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.
10547222
A Hybrid Ontology Directed Feedback Selection Algorithm for Supporting Creative Problem Solving Dialogues
We evaluate a new hybrid language processing approach designed for interactive applications that maintain an interaction with users over multiple turns. Specifically, we describe a method for using a simple topic hierarchy in combination with a standard information retrieval measure of semantic similarity to reason about the selection of appropriate feedback in response to extended language inputs in the context of an interactive tutorial system designed to support creative problem solving. Our evaluation demonstrates the value of using a machine learning approach that takes feedback from experts into account for optimizing the hierarchy based feedback selection strategy.
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.
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.
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.
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.
8726769
A Prototypes-Embedded Genetic K-means Algorithm
This paper presents a genetic algorithm (GA) for K-means clustering. Instead of the widely applied string-of-group-numbers encoding, we encode the prototypes of the clusters into the chromosomes. The crossover operator is designed to exchange prototypes between two chromosomes. The one-step K-means algorithm is used as the mutation operator. Hence, the proposed GA is called the prototypes-embedded genetic K-means algorithm (PGKA). With the inherent evolution process of evolutionary algorithms, PGKA has superior performance than the classical K-means algorithm, while comparing to other GA-based approaches, PGKA is more efficient and suitable for large scale data sets
18822397
A spoken-access approach for chinese text and speech information retrieval
This paper presents an efficient spoken access approach for both Chinese text and Mandarin speech information retrieval. The proposed approach is developed not only to deal with the retrieval of spoken documents, but also to improve the capability of human-computer interaction via voice input for information retrieval systems. Based on utilization of the mono-syllabic structure of the Chinese language, the proposed approach can tolerate speech recognition errors by performing speech query recognition and approximate information retrieval at the syllable-level. Furthermore, with the help of automatic term suggestion and relevance feedback techniques, the proposed approach is robust in allowing users using voice input to interact with IR systems at each stage of the retrieval process. Extensive experiments show that the proposed approach can improve the effectiveness of information retrieval via speech interaction. The encouraging results suggest that a Mandarin speech interface for information retrieval and digital library systems can, therefore, be developed.
32652355
Browsing the Chinese Web Pages Using Mandarin Speech
A speech interface that allows easy access to information on the WWW has the potential to make the browser more friendly and powerful. This paper, thus, presents a working Mandarin speech interface for using unconstrained Mandarin speech to control the WWW browser for conveniently browsing the Chinese Web pages. The interface currently provides speakable commands, bookmarks, and links. The experimental results show that our approach which specially consider the characteristics of the Chinese language is very effective, and very high accuracy can be achieved.
5874117
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud protection, target marketing, network intrusion detection, etc. Conventional knowledge discovery tools are facing two challenges, the overwhelming volume of the streaming data, and the concept drifts. In this paper, we propose a general framework for mining concept-drifting data streams using weighted ensemble classifiers. We train an ensemble of classification models, such as C4.5, RIPPER, naive Beyesian, etc., from sequential chunks of the data stream. The classifiers in the ensemble are judiciously weighted based on their expected classification accuracy on the test data under the time-evolving environment. Thus, the ensemble approach improves both the efficiency in learning the model and the accuracy in performing classification. Our empirical study shows that the proposed methods have substantial advantage over single-classifier approaches in prediction accuracy, and the ensemble framework is effective for a variety of classification models.
13006853
Novel likelihood estimation technique based on boosting detector
This paper presents novel likelihood estimation to be used for particle filter based object tracking. The likelihood estimation is built upon cascade object detector trained with Gentle AdaBoost (GAB), in order to capture the probability of existence of object. Two strategies are adopted to construct the likelihood functions: probability-intra-stage (PIS) corresponding to real output of each weak classifier in the same stage, and probability-outer-stage (POS) corresponding to the depth reached in the cascade detector. Five kinds of likelihood functions are thus proposed based on the trained GAB detector. Our experiment shows the likelihood functions are able to characterize probabilistically the existence of object accurately, having much higher confidence value in object regions than that in background, and that the integral strategy of PIS and POS is the best choice.