Design Study "Lite" Methodology: Expediting Design Studies and Enabling the Synergy of Visualization Pedagogy and Social Good
Design studies are frequently used to conduct problem-driven visualization research by working with real-world domain experts. In visualization pedagogy, design studies are often introduced but rarely practiced due to their large time requirements. This limits students to a classroom curriculum, often involving projects that may not have implications beyond the classroom. Thus we present the Design Study "Lite" Methodology (DSLM), a novel framework for implementing design studies with novice students in 14 weeks. We utilized the Design Study "Lite" Methodology in conjunction with Service-Learning to teach five Data Visualization courses and demonstrate that it benefits not only the students but also the community through service to non-profit partners. In this paper, we provide a detailed breakdown of the methodology and how Service-Learning can be incorporated with it. We also include an extensive reflection on the methodology and provide recommendations for future applications of the framework for teaching visualization courses and research.
Paper Reference: Uzma Haque Syeda, Prasanth Murali, Lisa Roe, Becca Berkey, & Michelle A. Borkin. “Design Study "Lite" Methodology: Expediting Design Studies and Enabling the Synergy of Visualization Pedagogy and Social Good”, In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI ’20), ACM, Paper 556, 1-12, 2020.
Service-Learning is a pedagogical model that integrates classroom learning objectives with community needs and service goals. In this work, we present a case study implementation of Service-Learning within a graduate visualization curriculum, utilizing the design study "lite" methodology to meet the project's goals within three months. In the case study, we worked with the Chester Square Neighborhood Association in Boston, MA, USA to help them improve their resident urban park by leveraging existing data, identifying current issues debilitating the park, and providing visualizations for insight. This case study demonstrates the "lite" methodology as a potential solution for a short-term design study approach as well as a viable approach in conjunction with Service-Learning, to facilitate visualization for social good.
Poster reference: Uzma Haque Syeda, Prasanth Murali, and Michelle Borkin. Chester square park: A case study of visualization for social good using design study “lite” methodology. In Posters presented at the IEEE Conference on Visualization (IEEE VIS 2019), Vancouver, Canada, October, 2019.
Service-Learning is an experiential learning model in which classroom learning objectives are aligned with community service to meet both educational and community goals. There are various methods of Service-Learning including volunteerism, community service, internships, and field education. Many positive effects of Service-Learning on students have been demonstrated including the development of a sense of meaning and purpose
to their academic studies, interpersonal and communication skills, and leadership skills. Service-Learning has also been shown to foster diversity awareness, exposure to other cultures, and an increased sense of community.
Many non-profit and community organizations are unable to visualize and analyze their data for reflection, planning, and decision making due to the lack of monetary resources to hire an expert or lack of time from their personnel due to small staff. Through Service-Learning, data science and visualization students can exercise their newly acquired skills and provide valuable (free) insights for non-profit organizations.
Hence, the symbiotic relationship between Service-Learning (community) partners achieving their goals, and novice students getting to work with real-world data prompts us to vouch for the inclusion of Service-Learning in visualization pedagogy. It can be used as a key application of Design Study "Lite" Methodology because it not only helps the community but also provides students with skills and experiences otherwise unattainable in a classroom environment. It provides students real-world data science experience and exposes them to a more realistic approach of creating visualizations. This allows the students to better learn the concepts of their Visualization course curriculum. It also develops them professionally and opens up future opportunities of working with the community. Moreover, having a real community stakeholder prompts the students to complete their projects sincerely and with utmost care and not just for the sake of achieving a good grade. Most importantly, it instills a sense of giving back to the community and a civic responsibility in students and enables them to make a positive impact on the community they live in.
How Service-Learning based Pedagogy is advantageous to women in STEM
The novel Service-Learning (S-L) based Data Visualization pedagogy by Dr. Michelle A. Borkin has increased the number of female students engaged in data visualization, and more broadly data science, at Northeastern University. Women are less likely than men to engage or stay in STEM fields (i.e., “leaky pipeline”) (Paquin 2006). One area of “leak” occurs at the undergraduate level based on the pedagogical styles of many STEM courses, which are not supportive for women. In order to develop a pedagogy in her course that is advantageous to women, Prof. Borkin chose to apply S-L. This innovative pedagogy with S-L has created the opportunity for more women to become engaged and successful with data visualization, and data science more broadly, through a cooperative non-competitive learning environment within the context of social impact. Many positive effects of S-L on students have been demonstrated, including the development of leadership skills (Astin, et al., 2000) and instilling a sense of meaning and purpose to their academic studies and interpersonal and communication skills (Eyler & Giles 1999). S-L has also been shown to foster diversity awareness, exposure to other cultures, and an increased sense of community (Eyler & Giles 1999).
In various disciplines, it has been shown that S-L is particularly advantageous and engaging for female students. For example, students in engineering courses with S-L reported a more appealing image of engineering, with scientific problems put in the context of society which appeals to students, particularly women (Kondrick 2003). The lack of experiential education with societal implications, which appeals particularly to women, may be one reason traditional STEM courses do not attract women (Seymour 2002). Research has demonstrated that the preferred learning style of women tends to be more “community oriented” (Baxter-Magolda 1992) and women have a unique way of learning and interpreting concepts that is contradictory to conventional, usually male dominated, programs (Kondrick 2003). This concept of cooperative non-competitive learning environments, inherent to S-L, hasbeen shown to attract girls to STEM programs in K-12 (Thom 2001). Paquin (2006) suggests that these aspects of S-L, in particular collaborative experiential learning, make it a possible solution to the “leaky pipeline” of women and underrepresented minorities in STEM. The innovative educational model for teaching data visualization is a novel application of S-L to data visualization education in computer science.
If you are interested to learn more about Service-Learning or Visualization for Social Good, scroll down to find a few links to get you started: