Enhancing Undergraduate AI Courses through Machine Learning Projects

It is generally recognized that an undergraduate introductory Artificial Intelligence course is challenging to teach. This is, in part, due to the diverse and seemingly disconnected core topics that are typically covered. The paper presents work funded by the National Science Foundation to address this problem and to enhance the student learning experience in the course. Our work involves the development of an adaptable framework for the presentation of core AI topics through a unifying theme of machine learning. A suite of hands-on semester-long projects are developed, each involving the design and implementation of a learning system that enhances a commonly-deployed application. The projects use machine learning as a unifying theme to tie together the core AI topics. In this paper, we will first provide an overview of our model and the projects being developed and will then present in some detail our experiences with one of the projects – Web User Profiling which we have used in our AI class

Unifying an Introduction to Artificial Intelligence Course through Machine Learning Laboratory Experiences

This paper presents work on a collaborative project funded by the National Science Foundation that incorporates machine learning as a unifying theme to teach fundamental concepts typically covered in the introductory Artificial Intelligence courses. The project involves the development of an adaptable framework for the presentation of core AI topics. This is accomplished through the development, implementation, and testing of a suite of adaptable, hands-on laboratory projects that can be closely integrated into the AI course. Through the design and implementation of learning systems that enhance commonly-deployed applications, our model acknowledges that intelligent systems are best taught through their application to challenging problems. The goals of the project are to (1) enhance the student learning experience in the AI course, (2) increase student interest and motivation to learn AI by providing a framework for the presentation of the major AI topics that emphasizes the strong connection between AI and computer science and engineering, and (3) highlight the bridge that machine learning provides between AI technology and modern software engineering

Pedagogical Possibilities for the 2048 Puzzle Game

In this paper, we describe an engaging puzzle game called 2048 and outline a variety of exercises that can leverage the game’s popularity to engage student interest, reinforce core CS concepts, and excite student curiosity towards undergraduate research. Exercises range in difficulty from CS1-level exercises suitable for exercising and assessing 1D and 2D array skills to empirical undergraduate research in Monte Carlo Tree Search methods and skilled heuristic evaluation design

Pedagogical Possibilities for the N-Puzzle Problem

In this paper we present work on a project funded by the National Science Foundation with a goal of unifying the Artificial Intelligence (AI) course around the theme of machine learning. Our work involves the development and testing of an adaptable framework for the presentation of core AI topics that emphasizes the relationship between AI and computer science. Several hands-on laboratory projects that can be closely integrated into an introductory AI course have been developed. We present an overview of one of the projects and describe the associated curricular materials that have been developed. The project uses machine learning as a theme to unify core AI topics in the context of the N-puzzle game. Games provide a rich framework to introduce students to search fundamentals and other core AI concepts. The paper presents several pedagogical possibilities for the N-puzzle game, the rich challenge it offers, and summarizes our experiences using it

Teaching and learning of performance measurement in OR/MS degrees

A review of existing UK MS/OR undergraduate programmes was completed to assess the extent and nature of performance measurement teaching. In addition, a survey of performance measurement practitioners was undertaken to obtain views on what should be taught in relation to performance measurement. A survey of 23 undergraduate MS/OR degrees in the UK revealed that all the academic respondents supported the inclusion of PM teaching. However, only four distinct PM classes could be found amongst these degrees. The PM techniques taught were broadly similar although the wider context of PM was taught in only 2 of the classes. A survey of a small number of PM practitioners revealed that the Balanced Scorecard and Benchmarking were the two most commonly applied PM techniques with the majority of respondents learning about PM from personal experience and reading rather than through formal education. It appears that there is an opportunity for MS/OR teaching to make a major contribution to the development of PM as a discipline. However, academic respondents whose MS/OR degree course did not teach PM indicated that lack of staff expertise in PM combined with an already full syllabus were the main barriers to introducing a PM class

The SBI Program and Student Outcomes: A Study of Business Policy Classes

This study represents a preliminary inquiry ID to determine the value of combining SBI and Policy into a singular curriculum. A comparison of this combined formal was made wi1h the traditional Policy course. A slightly modified Job Diagnostic Survey (Hackman & Oldham, 1975) and a skills/usefulness scale (Hoffman, Fon1eno1 & Viswanathan, 1990) was administered to assess the difference between the two groups. Results suggested that the combined format met or exceeded the ou1comes of the traditional Policy course

The State of American Indian & Alaska Native Education in California 2014

The findings from the California Indian Culture and Sovereignty Center's 2012 report confirmed the need for greater efforts to prepare, to recruit, to retain, and to graduate Native youth from institutions of higher education. In particular, the realization that AI/AN enrollment rates are declining across the CSUs was alarming. These results provided the basis to delve deeper into the program, outreach, and support of postsecondary institutions in the 2014 report to determine where enrollment and transfer numbers are decreasing or increasing; to determine what the best practices at state colleges and universities to attract, retain, and graduate AI/ANs are; and correspondingly to determine where we, as educators of AI/AN students in the state of California, need to improve

Pervasive Parallel And Distributed Computing In A Liberal Arts College Curriculum

We present a model for incorporating parallel and distributed computing (PDC) throughout an undergraduate CS curriculum. Our curriculum is designed to introduce students early to parallel and distributed computing topics and to expose students to these topics repeatedly in the context of a wide variety of CS courses. The key to our approach is the development of a required intermediate-level course that serves as a introduction to computer systems and parallel computing. It serves as a requirement for every CS major and minor and is a prerequisite to upper-level courses that expand on parallel and distributed computing topics in different contexts. With the addition of this new course, we are able to easily make room in upper-level courses to add and expand parallel and distributed computing topics. The goal of our curricular design is to ensure that every graduating CS major has exposure to parallel and distributed computing, with both a breadth and depth of coverage. Our curriculum is particularly designed for the constraints of a small liberal arts college, however, much of its ideas and its design are applicable to any undergraduate CS curriculum