Web-based knowledge-based system on liquid retaining structure design as instructional tool

2002-2003 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Intelligence-based educational package on fluid mechanics

Series: Lecture notes in computer scienceAuthor name used in this publication: KwokWing Chau2004-2005 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Designing web-based adaptive learning environment : distils as an example

In this study, two components are developed for the Web-based adaptive learning: an online Intelligent Tutoring Tool (ITT) and an Adaptive Lecture Guidance (ALG). The ITT provides students timely problem-solving help in a dynamic Web environment. The ALG prevents students from being disoriented when a new domain is presented using Web technology. A prototype, Distributed Intelligent Learning System (DISTILS), has been implemented in a general chemistry laboratory domain. In DISTILS, students interact with the ITT through a Web browser. When a student selects a problem, the problem is formatted and displayed in the user interface for the student to solve. On the other side, the ITT begins to solve the problem simultaneously. The student can then request help from the ITT through the interface. The ITT interacts with the student, verifying those solution activities in an ascending order of the student knowledge status. In DISTILS, a Web page is associated with a HTML Learning Model (HLM) to describe its knowledge content. The ALG extracts the HLM, collects the status of students\u27 knowledge in HLM, and presents a knowledge map illustrating where the student is, how much proficiency he/she already has and where he/she is encouraged to explore. In this way, the ALG helps students to navigate the Web-based course material, protecting them from being disoriented and giving them guidance in need. Both the ITT and ALG components are developed under a generic Common Object Request Broker Architecture (CORBA)-driven framework. Under this framework, knowledge objects model domain expertise, a student modeler assesses student\u27s knowledge progress, an instruction engine includes two tutoring components, such as the ITT and the ALG, and the CORBA-compatible middleware serves as the communication infrastructure. The advantage of such a framework is that it promotes the development of modular and reusable intelligent educational objects. In DISTILS, a collection of knowledge objects were developed under CORBA to model general chemistry laboratory domain expertise. It was shown that these objects can be easily assembled in a plug-and-play manner to produce several exercises for different laboratory experiments. Given the platform independence of CORBA, tutoring objects developed under such a framework have the potential to be easily reused in different applications. Preliminary results showed that DISTILS effectively enhanced learning in Web environment. Three high school students and twenty-two NJIT students participated in the evaluation of DISTILS. In the final quiz of seven questions, the average correct answers of the students who studied in a Web environment with DISTILS (DISTILS Group) was 5.3, and the average correct answers of those who studied in the same Web environment without DISTILS (NoDISTILS Group) was 2.75. A t-test conducted on this small sample showed that the DISTILS group students significantly scored better than the NoDISTILS group students

Designing a training tool for imaging mental models

The training process can be conceptualized as the student acquiring an evolutionary sequence of classification-problem solving mental models. For example a physician learns (1) classification systems for patient symptoms, diagnostic procedures, diseases, and therapeutic interventions and (2) interrelationships among these classifications (e.g., how to use diagnostic procedures to collect data about a patient's symptoms in order to identify the disease so that therapeutic measures can be taken. This project developed functional specifications for a computer-based tool, Mental Link, that allows the evaluative imaging of such mental models. The fundamental design approach underlying this representational medium is traversal of virtual cognition space. Typically intangible cognitive entities and links among them are visible as a three-dimensional web that represents a knowledge structure. The tool has a high degree of flexibility and customizability to allow extension to other types of uses, such a front-end to an intelligent tutoring system, knowledge base, hypermedia system, or semantic network

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

The guiding process in discovery hypertext learning environments for the Internet

Hypertext is the dominant method to navigate the Internet, providing user freedom and control over navigational behaviour. There has been an increase in converting existing educational material into Internet web pages but weaknesses have been identified in current WWW learning systems. There is a lack of conceptual support for learning from hypertext, navigational disorientation and cognitive overload. This implies the need for an established pedagogical approach to developing the web as a teaching and learning medium. Guided Discovery Learning is proposed as an educational pedagogy suitable for supporting WWW learning. The hypothesis is that a guided discovery environment will produce greater gains in learning and satisfaction, than a non-adaptive hypertext environment. A second hypothesis is that combining concept maps with this specific educational paradigm will provide cognitive support. The third hypothesis is that student learning styles will not influence learning outcome or user satisfaction. Thus, providing evidence that the guided discovery learning paradigm can be used for many types of learning styles. This was investigated by the building of a guided discovery system and a framework devised for assessing teaching styles. The system provided varying discovery steps, guided advice, individualistic system instruction and navigational control. An 84 subject experiment compared a Guided discovery condition, a Map-only condition and an Unguided condition. Subjects were subdivided according to learning styles, with measures for learning outcome and user satisfaction. The results indicate that providing guidance will result in a significant increase in level of learning. Guided discovery condition subjects, regardless of learning styles, experienced levels of satisfaction comparable to those in the other conditions. The concept mapping tool did not appear to affect learning outcome or user satisfaction. The conclusion was that using a particular approach to guidance would result in a more supportive environment for learning. This research contributes to the need for a better understanding of the pedagogic design that should be incorporated into WWW learning environments, with a recommendation for a guided discovery approach to alleviate major hypertext and WWW issues for distance learning

Graphical Data Mining for Computational Estimation in Materials Science Applications

In domains such as Materials Science experimental results are often plotted as two-dimensional graphs of a dependent versus an independent variable to aid visual analysis. Performing laboratory experiments with specified input conditions and plotting such graphs consumes significant time and resources motivating the need for computational estimation. The goals are to estimate the graph obtained in an experiment given its input conditions, and to estimate the conditions needed to obtain a desired graph. State-of-the-art estimation approaches are not found suitable for targeted applications. In this dissertation, an estimation approach called AutoDomainMine is proposed. In AutoDomainMine, graphs from existing experiments are clustered and decision tree classification is used to learn the conditions characterizing these clusters in order to build a representative pair of input conditions and graph per cluster. This forms knowledge discovered from existing experiments. Given the conditions of a new experiment, the relevant decision tree path is traced to estimate its cluster. The representative graph of that cluster is the estimated graph. Alternatively, given a desired graph, the closest matching representative graph is found. The conditions of the corresponding representative pair are the estimated conditions. One sub-problem of this dissertation is preserving semantics of graphs during clustering. This is addressed through our proposed technique, LearnMet, for learning domain-specific distance metrics for graphs by iteratively comparing actual and predicted clusters over a training set using a guessed initial metric in any fixed clustering algorithm and refining it until error between actual and predicted clusters is minimal or below a given threshold. Another sub-problem is capturing the relevant details of each cluster through its representative yet conveying concise information. This is addressed by our proposed methodology, DesRept, for designing semantics-preserving cluster representatives by capturing various levels of detail in the cluster taking into account ease of interpretation and information loss based on the interests of targeted users. The tool developed using AutoDomainMine is rigorously evaluated with real data in the Heat Treating domain that motivated this dissertation. Formal user surveys comparing the estimation with the laboratory experiments indicate that AutoDomainMine provides satisfactory estimation

The 1990 Johnson Space Center bibliography of scientific and technical papers

Abstracts are presented of scientific and technical papers written and/or presented by L. B. Johnson Space Center (JSC) authors, including civil servants, contractors, and grantees, during the calendar year of 1990. Citations include conference and symposium presentations, papers published in proceedings or other collective works, seminars, and workshop results, NASA formal report series (including contractually required final reports), and articles published in professional journals

NASA SBIR abstracts of 1990 phase 1 projects

The research objectives of the 280 projects placed under contract in the National Aeronautics and Space Administration (NASA) 1990 Small Business Innovation Research (SBIR) Phase 1 program are described. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses in response to NASA's 1990 SBIR Phase 1 Program Solicitation. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 280, in order of its appearance in the body of the report. The document also includes Appendixes to provide additional information about the SBIR program and permit cross-reference in the 1990 Phase 1 projects by company name, location by state, principal investigator, NASA field center responsible for management of each project, and NASA contract number