Selected Papers of the 18th Conference of Pan-Pan Pacific Association of Applied Linguistics

A Longitudinal Study on Japanese University Students’
Motivational Styles Toward Learning English in CMC Activities
Satoshi Yoshida and Michiko Nakano

Faculty of Education and Integrated Arts and Sciences, Waseda University
syoshida@aoni.waseda.jp, nakanom@waseda.jp

Abstract
This paper shows a part of our longitudinal study on Japanese university students’ motivational styles towardlearning English in computer-mediated communication (CMC) activities. The purpose of this study is
two-fold: (1) to elucidate the students’ motivational styles toward the activities by clustering each of theindividual motivational predispositions and (2) to discuss ideal learning environments for the students basedon Self-Determination Theory (e.g., Deci & Ryan, 1985). To do so, we administered a questionnaire with 24
items, each of which was designed to assess the types of intrinsic motivation, extrinsic motivation andamotivation among the students participated in the activities. The data were subject to exploratory factor
analysis to examine the internal structures of motivation constructs and the resulting individual factor scores
were subject to cluster analysis to classify the types of motivational styles among the students. The results
indicated that there must be four types of motivational styles whereby we can divide the students into (1)autonomous learners, (2) learners motivated by introjection (3) relatively demotivated learners and (4)amotivated learners. On the basis of these findings, we discussed the potential problems behind the CMC
activities and proposed some motivating strategies for the students with reference to SDT.

Keywords
Motivational Styles, Intrinsic Motivation, Extrinsic Motivation, Amotivation, Computer-MediatedCommunication

1

Introduction

With the recent development of information and communication technology (ICT), now we can have easy
and affordable access to the Internet. The ubiquitous nature of the Internet access has provided substantive
benefits for us and changed our lives in many ways. For example, the technological development enables us
to enjoy a number of opportunities to communicate with people around the world. In fact, the advent ofeasy-to-use mobile devices such as smartphones and tablet computers has accelerated the use of video-phone
call, instant messenger and short message service whereby we can communicate with others in the context ofcomputer-mediated communication (CMC). The increasing use of these CMC services, each of which isoften incorporated into social networking service (SNS), is vividly illustrated by the fact that the number of
SNS users has rapidly increased year by year (Ministry of Internal Affairs and Communications, 2012). The
growing popularity of CMC services subsumed into SNS demonstrates the potentiality of such ICT-enabledcommunication for promoting one’s reciprocal interactions with others, as an alternative to ordinary
face-to-face communication. In this vein, CMC has attracted significant attention and thus, been currently
studied as an interdisciplinary research topic.
Within the realm of English language education, in particular, the popularity of ICT-enabledcommunication has drawn renewed attention in late years, and the effectiveness of CMC on learners’
language achievements has been frequently researched and discussed under the rubric of computer-assisted
language learning (CALL). Indeed, with the aid of CMC, people who learn English as a foreign language(henceforth, EFL learners) come to be able to not only practice speaking English as a foreign language withnative speakers of English but also to practice using English as a Lingua Franca (ELF) with various English
users with different first languages. Therefore, this sort of CALL learning environment is considered to havea great potential to benefit the EFL learners. As a result, a number of higher education facilities have23Selected Papers of the 18th Conference of Pan-Pan Pacific Association of Applied Linguistics
incorporated some of CALL activities into their curricula of foreign language education (for details, see
Stockwell, 2012). As such, CALL comes to be recognized as a currently challenging and appropriate method
for increasing learners’ exposure to quasi-authentic English communication and thereby enhancing theirEnglish proficiency. However, there still remain some problems to be solved. One of the crucial problems tobe solved is lack of learners’ motivation toward CALL activities (Stockwell, 2012). As Nakano (2006)
pointed out, unless learners have enough motivation toward CALL, they will never improve their English
proficiency in the given learning context.
Informed by the above discussion and with reference to the relevant motivation theory called
Self-Determination Theory (SDT; Deci & Ryan, 1985; Ryan & Deci, 2000b, 2002), we have been conducting
a longitudinal study among the tertiary-level Japanese EFL leaners with the aim to depict their motivational
styles toward CALL activities and to discuss the potential motivating strategies to enhance their motivation.
The target CALL activities that we have dealt with in our previous surveys are called CCDL CMC activities,
which include video-conferences and CMC chat sessions subsumed in a distance learning program called
Cross-Cultural Distance Learning (CCDL). In our previous surveys (Nakano & Yoshida, 2008; Nakano,
Yoshida, & Owada, 2008; Yoshida, 2010; Yoshida & Nakano, 2009, 2010), we found that, as Nakano (2006)
pointed out, the students who opted to participate in the activities were found to be autonomously motivatedwhereas those who were externally regulated to engage in the activities were highly likely to be demotivatedand some were found to be amotivated to do so. This finding implied the applicability of SDT framework forinvestigating the potential motivational problems behind the target CMC activities. Yoshida and Nakano(2013) further discussed the effect of class types (i.e., elective or compulsory) on the students’ motivational
predispositions toward the target CMC activities among 21 different English classes (n elective = 5; n compulsory =16). As a result, we found that autonomy-supportive nature of elective classes can be one of the key elements
to predict the students’ motivational dispositions; indeed, all the elective classes were categorized into a
desirable class type where most of the students were, on average, predisposed toward autonomous learners.
However, we also found that controlling nature of compulsory classes could not necessarily be a key element
to predict the motivational predispositions among the students; in fact, only 8 out of the 16 classes (i.e.,
50 %) were categorized into an undesirable class type where most of the students were, on average,
predisposed toward externally regulated learners, and moreover, 4 out of the 16 classes were categorized into
the desirable class type mentioned above. These inconclusive findings can be attributable to our roughcategorization criteria used in our previous surveys and thus, called for a need to further illustrate thestudents’ motivational styles toward the target activities.
In the light of the findings in our previous surveys, therefore, we are currently conducting a series ofsurveys among the participating students in the target CMC activities. The primary aim of the current
surveys is two-fold: (1) to elucidate the students’ motivational styles toward the activities by clustering eachof the individual motivational predispositions and (2) to discuss ideal learning environments for the students
based on SDT. The research hypotheses we made in the light of the above research purposes were (1) there
must be, at least, more than 3 prominent motivational styles among the students1, and (2) if the resulting
motivational styles can be interpretable from the perspective of SDT, the research findings in the previous
SDT works can shed some light on our discussions on the ideal learning environments as well as effective
motivating strategies for the students. The following sections provide a brief summary of SDT.
1.1
Self-Determination Theory
To discuss the students’ motivational styles toward CCDL CMC activities, we have employed the theoreticalframework of SDT. SDT is a comprehensive theory on human motivation and thus, has been frequently
applied to the field of education (Deci, Vallerand, Pelletier, & Ryan, 1991; Reeve, 2002; Vallerand &Bissonnette, 1992) and second language acquisition (Hayashi, 2012; Noels, 2001a, 2001b, Noels, Pelletier,
Clément & Vallerand., 2000; Park, 2006; see also Dörnyei, 1994). The motivation concepts elaborated in
1

Yoshida and Nakano (2013) roughly divided the students’ motivational predispositions toward the target CMC
activities into the following three types: (1) predisposition toward autonomous learners (Mean factor scores on
autonomous types of motivation were higher than each of the grand means whereas the scores on controlled types ofmotivation were lower than each of the grand means.), (2) predisposition toward externally regulated learners (Meanfactor scores on controlled types of motivation were higher than each of the grand means whereas the scores on
autonomous types of motivation were lower than each of the grand means.), and (3) Others (Mean factor scores on the 6
factors were found to be almost equal to each of the grand mean.).

24Selected Papers of the 18th Conference of Pan-Pan Pacific Association of Applied Linguistics
SDT are called intrinsic motivation, extrinsic motivation and amotivation. As in Figure 1, these three types ofmotivation have been hypothesized to consist of the self-determination continuum.
On the continuum, three types of motivation are ordered along with the degree of self-determination (i.e.,autonomy) accompanying the resulting behaviors; that is, from left to right, the resulting behaviors can be
described as non-self-determined to fully self-determined. Thus, this relationship has been called
self-determination (or autonomy) continuum. On the basis of the degree of self-determination, each of thethree types of motivation has been defined as follows.
Behavior
Type of Motivation

Nonself-determined

Self-determined

Amotivaion

Extrinsic Motivation
Controlled

Intrinsic Motivation

Autonomous

Type of Regulation

Non-Regulation

External
Regulation

Inrojected
Regulation

Identified
Regulation

Integrated
Regulation

Intrinsic
Regulation

Locus of Causality

impersonalExternal

Somewhat
External

Somewhat
Internal

Internal

Internal

Figure 1: The self-determination continuum, slightly modified by the authors on the basis of Deci and Ryan
(2000, p.237)
1.1.1
Amotivation
Amotivation, which is placed on the left extreme, has been defined as the lack of motivation as well as
self-determination (Deci & Ryan, 2000), so that the resulting behaviors are supposed to be
non-self-determined. SDT has further enumerated a prominent feature of amotivation as absence ofintentionality to do the target activity. This feature is indicated by the dot-line between amotivation andextrinsic motivation in Figure 1.
1.1.2
Extrinsic motivation
The concept of extrinsic motivation elaborated in SDT is different from those discussed in the traditional
motivation theories in that SDT has defined the concept as, more or less, having some degree ofself-determination, and that SDT assumed four subtypes of extrinsic motivation called external regulation,
introjected regulation, identified regulation, and integrated regulation (Deci & Ryan, 2000).
External regulation is a type of extrinsic motivation with the least level of autonomy (Deci & Ryan,
1985). Thus, if our students are externally regulated to engage in the target CALL activities, they feel as if
they are forced to do so by the external pressures posed by teachers or learning environment. It is also
important to note that if the students are exposed to such pressures, they are highly likely to be demotivatedand finally amotivated toward the target activities (Nakano & Yoshida, 2008).
Introjected regulation is a slightly self-determined type of extrinsic motivation (Deci, Vallerand, Pelletier,& Ryan, 1991). Although this type of extrinsic motivation is said to be more desirable than external
regulation, the students whose behaviors are regulated by introjection are likely to feel as if they are forced toengage in the target activities by internal pressures posed by his/her own self (Deci & Ryan, 2000).
If the students come to digest the introjection, they are expected to identify the value or importance of theactivities in question. At this stage, the students are likely to regulate themselves to engage in the target
activities because they recognize themselves why they should do so; this is a main feature of identified
regulation. Thus, identified regulation has been regarded as an autonomous type of extrinsic motivation.
Lastly, integrated regulation has been defined as a fully autonomous type of extrinsic motivation (Deci &Ryan, 2000). As the self-determination continuum indicates, this type of motivation has been regarded as
almost the same as intrinsic motivation. According to Deci et al. (1991), however, there are some slightdifferences between these two types of motivation in that integrated regulation involves some instrumentality
with respect to doing the target activities.
1.1.3
Intrinsic motivation
Intrinsic motivation has been defined as “a prototypical form of self-determination” (Deci & Ryan, 1991,
p.253) and the resulting behaviors have often been described as fully self-determined (i.e., autonomous).
Thus, if the students in CCDL program are intrinsically motivated toward the target CMC activities, she/he is25

Selected Papers of the 18th Conference of Pan-Pan Pacific Association of Applied Linguistics
expected to engage in the activities “with a full sense of choice, with the experience of doing what one
wants” (p.253). It is also important to note that some previous SDT woks (Vallerand, Pelletier, Blais, Briere,
Senecal, & Vallieres, 1992, 1993) established a taxonomy for intrinsic motivation and conceptualized three
types of intrinsic motivation: intrinsic motivation for knowledge, intrinsic motivation for accomplishment
and intrinsic motivation for stimulation. These types are said to be categorized by the kinds of triggers thatare expected to provoke the sense of intrinsic motivation.

2
Method2.1
Participants
The participants in this study were 706 Japanese university students2. These students were all enrolled in thetarget CMC activities in the spring semester (n = 367) or/and in the fall semester (n = 336) of 2012, as a partof classroom activities or extra-curricular activities.
2.2
Questionnaire
Questionnaire used in this study was based on the Language Learning Orientation Scale (LLOS: Noels,
Pelletier, Clément & Vallerand, 2000; see also Park, 2006; Yoshida, 2010) and Academic Motivation Scale(Vallerand et al., 1992, 1993). This instrument contained 24 items, each of which was designed to be apossible reason for engaging in the CCDL CMC activities and can be divided into the following 7 subtypesof motivation. (Information in the parentheses represents the abbreviations for each of the seven subscales
and the number of the items included, respectively.)
Intrinsic motivation for knowledge (IMK: 3 items),
Intrinsic motivation for accomplishment (IMA: 3 items),
Intrinsic motivation for stimulation (IMS: 3 items),
Extrinsic motivation - identified regulation (EMID: 4 items),
Extrinsic motivation - introjected regulation (EMINTRO: 4 items),
Extrinsic motivation - external regulation (EMEX: 4 items),
Amotivation (AMOT: 3 items)
In responding to the questionnaire items, the students were asked to indicate to what extent each of thereasons corresponded to his or her reasons for participating in the CMC activities, along with 5-point Likert
Scale.
2.3
Analytic Procedure
First, we summarized the descriptive statistics for the 24 items in our questionnaire and checked ceiling
effect and floor effect.
Second, in order to examine the internal structure of motivation construct, the data gathered in both thespring and fall semesters of 2012 were combined and analyzed in terms of exploratory factor analysis (EFA).
In EFA3, we employed maximum likelihood method for factor extraction, Promax rotation for factor rotation
and retained those items with factor loading of above |0.35|, as in our previous surveys (e.g., Yoshida &Nakano, 2013). In deciding the appropriate number of factors to be extracted, we referred to the result of thetest of goodness of fit as well as scree plot provided in the analyses.
Lastly, the resulting individual factor scores were subject to cluster analysis (CA) to classify the types ofmotivational styles among the students. In CA, we employed both hierarchal and non-hierarchical cluster
analysis as in Hayashi (2012). As the first step, we conducted hierarchical cluster analysis to decide thenumber of clusters with reference to the resulting dendrogram, and then, as the second step, run
nonhierarchical cluster analysis.
3
3.1

Results and Discussion
Descriptive statistics

2

Those who did not answer more than 2 items on the questionnaire were excluded from the analysis.
All the analytic procedures used in EFA were the same as those in our previous surveys (for details, see Yoshida,2010; Yoshida & Nakano, 2009).
3

26

Selected Papers of the 18th Conference of Pan-Pan Pacific Association of Applied Linguistics
Table 1 shows the summary of descriptive statistics for the 24 items in our questionnaire.
As the resulting values of mean minus 1 standard deviation (i.e., M-1SD) indicate, the students’ responses
on items 13 (AMOT 1) and 21 (AMOT 2) might be affected by floor effect. As we encountered the sameproblem in our previous surveys (e.g., Yoshida & Nakano, 2013), we found that these items never happened
miscomputations in the process of EFA. Therefore, we decided to retain them in the following analyses.

27Selected Papers of the 18th Conference of Pan-Pan Pacific Association of Applied Linguistics
Table 1: Summary of Descriptive Statistics
Item
Item1
Item2
Item3
Item4
Item5
Item6
Item7
Item8
Item9
Item10Item11
Item12
Item13
Item14Item15
Item16
Item17Item18Item19Item20Item21
Item22
Item23
Item24

Subscale & Item No.
IMA3
EMID4
IMS3
EMEX4
IMK1
EMID3
EMINTRO4
EMEX3
IMK2
EMEX2
IMA2
AMOT3
AMOT1
EMINTRO3
IMA1
IMS1
EMID2
IMS2
EMID1
EMINTRO2
AMOT2
IMK3
EMEX1
EMINTRO1

M

SD
1.06
1.18
1.13
1.16
1.05
1.12
1.13
1.17
1.05
1.17
1.16
1.12
1.12
1.13
1.05
1.14
1.07
1.08
1.07
1.12
1.00
1.07
1.26
1.16

3.12
3.31
3.48
2.24
3.83
3.58
2.24
3.13
3.71
3.11
3.04
2.20
2.00
2.46
3.37
3.03
3.54
3.42
3.65
2.88
1.73
3.81
2.26
2.57

M+1SD
4.18
4.49
4.61
3.40
4.88
4.69
3.37
4.29
4.76
4.29
4.20
3.32
3.12
3.59
4.42
4.17
4.61
4.50
4.72
3.99
2.72
4.87
3.52
3.73

M-1SD
2.06
2.13
2.35
1.09
2.79
2.46
1.11
1.96
2.66
1.94
1.88
1.07
0.88
1.33
2.32
1.90
2.46
2.34
2.57
1.76
0.73
2.74
1.00
1.42

N
699
702
700
698
695
701
702
701
701
695
700
697
700
699
698
674
696
701
698
701
699
700
698
700

3.2
Results of EFA
On the basis of the above discussion, we put all the 24 items in EFA. As a result, we extracted 6 correlated
factors, χ2 = 214.56, df = 114, p < .0014. Table 2 shows the pattern matrix obtained in the final EFA. Table 3
summarizes the resulting correlation matrix among the 6 factors. In this matrix, each of the 6 factors wasarranged along with the self-determination continuum.
In the light of the results in Tables 2 and 3, we renamed each of the 6 factors as follows.
Factor 1: Autonomous Motivation for Knowledge (AMK)
Factor 2: Autonomous Motivation for Accomplishment (AMA)
Factor 3: Amotivation (AMOT)
Factor 4: Transitional Phase between EMEX and EMINTRO (EMEX to INTRO)
Factor 5: Introjected Regulation (EMINTRO)
Factor 6: Intrinsic Motivation for Stimulation (IMS).
As in Table 3, inter-correlations among the 6 extracted factors were found to show a sort ofquasi-simplex pattern, suggesting that there must be almost the same relationships as those hypothesized in
the self-determination continuum. This result also suggested a piece of evidence with respect to the constructvalidity of our questionnaire items (see Vallerand & Bissonnette, 1992).

4This result indicated that there might be more latent factors to be extracted. However, we stopped the analysis at thisstage on the basis of the interpretability of the resulting factor structure as well as the fact that further extraction mightwell cause Heywood case.

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Selected Papers of the 18th Conference of Pan-Pan Pacific Association of Applied Linguistics
Table 2: Pattern Matrix
Subscale
IMK1
IMK3
IMK2
EMID3
EMID2
IMS3
EMID4
IMA3
IMA2
EMEX2
AMOT1
AMOT3
AMOT2
EMEX4
EMINTRO4
EMEX1
EMEX3
EMINTRO2
EMINTRO3
EMINTRO1
IMS1
IMS2% of var.
eigenvalue

1

2

3

4

5

6

.946

.076

.061

.063

-.074

-.164

.872

-.172

.010

.072

-.115

.040

.869
.528
.490
.489
-.050
.030
-.056
.083
.044
.024
-.041
.019
.111
-.039
-.035
-.009
-.073
-.117
.023
.138
32.441
7.531

-.062
.221
.016
.264
.787
.746
.728
.433
.011
-.105
.122
-.001
.005
.000
.082
-.110
-.150
.307
.190
.024
11.814
3.129

-.006
-.019
-.059
.040
-.048
.024
.057
-.110
1.037
.707
.644
.008
-.048
.171
-.135
-.048
.191
.123
.035
-.040
4.426
1.398

.066
-.067
-.074
-.111
-.082
.014
.129
.060
-.204
.031
.164
.839
.790
.570
.385
.100
.115
.120
.007
-.101
3.009
1.083

-.094
.140
.144
.101
.066
-.236
-.134
.328
.058
.110
-.044
.001
.155
-.047
.186
.755
.680
.386
-.024
.193
2.351
1.035

.091
-.011
.248
-.057
-.177
.115
.297
-.033
-.007
-.022
.065
.026
-.035
-.067
-.005
.045
-.010
.050
.653
.597
2.281
.813

Note: Factor loadings of above |0.35| are highlighted in boldfaced type.

Table 3: Correlation Matrix
AMOT
AMOT
EMEX to EMINTROEMINTRO
AMA
AMK
IMS

(0.89)EMEX toEMINTRO.668(0.73)

EMINTRO

AMA

AMK

IMS

-.061
-.139
(0.82)

-.434
-.398
.563
(0.70)

-.483
-.556
.549
.645
(0.63)

-.304
-.326
.533
.581
.618
(0.80)

Note: The values in diagonal elements are Cronbach’s alpha reliability coefficient for each of the 6 factors.

3.3
Results of CA
The results of CA indicated that there must be four types of motivational styles and thereby we can divide thestudents into the following groups:
Group (1) Autonomous Learners (n = 262)
Group (2) Learners Motivated by Introjection (n = 88)
Group (3) Relatively Demotivated Learners (n = 249)
Group (4) Amotivated Learners (n = 104).
Figure 2 shows the graph representing mean factor scores calculated for the above 4 groups (see also
Appendix for details).
As in Figure 2, the students in Group (1) scored highly on autonomous types of motivation (i.e.,
EMINTRO, AMA, AMK and IMS) but scored lower than the grand means (i.e., zero) on the controlled typesof motivation (i.e., AMOT and EMEX to EMINTRO). Thus, we regarded these students as Autonomous
Learners. The students in Group (2) scored highly on the autonomous types of motivation (i.e., EMINTRO,
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Selected Papers of the 18th Conference of Pan-Pan Pacific Association of Applied Linguistics
AMA, AMK and IMS) but their scores on the controlled types of motivation (i.e., AMOT and EMEX to
EMINTRO) were also higher than the grand means. This result implied that the students in this group might
be suffered from dilemma as a result of introjection. Therefore we named these students Leaners Motivatedby Introjection. The students in Group (3) scored slightly lower than the grand means on autonomous typesof motivation (i.e., EMINTRO, AMA, AMK and IMS) and their scores on controlled types of motivation (i.e.,
AMOT and EMEX to EMINTRO) were found to be slightly higher than the grand means. The students inGroup (4) also showed the same but more obvious patterns as those in Group (3). As a result, we renamed
the students in Group (3) Relatively Demotivated Learners and those in Group (4) Amotivated Learners.

1.5
1
0.5
0
-0.5
-1
-1.5
-2
AMOT

EMEX to INTROEMINTRO

AMK

AMA

IMS

Group (1) Autonomous Learners (n = 262)
Group (2) Learners Motivated by Introjection (n = 88)
Group (3) Relatively Demotivated Learners (n = 249)
Group (4) Amotivated Learners (n = 104)

Figure 2: Motivational styles among students
3.4
Discussion
3.4.1
Four types of motivational styles and SDT
In 4.3, we found that there must be 4 types of motivational styles, which can be the benchmark for dividing
the students into 4 groups: Group (1) Autonomous Learners, Group (2) Learners Motivated by Introjection,
Group (3) Relatively Demotivated Learners and Group (4) Amotivated Learners. As we hypothesized, there
were possibly four prominent types of motivational styles among the students. Furthermore, each of these 4groups was highly interpretable and their features can be logically explained by SDT framework. This result
provides a piece of evidence with respect to the applicability of SDT framework for elucidating the students’motivational styles toward the target CMC activities. At the same time, the result must suggest anotherpossibility of SDT framework for discussing the ideal learning environments as well as effective motivating
strategies for enhancing the students’ motivation, as our research hypothesis (2) indicates. Drawing on thefindings in the previous SDT works (Deci & Ryan, 1985; Deci et al., 1991; Reeve, 2002), therefore, we
provide a brief summary on these motivational issues in the following section.
3.4.2
Ideal learning environments and effective motivating strategies for the students
To maintain the desirable motivational styles among the students in Group (1), the instructors in charge ofthe target activities should provide challenging materials and assignments, which are optimal for the
students’ English proficiency (Deci & Ryan, 1985), give supportive feedback on their performance (Reeve,2002) and incorporate what the students want to discuss into the topics to be discussed in the activities(Nakano & Yoshida, 2008; Yoshida, 2010).
To promote the internalization with respect to the task participation among the students in Group (2), theinstructor should employ autonomy-supportive teaching style as discussed above and encourage the students
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Selected Papers of the 18th Conference of Pan-Pan Pacific Association of Applied Linguistics
to internalize the reason why it is important to join the activities and to recognize what they can achieve in
the activities (Nakano, 2006).
To enhance motivation among the students in Groups (3) and (4), the instructors and designers of theactivities should strive to find out the potential demotivating factors. In so doing, it is important to examine
whether the current learning environment can satisfy the students’ psychological needs for autonomy,competence and relatedness, each of which has been regarded as important motivating factors in SDT.
According to the previous SDT works (e.g., Reeve, 2002), furthermore, it is better to check the following
points at the very beginning of course evaluation.
1.
Instructors’ teaching styles: To satisfy the students’ psychological needs for autonomy,check the instructors’ teaching styles. If their teaching styles are found to involve some controllingaspect, replace them with more autonomy-supportive teaching styles as much as possible.
2.
Level of the tasks, materials and assignments: To satisfy the students’ psychological needs
for competence, check the levels of tasks, materials and assignments provided in the target activities in
the light of the students’ English proficiency. If the levels are found to be inappropriate (i.e., too easy
or too difficult), it is important to adjust them to be optimal for the students.
3.
Grouping of the students: To satisfy the students’ psychological needs for competence andrelatedness, check whether there are significant differences in English proficiency among the students
in the same group. If some significant differences are found in some groups, it is better to regroup thestudents.
To further the discussion on the ideal learning environments, it is necessary to assess to what extent ourstudents could satisfy the three psychological needs in the target CMC activities in our future study.

4

Conclusion

The primary aim of the surveys cited in this paper was two-fold: (1) to elucidate the students’ motivational
styles toward the activities by clustering each of the individual motivational predispositions and (2) todiscuss the ideal learning environments for the students based on SDT. As in our research hypothesis (1), we
could find the following 4 different types of motivational styles among the students: Group (1) Autonomous
Learners (n = 262), Group (2) Learners Motivated by Introjection (n = 88), Group (3) Relatively DemotivatedLearners (n = 249), Group (4) Amotivated Learners (n = 104). The interpretability of these 4 motivational styles
indicated the applicability of SDT framework for duplicating the students’ motivational styles on one hand and, as
mentioned in our research hypothesis (2), further suggested another possibility of SDT framework forinvestigating the ideal learning environments as well as effective motivating strategies for the students on theother hand. On the basis of the discussion in 3.4, our future study will focus on the effect of the students’
psychological needs for autonomy, competence and relatedness on their motivational styles toward the target
CMC activities.
It is also important to note here that, in EFA conducted with the same procedures as in our previous
surveys, we extracted 6 correlated factors. The inter-correlations among these 6 factors showed a sort ofquasi-simplex pattern and furthermore, almost the same pattern as those found in the previous surveys. Thesefindings provided the reliability as well as the construct validity of our questionnaire items.
Acknowledgement
We would like to express our sincerest thanks to Hiroki Mori (Distance Learning Center, Waseda University)
for his cooperation in our data collection. We are also indebted to all the CCDL instructors.
References
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Appendix 1: Means and Standard Deviations for 4 groups
Motivational Styles
Autonomous Learners(n = 262)
Learners Motivated byIntrojection (n = 88)
Relatively DemotivatedLearners (n = 249)
Amotivated Learners(n = 104)AMOT

EMEX toINTRO

EMINTRO

AMK

AMA

IMS

-0.82 (0.38)-0.81 (0.48)

0.36 (0.67)

0.80 (0.48)

0.72 (0.61)

0.63 (0.58)

0.84 (0.79)

0.56 (0.74)

0.98 (0.55)

0.29 (0.51)

0.35 (0.61)

0.56 (0.49)

0.21 (0.68)

0.28 (0.70)-0.20 (0.53)-0.32 (0.50)-0.30 (0.51)-0.31 (0.57)

0.84 (0.97)

0.90 (0.81)-1.27 (0.70)-1.50 (0.75)-1.38 (0.62)-1.33 (0.63)

33