A major theme of this book is the use of computers for supporting collaborative learning. This is not surprising since computer-supported collaborative learning has become both a widespread educational practice and a main domain of research. Moreover, collaborative learning has deep roots in Asian educational traditions. Given the large number of researchers within this field, its scope has become very broad. Under this umbrella, one finds a variety of more specific topics such as: interaction analysis, collaboration scripts (e.g. the Jigsaw script), communities of practice, sociocognitive conflict resolution, cognitive apprenticeship, various tools for argumentation, online discussion or collaborative drawing tools (whiteboards), collaborative writing and the role of facilitators. Most research work on collaborative learning focuses on interactions rather than on the contents of environments, which had been the focus in the previous decades of learning technology research. However, there is no reason to focus on one aspect to the detriment of the other. The editors are pleased that the selected papers also cover multiple issues related to the storage, representation and retrieval of knowledge: ontologies for learning environments and the semantic web, knowledge bases and data mining, meta-data and content management systems, and so forth. This publication also reveals a growing interest for non-verbal educational material, namely pictures and video materials, which are already central to new popular web-based applications. This book includes contributions that bridge both research tracks, the one focusing on interactions and the other on contents: the pedagogical use of digital portfolios, both for promoting individual reflections and for scaffolding group interactions.
Welcome to the 14th International Conference on Computers in Education (ICCE) hosted by Beijing Normal University (BNU) and supported by the Ministry of Education (MOE) and Chinese Association for Artificial Intelligence (CAAI). The series of conferences started in Taiwan in 1989. The three first editions of ICCE occurred there and then the conference moved across many countries in the Asia-Pacific region: China, Singapore, Malaysia, Japan, Korea, New Zealand, Hong Kong and Australia. The ICCE series is organized by the Asia-Pacific Society for Computers in Education (APSCE). The ICCE is an international event, with strong participation from researchers from Asia and Oceania. Since the beginning, there has also been strong involvement from researchers in Europe and North-America.
These proceedings include the 45 full papers and 53 short papers that have been selected by an international board of scholars listed hereafter. All papers have been reviewed by three or at least two reviewers and double-checked by the Co-chairs of the programme committee. Altogether 254 papers were submitted, which represents a rate of acceptance of 18% if considering only long papers or 38% if including short papers. The content of this volume hence results from a severe selection process. In addition, 22 posters will be presented at the event.
A major theme of this conference is the use of computers for supporting collaborative learning. This is not surprising since computer-supported collaborative learning has become both a widespread educational practice and a main domain of research. Moreover, collaborative learning has deep roots in Asian educational traditions. Given the large number of researchers within this field, its scope has become very broad. Under this umbrella, one finds a variety of more specific topics such as: interaction analysis, collaboration scripts (e.g. the Jigsaw script), communities of practice, socio-cognitive conflict resolution, cognitive apprenticeship, various tools for argumentation, on-line discussion or collaborative drawing tools (whiteboards), collaborative writing and the role of facilitators.
Most research work on collaborative learning focuses on interactions rather than on the contents of environments, which had been the focus in the previous decades of learning technology research. However, there is no reason to focus on one aspect to the detriment of the other. Hence, we are quite pleased that the selected papers also cover multiple issues related to the storage, representation and retrieval of knowledge: ontologies for learning environments and the semantic web, knowledge bases and data mining, meta-data and content management systems, and so forth. These proceedings also reveal a growing interest for non-verbal educational material, namely pictures and video materials, which are already central to new popular web-based applications.
Interestingly, these proceeding include contributions that bridge both research tracks, the one focusing on interactions and the other on contents: the pedagogical use of digital portfolios, both for promoting individual reflections and for scaffolding group interactions. Another specificity of these proceedings, maybe due to regional policies, is the salience of language learning within the range of educational contents covered by learning technologies.
Among the other research trends that appear in the set of contributions, we find the educational use of mobile technologies and the design of educational games. The use of mobile devices and games opens new ways to think about learning technologies, namely the fact that tools that do not a priori appear as learning tools have perhaps more chances to enter into schools. There are nonetheless a limited number of papers on these issues since new conferences emerged in our community, which are devoted to these two subsets of learning technologies.
Finally, let us stress the truly interdisciplinary character of this volume. It contains contributions from the field of computer science, psychology and educational sciences, three fields that are sometimes bound together under the label of 'learning sciences'. The very positive aspect is that computational, pedagogical, cognitive or social factors are not only treated by different papers, but, in many cases, tackled within the same paper.
It is our great pleasure to have gathered these rich contributions within this volume. We hope all readers will share our enthusiasm for this exceptional event.
Program Committee Co-Chairs, Riichiro Mizoguchi, Osaka University, Japan; Pierre Dillenbourg, Swiss Federal Institute of Technology Lausanne, Switzerland; Zhiting Zhu, East China Normal University, China
Modern theories on learning and instruction call attention to learning environments that create constructivistic, situated, and collaborative learning experiences. Simulations offer specific features that enable self-directed, highly autonomous, high interaction learning. First, learning in these environments differs from learning in expository environments in that it puts a higher emphasis on inquiry processes such as hypothesis generation and testing and on regulative processes such as planning and monitoring. Second, these environments offer specific opportunities to situate learning in realistic settings, but they also offer the possibility to adapt reality to support learning. Third, inquiry learning presents opportunities for negotiation and collaboration. This presentation will set out characteristics of simulations discuss characteristic inquiry processes and associated problems, and examine what is needed to design effective inquiry learning environments.
Cui Guangzuo, Yang Gongyi, Chen Hu, Fei Chen, Guo Jiuling
7 - 14
An e-learning model with ICT technology (ELM) is proposed in this paper. With this model, some education technologies and e-learning evolution are interpreted, such as network education, mobile education, ubiquitous education, educational semantic web, and etc. In the meantime, the way of how to combine new ICT technologies into education is also demonstrated. After discussing the convenience and challenge of various education technologies, a new model called intelligent education is introduced and some recent research results are presented. At last, the author looks ahead the future of information technology and human related disciplines and their effects on education.
Rapid change in modern society requires higher levels of learning such as the acquisition of adaptive or “schematic” knowledge. Rather than the efficiency of simply applying what one has learned, the schematic knowledge acquisition emphasizes portability, sustainability, and dependability of learning outcomes. Schematic knowledge is expected to allow the learners to apply them to solve the wider scope of similar problems, as well as to identify new problems and create new solutions. We have been developing and testing college level learning environments to enhance the acquisition of such schematic knowledge in the domain of cognitive science, by heavily relying on understandings of how and why collaborative reflection benefits learning. In the two-year curricular we have developed, the students are first introduced to the notion of schematic learning by experiencing their own formation of schemata, and then are guided to reflect upon the process, through carefully designed collaborative activities. They will also be encouraged to integrate their experiences to technical literature through collaborative discussion in a dynamically arranged jigsaw variations. I will report on the theoretical bases of our practice, concrete learning activities, technological supports, and some results of the evaluative analyses of the learning processes and the outcomes.
The broad field of “computers in education” includes a diversity of approaches to using computers for learning. Each approach is based on an epistemology: a theory of how knowledge is gained. In this presentation, I will characterize the uses of technology and their corresponding epistemologies. I will single out intersubjective epistemologies as timely for research and practice, and call for development of technologies that offer social affordances and resources for meaning-making. The study of intersubjective meaning-making requires interactional analyses, but in new forms that transcend some of the assumptions and limitations of microanalysis and that can be coupled with other methodologies. The presentation illustrates these ideas with my research program on representational affordances for collaborative learning.
Presentation plays an important role in transmitting one's opinion and encouraging collaborative knowledge creation and decision-making processes. A key to producing persuasive presentation materials is to perform meta-cognitive activities well, but that is difficult for novice learners of presentation tasks. Furthermore, from the system-development viewpoint, it is difficult to develop a learning system with which learners can develop their presentation skills effectively because the cognitive activities in presentation task are typically not clarified. In this paper, we first present a cognitive model of the user who performs presentation task. We then overview two kinds of designed environments based on that model: one is for producing presentation materials that encourage learners to perform meta-cognitive activities; the other is a collaborative learning environment in presentation rehearsal, which encourages the transfer of context-dependent meta-cognitive knowledge among learning partners.
This paper proposes a modeling framework for learning and instructional design from the viewpoint of ontological engineering. One of the characteristics of this framework is a theory/paradigm-independent ontology for modeling learning/instruction. This paper discusses how our modeling framework with the theory/paradigm-independent ontology contributes to modeling learning and instruction from a comprehensive viewpoint of various educational theories.
In this paper, firstly we introduce four key elements of application of blending learning in teaching, and then we talk about the application of blending learning in the field of computer teaching based on the practical case of curriculum of ‘Fundamentals of Computer for University’.
This paper presents an effective approach, which combines association rules and clustering algorithm for extracting rules on the web. The advantage of the method is that it can provide more precise and detailed rules compared with traditional algorithms. The paper analyzed some issues in previous approaches first. Then the proposed method is presented. Experiments are performed to evaluate the performance of the combined approach. Experimental results show that the proposed method is more effective and efficient.
This paper reports the second of two studies on the impact of a Cognitive Apprenticeship-Based Learning Environment (CABLE) in the teaching of computer programming. The pedagogical model used in this study employs a combination of instructional strategies including directive support, responsive cognitive apprenticeship, collaborative learning, stimulating metacognition, using technologies via the use of tele-apprenticeship and online discussion. In an earlier study, students who participated within the CABLE project scored more highly on test scores, relative to comparable students who did not participate within CABLE, but these effects were found to be restricted to high-ability students. In the present study, students who participated within CABLE scored more highly than those participating within the non-CABLE group. However, with an enhanced CABLE environment, the benefits of CABLE were now evident in both ability groups, with the effects being more prominent within the low-ability group.
In this paper, we present the evaluation result of our constraint-based tutoring system for logic programming from which we derive the conclusion that students need diagnostic information and remedial hints corresponding to the stage of the problem solving process where they are stuck. For this reason, we propose a three steps diagnosis approach which consists of: diagnosis at the task analysis stage, diagnosis at the solution design stage and diagnosis at the implementation stage. Our diagnosis approach should not only help students learn logic programming, but also master the skills of task analysis and solution design.
This paper describes the CTi system that supports teachers in C programming courses. The CTi system provides teachers with student's model, various learning information and inductive instruction tools. Teachers using the system can provide effective feedback to students. Bayesian Belief Networks are used to represent a student's model and relationship between the structure of programming language and the student's knowledge. An empirical study showed the CTi system had positive effects on students' programming performance.
We propose a teaching method that yields similar results to actual development projects instead of coordinating actual projects which require much labor and expense. Moreover, we propose a method of efficiently editing teaching materials from a real scale open source software product. According to this method, students can have experiences to make decisions with foresight in a realistic development process, and teachers can create teaching materials efficiently and make repeated use of them. Our method is suited to students who have acquired an understanding of object modeling and object-oriented programming but who have no experience of software development on a realistic scale.
Takeshi Kitazawa, Masahiro Nagai, Hiroshi Kato, Kanji Akahori
81 - 88
This paper describes the evaluation of our science e-learning site 'Science Net' which elementary school students have used it for one year. First, the findings show that it is not only being used it for checking lesson content but also for asking questions, lesson revision, and searching for science information via a bulletin board system (BBS). Second, the users who have used it for checking lessons tend to score higher in the self-regulated learning strategies than the non users from the results of the Motivated Strategies for Learning Questionnaire (Pintrich · De Groot 1990), in terms of 2 of the cognitive strategies (When I study for a test, I try to put together the information from class and from the book, and so on), and 4 of the self-regulations (I work on practice exercises and answer end of chapter questions even when I don't have to; when I'm reading I stop once in a while and go over what I have read, and so on.).
Beaumie Kim, Manetta Calinger, Debbie Denise Reese
89 - 96
NASA Learning Technologies is a development effort to create learning tools that provide access to NASA content and data in an engaging and dynamic manner. The present study is the initiation of the design research for one of those developed tools, which provides access to the satellite imagery and scientific visualizations on a 3D globe. NASA education's challenge is not the incorporation of authentic high-tech resources. Rather, it is the preparation for educational use with well-defined science topics. The results of this study suggest that using this tool within a motivating context and an appropriate learning activity could provide positive impacts on science understanding and learning experiences.
ICT application in education has become one of the most attractive topic discussed in modern educational theory and practice. This paper try to verify the effect of ICT application in education, especially in development of students' advanced cognitive abilities, by confirmative experiments in online learning support system named PRIME. After data analysis, the paper gets the conclusions that the PRIME improves students' learning achievement by affect the students' advanced cognitive abilities, and the students' advanced cognitive abilities, as intermediate variables, play very important roles on the performances of students, where PRIME affects their learning.
Writing Chinese character is not trivial and people often commit stroke sequence error and stroke production errors. In this paper, we propose a web-based education system which allows users to practice Chinese handwriting freely. An Automatic Feedback and Analysis (AFA) tool is introduced to the system which can automatically check both the stroke sequence errors and stroke production errors by analyzing the online data of the learner's input character. Feedback will be provided if the learner commits errors in the stroke sequence and/or during stroke production. Experimental results demonstrated that our method can check multiple handwriting errors with encouraging accuracy. User studies showed that the learning time is shorter if our proposed system is used.
In this paper, we describe the development of our intelligent educational system for high school chemistry. Our goal is to put our system in practical use. To achieve our goal, the system must be usable for at least half a year or more. So we focus on the scale of a domain knowledge base (DKB) and a problem data base. We examine the framework of the chemical world model, and describe problem representation and knowledge representation. We tried to expand the DKBthe problem data base. We include an example of problem solving process using the DKB.
In this paper we introduce a pedagogical model that trains writing skills in a blended learning environment (online/in-class). The model has been successfully implemented in several university courses. The results of a formative evaluation support the effectiveness of the model but also point to problems related to the unfamiliar collaborative learning methods.
The usefulness of cases in creative generation has been widely discussed and well recognized. However, it has been also experimentally indicated that introducing cases can limit human creative generation. In this study, we investigate the effects of case presentation in the task domain of generating mathematical word problems. Mathematical word problems have two essential attributes: surface problem situations and the mathematical structures of solutions, the control of which is recognized as an important issue in learning mathematics. In response, we present problems as cases to participants while controlling those attributes, with the results indicating that such presentation actually provides different constraining effects based on the control to their problem generation. Based on the results, we propose a support system for generating word problems, which presents problems as cases by controlling similarities.
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