The influx of new technologies in higher education math has contributed to a new culture of data-driven instruction and decision-making. Solidus, in conjunction with Pearson, used human-centered research and design processes to discover which data is most important and how to display it to instructors. This project represents short- and long-term opportunities for Pearson to help define the new culture of data-driven education using innovative reporting tools.
The literature review covered general information on learning science and data visualization and specific studies regarding the data needs of students and instructors. We studied education, data collection systems, and ways data is being used in online learning tools and the classroom. Rather than stay within the confines of academic journals, we utilized many types of information sources to inform our research, including TED Talks, industry white papers, and news articles and analysis.
During our competitive analysis, we identified significant gaps in the reporting features of online learning system by investigating educational products from major publishers and startups. Additionally, we analyzed products from domains that rely heavily on reporting tools including games, fitness and health systems, analytics, and banking. We demonstrated the value in looking outside of education for inspiration to create the next great data visualization structure in educational systems.
In our field research, we used Contextual Inquiry (CI) to see how stakeholders—including instructors, students, and administrators—use online learning tools in the context of their work and the decisions they make. We also built empathy with those stakeholders by conducting intensive on-site interviews. Pearson serves institutions that vary in size, demographics, and technological resources, so we conducted interviews at several schools with people in different roles. In addition to talking to stakeholders who use Pearson products, we spoke to some who use competing products.
Like our research process, our design process started with a “go wide” and narrow philosophy. We used low-fidelity parallel prototypes to quickly develop multiple concepts that we tested with users.
After each round of testing, we consolidated our results and built new prototypes that used the most successful pieces of previous prototypes. As we settled on one concept, we moved into mid-fidelity prototyping to develop and test the interactions in our interface.
Finally, we built a high-fidelity, interactive prototype that included both a front-end data display and a small backend that used real sample classroom data. We employed an iterative process of building, testing, and evaluating to zero in on pertinent instructor needs and a clear visualization structure. We employed design research methods such as card sorting, think aloud, personas, and parallel prototyping to develop the concepts, visualizations, and content for the prototype.
Stephanie E. Butler came to Carnegie Mellon to study Human-Computer Interaction after a career in book publishing in New York City. As an editor, Stephanie covered topics as varied as freshman composition, contemporary linguistics, and Boston’s best ice cream in books, blogs, and apps. Her work in education led her to HCI. Stephanie has a bachelor’s degree in English from Harvard University. She once appeared on CNN to discuss tourism in Tokyo.
Paul Mandel joined the Human-Computer Interaction Institute after working as a robotics engineer, a front- end web developer and an intellectual property litigation consultant. While working in robotics, Paul became fascinated by how humans interact with robots, leading him to become interested in how humans interact with technology in general. Before CMU, Paul studied at the Franklin W. Olin College of Engineering and teaches swing dancing.
Auldyn Matthews came to the Human-Computer Interaction Institute after recently graduating from Ohio University studying Mathematics, Psychology, and Spanish. Her passion for games, technology, and education lead her to pursue a Master’s Degree in HCI at Carnegie Mellon. She loves creating elaborate Halloween costumes and her favorite number is φ.
KeVon Ticer comes to the MHCI program directly after finishing his undergraduate studies in Computer Science at Howard University. He is interested in designing and developing interfaces that will make it easier to learn complex things. He also is a big fan of casual dancing and a HUGE fan of ice cream.
Nina Xu is an Accelerated Master’s student at Carnegie Mellon University. She is completing her undergraduate studies in Information Systems and Human-Computer Interaction. Nina is interested in pursuing interaction design and front-end development. In her free time, she enjoys learning about music technology and production.