Engaging Students in Earthquakes via Real-Time Data and Decisions

Egger, Anne E.

doi:10.1126/science.1214293

“…The use of data analysis for contextualization represents an actively growing movement [1,16,10,6]. Upper division courses have employed situated learning experiences using data of varying size and complexity for several years [7,17]. However, this prior work has little evaluation of the impacts of data science in introductory education [16,6].…”

Section: Related and Prior Workmentioning

confidence: 99%

Computing with CORGIS

Bart

¹

,

Whitcomb

²

,

Kafura

³

et al. 2017

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To successfully bring introductory computing to non-CS majors, one needs to create a curriculum that will appeal to students from diverse disciplines. Several educational theories emphasize the need for introductory contexts that align with students' long-term goals and are perceived as useful. Data Science, using algorithms to manipulate real-world data and interpreting the results, has emerged as a field with crossdisciplinary value, and has strong potential as an appealing context for introductory computing courses. However, it is not easy to find, clean, and integrate datasets that will satisfy a broad variety of learners. The CORGIS project (https://think.cs.vt.edu/corgis) enables instructors to easily incorporate data science into their classroom. Specifically, it provides over 40 datasets in areas including history, politics, medicine, and education. Additionally, the COR-GIS infrastructure supports the integration of new datasets with simple libraries for Java, Python, and Racket, thus empowering introductory students to write programs that manipulate real data. Finally, the CORGIS web-based tools allow learners to visualize and explore datasets without programming, enabling data science lessons on day one. We have incorporated CORGIS assignments into an introductory course for non-majors to study their impact on learners' motivation, with positive initial results. These results indicate that external adopters are likely to find the CORGIS tools and materials useful in their own pedagogical pursuits.

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“…The instructor reported that, even after the course had ended, students applied similar analysis to other geographical regions relevant to their lives. This assignment contextualized the learning experience for the student, and created "a personal connection and positive affect that motivates their future learning" [5]. Corresponding projects, perhaps even using the same data source, are ripe for a programming class.…”

Section: Prior Workmentioning

confidence: 99%

“…In this project, students worked with real-time data on earthquakes [5]. Although students did not program, scientific computational tools were used to analyze the data and reach conclusions.…”

Section: Prior Workmentioning

confidence: 99%

Transforming introductory computer science projects via real-time web data

Bart

¹

,

Tilevich

²

,

Hall

³

et al. 2014

Proceedings of the 45th ACM Technical Symposium on Computer Science Education

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While computing is becoming increasingly distributed, programming projects in introductory classes remain mostly divorced from the student's day-to-day computing experiences. These experiences entail interacting with real-time Web-based data from sources that include weather reports, news updates, and restaurant recommendations. The disconnect between student experiences and the content of their programming projects is known to drive some students away from computing. In addition, to adequately prepare students for the realities of modern software engineering, educators should introduce issues pertaining to distributed computing early in the curriculum. To address these problems, we have created RealTimeWeb-an architectural framework that makes real-time web data accessible for introductory programming projects. The framework effectively introduces important real-time distributed computing concepts without overwhelming students with the low-level details that working with such data typically requires. Preliminary results indicate that our approach can be effective in the context of a typical CS2 course, and that real-time data is relevant to students. RealTimeWeb libraries and associated resources are publicly available for use, with multiple language bindings to many real-time data sources. A rapid-prototyping tool available through the project's website facilitates the development of client libraries with easily accessible APIs for new real-time Web-based data sources.

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Computing with CORGIS

Bart

¹

,

Whitcomb

²

,

Kafura

³

et al. 2017

Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education

View full text Add to dashboard Cite

To successfully bring introductory computing to non-CS majors, one needs to create a curriculum that will appeal to students from diverse disciplines. Several educational theories emphasize the need for introductory contexts that align with students' long-term goals and are perceived as useful. Data Science, using algorithms to manipulate real-world data and interpreting the results, has emerged as a field with crossdisciplinary value, and has strong potential as an appealing context for introductory computing courses. However, it is not easy to find, clean, and integrate datasets that will satisfy a broad variety of learners. The CORGIS project (https://think.cs.vt.edu/corgis) enables instructors to easily incorporate data science into their classroom. Specifically, it provides over 40 datasets in areas including history, politics, medicine, and education. Additionally, the COR-GIS infrastructure supports the integration of new datasets with simple libraries for Java, Python, and Racket, thus empowering introductory students to write programs that manipulate real data. Finally, the CORGIS web-based tools allow learners to visualize and explore datasets without programming, enabling data science lessons on day one. We have incorporated CORGIS assignments into an introductory course for non-majors to study their impact on learners' motivation, with positive initial results. These results indicate that external adopters are likely to find the CORGIS tools and materials useful in their own pedagogical pursuits.

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Engaging Students in Earthquakes via Real-Time Data and Decisions

Abstract: Seismicity and Relative Risk, the IBI Prize–winning module, utilizes freely available earthquake data to help students apply their knowledge to risk-related decision-making.

Cited by 3 publications

References 7 publications

Computing with CORGIS

Computing with CORGIS

Transforming introductory computer science projects via real-time web data

Computing with CORGIS

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