MoodleC

Moodle

Text Mining Analysis of Career Planning Documents Created by My Students

Kazushige IKUTALiberal Arts, Tokushima Bunri University

Abstract: A learning support website was constructed using Moodle in 2012 and has been used in my classroom. The students in my classes can experience student-based and cooperative activities on the Moodle website. In a class called “Information Communication C,” the students can improve their writing proficiency in Japanese by enjoying making letters to a newspaper and career planning documents. This paper provides the results of the text mining analysis of career planning documents created by my students. The results indicate that the graphs of word co-occurrence networks and correspondence analyses contribute to comprehending what my students are thinking. I want to accumulate the visual information and exploit it in mentoring. (Key words: higher education, career planning, mentoring, text mining, moodle)

1 Moodle 2

2013Moodle

C

Moodle

3

MoodleWord

4

CWord

Moodle3 5 10

28Word

− 71 −

KHCoder 5

KH Coder6

7

8

R 9

Jaccard 10

Word Cloud Word Cloud

KHCoder

R Jockers 11

3.����

281

22 Jaccard

0.1

� � �������

� 2 �������������

3 7 Case3Jaccard

446 116513 41

Case 19 Case 24

Case 24 165

136

8 6 Case 24

− 72 −

− 73 −

− 74 −

− 75 −

− 76 −

− 77 −

4 Case 10 7 Case 27600 20

3 Case 1Case 5 800

205 Case 13

Case 18 6 Case 20 Case 211000 40

8001000

800 1000Case 1 3

Word Cloud1

9Word Cloud 2

Case 1 10

11 12Word Cloud

� 9 ����������

� 10 Case 1 ���

� 11 Case 1 ��������

� 12 Case 1 � Word Cloud

− 78 −

3 Case 1

10

11

12Word Cloud

Word Cloud

JaccardKH Coder

Jaccard

JaccardCase 1

Jaccard 0.2 0.3 0.413

Jaccard0 1

− 79 −

3 Case 1 13Jaccard 0.1 0.2

24 0.1 0.2

Jaccard

13 Jaccard0.3

13Jaccard 0.4

13Jaccard

0.1

4.���������

201314

1

� 14 �����������������

2

3 4

15

� 15

5.����

Cyndi LauperTrue Colors

true colortrue color

− 80 −

1) Moodle

11 pp.125-135 20142) Rice, W., 2011, Moodle 2.0 E-Learning Course

Development, Birmingham, Packt Publishing3)

http://www.mext.go.jp/b_menu/shingi/chukyo/chukyo0/toushin/1325047.htm 2012.8.28 2013.2.14

4) 2007

5)

20146)

version 2.3.1 . NAIST TechnicalReport,

, 20037) R pp.87-91

20098) Danowski, J. A.: Network analysis of message

content, Progress in communication sciences, vol. 12, pp. 198-221, 1993

9) R Core Team, R: A language and environmentfor statistical computing, R Foundation for Sta

tistical Computing, Vienna, Austria, http://cran.r-project.org/doc/manuals/r-release/fullrefman.pdf,2014

10) Konchady, M., 2006, Text Mining Application Programming, pp.269-271, Boston, Charles River Media

11) Jockers, M. L., 2014, Text Analysis with R for Students of Literature, pp.150-151, Switzerland, Springer International Publishing

− 81 −