolded approach.. but really I've come to learn that a more scaffolded approach is actually useful for all classes. Everyone can benefit from going through this process including teachers because it forces you to keep questioning what you are looking at for deeper meanings.
I feel that a data visualization requires a deeper, more scaffolded approach when students are struggling to understand the underlying messages. This usually happens when the visualization is too complicated and most of the time not straightforward about what information the students need to take away, just as we discussed in the session. I also feel that often that finding visualizations for specific topics are very difficult to find and oftentimes especially for world one it is difficult to mind multiple visualizations on the same topic with the same dates. I know it is because they are just estimates and I remind my students that but it is still hard for them to grasp and I get questions all the time which date they should go by.