The IAFOR Journal of Education

Volume 1 - Issue 1 - Spring 2013

Practical Consideration of Pair Problem Solving in Computer Literacy
Education
Yoshihiko Oya
Kimiko Uchida

Authors’ Note
This study received financial support from 2008 to 2009 scientific research grants anda Grant-in-Aid© for Scientific Research (Issue Number: 20500816).

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Abstract
Direct instruction to students enrolled in a computer literacy program at theundergraduate level frequently involves difficulties due to varied knowledge levels
and skills among the students, as well as an increase in the number of unmotivatedstudents. An available solution is the pair problem solving approach which can prove
to be effective as an effective method. This report shares the findings of aninvestigation regarding the efficacy of pair problem solving, as compared toindividual problem solving in computer literacy education. Furthermore, the paired
approach analysis was able to extract specific criteria for successful pairs. The
research, which included two (paired and individual) 15-minute practicalexaminations and questionnaires, a test on basic scholastic ability, and a survey on PC
experiences, was conducted with approximately 280 students from three universities
who were enrolled in a computer literacy program in 2008 and 2009. The results
reveal that the overall scores of the pairs exceeded those of the individuals. Moreover,more than 90% of students found pair problem solving to be a positive experience.
From the viewpoint of learning effectiveness, it is worth mentioning that the mosteffective pair combinations included those with a small difference in basic academic
ability, a large difference in PC experience, and a partner of the opposite sex.
Keywords: pair problem solving, computer literacy

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Introduction
With the advent of declining university enrollments, university instructions are
becoming difficult to be followed because of different cognitive and behavioral
characteristics observed in students, such as lower academic ability and intellectual
curiosity (Figure 1).
The skills needed to operate a computer have diversified and the computer literacy
gap has expanded.
Because of this, there have been arguments for the necessity to strictly review
educational content and methodology particularly for computer literacy education(Murakami et al., 2008). Given the current situation, interactive and participatory
approaches for effective instructions that focus on the student have been taking place.
It has been reported that cooperative learning is very effective in research and inpractice, particularly for pairs and small groups. Therefore, the expectations fromthese methods are increasing (Yasunaga, 2008, Tachibana et al., 2010).

Problems of University
Computer Literacy
Education

Possibility of Pair
Learning Approach

Gap in info rmatio ne ducatio n amo ng H igh
Scho o ls.

Dive rsificatio n in PC
o pe rating skills.

Since pair pro ble m so lving
is e ffe ctive whe n the re are
varying le ve ls o f abilitie s,
it is e ffe ctive in addre ssing
the lite racy gap.

De cre ase in stude nts'
acade mic abilitie s andinte lle ctual curio sity.

Gre ate r co mpute r lite racy
gap at the time o f e nro llingin a unive rsity.

It is po ssible to imple me nt
this appro ach witho ut
affe cting the numbe r o f
stude nts o r te ache rs.

Current Status ofUniversity Education

Atte nuatio n o f stude nts'
se nse o f purpo se andpassive class attitude .

Le arning thro ugh a
traditio nal class appro ach isdifficult.
( tr aditio n al appr o ac h = o n e te ac h e r
te ac h in g all stu de n ts at o n c e )Figure 1 Background of research

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Acco mmo date s stude nts
ne e ds with a classstructure that fo cuse s o nmutual inte ractio ns o f
le arne rs.

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The effects of the pair approach within information education suggest possibilities,
such as encouraging information literacy, and stimulating students’ desire to learn,(Takahashi et al., 2004) as well as improving their ability to complete tasks, solve
problems, and learn independently (Terakawa et al., 2005). On the other hand, there
are indications that depending on the pair combination, there may not always be aneffect on learning or that there might be issues with developing methods to form
effective pairs (Kaneko et al., 2007, Takahashi et al., 2010). However, regardless ofthe numerous reports on the subject, there is a lack of understanding of pair
combinations or combination criteria because there are few studies that deal with thisissue. Keeping this in mind, the authors of this study introduced a pair approach into
university computer literacy education in 2008. They examined the effectiveness of
this approach by comparing individual problem solving with pair cooperative problem
solving and verifying the effects pair combinations have on the results. Thus far, it isevident that pair cooperative problem solving improved the overall task achievementlevel and was particularly effective for students with lower grades and with mixedgender pairs (Uchida et al., 2010). The students’ assessment of pair learning was high,indicating that this method was effective in meeting students’ needs (Uchida et al.,2010). However, this method also has certain disadvantages such as striking
differences observed between pair results and either no or negative effects withcertain pair combinations.

This study first reports the problem solving results with pairs from a pair combination
criteria perspective based on the results of pair solving approach in class, conductedfrom 2008 to 2009. It also focuses on the problem-solving process as an index forlearners’ awareness toward working as pairs as well as the quantitative changes in

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Volume 1 - Issue 1 - Spring 2013utterances among pairs, as a means to examine the issues of problem solving for
selected pairs. Finally, the study considers the pair learning effect from the amount ofutterances and survey results to determine how cooperative problem solving iseffective through conversation and student trends.

Methodology
The subjects of this study were enrolled in a computer literacy program in 3
departments of 2 private universities in Aichi Prefecture. A total of 7 classes and 280
students participated each year for 2008 and 2009. In April, students were surveyed
on pair combination criteria and in July, experimental classes were held for pairtesting (Figure 2).
April

Survey pair composition
basicsApril -June

Classes using traditional
approach (one teacher
teaches all students at once)

Basic acade mic ability surve y
Surve y re garding PC e xpe rie nce

Co mpute r lite racy practical le sso ns

De te rmine pairs rando mly

July

Test classes for pair work

Te st 1 （individually ）15 minute s

Fre e co nve rsatio n
5 minute s

Fre e co nve rsatio n
5 minute s

Te st 1 （in pairs ） 　15 minute s

Te st 2  　（in pairs ） 　15 minute s

Te st 2 （individually ）15 minute s

Que stio nnaire Surve yFigure 2 Outline of the study

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Pair Combination Criteria
In 2008, students were surveyed on their basic academic ability, computer experience,
interest in computers, and typing speed in order to gain basic data regarding the pair
combination criteria. Of these four criteria, a prior study has acknowledged therelationship between basic academic ability and scholastic performance of students
after enrolling in university, adapting to university education, and scores in thenational exams. Three other items reflected computer literacy before university,
which is the basic premise for computer literacy education, and were included
because objective data on them is relatively easy to obtain.

Given the results of 2008, the 2009 survey focused on 2 indicators; basic academic
ability, which implied involvement in problem solving and performance in pairs, andcomputer experience before university.

The basic academic ability survey consisted of 20 math and kanji (Japanese character)problems and used an adjusted difficulty level so that performance would
approximate a normal distribution. Math problems were composed of basic mathproblems developed to measure university students’ academic abilities. Kanji
problems referenced the kanji test that measures basic Japanese ability. The survey
lasted 20 minutes and surveys were collected individually for each participant.

The survey on computer experience before university had 20 multiple-choicequestions about the Internet, software, and computer usage inside and outside theschool. In the 2008 survey, there were few questions and the multiple choice answers
varied based on the question. The 2009 survey improved on these two issues. The

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survey time lasted 5 minutes and surveys were collected individually for eachparticipant.

Pair Problem Solving
After 8–10 practical computer literacy classes, students were tested (Test 1 and Test
2) individually and in pairs for 15 minutes (22 questions) based on word-processing
proficiency. Pair groupings were randomly selected to determine the effect of pair
combination criteria. Then, students in each department were divided without bias perclass. Approximately half of the students took Test 1 individually followed by Test 2
in pairs. The remainder of the class took Test 1 in pairs followed by Test 2
individually. In each of the divided groups, almost all students were in the same yearof school and from the same academic discipline. Since one teacher taught the samematerial to both groups, the difference between the groups is presumed to be
negligible. During the test, students solved problems in pairs and individually, and theresults were collected individually for each participant. According to preliminary
investigation, the dispersion for Test 1 and Test 2 was set to a certain level adjusting
the difficulty level so that the average variance of correct responses differed by 15 to
20 percent. Furthermore, in order to eliminate the issues with testing order in 2009
and 2008, the tests were conducted in the reverse order (switching Test 1 and Test 2).

Before the pair test, students were given five minutes for free conversation to develop
smooth communication for each pair’s first encounter. Twenty minutes of
conversation was recorded from the time free conversation began to the end of thepair test. After the test, the students took a survey about their method of problem
solving in pairs. The 2009 survey improved upon the issues with multiple choice109

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Volume 1 - Issue 1 - Spring 2013expressions that were apparent during the 2008 study. The survey time lasted 5
minutes and surveys were collected individually for each participant.

Analysis of Results
The analysis of the results employed a standard deviation as a standardized score tocomparatively examine the values from Test 1, Test 2, basic academic ability, andcomputer experience. The amount of utterance was determined by converting theconversations recorded during the pair tests into text. The number of times students
spoke was treated as the amount of utterances and the number of characters wastreated as the utterance character count. The analysis of the pair results used in thisstudy consists of the values that were calculated by subtracting the individual testscores (standard deviation) from each subject’s pair test scores (standard deviation),
added according to pairs.

Results and Interpretation
OutlineLooking at the results from the individual and pair practical tests 1 and 2, the pairtests (average standard deviation: 50.65 in 2008 and 51.62 in 2009) surpassed thescores from the individual test (average standard deviation: 49.34 in 2008 and 48.36
in 2009) (ρ = 0.0015 for 2008 and ρ = 0.0001 for 2009). As an overall trend, thisindicates that the task achievement level improves through pair problem solving.
However, from an individual perspective, there was either no difference between thepair and individual results or the pair results were negative for close to 40% of
students. On examining the relationship between pair and individual tests, trends wereindicated in which pair problem solving had relatively less effect for students who

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scored high in the individual test, while students who scored lower improved (Figure3). Previous research has also extrapolated that working in pairs is more effective forstudents

with

lower

40

grades.
y = -0.5658x + 29.643
R² = 0.3657

30

Pair Results

20

10
0
0

10

20

30

40

50

60

70

80

t value

 　 　ρ

-10
-20
-30

Individual Scores

Figure 3 Individual scores and pair results
Criteria for Pair Combination
Table 1

Pair Com bination
Criteria

Pair Results and Pair Combination Criteria

H （High Pair Results ） L （Low Pair Results ）
 　 　ｎ

 　 　m

 　 　s.d.

 　 　m 　 　s.d.

Basic Academ ic
Ability Difference

92

8.85

6.24

36 14.45

8.29

3. 63

0. 001 * *Difference in PC
Experience

92

8.88

6.81

36

6.86

1. 26

0. 211

 　 　ｎ

7.17

* * ρ<. 01

As for the criteria for pair combination, analysis was conducted for two indicators
suggested to be effective in the 2008 study, computer experience before university
and basic academic ability (Table 1). Group H with a pair score above +10 and GroupL with a score below −10 were selected in order to examine the characteristics of the111

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Volume 1 - Issue 1 - Spring 2013pair learning effect. A comparison of groups H and L indicated that the basic
academic ability gap was small. The reason for this is that the gap in basic academic
ability reflects the level of high school that students came from, the academic
discipline, desire to learn, and class attitude. It is possible that these disparities affectthe amount and quality of communication in pair testing. On the other hand, trends
indicated that the gap in computer experience was greater in Group H and lesser inGroup L, although the difference between the two was insignificant. The idea was thatstudents with richer experience taught the students who lacked experience, which
made the pairs more effective. However, the hypothesis is that for pairs with a lower
computer experience, students would get stuck or need help in the same places, andalthough they consulted each other, they could not solve the problems.
Table 2 Pair Results by Gender and Amount of Conversational Utterance

Pair Results

Amount ofConversational
Utterance

same

0.85

2138.3

mixed

6.3

2114.8same

1.68

2200.1

mixed

4.3

2127.4

Pair Gender

Male

FemaleIn addition to the two indicators—basic academic ability and computer experience
before university—it was clear that gender was a factor in problem solving andperformance. Males uttered less overall and male gender pairs were less effective,
while mixed-gender pairs were more effective (Table 2). On the other hand, females
overall were more vocal, although the result was that females vocalized more withsame gender pairs as opposed to mixed-gender pairs. However, females achieved
greater results with mixed-gender pairs as opposed to same gender pairs. Furthermore,

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there was a high correlation between the amount of utterances and the pair resultswith females than with males. The outcome determined that mixed-gender pairs are
more effective, followed by female pairs with male pairs being the least effective.

From the above results, it can be concluded that the most effective pair combinations
have a small gap in basic academic ability, a large gap in computer experience, and apartner of the opposite sex.

Pair Learning Effect and the Amount of Utterances
The vocal data (roughly 100 per year) collected during the pair test was converted
into text. The conversation was analyzed by the amount of utterances and thecharacter count of the utterance.

There was a strong correlation (r = 0.98, y = 19.3x) between the amount of utterances
and utterance character count. The average number of times students uttered during
the 15 minute, 22 question (Q1–Q22) pair test was 106.0 and the average utterance
character count was 2107. In other words, it was evident that there were 7
conversational exchanges every minute and they spoke roughly 20 characters at atime. Moreover, depending on each pair, the utterance character count wasdisproportionate (highest was 4733 characters and lowest was 83 characters) and there
was a large difference between the test results. Examination of the relationshipbetween the overall utterance and pair results showed that vocal pairs were more
effective (Figure 4, r = 0.42).

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Looking at utterances for each question, there was more utterance for Q2 (insert apage number in the center of footer) in Test 2, which had a character count of 342,
than Q9 (create an autoshape, and insert characters) in Test 1, which had a charactercount of 188. From these results, we can conclude that depending on the pair, there
was a communication gap and a significant increase in utterances for problems withfunctions including a lot of steps or functions that were used less frequently during
the class.

Looking at the changes in utterances over time, utterances increased in the latter halfof Test 1, which had a higher average score, and the utterance was particularly highfor Q13–Q18. In contrast, Test 2 had higher utterances for Q1–Q11 with significant
reduction in the latter half. Furthermore, there was a difference between Test 1 andTest 2 for the pair learning effect by problem.

30

y = 0.0687x - 3.427
R² = 0.17767

Pair Results

20
10
0
0

50

100

150

200

250

300

350

400

-10
-20
-30

Amount of Verbal Communication

Figure 4 Relationship between pair results and amount of conversational utterance

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Pair Results

20
10
0

-10

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Q No.

-20
-30

Figure 5 Pair results by each question（● –Test1 ○ –Test2）

While it was more effective in questions Q13–Q18 for Test 1, Test 2 indicatednegative values for Q16–Q21, which was lower than individual scores (Figure 5).
Compared to Test 1, the difficulty level for Test 2 was slightly higher. This led
students to spend more time communicating during the pair test, leaving less time forthem to solve problems in the latter half of the test.

As demonstrated above, the amount of utterances changed during problem solving foreach pair depending on the difficulty level of the problem and their time management
skills, suggesting that it impacted the positive effect of working in pairs.

Learner Awareness for the Pair Test
Judging from the results of the survey conducted after the pair test, a relationshipbetween the effectiveness of pairs and a trend toward awareness of the pair test wasconsidered. In 2008, the survey included 10 items in 2008, whereas it comprised 11
items in 2009.

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Table 3

Volume 1 - Issue 1 - Spring 2013

Survey Items with Significant Differences from Pair Results
Survey Item

Pair Result

ｎ

m

H

174

2.41

L

86

1.99

H

174

2.54

L

86

2.25

H

98

2.33

L

42

2.66

H

76

0.28

L

44

0.07

H

174

2.69

L

86

2.52

Easier to solve as a pair than individually

Consulted during the pair test

A free conversation time before the pair testis necessary

There was sufficient time for the pair test

Communication during the pair test was usefulρJudgement

0.0001**0.0017**0.0028**0.0053**0.0174*

Analysis of the significant difference between Group H, which was highly effective interms of the pair learning effect, and Group L, which was less effective, wasconducted with respect to these questionnaire items. The results of the common items
from 2008 and 2009 were totaled together.

First, Table 3 shows the items that pointed the significant differences. These results
infer a willingness to solve problems cooperatively and communicate with each other,and whether or not they had sufficient time determined how effective pair learningwas. As such, a positive attitude and increasing participation awareness of cooperative
problem solving, expanding the ability to communicate, and improving time
management skills are essential to promoting effective pairs.

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We can interpret from the survey items (Table 4) where there was no significant
difference between confidence in the class and students’ interest toward computers,
and these items are unrelated to the effect. Free conversation time beforehand, the pairtesting evaluation, and students’ interactions that were high across the board, areuseful suggestions for setting up pair approach classes.

Table 4

Survey Items with No Significant Difference with Pair Results
Survey Item

Pair Result

ｎ

m

H

76

1.47

L

44

1.41

H

98

2.72

L

42

2.66

H

98

2.65

L

42

2.60

H

76

1.82

L

44

1.72

H

98

2.50

L

42

2.60

Pair works were easy to understandρ

0.3193

Free conversation time was sufficient

0.2808Pair work approach works well0.2677

Interest in computers

0.2673

Friendly interaction with partner

0.2096

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Judgement

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Conclusion
The results from the two-year experimental classes with pair testing provided thefollowing findings within computer literacy education at university.
1) Pair problem solving was higher than individual problem solving and it confirmedthat pair task achievement was higher overall. On the other hand, from anindividual perspective, working in pairs was ineffective or less effective for nearly
40% students.
2) The study inferred that the combination of criteria such as mixed-gender pairs withsimilar academic ability and differing computer experience was highly effective.
3) The study discovered characteristics such as a greater discrepancy in the amount ofutterances for certain pairs and remarkable increase in utterances for questions
involving functions with more process steps or functions that were used lessfrequently in class.
4) Amount of utterances changed depending on the difficulty level of the problem ortheir time management skills, indicating an impact on the effect of working inpairs.
5) The study suggested that it is possible to improve pair learning results byimproving students’ participation awareness and positive attitude toward
cooperative learning, as well as improving their ability to communicate and time
management skills.

Further detailed analysis of the issues related to the pair learning approach will be
conducted to resolve factors that affect the positive effect of pair learning. In addition,
this study captured the pair learning effect through short-term experimental classes
and consideration of further long-term application is necessary.

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References
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Murakami, H., Yamasaki, H., & Terada, Y. (2008). An inspection of skills of acomputer and a literacy education for freshmen. IEICE Technical Report. 108(88), 1-8 (in Japanese).
Takahashi, K., & Shintani, K. (2004). Study of cooperative learning which values
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Tachibana, H., & Fujimura, N. (2010). Knowledge Integration Through Collaborative
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Uchida, K., & Oya, Y. (2010). Conversation Characteristics in Paired Learning at
Computer Literacy Education. Forum on Information Technology 2010, 649650 (in Japanese).

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Yasunaga, S. (2008). Classroom Reform in Higher Education －A Review of the Useof Cooperative Learning. Annual Report of Educational Psychology in Japan,
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