Data Mining - Concepts and Techniques.

Mobile and wireless communication technologies not only enable anytime and anywhere learning, but also provide the opportunity to develop learning environments that combine real-world and digital-world resources. Nevertheless, researchers have indicated that, without effective tools for helping students organize their observations in the field, the mobile learning performance could be disappointing. To cope with this problem, this study proposes an interactive concept map-oriented approach for supporting mobile learning activities. An experiment has been conducted on an elementary school natural science course to evaluate the effectiveness of the proposed method. The experimental results show that the proposed approach not only enhances learning attitudes, but also improves the learning achievements of the students.

An interactive concept map approach to supporting mobile learning activities for natural science courses

Recent advances in mobile and wireless communication technologies have enabled various new learning approaches which situate students in environments that combine real-world and digital-world learning resources; moreover, students are allowed to share knowledge or experiences with others during the learning process. Although such an approach seems to be promising and innovative, researchers have indicated several problems when applying it to practical applications, in particular, the lack of proper strategies or tools to assist the students to learn collaboratively in such a learning scenario with abundant content. Students might feel interested when using the mobile devices to learn; however, without proper assistance or guidance, their learning achievements are usually disappointing. To cope with this problem, this study proposes a concept map-oriented Mindtool for collaborative ubiquitous learning. Experimental results from a natural science course in an elementary school show that this approach not only enhances learning motivation but also improves the learning achievements of the students. [ABSTRACT FROM AUTHOR]

A concept map approach to developing collaborative Mindtools for context-aware ubiquitous learning

Scholars have identified that learning in an authentic environment with quality contextual and procedural supports can engage students in thorough observations and knowledge construction. Moreover, the target is that students are able to experience and make sense of all of the learning activities in the real-world environment with meaningful supports, such that their learning motivation can be promoted, knowledge can be sensibly constructed, and skills can be fully developed. To develop potential tutoring strategies and learning activity models using mobile, wireless, and sensing information and communication technologies (ICT) in a real-world learning environment, a four-year national e-learning research project entitled "Mindtool-Assisted In-field Learning (MAIL)" has been funded by the National Science Council of Taiwan since 2008 in an effort to lead the development and innovation of Learning Technology. The integrated project aimed to develop Mindtool- assisted knowledge construction models, assessment models, guidance models, and reflection strategies for cutting-edge context-aware ubiquitous learning. Moreover, a series of learning activities has been conducted to examine the effectiveness of the proposed learning strategies and models. Each year, more than 1,500 students have participated in the in-field learning activities with the designed approaches. Based on the results of a series of experiments, it was found that the students' learning performance as well as their in-field inquiry ability was significantly improved, showing the effectiveness of the Mindtool-assisted ubiquitous learning approach and the success of the MAIL project. In this paper, the background, objectives, theoretical foundations, systems, research issues, applications, and findings of the MAIL project are presented. Finally, the scaling-up plan for applying these research-proven learning models to all levels of educational settings in Taiwan is also addressed.

https://www.jstor.org/stable/jeductechsoci.17.2.4

Mindtool-Assisted In-Field Learning (MAIL): An Advanced Ubiquitous Learning Project in Taiwan

In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of the concepts identified in the concept map developed by the student. The evaluation of a student's understanding of the topic is assessed by analyzing the curve of the graph generated by this tool. This technique makes extensive use of XML parsing to perform the required evaluation. The tool was successfully tested with students from two undergraduate courses and the results of testing are described in this paper.

Artificial Intelligence-Based Student Learning Evaluation: A Concept Map-Based Approach for Analyzing a Student's Understanding of a Topic

Concept maps have been adopted extensively in teaching and assessment. Assess ment schemes, including the closeness index and the N-G method, have also been widely applied to evaluate the quality of students' concept maps. Teachers must make great efforts to evaluate students' concept maps, because present concept map assessment schemes do not reveal ways to help them improve such maps. Additionally, teachers cannot easily provide constructive suggestions to students to improve their learning, particularly when concept maps incorporate many concept; and links. This work presents linkage algorithms that can he used to discover the patterns (such as confused concepts, substitute concepts, and hidden wrong concepts) in concept maps to support assessment. Teachers can use the discovered patterns not onty to become aware of the conceptions of students, but also to improve students' conceptions efficiently.

Assessment Based on Linkage Patterns in Concept Maps

Introduction Searching the Web has become an important learning activity as the Web holds a vast amount of multimedia information which is more up-to-date, relevant to the goals and interests of users, and more convenient than that of the more traditional libraries, encyclopedias, and periodicals serving similar purposes (Sloane, 1997). The World Wide Web has become an extremely important learning resource, augmenting in many cases supplanting traditional resources. However, learning on the Web requires not only information finding but also information discovery which involves finding relevant information, collecting that information, and developing an understanding of the information and the relationships within it (Marchionini, 2006). Such information discovery on the Web is critical to learning since it enables students to experience cognitive restructuring and develop new ideas (Kerne et al., 2007). However, most studies of discovery on the Web focus on developing approaches for promoting personal discovery during the search process. There have been few studies on providing a means of supporting Web co-discovery through which a group of students can learn by exploring the Web together. Although Web search is usually undertaken as a solitary activity, studies of Web searching revealed that students often search jointly for information to accomplish their group tasks, their group projects or assignments (Sidler et al., 1997; Large et al., 2002). For example, a student may ask his/her group members for advice or assistance in obtaining crucial information on the Web. Web co-search may afford advantages such as division of responsibilities for search tasks, an awareness of group members' search processes and results, and the persistence of co-discovery activities (Amershi & Morris, 2008). In addition, Web co-search not only improves the quality of discovery, but provides more explanatory and coordinated activities which are, in turn, important to successful discovery (Okada & Simon, 1997). Therefore, Amershi and Morris (2008) have advocated that Web co-discovery is a more successful discovery process than is individual Web discovery. As more and more learning resources become available on the Web, supporting such collaborative discovery on Web content in educational settings becomes increasingly exigent and essential. There are two main approaches to supporting face-to-face Web co-discovery: the shared approach and the parallel approach (Amershi & Morris, 2008). In the shared approach, group members share a single computer enabling faceto-face communication, which can boost highly interactive and joint collaboration. However, the shared approach limits equal participation among group members since only one member can control the shared computer's input device at any given time. On the other hand, in the parallel approach, each group member can operate a computer autonomously to access the Web. However, the parallel approach may interfere with collaboration since each member works separately on an individual computer and there is no shared workspace (Liu et al., 2009). These limitations therefore call for another approach that combines the advantages and avoids the disadvantages of the existing two approaches: i.e. facilitating autonomous and joint collaborative participation among group members in face-to-face Web co-discovery activities. The emergence of low-priced computers has made possible many one-to-one collaborative learning scenarios in which each student brings his/her own handheld computer to learning places such as classrooms or libraries (Chan et al., 2006). Recent studies (Maekawa et al., 2006; Amershi & Morris, 2008) have proposed Web co-search environments using a single computer with multiple personal mobile computers, like mobile phones, to promote discovery efficiency in Web co-search scenarios. However, these systems focused specifically upon collaborative Web searching while Web co-discovery involves not only searching, but also the integration of, and reflection on, the web search results contributed by peers. …

Contributing, Exchanging and Linking for Learning: Supporting Web Co- Discovery in One-to-One Environments

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Ping Hsing Don

Author Tools

Chat about Author

Papers

Assessment Based on Linkage Patterns in Concept Maps

Contributing, Exchanging and Linking for Learning: Supporting Web Co- Discovery in One-to-One Environments