The Explore of the Web-Based Learning Environment Base on Web Sequential Pattern Mining

2009 ◽  
Author(s):  
Hai-yan Wu ◽  
Jing-jun Zhu ◽  
Xin-yu Zhang
Keyword(s):  
Learning Environment ◽  
Pattern Mining ◽  
Sequential Pattern Mining ◽  
Sequential Pattern ◽  
Web Based ◽  
Web Based Learning ◽  
The Web

Constructing a ‘third space’ for EFL learners: Where language and cultures meet

ReCALL ◽  
2007 ◽  
Vol 19 (2) ◽  
pp. 224-241 ◽  
Author(s):  
MEEI-LING LIAW
Keyword(s):  
Learning Environment ◽  
Language Learning ◽  
Intercultural Competence ◽  
Discussion Boards ◽  
Online Forums ◽  
Extensive Reading ◽  
Web Based ◽  
Web Based Learning ◽  
On Line ◽  
The Web

Efforts have been made by language educators and researchers to use computer technology to assist L2 learners’ growth in either linguistic or intercultural competence. Nonetheless, web-based environments devoted to developing both types of competences in tandem are new and experimental. The purpose of this project, which involves the collaboration of EFL educators and computer engineers in Taiwan, is to establish an innovative web-based environment to support students in tertiary levels to develop both types of competences. This web-based EFL learning environment experiments with a few main features: (1) instead of reading articles about a foreign culture, the users of this website read articles about their native culture; (2) two on-line computer-based support tools, a bilingual concordancer and a dictionary, are made available to provide students with contextual supports for language learning; and (3) discussion boards are provided for intercultural communication. The web-based learning environment contains several instructional units. While working on a unit, students read an article and then answer comprehension and vocabulary questions. After reading, students share their responses to the articles with intercultural conversation partners via online forums. To evaluate the effectiveness of the learning environment, the researcher recruited a group of Taiwanese university students to test-use the system. Frequencies of the uses of the two e-referencing tools were calculated. The students’ responses to a questionnaire were examined and informal interviews with the students were conducted. Finally, the students’ forum entries were analyzed. The findings revealed initial interest in using e-referencing tools but a dramatic decrease in use after the first few units had been completed. The students used the concordancer as a link to extensive reading materials and suggested adding pronunciation tools to the dictionary. Questionnaire findings showed that students were generally satisfied with the design of the web-based learning environment. An analysis of the students’ forum entries revealed increases in the length and complexity of sentences in their writings, as well as reductions in grammatical errors, as more units were completed. As for intercultural learning, the content analysis of the forum entries demonstrated different types of intercultural competences. Based on the findings, some implications for revision of the virtual environment to enable more effective learning of English as a foreign language and greater development of intercultural competence are drawn.

scholarly journals A Review on Design and Development Of Sequential Patterns Algorithms In Web Usage Mining

2021 ◽  
Vol 12 (2) ◽  
pp. 1634-1639
Author(s):  
V Aruna, Et. al.
Keyword(s):  
Web Mining ◽  
Pattern Mining ◽  
Pattern Discovery ◽  
Relevant Information ◽  
Sequential Pattern Mining ◽  
Web Usage Mining ◽  
Sequential Pattern ◽  
Web Usage ◽  
Hidden Data ◽  
The Web

In the recent years with the advancement in technology, a  lot of information is available in different formats and extracting the  knowledge from that data has become a very difficult task. Due to the vast amount of information available on the web, users are finding it difficult to extract relevant information or create new knowledge using information available on the web. To solve this problem  Web mining techniques are used to discover the interesting patterns from the hidden data .Web Usage Mining (WUM), which is one  of the subset of  Web Mining helps in extracting the hidden knowledge present in the Web log  files , in recognizing various interests of web users and also in  discovering customer behaviours. Web Usage mining  includes different phases of data mining techniques called Data Pre-processing, Pattern Discovery & Pattern Analysis. This paper presents an updated focused survey on various sequential pattern mining  algorithms  like  apriori-based algorithm , Breadth First Search-based strategy, Depth First Search strategy,  sequential closed-pattern algorithm and Incremental pattern mining algorithm which are used in Pattern Discovery Phase of WUM. At last , a comparison  is done based on the important key features present in these algorithms. This study gives us better understanding of the approaches of sequential pattern mining.

Investigating Higher Education and Secondary School Web-Based Learning Environments Using the WEBLEI

2012 ◽  
pp. 93-104 ◽  
Author(s):  
Vinesh Chandra ◽  
Darrell Fisher ◽  
Vanessa Chang
Keyword(s):  
Higher Education ◽  
Learning Environment ◽  
Learning Environments ◽  
New Technologies ◽  
Digital Technologies ◽  
Classroom Learning ◽  
Web Based ◽  
Initial Development ◽  
Web Based Learning ◽  
The Web

Classroom learning environments are rapidly changing as new digital technologies become more education-friendly. What are students’ perceptions of their technology-rich learning environments? This question is critical as it may have an impact on the effectiveness of the new technologies in classrooms. There are numerous reliable and valid learning environment instruments which have been used to ascertain students’ perceptions of their learning environments. This chapter focuses on one of these instruments, the Web-based Learning Environment Instrument (WEBLEI) (Chang & Fisher, 2003). Since its initial development, this instrument has been used to study a range of learning environments and this chapter presents the findings of two example case-studies that involve such environments.

scholarly journals Closed sequential pattern mining for sitemap generation

2020 ◽  
Author(s):  
Michelangelo Ceci ◽  
Pasqua Fabiana Lanotte
Keyword(s):  
Web Site ◽  
Pattern Mining ◽  
Sequential Pattern Mining ◽  
Design Concept ◽  
Sequential Pattern ◽  
Website Design ◽  
Web Graph ◽  
Textual Content ◽  
Website Content ◽  
The Web

Abstract A sitemap represents an explicit specification of the design concept and knowledge organization of a website and is therefore considered as the website’s basic ontology. It not only presents the main usage flows for users, but also hierarchically organizes concepts of the website. Typically, sitemaps are defined by webmasters in the very early stages of the website design. However, during their life websites significantly change their structure, their content and their possible navigation paths. Even if this is not the case, webmasters can fail to either define sitemaps that reflect the actual website content or, vice versa, to define the actual organization of pages and links which do not reflect the intended organization of the content coded in the sitemaps. In this paper we propose an approach which automatically generates sitemaps. Contrary to other approaches proposed in the literature, which mainly generate sitemaps from the textual content of the pages, in this work sitemaps are generated by analyzing the Web graph of a website. This allows us to: i) automatically generate a sitemap on the basis of possible navigation paths, ii) compare the generated sitemaps with either the sitemap provided by the Web designer or with the intended sitemap of the website and, consequently, iii) plan possible website re-organization. The solution we propose is based on closed frequent sequence extraction and only concentrates on hyperlinks organized in “Web lists”, which are logical lists embedded in the pages. These “Web lists” are typically used for supporting users in Web site navigation and they include menus, navbars and content tables. Experiments performed on three real datasets show that the extracted sitemaps are much more similar to those defined by website curators than those obtained by competitor algorithms.

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