DISTRIBUTION OF DIFFERENT TYPES OF HESITATION PHENOMENA 169
Distribution of different types of hesitation
phenomena and their patterns of correlations (2)
Tomohito Ishikawa
Abstract
The present study is an extension of Ishikawa (2012), which deals with a different set of sub-corpus of Ishikawa (2008), addressing the
following three research questions. The first question was: Is the
distribution of different types statistically significantly different from
uniform? This research was originally posed by Shriberg (1994) in her
study of first language (L1) hesitation phenomena. The second research question was: What are the relationships between different types of
hesitation phenomena as well as the relationships between different
types of hesitation phenomena and perceptions of task difficulty? In
order to answer these research questions, a sub-corpus was analyzed,
which was originally used in Ishikawa (2008). The final research
question was: Are there any emerging differences in patterns of
distributions of hesitation phenomena when task complexity is
manipulated? The results showed that similarly to Ishikawa (2012),
distributions of different types of hesitation phenomena were not
uniform, and that several significant correlations were found between
hesitation phenomena and perceptions of task difficulty and among
different types of hesitation categories. The comparisons of the results of the present study and those of Ishikawa (2012) also showed that despite the fact that both studies were based on spoken performances of different pedagogical tasks, the distributions of the seven categories of hesitation phenomena did not differ from each other both in terms of raw frequencies as well as T-unit-based ratio measures.
Introduction
Ishikawa (2012) addressed two research questions. The first question concerned investigation into the distribution of different types of hesitation phenomena, such as filled pauses. The second research question was about the relationships between different types of hesitation phenomena as well as the relationships between different types of hesitation phenomena and perceptions of task difficulty. Ishikawa's (2012) results showed that distributions of different types of hesitation phenomena were far from uniform, and that several significant correlations were also found between hesitation phenomena and perceptions of task difficulty and among different types of hesitation categories.
As an extension of Ishikawa (2012), using a different sub-corpus of Ishikawa (2008), the present study first examined distributions of different types of hesitation phenomena proposed by Shriberg (1994); (1) deletion (DEL); (2) repetition (REP); (3) substitution (SUB); (4) insertion (INS); (5) filled pauses (FP); (6) hybrid (HYB); and (7) articulation (ART). Ishikawa (2012), using a sub-corpus of Ishikawa (2008), showed that the distributions of the different types of hesitation phenomena observed in his study were far from uniform; namely, Filled Pauses (FP) was the most frequent hesitation type, followed by Repetitions (REP), Deletions (DEL) and Substitutions
DISTRIBUTION OF D1NN'BRENT TYPES OF HESITATION PHENOMENA 171 (SUB) in this statistically significant order. The occurrences of the categories of Insertions (INS), Articulations (ART) and Hybrids (HYB) were much less frequent then the aforementioned four hesitation categories, and no statistically significant differences were found among the latter three types.
Also examined in the present study were correlations between hesitation phenomena plus ones between perceptions of task difficulty and hesitation categories.
As suggested above, the present study, three research questions were put forth. The first question was: Is the distribution of different types statistically significantly different from uniform? The null hypothesis is that each type will occur equally; the alternative hypothesis is that some types are more likely than others. This research question and the hypotheses were addressed in Shriberg (1994), which used Ll corpus, and in her case the null hypothesis was rejected. In the present study, this research question was addressed by using a simple frequency measure and a ratio measure.
The second research question was: What are the relationships between different types of hesitation phenomena as well as the relationships between different types of hesitation phenomena and perceptions of task difficulty?
The second research question is more exploratory and descriptive. Thus, the goals of this article are three-fold: to describe and examine (1) distributions of different types of hesitation phenomena, and (2) correlations among different types of hesitation and their correlations with perceptions of task difficulty.
The third research question was: Are there any emerging differences in patterns of distributions of hesitation phenomena when task complexity is manipulated? In order to answer this research question, the results obtained in the present study and those reported in Ishikawa (2012) were comparatively examined.
Methodology Participants
The participants for the present study were college students learning English as an L2, whose L1 was Japanese (N = 24; male = 2, female = 22).
They were either English majors or English for Academic Purposes (EAP) Economics students at two universities in Tokyo. The participants' proficiency levels ranged approximately between low to high intermediate.
The proficiency test scores of the English majors at a prestigious university were not available, but they participated in subject matter classes taught in English. The minimum score of the EAP Economics students at the other university was 450 on the paper-based TOEFL. Their ages ranged from 18 to 35 years old, with an average age of 22.2 years old. Their mean length of stay in English-speaking countries was approximately 8 months and the mean length of English instruction prior to this study was approximately 11 years.
Materials
Since one of the goals of the current study is to compare the results of the present study with those of Ishikawa (2012), brief descriptions of the pedagogical tasks will be provided. Originally three types of pedagogic tasks were employed in Ishikawa (2008): no reasoning task, the results of which is reported in Ishikawa (2012); simple reasoning task, the results of which is reported in the current article; complex reasoning task.
In the no reasoning task (see Appendix A for the task and Appendix C for the instructions), the learner simply described the current human relationships between the section members represented on the task sheet. The nature of human relationship was represented by different types of lines on the task sheet; namely, the solid line (originally colored in blue) between section members represented a good human relationship, and the broken line (origi-
DISTRIBUTION OF DIFFERENT TYPES OF HESITATION PHENOMENA 173 nally colored in red) a bad one. Essentially, in the no reasoning task, necessary information to transfer to the company president (i.e., human relationships between the section members) was available in the learner's task materials. Therefore, the learner's main task was to transfer given information to the president without necessarily conducting intentional reasoning. In order to elicit sufficient L2 speech data for analysis, a setting was chosen, where the manager was in charge of four members rather than two or three members.
On the other hand, the simple reasoning task ((see Appendix B for the task and Appendix D for the instructions)) required the learner to report to the company president about human relationship changes that were not given to the learner. In performing the task, the learner had to select a "trigger" out of four choices (i.e., one of the section members either lost a floppy disk, showed up late for a meeting, lost an important document, or deleted data on a computer). The trigger was assumed to have caused hypothetical human relationship "trouble" (represented by an arrow) between section members.
Thus, before the participant performed a task, they chose only one trouble trigger and assigned it to one of the section members (i.e., the learner decided who committed what kind of job mistake). This means that in order to complete the task, the learner was required to "fill the gap" between the initial and the goal/desired states, which required reasoning. Furthermore, in order to perform the task used in the present study, where human relationship changes were required to be reported to the president, it was most natural for the learner to mentally represent and manipulate psychological concepts.
Procedures
The experiment was conducted on an individual basis. Before the experiment began, the researcher told the participant to perform three tasks,
one of which was the task relevant to the present study. The researcher then passed the task-instructions sheet to the participant. Both instructions sheets were originally written in their first language (i.e., Japanese). The participant was also informed in advance that the answering machine would stop after three minutes but they did not have to keep talking for three minutes. After each planning session, the researcher read out the message on the answering machine ("Hi, you have reached xxx-xxx-xxxx. I cannot come to the phone right now. Please leave a message after the beep. Thanks."). A beep sound followed and the recording started. After completing the speaking task, the learner responded to a brief written questionnaire, which was created to assess the learner's subjective perceptions of task difficulty (see below for details of the questionnaire items).
Hesitation measures
The present study employed seven hesitation measures based on Sbhriberg's classification system (Shriberg, 1994). Her system is originally developed for same-turn disfluencies and is designed to handle only within- sentence disfluencies. Other speech phenomena not considered in her system include: silent pauses, pathological stuttering, discourse markers, uncorrected errors (Shriberg, 1994, p. 2, 6-7, chapter 4, and some specific cases are mentioned in this thesis). The coding methods described in the present article were almost identical to Shriberg's though some minor modifications were made.
Shriberg distinguishes basic disfluency types from complex ones, which contain more than one disfluency episode (an example is given below).
Although Shriberg treats both simple and complex disfluencies separately, I decomposed complex disfluencies into their disfluency components and counted each disfluency episode separately. The decomposition was
DISTRIBUTION OF DIFFERENT TYPES OF HESITATION PHENOMENA 175 necessary in order to add consistency in counting the number of disfluencies,
which previous studies did not clarify criteria about, which is criticized by Ellis and Barkhuizen (2005). A sample of complex disfluencies given by Shriberg (1994, p. 58) is:
he she she liked it
This is regarded as a complex disfluency because: (1) "he" is substituted by the fist "she," which is the output of the first repair; (2) the output of the first repair operation (i.e., "she") is also an input to the second repair operation. That is, the output of the first repair operation is repeated (i.e., repaired) by the second "she." Formally, the sample above is represented as follows:
he she she liked it [R[ s . s]. r ]
The two sets of square brackets in the above example indicate that two disfluency components are involved in this case (i.e., "he she" and "she she").
Such cases are called complex disfluencies because the first "she" is involved in two disfluency components. In the present study, however, I did not distinguish simple and complex disfluencies as Shriberg did, and decomposed complex ones into simple ones. For instance, rather than treating the above example as a single complex disfluency, I treated it as two disfluencies or two disfluency episodes. In other words, the number of disfluency episodes is equal to the number of interruption points.
Following Shriberg's classification scheme of hesitation, seven disfluency measures were employed in the present study. Table 1 presents the seven
Table 1 Shriberg's disfluency type and samples from my corpus
(Table 1 is taken from Ishikawa (2010) and modified by the author)
Disfluency type Samples from my corpus
DEL
REP
SUB
INS
FP
HYB
ART
^ so th- he can figure out what is going on [d-.]
^ and Kate and John s- ah ok I have to , report the relationships between Kate John ah Nick and Cathy [cdddd-.f]
^ but he but because of his lost of important document [cd.]
^ Joe came late came late for a meeting [rr.rr]
^ so because of ah because of the Beth's showing up later for the meeting [rr.frr]
^ till Joe come came to the meeting [s.s]
^ Mike was confusing confused about the next presentation [s.s]
^ Joe was working with secretary Ann ah af- before trouble Es-.
s]
^ and she is actually she is a strict person about the time [rr.irr]
^ Beth showed up later for the meeting the important meeting [rr.rir]
^ um we also have a problem with Cathy and John [.f]
(example of s + i)
^ Ann did not have relationships good relationship with Bob [s.is]
^ this is nam Minami calling [r--.r]
^ secretary pa- Cathy [r--.r]
Note. DEL = Deletions; REP = Repetitions; SUB = Substitutions; INS FP = Filled pauses; ART = Articulations; HYB = Hybrids.
= Insertions;
disfluency categories and their actual samples from my corpus: 1) deletion (DEL); 2) repetition (REP); 3) substitution (SUB); 4) insertion (INS); 5) filled pauses (FP); 6) hybrid (HYB); and 7) articulation (ART). Shriberg (1994) also includes a category conjunction (CON); in the present study, this category was not analyzed partly because this is a category based on a grammatical category of conjunction. This means that even when conjunctions are repeated, the episodes were not coded as REP but CON. By eliminating the CON category, the present study respected patterns of hesitations; therefore, the above example was coded as REP not CON.
DISTRIBUTION OF DIFFERENT TYPES OF HESITATION PHENOMENA177 Task-difficulty questionnaire
The task-difficulty questionnaire was adopted from Robinson (2001b), who included items assessing interest, ability, motivation, stress, and perceived task difficulty. In addition to these, the present study included three items assessing concentration, response to time pressure, and anxiety. The questionnaire was used to check whether task complexity conceptualized by the task designer is matched by perceptions of difficulty on the part of the L2 learner.
1) Concentration (this task required concentration/this task did not require concentration)
2) Time pressure (I did not feel time pressure during task performance/I
felt time pressure during task performance)
3) Anxiety (this task made me anxious/this task did not make me anxious) 4) Stress (I felt frustrated during task performance/I did not feel frust-
rated during task performance)
5) Difficulty (this task was easy/this task was difficult)
6) Interest (this task was interesting/this task was not interesting) 7) Ability (I did not do this task well/I did this task very well)
8) Motivation (I want to do tasks like this/I don't want to do tasks like this)
The learner was asked to respond to each item along a ten-point Likert scale (ranging from 0 to 9). The questionnaire items were written in the learners' Ll. In coding the data, a score of 0 was assigned to the semantically most negative learner response to each questionnaire item (e.g., no time pressure, no anxiety) and a score of 9 to the semantically most positive learner response (e.g., highest time pressure, highest anxiety) to each
questionnaire item.
Results
Figure 1 shows distributions of different types of hesitation phenomena and their raw frequencies. In total, 367 disfluency phenomena are observed.
Figure 1 shows Filled Pauses (FP) is the most frequent hesitation phenomena.
The second most frequent type of hesitation phenomena is Repetitions (REP), which is followed by Deletions (DEL) and Substitutions (SUB). The occurrences of the categories of Insertions (INS), Articulations (ART) and Hybrids (HYB) are much less frequent.
The first question was: Is the distribution of types statistically significantly different from uniform? The null hypothesis is that each type will occur equally; the alternative hypothesis is that some types are more likely than
180 160 c„140 U a9120 8100
o ° 80
N I 60 Z 40 20
0 FP REP DEL SUB INS ART ' HYB Figure 1. Distributions of different types of hesitation phenomena DEL = Dele-
tions; REP = Repetitions; SUB = Substitutions; INS = Insertions; FP
= Filled pauses; ART = Articulations; HYB = Hybrids.
Table 2
DISTRIBUTION OF DIFFERENT TYPES OF HESITATION PHENOMENA 179 Results of Ryan's Method: Critical Ratio, P-Value, and Nominal Alpha Level
Comparison Critical ratio p-value Nominal alpha level
FP>REP FP>DEL FP>SUB FP>INS FP>ART FP>HYB REP>DEL REP>SUB REP>INS REP>ART REP>HYB DEL>SUB DEL>INS DEL>ART DEL>HYB SUB>INS SUB>ART SUB>HYB INS=ART INS=HYB ART=HYB
2.92 7.18 9.46 11.76 11.99 11.76 4.36 6.85 9.48 9.75 9.48 2.63 5.89 6.25 5.89 3.5 3.94 3.5 0.29 -0 .27
0.29
p=0.0036 p<0.0002 p<0.0002 p<0.0002 p<0.0002 p<0.0002 p<0.0002 p<0.0002 p<0.0002 p<0.0002 p<0.0002 p=0.0082 p<0.0002 p<0.0002 p<0.0002 p=0.0004 p<0.0002 p=0.0004 ns
ns ns
0.01429 0.00714 0.00476 0.00286 0.00238 0.00286 0.01429 0.00714 0.00357 0.00286 0.00357 0.01429 0.00476 0.00357 0.00476 0.00714 0.00476 0.00714 0.01429 0.01429 0.00714
Note. DEL = Deletions; REP = Repetitions; SUB = Substitutions; INS = Insertions; FP = Filled pauses; ART = Articulations; HYB = Hybrids.
others. In order to answer the first research question, the Chi square analysis was conducted. The results of the analysis was statistically significant (z2(6)=411.346, p<.01). Subsequently, in order to locate statistically significant differences between the hesitation categories, Ryan's method was applied to the dataset, using Tanaka and Nakano's (2012) js-STAR 2012.
Table 2 presents the results of the analyses. As is clear from Table 2, except for the three comparisons between INS, ART and HYB, all the comparisons were statistically significant.
Table 3 Descriptive Statistics for the Occurrences of Different Types of Hesitation Phenomena per T-unit
M SD
DEL/T REP/T SUB/T INS/T FP/T ART/T HYB/T
0.166 0.372 0.097 0.021 0.532 0.017 0.003
0.163 0.330 0.086 0.036 0.040 0.040 0.012
Note. DEL/T = Deletions per T-unit; REP/T = Repetitions per T-unit; SUB = Substitutions per T-unit; INS = Insertions per T-unit; FP/T = Filled pauses per T-unit; ART/T = Articulations per T-unit; HYB/T = Hybrids per T-unit.
Table 3 shows descriptive statistics for the occurrences of different types of hesitation phenomena per T-unit. Similarly to the previous results of distributions of different types of hesitation phenomena, the results of the occurrences of different types of hesitation phenomena per T-unit showed an identical order of occurrences of different types of hesitation phenomena, which is shown in Figure 2. Table 3 also shows that individual differences in the production of different types of hesitation phenomena can be observed in FP, REP, and DEL, as shown by relatively larger standard deviations.
In order to examine statistically significant differences, normality of the distributions were tested using the Shapiro-Wilk tests. The results showed that except for the measure of FP per T unit, all the measures were not normally distributed. Consequently, Friedman's ANOVA was applied to the dataset. The result was statistically significant 062(6)=100.881, p<.01, effect size=7.783). Subsequently, individual Friedman's tests were applied to the dataset. Subsequently, two-tailed Wilcoxon tests were applied to the dataset with the significance level being adjusted to .00238 (= .05/21) as a result of the Bonferroni method. Table 4 summarizes the results of the two-tailed
DISTRIBUTION OF DIFFERENT TYPES OF HESITATION PHENOMENA 181
Figure 2.
0.6
0.5
K, 0.4
U a N
'6 0.3
O 2 0.2 a)
I Z 0.1
FP REPTDELTSUBINS~ARTHYB
Distributions of occurrences of different types of hesitation phenome- na per T-unit DEL/T = Deletions per T-unit; REP/T = Repetitions per T-unit; SUB = Substitutions per T-unit; INS = Insertions per T-unit;
FP/T = Filled pauses per T-unit; ART/T = Articulations per T-unit;
HYB/T = Hybrids per T-unit.
Wilcoxon tests. The results showed that there were six non-significant pairs, which were between adjacent categories (e.g., FP/T vs. REP; DEL vs. SUB) plus a single non-adjacent pair between INS/T versus HYB/T.
The second research question was: What are the relationships between different types of hesitation phenomena as well as the relationships between different types of hesitation phenomena and perceptions of task difficulty?
Table 5 shows Spearman correlation coefficients of different types of hesitation phenomena per T unit and perceptions of task difficulty. REP/T correlated statistically significantly with Time Pressure (rs= .50, p = .02). This means that learners who felt time pressure produced more repetitions per T-unit. Motivation also correlated statistically significantly with REP/T (rs=
Table 4 Results of the Two-Tailed Wilcoxon Test
z p-value Effect size
FP/T=REP/T FP/T>DEL/T FP/T>SUB/T FP/T>INS/T FP/T>ART/T FP/T>HYB/T REP/T>DEL/T REP/T>SUB/T REP/T>INS/T REP/T>ART/T REP/T>HYB/T DEL/T>SUB/T
DEL/T>INS/T DEL/T>ART/T DEL/T>HYB/T SUB/T>INS/T SUB/T>ART/T SUB/T>HYB INS/T=ART/T INS/T=HYB/T ART/T=HYB/T
-2 .129 -4 .031 -4 .076 -4 .109 -4 .016 -4.108 -3 .511 -3 .660 -4.016 -4 .092 -4 .109 -2 .015 -3 .420 -3.502 -3.724 -3 .058 -3 .299 -3 .520 -0.317 -2 .038 -1 .753
ns p=.00006 p=.00005 p=.00004 p=.00006 p=.00004 p=.00045 p=.00025 p=.00006 p=.00004 p=.00004 ns p=.00063 p=.00046 p=.00020 p=.00222 p=.00097 p=.00043 ns
ns ns
-0.31 -0 .31 -0 .32 -0 .31 -0 .32 -0 .27 -0 .28 -0 .31 -0 .32 -0.32 -0 .26 -0 .27 -0 .29 -0 .24 -0 .25 -0 .27
Note. DEL/T = Deletions per T-unit; REP/T = Repetitions per T-unit; SUB = Substitutions per T-unit; INS = Insertions per T-unit; FP/T = Filled pauses per T-unit; ART/T = Articulations per T-unit; HYB/T = Hybrids per T-unit.
- .41, p = .04), FP/T (rs= -.43, p = .04), and SUB/T (rs= -.47, p = .02), which means that learners who produced fewer repetitions, filled pauses, and substitutions per T-unit felt more motivated to perform similar tasks in the future.
Table 6 shows Spearman correlation coefficients between different types of hesitation phenomena per T-unit. As Table 6 shows, DEL/T correlated statistically significantly with REP/T (rs= .71, p < .01) and FP/T (rs= .46, p = .03), which means that learners who produced more deletions also produced
DISTRIBUTION OF DIFFERENT TYPES OF HESITATION PHENOMENA183 Table 5 Spearman Correlation Coefficients of Different Types of Hesitation
Phenomena per T-unit and Perceptions of Task Difficulty
CON TMP ANX FRS DIF INT ABL MTV
DEL/T REP/T SUB/T INS/T FP/T ART/T HYB/T
- .06 - .06 -.21
.18 .13 .31 - .05
.38 .50*
-.23 .27
.13 .12 -.14
-.01 - .01 - .09 - .12 .09 .08 - .06
.11 .19 - .01
.11 .10 .39 - .08
.14 .30 - .21
.33 .01 .18 .05
- .05 - .02 - .16 .26 - .25
.32 - .32
- .10 -.02
.17 - .28 .03 - .03 -.22
-.37 - .47*
- .13
~.43*
-.20 - .26
Note. *p<.05; N = 24; DEL/T = Deletions per T-unit; REP/T = Repetitions per T-unit; SUB = Substitutions per T-unit; INS = Insertions per T-unit; FP/T = Filled pauses per T-unit; ART/T = Articulations per T unit; HYB/T = Hybrids per T-unit;
CON = Concentration; TMP = Time Pressure; ANX = Anxiety; FRU = Frustration;
DIF = Difficulty; INT = Interest; ABL = Ability; MTV = Motivation.
Table 6 Spearman Correlation Coefficients Between Different Types of Hesita- tion Phenomena per T-unit
REP/T SUB/T INS/T FP/T ART/T HYB/T
DEL/T REP/T SUB/T INS/T FP/T ART/T
;.71** .28
.29
.18 .36 .08
.46*
.25 .47*
.05
.25 .25 .35 A9*
.08
.23 .20 .20 - .13 .20 - .09 Note. *p<.05; **p<.01; N = 24; DEL/T = Deletions per T-unit; REP/T = Repeti- tions per T-unit; SUB = Substitutions per T-unit; INS = Insertions per T-unit; FP/T
= Filled pauses per T unit; ART/T = Articulations per T-unit; HYB/T = Hybrids per T unit.
repetitions and filled pauses. SUB/T also correlated statistically significantly with FP/T (rs= .47, p = .02). This means that learners who produced more substitutions also produced more filled pauses. Finally, INS/T correlated statistically significantly with ART/T (rs= .49, p < .02), which means that learners who produced more insertions also produced more articulation-
21 U N 0 0 U O O N O z
200 180 160 140 120 100 80 60 40 20 0 Figure 3.
SR
^ NR
FP REP DEL SUB INS ART HYB
Comparisons of distributions of different types of hesitation phe- nomena with those of Ishikawa (2012) SR = Simple Reasoning;
NR = No Reasoning; DEL = Deletions; REP = Repetitions; SUB
= Substitutions; INS = Insertions; FP = Filled pauses; ART = Articulations; HYB = Hybrids.
related hesitations.
Finally, the third research question was: Are there any emerging differences in patterns of distributions of hesitation phenomena when task complexity is manipulated? In order to answer the research question, raw frequencies of occurrences of the seven categories of the hesitation phenomena were plotted, which aided comparisons of the results of the current article and Ishikawa (2012).
Figure 3 presents the frequencies of occurrences of the seven categories of the hesitation phenomena of the present study and Ishikawa (2012), which appear quite similar despite the fact that both tasks differed in the degree of intentional reasoning. In order to answer the first research question, seven Chi
0.6
1 0.5 H
a 0.4
a) U
I::
5 z 0.1
Figure 4.
DISTRIBUTION OF DIFFERENT TYPES OF HESITATION PHENOMENA
.532 0.519
0.097 0.090
0.021 0.018
SR
^ NR
0.017 0 0.017 .017 0.003
185
0 LL ---
FP REP DEL SUB INS ART HYB
Comparisons of distributions of different types of hesitation phe- nomena per T-unit with those of Ishikawa (2012) SR = Simple Reasoning; NR = No Reasoning; DEL/T = Deletions per T-unit;
REP/T = Repetitions per T-unit; SUB = Substitutions per T-unit; INS
= Insertions per T-unit; FP/T = Filled pauses per T-unit; ART/T = Articulations per T-unit; HYB/T = Hybrids per T-unit.
square analyses were conducted, with the significance level being adjusted to .0078 (= .05/7) as a result of the Bonferroni method. The results of the analyses were not statistically significant.
Subsequently, T-unit ratio measures between the two studies were examined. Figure 4 presents the results of the T unit ratio measures of the present study and Ishikawa (2012), which again appear quite similar despite the fact that both tasks differed in the degree of intentional reasoning. In order to answer the first research question, Friedman's ANOVAs were applied to the dataset, with the significance level being adjusted to .0078 (= .05/7) as a result of the Bonferroni method. The results of the analyses were not
statistically significant, which indicated that despite the differences in task complexity, the distributions of the seven categories of L2 hesitation phenomena did not differ statistically significantly.
Discussion and Conclusion
The goals of the present study were three-fold: They were to 1) describe and examine distributions of different types of hesitation phenomena, 2) describe and examine correlations among different types of hesitation and their correlations with perceptions of task difficulty, and 3) compare the results of the present study with those of Ishikawa (2012).
With respect to the first research questions, the results of the distribution of different types of L2 hesitation phenomena revealed that the relative order of the occurrences of different types of L2 hesitation phenomena were not uniform and quite similar to the one of L1 hesitation phenomena. Thus, Filled Pauses (FP) was the most frequent hesitation phenomena and the second most frequent type of hesitation phenomena was Repetitions (REP), which is followed by Deletions (DEL) and Substitutions (SUB). The occurrences of the categories of Insertions (INS), Articulations (ART) and Hybrids (HYB) are much less frequent. These patterns of distribution were identical to those of Ishikawa (2012), which was further reinforced by the obtained answers to the third question.
The results of correlation analyses also suggested some links between hesitation phenomena and post-task-elicited perceptions of task difficulty.
Similarly to Ishikawa (2012), many hesitation phenomena were correlated with the learner's motivation to perform similar tasks in the future. There is a possibility that some hesitation phenomena may be perceived by the L2 speaker as negative reinforcers, which would likely reduce the commitment
DISTRIBUTION OF DIFFERENT TYPES OF HESITATION PHENOMENA187 of the L2 speaker to perform similar tasks in the future. If this is the case,
sequencing tasks from a simple to complex order may be a promising one from a motivational perspective.
Finally, there is an issue of production measures. While the current study as well as Ishikawa (2012) examined raw frequencies and T-unit-based measures, there are other measures that might change the whole picture of the results. For instance, T-unit may differ in length depending on the complexity
of the syntactic structures the L2 learner employ. This may be especially true to intermediate learners. Considering these limitations, the use of clause- based ratio measures may be a more promising alternative. Other non- syntactic ratio measures are also promising since advanced learners tend to produce more participle constructions, which increase the length of clauses (Wolfe-Quintero, Inagaki, & Kim, 1998). Such alternatives include syllable- based ratio measures, such as filled pauses per syllable, and temporal ratio measures such as repetition per minute. For these reasons, the results obtained in the present study need to be examined further by shedding different light on L2 hesitation phenomena.
References
Ellis, R., & Barkhuizen, G. (2005). Analyzing learner language. Oxford: Oxford University Press.
Ishikawa, T. (2008). The effect of task demands of intentional reasoning on L2 speech performance. The Journal of Asia TEFL, 5, 29-64.
Ishikawa, T. (2010). Coding disfluency phenomena for a fluency measure in TBLT research. Journal of Soka Women's College, 40, 101-130.
Ishikawa, T. (2012). Distribution of Different Types of Hesitation Phenomena and Their Patterns of Correlations (1). Journal of Soka Women's College, 43, 39-59.
Shriberg, E. (1994). Preliminaries to a theory of speech disfluencies. Unpublished doctoral dissertation, University of California, Berkeley.
Tanaka, S., & Nakano, H. (2012). js-STAR. [software]. Available from http://www.
kisnet.or.jp/nappa/software/star/freq/chisq_lxj.htm
Wolfe-Quintero, K., Inagaki, S., & Kim, H. (1998). Second language development in writing: Measures of fluency, accuracy, and complexity. University of Hawaii:
Second Language Teaching and Curriculum Center.
Author Note
I thank Professor Peter Robinson at Aoyama Gakuin University for his consistent encouragement throughout my academic life. Thank are also due to Dr. Elizabeth Shriberg at Speech Technology & Research Laboratory, CA, for her useful advice on disfluency analysis and coding, and Dr. Francesc Tarr?s at the Universitat Polit?cnica de Catalunya, Spain, for his permission to use his face database in the present study, which was created by F.Tarr?s and A. Rama, or "GTAV Face Database" available at http://gps-tsc.upc.es/
GTAV/ResearchAreas/UPCFaceDatabase/GTAVFaceDatabase.htm).
Section Chief
DISTRIBUTION OF DIFFERENT TYPES OF HESITATION PHENOMENA
Appendices
Appendix A. Simple-reasoning task
Mike
C._ Secretary
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Appendix B. Complex-reasoning task
Section
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Secretary
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Section Chief
Section Chief
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Appendix C. Instructions for the No Reasoning Task
In this task, you will play the role of a company's general manager. Today you are supposed to report to the president about the human relations between people in your section, which was established a week ago. In order to report to the president, you decided to make a phone call but the president was not at home. Now, you have decided to leave a message on his answer machine.
Performance goal: As general manager, report to the president in English about the human relations of the new section by leaving a message on the president's answer machine.
Below is an explanation of your task.' , } "°'.°
You will be given a task sheet.
The task sheet contains the following information:
• Persons' names , pictures, and positions in the section.
• Links between the section members' pictures: Good human relations are represented by blue solid lines and non-good human relations by red
broken lines.
human relations, names, pictures, and positions
Information on the task sheet
DISTRIBUTION OF DIFFERENT TYPES OF HESITATION PHENOMENA191 When you report to the president, please keep in mind the following points
• Describe the current human relationships of the office members to the president. Assume that the president does not have any information about
the section.
If you have questions, you can ask now. If you have no questions, please read the "Performance goal" one more time. You have three-minute planning time. Also, note that the maximum time length for recording of the answering machine is three minutes.
Appendix D. Instructions for the Simple Reasoning Task
In this task, you will play the role of a company's general manager. Today you are supposed to report to the president about the human relations between people in your section, which was established a week ago. But yesterday trouble happened and human relationships between the section members changed. In order to report to the president, you decided to make a phone call but the president was not at home. Now, you have decided to leave a message on his answer machine.
Performance goal: As general manager, report to the president in English about the trouble and changes in human relations by leaving a message on the president's answer machine.
Below is an explanation of your task.
You will be given a task sheet.
The task sheet contains the following information:
• Arrows (•), which represent unspecified processes of human relation- ship changes.
• Persons' names , pictures, and positions in the section.
human relations
before the 11.^111^
trouble, names, pictures, and positions
human relations before the
trouble, names, pictures, and positions
Information on the task sheet
• Links between the section members' pictures: Good human relations are represented by blue solid lines and non-good human relations by red broken lines.
When you report to the president, please keep in mind the following points
• You will receive a list of job mistakes. Choose just one mistake, which is a trouble trigger, not the direct cause of the human relationship changes.
Assign the selected trouble trigger to one person.
• Please explain why the human relationships in your section changed.
Assume that the president does not have any information about the
section.
If you have questions, you can ask now. If you have no questions, please read the "Performance goal" one more time. You have three-minute planning time. Also, note that the maximum time length for recording on the answering machine is three minutes.
