While there has been an explosion of impressive, data-driven AI applications in recent years, machines still largely lack a deeper understanding of the world to answer questions that go beyond information explicitly stated in text, and to explain and discuss those answers. To reach this next generation of AI applications, it is imperative to make faster progress in areas of knowledge, modeling, reasoning, and language. Standardized tests have often been proposed as a driver for such progress, with good reason: Many of the questions require sophisticated understanding of both language and the world, pushing the boundaries of AI, while other questions are easier, supporting incremental progress. In Project Aristo at the Allen Institute for AI, we are working on a specific version of this challenge, namely having the computer pass Elementary School Science and Math exams. Even at this level there is a rich variety of problems and question types, the most difficult requiring significant progress in AI. Here we propose this task as a challenge problem for the community, and are providing supporting datasets. Solutions to many of these problems would have a major impact on the field so we encourage you: Take the Aristo Challenge!
Integrating robotics activities in science curriculum provides rich opportunities to engage students in real world science and help them to develop conceptual understanding of physics principles through the process of investigation, data analysis, engineering design, and construction. In addition, students become more confident learners and develop better problem-solving and teamwork skills. In this paper we describe a successful use of LEGO® MINDSTORMS® in designing robotics-based activities for teaching high school physics classes. Students design and perform novel science investigations with a toolset that helps them achieve a high reproducibility in their experimental designs. Several example projects that utilize LEGO MINDSTORMS are presented.
Creating new kinds of educational software has been one motivation for qualitative physics. Our research has brought us to the stage where we are now creating such software, and focusing some of our efforts on investigating how its educational benefits can be optimized. This essay describes one architecture of the three that we are developing: The incorporation of self-explanatory simulators into active illustrations, systems that provide an environment for guided experimentation. We start by examining why qualitative physics is useful for science education, and then describe the active illustrations architecture. We then discuss some of the issues that have arisen in moving our software from laboratory to classroom, and our plans for deployment.
Reyes, Maritza (University of Texas at Austin) | Perez, Cynthia (Texas Tech University) | Upchurch, Rocky (New Deal High School, Lubbock, Texas) | Yuen, Timothy (University of Texas at San Antonio) | Zhang, Yuanlin (Texas Tech University)
This paper discusses the design of an introductory computer science course for high school students using declarative programming. Though not often taught at the K-12 level, declarative programming is a viable paradigm for teaching computer science due to its importance in artificial intelligence and in helping student explore and understand problem spaces. This paper describes the authors' implementation of a declarative programming course for high school students during a 4-week summer session.
This paper describes work from the Bridges to Computing project at Brooklyn College of the City University of New York. This project focuses on the transition from high school to college with the intention of encouraging more students to study some aspect of computer science. The Bridges project has both introduced new undergraduate courses into our computer science curriculum and revised existing courses, as well as developed activities for high school students to help better prepare them for college-level computer science. Here, we report on the use of ideas from artificial intelligence implemented within several of these interventions.