Please listen to the presentation, read detailed slides and return to first post to make your comments below the corresponding paper author's post. Session Chair: Shun Okuhara Session Theme: Education and Support Session Number: 5 Paper No: 19 Session and Talk No: TS5-2 Type: Short Co-authors: Ryo Sugawara, Shun Okuhara and Yoshikazu Sato Title: Exploratory Study on Correlations between Students’ Characteristics and Effects in the Case of Online Learning on University Students

2. 1. Introduction
Since the early days of e-learning, the low completion rate has been identified as a
significant problem. For example, A topic by Johdan is included, which places the
average completion rate of massive online courses at only 4.6% [1]. A topic by Lewin at
only 6.5% [2] .
As pointed out by e-Learning Consortium Japan [3], "In the case of asynchronous
learning, there are cases where learning is not completed within the designed period or
learning is not performed at all if the pace of learning is left to the student's spontaneity.
To reduce the occurrence of incompletion and increase the rate of completion, it is
important for supervisors to encourage stu-dents with slow progress to proceed with
learning." Sugawara et al. [4, 5] have verified that such efforts are effective for raising
the rate of completion. While e-learning is supposed to be done voluntarily, a
mechanism for voluntary e-learning that enables the achievement of a high completion
rate has yet to be developed.
2
2020.11.25 WED

3. 1. Introduction
The failure to ensure spontaneous e-learning may not, in fact, be due to structural
problems in the e-learning system itself, but may rather be at-tributable to a gap
between the instructional design of materials provided by e-learning and the learning
characteristics (approaches to learning) of students. That is, if aptitude-intervention
interaction is not taken into account, students may drop out during the learning course,
or may exhibit low learning effects even if they complete the course.
In other words, as there is an interaction between learning characteristics and
intervention (instruction method or instructional design), and learning effects differ
depending on the combination of both, students with a characteristics that does not
match the specific e-learning intervention are considered not suitable for the
intervention.
3
2020.11.25 WED

4. 1. Introduction
4
As a case study, we investigated the learning characteristics of students who
scored well in a placement test (web test for allotting students to different difficulty
levels of e-learning) conducted as part of pre-enrollment education for University
A.
2020.11.25 WED

5. 5
TABLE1 Testing Environment and Number of Candidates
2. Method
Using the scores and learning histories (the number of logins to the e-learning
system) of students who took the placement test (hereinafter referred to as the
"test") for pre-enrollment education (Students study using the e-learning system
at home. In promoting e-learning, we present a model learning plan that clearly
shows the learning period in the class session before the course) conducted by
University A in fiscal years 2016 and 2017 (TABLE Ⅰ)
2020.11.25 WED

6. 6
2. Method
TABLE2 Classification of Approaches to Learning
We analyzed the correlation between the test score (we use the same test items,
and it is possible to compare with age) and the learning characteristics using
seven approaches to learning classified exploratory of each student (TABLE 2) [4,
5, 6, 7, 8].
2020.11.25 WED

7. 7
3. Learning Characteristics and Learning Effects in Students
TABLE3 Completion Rate in e-Learning for Different Approaches to Learning
2020.11.25 WED

8. 8
3. Learning Characteristics and Learning Effects in Students
TABLE4 Percentage of Placement Scores per Approaches to Learning (Fiscal 2016)
2020.11.25 WED

9. 9
3. Learning Characteristics and Learning Effects in Students
TABLE5 Percentage of Placement Scores per Approaches to Learning (Fiscal 2017)
2020.11.25 WED

10. 10
4. Discuttion
In this study, we hypothesized and verified a reason for the low
completion rate of students who took an e-learning course. As there is an
interaction between learning characteristics and e-learning interventions,
and learning effects differ depending on the combination of both, we
hypothesized that students with learning characteristics that do not match
the specific e-learning instructional design would not be suitable for the
instructional design.
Our results indicate that the completion rate and the achievement rate of
e-learning (indicating whether the student has finished the e-learning
assignments) depend greatly on the student's learning characteristics.
Students whose learning characteristics matched the specific e-learning
intervention exhibited positive learning effects, while students with
discrepancy in aptitude-intervention interaction may not have been suited to
the e-learning intervention.
2020.11.25 WED

11. 11
REFERENCES
[1] Jordan, K. MOOC Completion Rates:The Data, Available
at: http://www.katyjordan.com/MOOCproject.html
2013 [Accessed: 20/01/4].
[2] Lewin, T . One Course, 150,000 Students, Available
at: http://www.nytimes.com/2012/07/20/education/edlife/anant agarwal
discusses free online courses offered
by a harv ard mit partnership.html? ref=education, 2012 [Accessed:
20/01/9].
[3] Glossary of e-Learning Consortium Japan "Completion rate," 2017
(http://www.elc.or.jp/keyword/detail/id=115), in Japanese.
[4] Sugawara, R. "Change in the scholastic ability and learning pattern of
students who passed admissions
office and recommendation-based examinations: Based on the statistical
analysis of a placement test and
an end-of-course examination," Meisei (research bulletin of Meisei
Education Center, Meisei University)7:49-
56, 2017, in Japanese.
2020.11.25 WED

12. 12
REFERENCES
[5] Sugawara, R. et al., "Use of e-learning for improving the learning
characteristics and aca-demic ability of students who passed AO and
recommendation-based examinations,“ Research Report of JSET
Conferences, 17-1, 403-406, 2017, in Japanese.
[6] Meisei Education Center. " FY 2016 Pre-Enrollment Education Program
Implementation Report," Meisei (research bulletin of Meisei Education
Center, Meisei University)8:72-81, 2018, in Japanese.
[7] Meisei Education Center. " FY 2017 Pre-Enrollment Education Program
Implementation Report," Meisei (research bulletin of Meisei Education
Center, Meisei University)9:88-93, 2019, in Japanese.
[8] Education Administration Support, WAO CORPORATION CO.,LTD,
Available at http://edu.wao-corp.com/remedial/ [Accessed: 20/01/4].
2020.11.25 WED