学生データを利活用した大学院教育の質保証に関する一考察

24
1)
1)
3127
2)
2)
2010
2014
institutional research
A Study for Quality Assurance of Graduate Education using Student Data
Through constructing the Integrated Database of Education and Student Learning
Toru HAYASHI1)
Shinobu HASEGAWA2)
1) Center for the Promotion of Higher Education, Yamaguchi University
2) Research Center for
Advanced Computing Infrastructure, JAIST
Abstract: Japan Advanced Institute of Science and Technology (JAIST) had accepted governmental funding project
“Quality Assurance for Graduate Education with International Coherence” from 2010 to 2014. We have constructed the
integrated database of education and student learning for analysis of graduate education. At the viewpoint of enrollment
management, this database covers huge data of education and student learning for the analysis of curriculum
development and student engagement. Although some examples of such database on undergraduate education have
already been conducted, our challenge will become a leading case on graduate education. As JAIST has an advanced
and systematic educational system focusing on coursework, this database will become useful to improve curriculum
development and student engagement. This paper describes the approach and process to construct the database, and
suggests the rough results and perspectives concerning data analysis.
(Keywords: institutional research, graduate education, quality assurance, data integration and analysis)
1.
1)
10
24
3127
2)
2.1
IR
IR
IR
3)
6)
3
IR
IR
7)
IR
2004
Fact
Book
8)
4)
IR
9)
2010
2010
2014
2009
GP
4
IR
10)
26
5)
11)
2010
2.
12)
11
24
3127
13)
5
3
GP
IR
EM
EM
3
2.2
(1)
EM
(2)
IR
BI
Business
Intelligence
12
24
3127
(3)
2.3
(4)
2000
(5)
Q1
2000
Q2
Q3 2000
Q4 2000
10
Q5
1
Q6
Q7
10
IR
13
24
3127
392
3.1
1
2
(1)
CSV
Excel
(2)
(3)
3DES
FTPS
3.
Xeon X7350 (2.93GHz) ×2
2
14
24
64GB 73GB
X2 (RAID1)
CPU1
4GB
3127
3.2
2
2.2
(1)
(2)
Interstage Information Storage v.10.0 (IIS)
IIS
(3)
CSV
(4)
(5)
5
7
13
CSV
1
1
SQL Server 2008 R2 Standard
Interstage Information Integrator v.10.1 (III)
SharePoint Server 2010 (SPS)
III
IIS
III
CSV
CPU
CPU 4
3.3
8GB
1 A
1 1
3
IIS
SQL
1
G
24
3127
GPA
37
2
72 80
1
1
1
3
2
4
3.4
1
5
SharePoint Server 2010
5
1
4
7
5
2011
4
1
16
24
3127
2012
4
4.1
5
000
100
200
400
4.
600
2.2
6 7 8
5
1 1
2
5
17
1 2
2 1
9
2 2
2
24
3127
6
6
6
4.2
2008
M
14)
M
6
2
M
7
2
5
(3)
1
24
3127
100
(1)
(2)
600
400
200
4.3
100
000
(5)
7
8
7
200
1
1
3
8
19
2
3
2
4
4
24
3127
SQL
1
9
1
1
10
IR
1
300 400
10 20MB
SharePoint
1/3
SQL
1/2
9
5.
4.4
2000
2010
4,746
1
7
8
50
200MB
20
24
3127
2.2
2015
1
1)
IR
3.4
, 2011
2)
IR
,
,10, 29-36,
2011
3)
, IR
,
,
, 15-98,
2012
4)
IR
, 31, 1, 19-27, 2014
5)
:
26
6)
IR
, 2015
, IDE
, 528, 4-12, 2011
7)
,
15)
, 1, 69-77,
2013
8)
,
20
,
21
24
2009
9)
IR,
IDE
10)
, 528, 43-47, 2011
IR
,
http://www.irnw.jp/, (2015
11)
12
28
)
21
,
http://www.kuins.ac.jp/kuinsHP/extension/
renkei09/index.html, 2015 12 28 )
12)
, Between, 2-3
8-9, 2012
13)
, CGEI
2011,
, 23-27, 2012
14)
JAIST
2012, 10, 2012
15)
,
2012, http://www.mext.go.jp/b_menu/shingi/
chukyo/chukyo0/toushin/1325047.htm,
2015 12 28 )
22
3127