16808221
A Collaborative Support Tool for Creativity Learning: Idea Storming Cube
Creativity plays an important role in many learning activities but how to enhance creativity with the support of modern computer tools deserves further studies. In this paper, we propose a game-based collaborative creativity support system called Idea storming cube to support creative thinking and help a user form a perspective-shift thinking habit. The system analyzes the knowledge acquired from the history of user inputs and compares it with the ideas possessed by the domain expert and other users in the current brainstorming group. The system is designed to provide user-, goal- and context-sensitive supports with this mechanism that stimulates more divergent thinking. We have implemented the proposed game with a magic-cube-like HCI for collaborative idea generation. A case study for preliminary evaluation of the system is also reported in this paper.
5809000
VIBRANT: A Brainstorming Agent for Computer Supported Creative Problem Solving
This paper describes key issues underlying the design of a tutoring system that brainstorms with students in order to support qualitative problem solving. Cognitively oriented and socially oriented support are enabled by two technologies, namely heuristic-based feedback generation and community-data-driven social recommendation. Formal representations and corresponding automated reasoning procedures for these technologies are introduced.
9329231
Idea Storming Cube: A Game-based System to Support Creative Thinking
This paper describes a collaborative game-based creativity support system, idea storming cube, in support of creative thinking. It aims to make people form a creative and perspective-shift thinking habit. The system acquires knowledge from domain expert, user inputs history, and individuals in the current brainstorming group, and then provides user-, goal- and context-sensitive supports. Comparing to classic tutoring systems, it focuses more on stimulating divergent thinking. The system can be put into the basic mode or the idea generation mode in order to support different gaming objectives. A case study for preliminary evaluation of the proposed HCI tool for collaborative idea generation is also reported in this paper.
376739
An empirical exploration of using Wiki in an English as a second language course
In this paper, we present an empirical study of using a new and cost-effective Web-based collaboration software, Wiki, in a freshman-level English as a second language (ESL) course. This paper explores and observes the scenario: what if the Wiki tool were to be used in an English as a second language course in Taiwan? Students who attended this study practiced English writing on a Wiki Web site. The data about their usage and learning achievements was collected and analyzed. Our finding of a significant, but inverse, relation between students' editing usage and academic performance challenges some idealistic hypotheses that Wiki technology is "naturally beneficial" to learning. We believe that building an instructive or constructive instructional model with Wiki in a rigorous manner requires more empirical evidence. This study provides fresh evidence that will hopefully serve as an impetus to fill that gap.
9426825
Adaptive presentation for effective Web-based learning of 3D content
In this paper we focus on incorporating adaptive presentation and 3D visualization into Web-based learning environments to enhance learners' learning outcomes, especially to facilitate learners' spatial reasoning on geometric topics in computer graphics. This system is called CooTutor (coordinate tutor). According to educational media studies, "Media and Method" are the main concerns of developing such a system. In CooTutor, interactive 3D media is used to present spatial relations effectively to the learners. Instructional methods and strategies are embedded in its adaptive mechanism by incorporating ITS (intelligent tutoring systems) techniques. Since geometric transformation is the example domain of our study, learners' spatial ability is considered as an index for adapting the presentation. To achieve better abstraction and flexibility, we have chosen to separate the concept sequencing from the underlying learning materials. We believe that Web-based learning could take more advantages of available computing power to enhance learning by realizing innovative instructional design, as in the case of 3D interactive presentation.
12981432
A web-based tutoring system with styles-matching strategy for spatial geometric transformation
It has been a major objective for researchers to develop computer systems that can effectively deliver instruction to learners. Therefore, how to incorporate instructional strategies in computer-assisted learning systems in a systematic manner deserves further investigation. In this paper, a style-matching strategy that attempts to match learning materials' styles to learners' latent traits is proposed and realized in a web-based tutoring system, called CooTutor. The mechanism of adaptive material selection takes learners' different spatial ability and learning styles as an integral learning profile into account, and performs traits-based personalization of learning experience. This system is specifically designed to conquer the difficulty of tutoring the topic on fundamental spatial geometry in conventional curriculums. By conducting empirical evaluation with a small group of students, it is found that CooTutor is generally beneficial to learning the domain, but the effect of the styles-matching mechanism remains inconclusive. The work aims to contribute to the community of adaptive hypermedia in providing an explorative example adopting the concern of individual difference for personalization. The system design, a usage scenario, and an exploratory evaluation are presented in this paper as implications for further studies.
10685141
Loadstar: A Load Shedding Scheme for Classifying Data Streams
We consider the problem of resource allocation in mining multiple data streams. Due to the large volume and the high speed of streaming data, mining algorithms must cope with the effects of system overload. How to realize maximum mining benefits under resource constraints becomes a challenging task. In this paper, we propose a load shedding scheme for classifying multiple data streams. We focus on the following problems: i) how to classify data that are dropped by the load shedding scheme? and ii) how to decide when to drop data from a stream? We introduce a quality of decision (QoD) metric to measure the level of uncertainty in classification when exact feature values of the data are not available because of load shedding. A Markov model is used to predict the distribution of feature values and we make classification decisions using the predicted values and the QoD metric. Thus, resources are allocated among multiple data streams to maximize the quality of classification decisions. Furthermore, our load shedding scheme is able to learn and adapt to changing data characteristics in the data streams. Experiments on both synthetic data and real-life data show that our load shedding scheme is effective in improving the overall accuracy of classification under resource constraints. keywords: data mining, data streams, load shedding, classification, quality of decision, feature prediction, Markov model.
14482795
Collaborative multi-agents for workflow management
Workflow management helps organizations to organize their work on different activities in such a way that the predictable underlying processes are carried out effectively and efficiently in a distributed environment. We describe a business workflow management system with intelligent multi-agent support in a collaborative organization environment. With the help from multi-agent collaboration, our workflow management system can organize the organization's work processes and provide resource control, data mediation, semantic mapping, and knowledge visualization processing. Such systems are able to manage the organizational workflow more effectively and more efficiently.
14076500
False-Peaks-Avoiding Mean Shift Method for Unsupervised Peak-Valley Sliding Image Segmentation
The mean shift (MS) algorithm is sensitive to local peaks. In this paper, we show both empirically and analytically that when using sample data, the reconstructed PDF may have false peaks. We show how the occurrence of the false peaks is related to the bandwidth h of the kernel density estimator, using examples of gray-level image segmentation. It is well known that in MS-based approaches, the choice of h is important: we provide a quantitative relationship between false peaks and h. For the gray-level image segmentation problem, we provide a complete unsupervised peak-valley sliding algorithm for gray- level image segmentation.
18937658
Mining associations by pattern structure in large relational tables
Association rule mining aims at discovering patterns whose support is beyond a given threshold. Mining patterns composed of items described by an arbitrary subset of attributes in a large relational table represents a new challenge and has various practical applications, including the event management systems that motivated this work. The attribute combinations that define the items in a pattern provide the structural information of the pattern. Current association algorithms do not make full use of the structural information of the patterns: the information is either lost after it is encoded with attribute values, or is constrained by a given hierarchy or taxonomy. Pattern structures convey important knowledge about the patterns. We present an architecture that organizes the mining space based on pattern structures. By exploiting the interrelationships among pattern structures, execution times for mining can be reduced significantly. This advantage is demonstrated by our experiments using both synthetic and real-life datasets.
17534271
User defined aggregates in object-relational systems
User-defined aggregates are essential in many advanced database applications, particularly in expressing data mining functions, but they find little support in current systems including object-relational databases. Three serious limitations of current systems are (i) the inability to introduce new aggregates (e.g., by coding them in procedural language as originally proposed in SQL3), (ii) the inability to return partial results during the computation (e.g. to support online aggregation), and (iii) the inability to use aggregates in recursive queries (e.g. to express bill of materials and optimized graph searches). In this paper, we presents a unified solution to these problems which realizes the SQL3 original proposal for user-defined aggregates (U-DAs), and adds significant improvements in terms of expressive power and ease of use: in fact our SQL-AG system also supports online aggregation, monotonic aggregation, and a high-level aggregate definition language named SADL. We focus on applications of UDAs and SADL.