Education
Training Watson — A Cognitive Systems Course
Wollowski, Michael (Rose-Hulman Institute of Technology)
We developed a course in which students train an instance of Watson and develop an application that interacts with the trained instance. Additionally, students learn technical in-formation about the Jeopardy! version of Watson and they discuss a future infused with cognitive assistants. In this poster, we justify this course, characterize major assessment items and provide advice on choosing a domain.
Using Declarative Programming in an Introductory Computer Science Course for High School Students
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.
An Online Logic Programming Development Environment
Reotutar, Christian (Johns Hopkins University) | Diagne, Mbathio (Minneapolis Community and Technical College) | Balai, Evgenii (Texas Tech University) | Wertz, Edward (Texas Tech University) | Lee, Peter (University of California, Berkeley) | Yeh, Shao-Lon (Lubbock High School, Lubbock, Texas) | Zhang, Yuanlin (Texas Tech University)
Recent progress in logic programming, particularly answer set programming, has enabled us to teach it to undergraduate and high school students. We developed an online answer set programming environment with simple interface and self contained file system. It is expected to make the teaching of answer set programming more effective and help us to reach more students.
A.I. as an Introduction to Research Methods in Computer Science
Ramanujan, Raghuram (Davidson College)
While many computer science programs offer courses on research methods, such classes typically tend to be aimed at graduate students. In this paper, we propose a novel means for introducing undergraduate students to research experiences in computer science — via an introductory Artificial Intelligence (A.I.) course. Students explore the content areas typically covered in an upper-level A.I. course (heuristic search, constraint satisfaction, game-playing etc.), while also learning about the mechanics of how empirical research is conducted in this field.
IRobot: Teaching the Basics of Artificial Intelligence in High Schools
Burgsteiner, Harald (Graz University of Applied Sciences) | Kandlhofer, Martin (Graz University of Technology) | Steinbauer, Gerald (Graz University of Technology)
Profound knowledge about Artificial Intelligence (AI) will become increasingly important for careers in science and engineering. Therefore an innovative educational project teaching fundamental concepts of AI at high school level will be presented in this paper. We developed an AI-course covering major topics (problem solving, search, planning, graphs, datastructures, automata, agent systems, machine learning) which comprises both theoretical and hands-on components. A pilot project was conducted and empirically evaluated. Results of the evaluation show that the participating pupils have become familiar with those concepts and the various topics addressed. Results and lessons learned from this project form the basis for further projects in different schools which intend to integrate AI in future secondary science education.
A Survey of Current Practice and Teaching of AI
Wollowski, Michael (Rose-Hulman Institute of Technology) | Selkowitz, Robert (Canisius College) | Brown, Laura E. (Michigan Technological Institute) | Goel, Ashok (Georgia Institute of Technology) | Luger, George (University of New Mexico) | Marshall, Jim (Sarah Lawrence College) | Neel, Andrew (Discover Cards) | Neller, Todd (Gettysburg College) | Norvig, Peter (Google)
The field of AI has changed significantly in the past couple of years and will likely continue to do so. Driven by a desire to expose our students to relevant and modern materials, we conducted two surveys, one of AI instructors and one of AI practitioners. The surveys were aimed at gathering infor-mation about the current state of the art of introducing AI as well as gathering input from practitioners in the field on techniques used in practice. In this paper, we present and briefly discuss the responses to those two surveys.
Creating Interactive and Visual Educational Resources for AI
Singh, Sameer (University of Washington) | Riedel, Sebastian (University College London)
Teaching artificial intelligence is effective if the experience is a visual and interactive one, with educational materials that utilize combinations of various content types such as text, math, and code into an integrated experience. Unfortunately, easy-to-use tools for creating such pedagogical resources are not available to the educators, resulting in most courses being taught using a disconnected set of static materials, which is not only ineffective for learning AI, but further, requires repeated and redundant effort for the instructor. In this paper, we introduce Moro, a software tool for easily creating and presenting AI-friendly teaching materials. Moro notebooks integrate content of different types (text, math, code, images), allow real-time interactions via modifiable and executable code blocks, and are viewable in browsers both as long-form pages and as presentations. Creating notebooks is easy and intuitive; the creation tool is also in-browser, is WYSIWYG for quick iterations of editing, and supports a variety of shortcuts and customizations for efficiency. We present three deployed case studies of Moro that widely differ from each other, demonstrating its utility in a variety of scenarios such as in-class teaching and conference tutorials.
Design of an Online Course on Knowledge-Based AI
Goel, Ashok K. (Georgia Institute of Technology) | Joyner, David A. (Georgia Institute of Technology)
In Fall 2014 we offered an online course on Knowledge-Based Artificial Intelligence (KBAI) to about 200 students as part of the Georgia Tech Online MS in CS program. By now we have offered the course to more than 1000 students. We describe the design, development and delivery of the online KBAI class in Fall 2014.
Teaching Big Data Analytics Skills with Intelligent Workflow Systems
Gil, Yolanda (University of Southern California)
We have designed an open and modular course for data science and big data analytics using a workflow paradigm that allows students to easily experience big data through a sophisticated yet easy to use instrument that is an intelligent workflow system. A key aspect of this work is the use of semantic workflows to capture and reuse end-to-end analytic methods that experts would use to analyze big data, and the use of an intelligent workflow system to elaborate the workflow and manage its execution and resulting datasets. Through the exposure of big data analytics in a workflow framework, students will be able to get first-hand experiences with a breadth of big data topics, including multi-step data analytic and statistical methods, software reuse and composition, parallel distributed programming, high-end computing. In addition, students learn about a range of topics in AI, including semantic representations and ontologies, machine learning, natural language processing, and image analysis.
Conceptualizing Curse of Dimensionality with Parallel Coordinates
Devi, G. (Indian Institute of Technology, Madras) | Chauhan, Charu (Indian Institute of Technology Madras) | Chakraborti, Sutanu (Indian Institute of Technology Madras)
We report on a novel use of parallel coordinates as a pedagogical tool for illustrating the non-intuitive properties of high dimensional spaces with special emphasis on the phenomenon of Curse of Dimensionality. Also, we have collated what we believe to be a representative sample of diverse approaches that exist in literature to conceptualize the Curse of Dimensionality. We envisage that the paper will have pedagogical value in structuring the way Curse of Dimensionality is presented in classrooms and associated lab sessions.