1 Graduate School, Tokyo Gakugei University (JAPAN)
2 Tokyo Gakugei University (JAPAN)
About this paper:
Appears in: INTED2022 Proceedings
Publication year: 2022
Pages: 9218-9225
ISBN: 978-84-09-37758-9
ISSN: 2340-1079
doi: 10.21125/inted.2022.2393
Conference name: 16th International Technology, Education and Development Conference
Dates: 7-8 March, 2022
Location: Online Conference
Learners should be able to enrich each other's knowledge, experience, and skills, find ways to solve problems, and create new knowledge through collaborative processes.

In other words, to create new knowledge, we require not only individual thinking but also cooperation and collaboration among learners. The idea is not just to share knowledge but to share it while utilizing the perspectives of others, and to develop human resources who can create new knowledge through the process of perceiving knowledge from multifaceted and multiple perspectives.

The purpose of this study is to support knowledge sharing among learners in a community by utilizing their multifaceted and multiple perspectives. In this study, we focus on the titles of Web articles shared by learners and first try to visualize the learners' interests and concerns by feature words using KH Coder, a software application for quantitative analysis of text data. A feature word is a word that represents meaningful information or features found in text data by means of text analytics. We visualize learners' interests and concerns by using the top ten feature words according to the Jaccard coefficient.

For this purpose, we simulated and evaluated the visualization of learners' interests and concerns using feature words extracted by text analytics, modeled a method for knowledge-sharing among learners, implemented it in the system, and developed a knowledge-sharing support system.

The functions of this system are as follows:
Function 1 Knowledge Accumulation: Learners enter the URL of the article along with their "awareness" and "knowledge gained", and the title is automatically stored.
Function 2 Display Feature Words: The feature words of each student extracted from the article URL title text are displayed.
Function 3 Various Searches: It is possible to search by keywords that interest the user among the feature words of each learner or by the registered name of each learner.
Function 4 Knowledge Sharing: Learners can share their submissions on the Web screen and can also click to view the article page.
Function 5 Mutual Reaction: Learners can respond to others' posts by responding "helpful" or entering comments.

We conducted a practice using the developed system to determine its effectiveness. Our findings showed that knowledge sharing using this system enabled participants to learn the characteristics of each other's acquired knowledge, to find others with whom they wanted to interact, and to create new ideas through knowledge sharing.

In addition, by learning about each other's interests and concerns, participants were able to learn not only about others with similar interests and concerns but also those with other ones in fields different from their own. In order to create new ideas, some learners felt it would be effective to collaborate with others who have interests and concerns in different fields from their own. This suggests that our system has the potential to help learners capture knowledge from multifaceted and multiple perspectives.

In the near future, we plan to expand our practice to communities that include unacquainted learners to further evaluate the system, and to clarify the process of capturing knowledge from multifaceted and multiple perspectives.
Knowledge sharing, text analytics, feature words, search function, community, computer supported collaborative learning.