In the context of a research skills class for undergraduates, we find that providing students background on the scientific method, literature review, writing an abstract, etc. leaves little time for exposing students to actual research. Previously in this class, one assignment involved student teams of four brainstorming for a short time before conducting an experiment that could be performed over a 1-hour period. Some of the experiments included: counting the number of cars of a particular color to estimate an entire population, characterizing the skittish behavior of squirrels, monitoring coffee preferences at a local Starbucks, and estimating the chance of receiving a ticket while parked illegally on campus. While the students enjoyed designing and performing these experiments, we felt the experience did not reflect the rigor that research and experimentation demand. To rectify this situation, we supplemented the data collection activity with a new project; an educational kit was used to provide a systematic procedure for fabricating a dye-sensitized solar cell (DSSC). The kit presents an opportunity for students to fabricate devices as well as design a set of experiments for testing them with several options for controlled variables in a short amount of time.

Scam is a Scheme-like programming language designed for teaching a wide variety of programming language concepts. Scam, at its heart, is an impure functional language, designed to be modified and extended. There are no keywords in the language and every special form, including function definition, is a true function that can be overridden. Consequently, SCAM is ideal for introducing concepts such as object encapsulation and inheritance, aspects, and language subsetting. Both Implementations and applications of these concepts can be added to Scam via student programming projects. This paper introduces Scam and gives a series of projects and solutions that are appropriate for a Programming Languages course.

A dissatisfaction appears to permeate the process of educating computer science students. Both students and instructors seem uninspired in the classroom, resulting in many attempts to enliven, freshen, and improve the experience. These attempts show efficacy, but the pace of improvement is slow. 100 Problems (100P) is an innovative guided discovery curriculum in which students are freed from the classroom and instead work on 100 concept- and research-related problems throughout their undergraduate careers. The 100 problems guide the students to discover the fundamental knowledge and skills required of a graduate of the degree program. Each student is free to create an individualized mode of learning and discovery. As such, the curriculum fosters deep learning among students and challenges students' intellectual growth. In this paper we introduce the 100P curriculum, describe the 100P course format and our experiences offering courses in this format, and report our early findings.

With the huge growth and the market for laptop and palmtop computer purchases, a rapid increase of mobile usage in the Internet is expected. As mobile nodes move in a wireless computer network, a mobile node must determine when to switch its link-level point of attachment to the wired network. In this paper, we present six cell switching techniques and discuss their attributes. Specifically, we present the Late, Early, and Strong cell switching techniques and three variations of them. We then investigate the performance of these six techniques to discover the best method a mobile node should use to determine when to perform its re-attachment to the wired network.

Current expert system technology tends to rely on the use of shallow empirically based experiential knowledge. With only this type of knowledge available, expert systems have been capable of reaching a high level of agreement with human experts in a limited area of expertise. However, due to the nature of their knowledge, such systems fall short of human expertise in many ways. The human diagnostic process is examined as it relates to the malfunction of mechanical and electrical devices. An expert system design is presented, called the integrated diagnostic model (IDM), that attempts to address some of the issues involved in bridging the gap between human and computer expertise. The IDM contains two different types of knowledge, one based on experience and one based on how the device to be diagnosed functions. These two types of knowledge are used together during a diagnostic session to determine what is wrong with the device. To demonstrate how the IDM works, an interaction with a prototype system that was built using the IDM is described; then research on extensions to the IDM is discussed.

Existing expert systems have a high percentage agreement with experts in a particular field in many situations. However, in many ways their overall behavior is not like that of a human expert. These areas include the inability to give flexible, functional explanations of their reasoning processes, and the failure to degrade gracefully when dealing with problems at the periphery of their knowledge. These two important shortcomings can be improved when the right knowledge is available to the system. This paper presents an expert system design, called the integrated diagnostic model (IDM), that integrates two sources of knowledge, a shallow, reasoning-oriented, experiential knowledge base and a deep, functionally oriented, physical knowledge base. To demonstrate the IDM's usefulness in the problem area of diagnosis and repair, an implementation in the mechanical domain is described.

article Free Access Share on LDC-1: a transportable, knowledge-based natural language processor for office environments Authors: Bruce W. Ballard Dept. of Computer Science, Duke Univ., Durham, NC Dept. of Computer Science, Duke Univ., Durham, NCView Profile , John C. Lusth Dept. of Computer Science, Duke Univ., Durham, NC Dept. of Computer Science, Duke Univ., Durham, NCView Profile , Nancy L. Tinkham Dept. of Computer Science, Duke Univ., Durham, NC Dept. of Computer Science, Duke Univ., Durham, NCView Profile Authors Info & Claims ACM Transactions on Information SystemsVolume 2Issue 1Jan. 1984 pp 1–25https://doi.org/10.1145/357417.357418Published:01 January 1984Publication History 24citation436DownloadsMetricsTotal Citations24Total Downloads436Last 12 Months19Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF