This workshop introduces participants to the concepts and use of BRIDGES, a software infrastructure for programming assignments in data structures and algorithms courses. BRIDGES provides two key capabilities, (1) easy to use interface to real world datasets spanning social networks, entertainment (movies on IMDB, song lyrics), scientific data (real-time USGIS Earthquake Data), civic issues (crime data), and literature (books); and (2) a visualization of the acquired data can be used in assignments by students to populate their implemented data structures, including the capability to bring out attributes of the dataset. The visualizations are displayed on the BRIDGES website and aremore »
Bringing Real-World Data, Interactive Games and Visualizations into Early CS Courses
This workshop provides instructors with a hands-on introduction to BRIDGES, a software infrastructure for programming assignments in early computer science courses, including introductory programming (CS1, CS2), data structures, and algorithm analysis. BRIDGES provides capabilities for creating more engaging programming assignments, including: (1) a simplified API for accessing real-world data sets, including from social networks; scientific, government, and civic organizations; and movie, music, and literature collections; (2) interesting visualizations of the data, (3) an easy to use API that supports creation of games that leverage real-world data, and, (4) algorithm benchmarking. Workshop attendees will engage in hands-on experience with BRIDGES with multiple datasets and will have the opportunity to discuss how BRIDGES can be used in their own courses.
- Publication Date:
- NSF-PAR ID:
- 10162420
- Journal Name:
- SIGCSE '20: Proceedings of the 51st ACM Technical Symposium on Computer Science Education
- Page Range or eLocation-ID:
- 1391 to 1391
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
This demo introduces participants to the concepts and application of BRIDGES, a software infrastructure designed to facilitate hands-on experience for solving traditional problems in introductory computer science courses using data from real-world systems that are of interest to students, such as Facebook, Twitter, and Google Maps. BRIDGES provides access to real-world data sets for use in traditional data structures programming assignments, without requiring students to work with complex and varied APIs to acquire such data. BRIDGES also helps the students to explore and understand the use of data structures by providing each student with a visualization of operations performed onmore »
-
In this poster we present BRIDGES, a software infrastructure for programming assignments in data structures and algorithms courses, that has been in use at multiple institutions over the past 2 years. BRIDGES was developed to engage students at the sophomore level in critical foundational courses, to improve retention and reduce attrition rates. BRIDGES provides two key capabilities: (1) easy to use interface to real world datasets spanning social networks, entertainment (movies on IMDB, song lyrics), scientific data (real-time USGIS Earthquake Data), civic issues (crime data), and literature (books); and (2) a visualization of the acquired data can be used inmore »
-
Although undergraduate enrollment in Computer Science has remained strong and seen substantial increases in the past decade, retention of majors remains a significant concern, particularly for students at the freshman and sophomore level that are tackling foundational courses on algorithms and data structures. In this work, we present BRIDGES, a software infrastructure designed to enable the creation of more engaging assignments in introductory data structures courses by providing students with a simplified API that allows them to populate their own data structure implementations with live, real-world, and interesting data sets, such as those from popular social networks (e.g., Twitter, Facebook).more »
-
Computer Science students in algorithm courses often drop out and feel that what they are learning is disconnected from real life programming. Instructors, on the other hand, feel that algorithmic content is foundational for the long term development of students. The disconnect seems to stem from students not perceiving the importance of algorithmic paradigms, and how they impact performance in applications. We present the point of view that by solving real-world problems where algorithmic paradigms and complexity matter, students will become more engaged with the course and appreciate its importance. Our approach relies on a lean educational framework that providesmore »