Category: xSpr14 Assignments

Redesigning the Seminar

Posted on Author Marissa Block

First off, I think that a data visualization seminar is an incredibly important and relevant course, and it is worth continuing, especially when considering the shift of print journalism to online media. Since there is so much value in data visualization, I think it would be more effective to expand the seminar rather than shrink it into a 3-week module in an existing course. As a fan of the visualizations produced by The Economist and the New York Times, I began the seminar too ambitiously, and thought I would be able to produce similar visualizations. My lack of coding knowledge was definitely a source of frustration. Thus, from my personal experience, I think that option 3, expanding the course with more content and coding, is the best method of redesigning the seminar. This would enable the students to already have a set of tools to create visualizations before working with a community partner. I felt in the first few weeks of the seminar that I couldn’t really begin a fruitful relationship with my community partner because I had very limited data viz skills at the time.

Though, community partners should definitely remain a component of the course, because it offers a real world opportunity to put the skills you have learned to work. At the same time, more emphasis on coding might seem daunting to non-techie people. However, it is probably better to struggle through class with others than struggle alone. Therefore, it might also be beneficial to pair up students and have them work together with a community partner. Finally, I think that the talk from Alvin Chang was helpful in that it enabled me to take a step back from the more technical aspects of data viz, and remember what is the objective or the issue is that I am trying to address through my visualization, and how can I tell an effective story with it.

Assignment 12: Redesigning Seminar

Posted on Author Minh Anh Nguyen

Considering the pros and cons of each of the three options for the course structure, I think that the last option, which is to expand the course into a larger one-credit course, is the best option if the instructor is to redesign this course. Even though with the current structure, students have a chance to work with the community partners throughout the whole semester, and have a lot of time to get to know them as well as their data visualization goals well, the class only meets for one hour per week, which somewhat limits the amount of material that can be covered. Moreover, since students started working with community partners from the beginning of the semester and did not have any prior knowledge about data visualization, for most of them, the first half of the semester was mostly about analyzing data and talking with community partners about prioritizing ideas. Although these are all very important factors in the process of creating data visualizations, they are not the main focuses of the course. I think students could have spent much more time on the main focus of the course, which is data visualization, if they already have sufficient knowledge on visualizing data by the time they start working with their community partners.

If the course is expanded into an one-credit course and divided into two parts, with more data visualization content and coding instruction during the first half, and students working on community partner projects during the second half, I think both the students and community partners will make use of their time much more efficiently. Students start their work with their partners after already being introduced to the concepts and techniques of data visualization, so they would have much better and clearer ideas when discussing with their partners on how to achieve their goals with the data visualization tools. Moreover, with more data visualization contents and coding instructions introduced, this course is also a great option for students who are interested in the course material to fulfill the Numerical & Symbolic reasoning requirement. The only downside I see in this structure is that since the time students and community partners have to work together is shortened, they must find ways to make the best use of it. Therefore, it might help a lot if before working with the students, community partners have already prioritized their goals and ideas, had the data ready to use, and done some preliminary analysis if possible.

The first option, which is to insert data visualization as a 3-week module into a topical seminar, does not sound like an appealing option for me. Even though it is very helpful for students who take a topical seminar and want to gain additional knowledge on data visualization, I think to be able to effectively use data visualization tools, a 3-week period is too short to introduce all of the materials necessary. Incorporating data visualization materials into a topical seminar is a great option to get some introduction on data visualization, but a more focused, intensive course like in the third option should be offered as well for students who want to go more in-depth into this subject.

Redesigning Seminar

Posted on Author Ben Peterson

Discussing how this seminar could be better built is tough, as I feel the way which it was taught this semester was extremely productive and successful. This being said, I feel redesigning it to be taught the final way suggested in this prompt, with half a semester of coding, and half a semester of working with community partners, could be a positive change.

In the way this seminar was taught, it had its students learning tools as they went along, and not  always having the skills to utilize every tool to the fullest extent. I feel this could be easily remedied by giving some basics on javascript code, html code, and the wide variety of options to visualize data, prior to actually working on application of these skills. Additionally, once this first task is completed, the second half of the seminar would be solely work-based, which I think would allow for strong relationships with community partners, and better emulate a highly-focused work environment.

I believe the seminar worked extremely well with the way which it was taught this past semester, however, I feel getting deeper into the code the first quarter, and working solely on implementing it the second quarter, could be a better option.

Assignment 12: Redesigning the Seminar

Posted on Author Minh Nguyen

Among the three curricular models, I think the last option is the most potential one for redesigning the data visualization course. The idea of separating the course material into two halves is necessary since the students can learn more and be proficient with different techniques of data visualization before meeting with their partners in the second half of the semester. I suggest adding more homework assignment for each class, so students have chances to practice designing different kinds of visualization with simulated datasets. It will help to build up confidence as well as experience before students meet their partners. Another reason for this option is this course structure making students to work as a same pace. Judging from my personal experience, Minh Anh and I employ more techniques from the first half of the semester for our Lottery Winning project such as “creating thematic maps with Google Fusion table” etc. Therefore we had more work to do from the beginning and not much work in the end. Nevertheless, some students in our class have fewer things to do from the first half and have to work so hard in the end of the semester. Last but not least, a 1 – credit course means students have more time to enforce course materials through several classes meeting per week. For me the disadvantage for “0.5 credit seminar” is meeting once a week, which takes a quite to refresh my mind what we had learned from the last week seminar. The only con for the last option is the fulfillment of Numerical & Symbolic reasoning requirement. Even though data visualization, especially with scatter plot, requires some basic understanding of econometrics, the course material may not be enough to meet this distribution compared to the other mathematical classes.

Curricular models 1 and 2 are not as effective as model 1, but they also have some advantages and disadvantages that should be taken into consideration. Although the cons for option 2 are listed above, a current 0.5 credit seminar combined with 0.5 credit internship may be a great selection for seniors, people who are busy with applying for graduate school, writing thesis, looking for an internship or simply need more time to work independently outside class. Therefore it depends on people who are interested in taking the seminar next semester, instructor can be flexible with the time schedule for the class. Model 1 is great in term of concise course materials in three weeks. However it requires a specific subject for the seminar, and data visualization is only a subset topic for the class. As I read the description for Educational Studies 308, this class is designed for the studies of cities, suburbs, and schooling in the metropolitan Hartford area; one of the research skills is creating interactive data visualizations on school choice policies. Since students may have different interests or work with different type of community partner, it is challenging to finalize a single topic for this seminar.

Last but not least, it is effective if the community partners have their databases ready for use and finalize their goals of data visualization before working with Trinity students. On the first few meetings, community partners discuss about their priorities and how Trinity students can help them to create data visualization that benefits their goal. Each week students make different rough drafts of map, chart or graph based on the goals, and show community partner to receive constructive feedbacks. In the end of the semester, community partners will choose the best data visualizations that meet their goals for future uses.