Do different instructional styles affect students' learning on summer assignments?

Abstract

Summer vacation is considered a cause of loss in students' learning performance. In this study, we investigated the differences in learning behaviors in reading learning materials and time-related behavior patterns regarding summer assignments among three classes under different instructional styles. The results showed that students' learning behaviors in summer were correlated with instructional styles in school.

Full text

Do different instructional styles affect students’ learning on summer assignments?
Li Chen
Graduate School of Human-Environment Studies
Kyushu University
Fukuoka, Japan
chenli@mark-lab.net
Yufan Xu
Graduate School of Human-Environment Studies
Kyushu University
Fukuoka, Japan
xuyufan@mark-lab.net
Xuewang Geng
Graduate School of Human-Environment Studies
Kyushu University
Fukuoka, Japan
geng@mark-lab.net
Hiroaki Ogata
Academic Center for Computing and Media Studies
Kyoto University
Kyoto, Japan
hiroaki.ogata@gmail.com
Atsushi Shimada
Faculty of Information Science & Electrical
Engineering
Kyushu University
Fukuoka, Japan
atsushi@ait.kyushu-u.ac.jp
Masanori Yamada
Faculty of Arts and Science
Kyushu University
Fukuoka, Japan
mark@mark-lab.net
Abstract—Summer vacation is considered a cause of loss in
students’ learning performance. In this study, we investigated
the differences in learning behaviors in reading learning
materials and time-related behavior patterns regarding
summer assignments among three classes under different
instructional styles. The results showed that students’ learning
behaviors in summer were correlated with instructional styles
in school.
Keywords--self-regulated learning; time management;
learning behaviors; vacation assignments
I. INTRODUCTION
Different from learning at school, students’ learning
during the vacation time is not that intensive and
concentrated. Thus, it is indicated that vacations affect
mathematics learning negatively because it mostly occurs in
school time and vacations may interrupt students’ learning
rhythm and stop providing students with the opportunities to
practice [1]. In some occasions, summer learning loss could
even reach almost one month of instruction [2]. According to
Mccombs et al. [3], students' performance or skills
deteriorate rapidly over time if practice or other
reinforcement is lacking, but the rate of decay varies by task
or skill, that is, decay would become slower if provided tasks
are continuous with cues or time requirements. Therefore, in
order to reduce summer learning loss, it is necessary to
attach importance to instruction or practice during summer
vacation.
However, since students conduct their learning
autonomously without any monitoring and management by
instructors during their summer vacation, students have to
regulate their learning effectively. Self-regulated learning
(SRL) is an important construct of learning that includes
cognitive, metacognitive, motivational and behavioral
aspects in learning processes [4]. It is considered an effective
way to enhance students' learning motivation and reflect on
their learning process [5].
As one of the key aspects of SRL, time management was
correlated with students’ time-related learning behaviors and
can be used to understand the extent to which students’
procrastination affects their academic work [6][7]. In the
online learning environment, it is possible to collect
educational data related to students’ learning and analyze
these data to predict learning outcomes, inform instructors
and learners with the final purpose for improving learning
environment by a learning analytics (LA) approach [8].
Therefore, this study aimed to investigate the differences in
students’ learning behaviors in summer learning, and
students’ time-related learning behaviors patterns in summer
learning among three classes with different instructional
styles.
II. METHODOLOGY
A. Participants and the experimental classes
This study was conducted in three mathematics classes in
a senior high school in Japan. The participants were 80 tenth-
grade students. Students are divided into three mathematics
classes by proficiency level (the proficiency level of students
in Class 1 is higher than that of students in other two classes,
Class 2 and 3), and the three classes were instructed by three
different teachers with different instructional styles.
Specifically, the teacher in Class 1, who prefers the
traditional instructional design, mainly used print textbooks
rather than digital materials readers during the lessons. In
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2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT)
2161-377X/20/$31.00 ©2020 IEEE
DOI 10.1109/ICALT49669.2020.00053

Class 1, the main instructional style was the lecture. The
teacher in Class 2 is more willing to accept new technology
and mainly uses e-textbooks (the same content as the print
textbooks). In Class 2, the main instructional style was the
lecture as in Class 1. The teacher in Class 3 also mainly uses
print textbooks, but this teacher prefers delivering paper-
based assignments and explanations through the digital
devices (i.e., using airdrop through iPad). In Class 3, the
teacher had set a large amount of time for students’ group
discussion and exercises.
B. Design and procedure
This study examined how the students did the summer
vacation assignments and what their behavior patterns were
during the vacation time, both of which were strongly related
with students’ self-regulated awareness. The duration of this
study was one month from 19th July to 20th August, 2019.
During the summer vacation, students were asked to learn
the provided mathematics materials and to finish the
questions on them. The contents of the learning materials for
summer vacation were distributed on the BookRoll system
(digital materials reader system). Students can use some
functional tools on BookRoll while reading these digital
materials. For example, the Annotation function to add
annotations, Marker function to highlight the contents [9].
All the learning logs of operating these functional tools on
BookRoll were collected to represent students’ reading
processes. After reading and learning the provided materials,
students were also expected, but not mandated, to complete
the assignment on the related contents.
C. Data collection and analysis
In this study, 8 types of basic learning logs on BookRoll
during the whole summer vacation were collected and listed
as following. However, Del_An was not analyzed in this
study since the number was zero.
• Next/Prev: turning to the next/ previous page
• Add_An/Del_An: adding/deleting annotations
• Add_Bm/Del_Bm: adding/deleting bookmark
• Add_Mk / Del_Mk: adding/deleting markers
As for the data analysis, first, a one-way Analysis of
Variance (ANOVA) was conducted to compare the
difference of learning logs during summer vacation among
three mathematics classes. Then post-hoc analysis was
conducted to compare the differences between each pair of
groups on variables which was found significant differences.
III. RESULTS AND DISCUSSION
A. Differences in learning behaviors among three
mathematics classes
To examine whether the learning behaviors of students’
reading on BookRoll showed significant differences among
the three mathematics classes, ANOVA was conducted.
According to the results, significant differences were found
at the p<.05 level in Next and Prev among three performance
groups. To compare the differences between each pair of
three classes, post-hoc analysis using Tukey's Test was
conducted. The results are shown in Ta bl e I . The results of
post-hoc analysis using Tukey’s test indicated that the mean
score of Next variable for Class 1 was significantly lower
than that for Class 2 and Class 3 respectively. The mean
score of Prev variable for Class 1 was also significantly
lower than Class 3; however, Class 2 did not significantly
differ from the other two classes. It means that students in
Class 1, who have the highest proficiency level among the
three classes, viewed the mathematics learning materials on
BookRoll as their summer vacation assignments least
frequently. Class 3 students also showed more frequent
behaviors of turning to the previous pages than students in
Class 1, indicating their learning strategy of rehearsal, which
means repeating the reading of learning materials in this
research [10]. According to Berger and Karabenick [11], the
value and cost that mathematics students felt would affect
their use of rehearsal strategy positively. However,
significant difference was not found in the behaviors of using
functional tools among the three classes. Since using
rehearsal strategy with functional tools was more effective
during collaboration rather than individual work, it possibly
caused the lack of using such tools [12].
TABLE I. RESULTS OF ANOVA AMONG THREE CLASSES
Var i a b l e
Mean (SD)
F
p
Post-
hoc
Class 1
(n=32)
Class 2
(n=24)
Class 3
(n=24)
Next
1.34
(3.82)
78.50
(120.60)
90.54
(130.17)
7.149**
0.001
2>1*,
3>1**
Prev
0.03
(0.18)
34.42
(66.41)
43.63
(83.89)
4.417*
0.015
3>1*
Add_Mk
0.34
(1.95)
1.04
(4.10)
3.21
(12.30)
1.134
0.327
Add_An
0.00
(0.00)
0.04
(0.20)
0.00
(0.00)
1.172
0.315
Add_Bm
0.00
(0.00)
0.04
(0.20)
0.00
(0.00)
1.172
0.315
Del_Mk
0.06
(0.35)
0.46
(1.29)
0.71
(3.26)
0.800
0.453
Del_Bm
0.00
(0.00)
0.04
(0.20)
0.00
(0.00)
1.172
0.315
**p < .01, *p < .05
B. Different time-related behavior patterns of three classes
In order to examine what the time-related behavior
patterns of students’ reading on their summer assignments
are, we compared students’ daily operations on BookRoll
among the three classes during their summer vacation. In this
study, we compared the different behavior pattern of Next
and Prev, which showed significant differences among three
classes, and the pattern of Prev was similar to Next.
Concerning the Next behaviors (similar to Prev), students
in Class 1 have hardly ever accessed BookRoll during the
whole vacation time, while in Class 2 and Class 3, students
became active in accessing learning materials from about last
week of the vacation. The teacher in Class 1 rarely used
digital materials readers during his lessons, and he also
preferred the traditional paper-based way of assignment
submission. Thus, students in Class 1 also tended to be more
unwilling to use BookRoll to deal with their summer
vacation assignments. The teachers in Class 2 and Class 3
usually asked students to upload their daily assignments
during the school time; therefore, students in these two
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classes seem to have formed the habit of uploading their
assignments for teachers’ real-time check. When solving
problems, students with higher proficiency level were
considered to pay more attention to more complex cognitive
processes, than those with lower proficiency level [13].
However, in this study, the easy contents of the materials
might inhibit the motivation for higher proficiency level
students.
As for the type of behaviors in an e-learning environment,
students in Class 2 can be considered as procrastination
behavior type because they waited to deal with tasks or
assignments until the last moment before the deadline, and
whether this type of behavior can be seen as effective or not,
depends on the completion of the provided tasks [14].
Compared with Class 2, students in Class 3 showed better
learning habits while doing summer assignments, an action
which is considered be related with usual delivery way of
learning resources. Thus, it can be inferred that students were
more likely to access to e-learning materials out of class, if
they were used to using their own device to view the
materials from the teacher.
Figure 1. Daily operations of Next on BookRoll system of three classes
IV. CONCLUSIONS AND LIMITATIONS
In this study, we investigated the differences in behaviors
and time-related behavior patterns in how students fulfill
summer assignments among three classes under different
instructional styles. The results showed that students who
used digital materials readers in their usual learning, tended
to access summer vacation e-learning materials more
frequently than paper-based learners did. Also, students’
procrastination learning type was found in most students.
Based on the results, some implications were provided on
the way to assign summer assignments. Since students’
behaviors during summer vacation were related to the means
of delivery and submission of usual assignments in school, it
is suggested that teachers should consider the consistency of
approach when designing summer assignments in and out of
class. Moreover, since students with better learning habits in
an e-learning environment showed higher learning
performance than the procrastination learning type [14], it is
also suggested that teachers help student try to overcome
procrastination by instructional strategies, for example,
maintaining and enhancing students’ se lf-awareness.
However, in this study, students’ summer vacation
assignments were not assessed to see the completion of
assignments, which should be our future work. Moreover,
the difference in students’ performance levels should also be
considered in the analytics.
ACKNOWLEDGMENT
We would like to thank Ms. Satomi Hamada for her
contribution to this research. This research was supported in
part by JSPS KAKENHI JP19H01716, JST AIP Grant No.
JPMJCR19U1, and Cross-Ministerial Strategic Innovation
Promotion Program from Cabinet Office.
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