Vol 10 No 4 - March 2015

International Journal
of
Learning, Teaching
And
Educational Research
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Vol.10 No.4

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VOLUME 10 NUMBER 4 March 2015
Table of Contents
A Study of Consonant Clusters in an EFL Context ............................................................................................................1
Ruhollah Khanbeiki and Seyed Jalal Abdolmanafi-Rokni
Do Emotional-Social Intelligence, Caring, Moral Judgment and Leadership of Physical Therapy Students Predict
their Clinical Performance? ................................................................................................................................................ 15
Hélène Larin and Jean Wessel
Integrating Teaching Resources and Assessment Tasks to Enhance Student Experience........................................... 28
Dr Sujana Adapa
Clustering Analysis of Attitudes of Prospective Computer Programmers towards Programming .......................... 40
Özcan ÖZYURT and Hacer ÖZYURT
Does Inquiry-Learning Support Long-Term Retention of Knowledge? .......................................................................51
Sarah Schmid and Franz X. Bogner
Enhancing Agricultural Education Lecturers’ Teaching Effectiveness in Nigeria Colleges of Education: The
Human Resource Supervision Perspective........................................................................................................................ 71
Camilus Bassey Ben and Ajigo Ikutal
Middle School Students Academic Motivation: A Missing Element in a General Education Quality Improvement
Program in Ethiopia ............................................................................................................................................................ 84
Abebe Kinde Getachew
Evaluating Asynchronous Discussion as Social Constructivist Pedagogy in an Online Undergraduate
Gerontological Social Work Course ...................................................................................................................................94
Cari L. Gulbrandsen, Christine A. Walsh, Amy E. Fulton, Anna Azulai and Hongmei Tong
The Amalgamation of Conventional Universities and Open/ Distance Learning and their Effects on Students’
Performances ...................................................................................................................................................................... 112
Saher H. EL-Annan Ph.D

1
International Journal of Learning, Teaching and Educational Research
Vol. 10, No. 4, pp. 1-14, March 2015
A Study of Consonant Clusters in an EFL Context
Ruhollah Khanbeiki
English Department, Science and Research Branch, Islamic Azad University,
Gorgan, Iran
Seyed Jalal Abdolmanafi-Rokni
English Department, Golestan University, Gorgan, Iran
Abstract
The objective of the present study was to provide answers to the questions
whether Persian learners of English would have the same number of vowel
insertions in the initial and final consonant clusters and also to see if the
phonological system of the Persian students' mother tongue would have any
effect on their learning of the pronunciation of the initial and final consonant
clusters. To this end, sixty female intermediate EFL learners were administered a
pronunciation test. The analysis of the participants' performances in the test
showed that the number of vowel insertions they had in the initial consonant
clusters was not the same as that of final consonant clusters, and using a chi
square displayed that the problem of vowel insertion was found to be much
more severe with initial consonant clusters as the participants highly added
vowels to such clusters. Furthermore, it was found that Persian language's
syllable structure does really affect the learning of consonant clusters (i.e.
transfer from mother tongue).
Keywords: pronunciation, consonant clusters, transfer, EFL learners
Introduction
Pronunciation is one aspect of the language teaching process that is tackled by
every L2 learner in his journey to acquire native-like proficiency in the target
language. For any learner to become proficient in an L2, he has to improve all
aspects of language, one of which is pronunciation. Mastering the pronunciation
of a language is highly important in terms of communication since in many cases
the replacement of one sound for another will result in changes in meaning,
hence affecting the flow of communication. Therefore, one of the aims of the
teachers must be training the students to pronounce sounds as native speakers
of the target language. Accordingly, analyzing the problems learners may face in
learning the accurate or at least an acceptable pronunciation of the target
language deserves to be thoroughly and intensively inspected.
© 2015 The authors and IJLTER.ORG. All rights reserved.

2
Playing the central role in face to face communication, pronunciation should also
be highly taken into account by English teachers. In fact, teachers should adopt
the approach that best helps students acquire native-like or intelligible
pronunciation so that they can become efficient members of the English-
speaking community in which they communicate and also so that they are not
known to have non-native pronunciation errors as such errors may place the
speaker at a professional or social disadvantage (Morley, 1991).
Although there has been little research on the teaching and learning of
pronunciation, "there is theoretical and technical work to help us understand the
processes involved in developing phonology in a second language and the
factors that contribute to it" (Lightbown & Spada, 2006, p. 104). The thing that
has helped a lot to explain some aspects of first language influence on second
language learners' phonological development has been contrastive analysis. One
example of L1 influence on L2 phonological development is Persian learners'
inability to correctly pronounce English consonant clusters. Actually, Persian
learners of English usually tend to insert vowels into English consonant clusters,
especially those that occur in the initial position. To Cook (1991), L2 learners do
this to make English conform to the syllable structures of their first languages.
According to Keshavarz (2008a), such a tendency on the part of Persian learners
of English is because Persian syllable structure does not allow initial consonant
clusters. To him, Persian learners of English say ‘I e-speak e-Spanish’ instead of
‘I speak Spanish’ because they are unaware of the ways English consonants can
be combined to form the so-called consonant clusters and also because they have
got used to Persian syllable structure. Cook (1991) maintains that some of the
problems L2 learners have regarding the issue of pronunciation learning is
related to the differences between the syllable structure of the two languages, i.e.
the combinations of consonants and vowels, rather than the differences between
single phonemes. Thus, the failure of the Persian learner to correctly pronounce
the word 'speak' without the epenthetic vowel is because he/she is unaware of
the ways consonants can be combined in English- the permissible consonant
clusters.
Therefore, one way to explain the problems Persian learners have in learning the
rules of consonant cluster present in English syllable structure is through CAH
(contrastive analysis hypothesis). As the name implies, the most important aim
of CAH is to compare and contrast two specific languages to find the similarities
and differences between them. Using the findings of CAH, contrastivists try to
predict the probable errors learners will encounter during their process of
learning a second language with the aim of preventing learners from making
those errors in advance (Keshavarz, 2008b). James (1980) claims that CA is done
at different levels of language consisting of phonology, morphology and syntax.
Therefore, as related to the present study, one of the aims of CAH is to find the
similarities and differences between two specific languages in the area of
phonology.

3
According to Ziahosseiny (2006), teachers and textbook writers use CAH to find
out which aspects of language are similar to or different from the students'
mother tongue. The general belief is that the degree of the difference between
the learners' native language and the target language can bring about greater
difficulty. Lightbown and Spada (2006) point out that the evidence supporting
the CA hypothesis originates partly from the observation that it takes learners
longer to become highly fluent in a particular second or foreign language if that
language is considerably different from their first languages. Thus, the learners'
first language plays an important role in the development of second or foreign
language phonology.
As Lightbown and Spada (2006) continue, there are some other factors, such as
the amount and type of exposure to the target language and the degree of use of
the first language, that substantially contribute to the development of
pronunciation. Piske, Mackey, and Flege (2001), based on some studies, have
found that the longer the students are exposed to a language, the more their
pronunciation will improve (Lightbown & Spada, 2006). They also found that
the greater they continue to make use of their first language, the stronger their
accents in the second language will be. Therefore, CAH enables the teacher to
know how easy or difficult a particular aspect of language will be for a
particular group of students with a particular mother tongue (Ziahosseiny,
2006).
In fact, Ziahosseiny (2006) maintains that if the aspect is easy, the teacher will
devote less class time to that aspect, and if it is difficult, more time and more
exercises will be devoted to that particular aspect of the language. He also points
out that the other users of the findings of CAH are textbook writers whose
intention is to decide which aspects of the language should be presented first
and which later, based on the degree of difficulty.
Transfer from Mother Tongue and the Learning of Consonant Clusters
Hudson (2000), discussing the main reasons for the superiority of child first
language acquisition over adult second language learning, points out that the
reasons for this dominance are rooted in ‘cognitive, affective, and biological
differences’ between adults and children. He explains that cognitive differences
refer to the ability on the part of adults to consciously process their knowledge
of things, including knowledge of language. To him, adults' ability to
consciously process language is due to their having analytic and meta-linguistic
knowledge about the language, i.e. their ability to talk about language and how
it works. Moreover, as he continues, adults have ‘prior knowledge of their native
language’.
Lightbown and Spada (2006) maintain that this prior knowledge can be an
advantage in the sense that learners have an idea of how languages work.
However, they continue that it can also be a drawback when it causes learners to
make interferential errors. In fact, according to Hudson (2000), adults have some
expectations, based on their native language, about the target language.
Interferential errors, to him, occur when their expectations about the target
language are incorrect because the two languages are different from each other

4
with respect to a specific rule. That’s why transfer, as contrastivists maintain,
plays an important role in learning a second language. Actually, to Lado (1957),
language transfer has always been fundamental to any theory of second
language phonological development. The terms that seem necessary to be
explained here are transfer, interference, and overgeneralization.
Followers of behavioristic psychology think that when a person learns two
specific things successively, the first learning affects the second one
(Ziahosseiny, 2006). To Carl James (1980) this influence is called ‘transfer’. In
fact, he (p. 11) defines transfer as "the effects of one learning task on a
subsequent one". According to Hudson (2000), transfer is the influence that
earlier knowledge has on the acquisition of later knowledge. Ziahosseiny (2006)
and Hudson (2000) declares that transfer can happen in two ways: positive or
negative. To them, if the first learning is similar to the second one, then positive
transfer happens. The outcome of positive transfer is that the first learning helps
the second one, i.e. makes it easier. However, if the first learning is different
from the second one, then negative transfer happens; that is, the first learning
causes difficulty for the second one.
According to Brown (2000), negative transfer can be referred to as ‘interference’.
Hudson (2000) maintains that negative transfer occurs when categories in L1 and
L2 are similar to each other in some ways but different in others. He continues
that such categories may present persistent problems of transfer referred to as
interference. To him, foreign accent, which is so common in adult language
learning, is mostly because of transfer of phonological categories. Ziahosseiny
(2006) maintains that more time and exercise is needed for the learner to be able
to overcome the difficulty made by interference.
As far as the acquisition of second language phonology is concerned, Kranke
and Christison (as cited in Richards & Renandya, 2002) declare that interference
from learners' first language affects the acquisition of the second language sound
system more than other systems (such as grammar). That’s why, as Jones and
Evans (1995) claim, a large number of teaching pronunciation materials include
sections on contrastive analysis. These sections, though helping teachers predict
where their students will make a mistake and which forms are more difficult for
them to learn, are often misleading because these predictions are usually made
for individual sounds and sound segments not for supra-segmental features that
are usually overlooked in these books. The important question which is very
much in debate is "the extent to which inter-language phonology is affected by
L1 transfer" (Richards & Renandya, 2002, p. 181).
According to contrastive analysts, the most important factor that affects
language learning in general and pronunciation learning in particular is
interference from mother tongue. Actually, as Brown (2000) maintains, the early
stages of learning an L2 are especially in danger of inter-lingual transfer from
the native language, or interference (Cook, 1991). They continue that in these
beginning stages, before getting familiar with the system of the second language,
the learner makes use of his native language as the only easily accessible

5
linguistic system. To Brown (2000), while all errors cannot be the result of
transfer from mother tongue, many such errors can be seen in learner speech. He
believes that once learners have passed the beginning stages of learning an L2,
more and more 'intra-lingual' transfer is manifested, i.e. more universal
processes of acquisition common to both L1 and L2 can be seen in the learners'
speech. Thus, his suggestion for teachers is that they should be familiar with
their learners' native language so that they can more easily detect and analyze
their errors.
While transfer from mother tongue, as explained above, has been known by
contrastive analysts as the only source of pronunciation errors made by learners,
other sources are also explained by different researchers during the past century.
Tarone's (1978) claim is that transfer forms only one of the factors affecting the
inter-language phonology while other factors such as overgeneralization,
approximation, and avoidance are much more important. Fledge (1987) points
out that learners, once facing a new sound system, compare it with their L1
sound system. He continues that if they find the two systems similar to each
other, they use their existing categories; however, when they run into unknown
features, they create new categories. Eckman (1977) uses the term ‘markedness’
to talk about the features that are naturally more difficult than others
irrespective of the learners' first language.
According to Ziahosseiny (2006), contrastivists believing in the strong version of
CAH assume that the degree of difficulty depends upon the degree of
differences. In other words, the more different the items are, the more difficult
they will be for learners to learn. Thus, based on the strong version of CAH, it is
interference due to negative transfer that is the only source of all errors. In other
words, as Brown (2000) asserts, based on the strong version of CAH, second
language learning is principally a process of acquiring whatever items are
different from the first language. However, this is not true because, as
Ziahosseiny (2006) maintains, interference forms only one third of the errors
made by second language learners and such a narrow view of interference
overlooks the intra-lingual effects of learning.
Therefore, based on the strong version of CAH, it is the syllable structure of
Persian language that causes errors on the part of Persian learners of English to
accurately pronounce English consonant clusters (Keshavarz, 2008a). According
to Keshavarz (2008b), when encountering a word that contains initial consonant
clusters, the Persian learner of English negatively transfers his knowledge of
Persian syllable structures to pronounce that specific word. He continues that
this is because of the fact that initial consonant clusters are not allowed in
Persian; therefore, Persian speakers insert a vowel before or in between the
cluster to make it easier to pronounce. Thus, they pronounce the word ‘street’ as
/ɛstɛrit/ and ‘tree’ as /tɛri/.
Cook (1991), explaining the reason why most L2 learners find it difficult to learn
English consonant clusters, states that part of interlanguage phonology is the
rules for forming syllables. To him, L2 learners, before leaning the rules

6
underlying English syllable structure, often try by one means or another to make
the L2 syllables fit their L1s. Simply stated, they make L2 syllables conform to
the syllable structures of their first languages by inserting extra vowels among
English consonant clusters. Examples are Koreans saying /kəla:s/ for 'class' or
Arabs saying /bi læstik/ for 'plastic'.
Prator (1967), a proponent of the strong version of CAH, has made a hierarchy
that shows the degrees of difficulty of different items of language (Keshavarz,
2008b). Based on this hierarchy, initial consonant clusters can be put in level 4,
which is over differentiation. Keshavarz (2008b) and Brown (2000) define over
differentiation as: a new item which is completely different from the native
language must be learned entirely. According to Keshavarz (2008b), initial
consonant clusters must be very difficult for Persian learners of English to learn.
However, according to the weak version of CAH, as Ziahosseiny (2006) asserts,
when a phonological error (such as the Persian learner being unable to correctly
pronounce the English sounds [θ and ð]) occurs, it is not due to the interference
of the first learning with the second one; rather, it is owing to the fact that the
learner has not yet learned how to say the English sounds, so he draws upon the
sounds from his first learning. In other words, he gets help from Persian, not
that Persian interferes with his learning. Therefore, based on the weak version of
CAH, and as far as the learning of English consonant clusters is concerned, the
Persian learner's adding epenthetic vowels to initial consonant clusters is not
due to the interference of the first learning (Persian) with the second one
(English); rather, the learner gets help from Persian to pronounce English
consonant clusters via the use of the Persian syllable structure or as Cook (1991)
maintains he carries over a feature of his first language phonology into English.
As opposed to the strong and weak versions of CAH, which state that learners of
a foreign language learn on the basis of differences, the moderate version of
CAH assumes that errors are made on the basis of similarities, not differences
(Ziahosseiny, 2006). In other words, as Ziahosseiny (2006) claims, learners make
errors in learning a specific item because they consider that particular item to be
similar to the one they already know. To explain, the more the new item to be
learned is similar to the one the learner already has in his mind from his first
language, the more difficult it will be for him to learn that particular item. As for
initial consonant clusters, the Persian learner has not yet come across such a
structure (initial consonant clusters) in his L1. Thus, he thinks it is similar to the
one he already knows (the syllable structure of Persian language). That is why
he makes use of Persian syllable structure instead of the structure of English
syllables to pronounce initial consonant clusters.
As a result and based on the literature existing in the area of pronunciation
learning, the conclusion Keshavarz (2008b) offers is that errors made by Persian
learners of English in pronouncing consonant clusters can be classified as inter-
lingual errors (interference), rather than intra-lingual ones (overgeneralization).
In other words, the source of error is not found in the students' target language
(English), but in their mother tongue (Persian). He explains that this

7
phonological error (mispronouncing English consonant clusters by Persian
learners) is made because of the differences in the syllable structure of the two
languages (English and Persian). According to him, no initial consonant cluster
is permitted in Persian, i.e. each consonant in the initial position is either
preceded or followed by a vowel. As a matter of fact, he claims that students
usually tend to transfer the pronunciation features of their mother tongue to the
sound system of the L2. Hence, he continues that it is not surprising that
Persian-speaking learners of English pronounce words such as ‘school’ and
‘street’ as /esku:l/ and /esterit/, and ‘try’ and ‘class’ as /terai/ and /kelas/,
respectively.
Having discussed the reasons for student errors in the area of pronunciation, the
research will now offer the methods presented by different approaches to
language teaching in the 20th century for how to remove such errors from the
students' speech. It will also review the researches done in this area. The two
common methods presented by the various approaches to language teaching
over the past century for the teaching of phonology, as mentioned earlier in this
paper, have been explicit versus implicit and there has always been a hot debate
about which one is more effective.
Objectives of the Study
To achieve the purpose of the study, the following two null hypotheses are
formulated as follows:
H1: Persian learners of English have the same number of vowel insertions
in the initial and final consonant clusters.
H2: The phonological system of the Persian students’ mother tongue has
no effect on their learning of the pronunciation of the initial and final consonant
clusters.
Methodology
Participants
The sample in this study included 60 female intermediate EFL learners studying
English at a language school in Gorgan. They aged between 15 and 17 and were
selected from a whole population of 152 students who were initially asked to
participate in the study from three different language schools in Gorgan, Iran.
Instrumentation
A pronunciation test was used in this study. The aim was to see whether the
selected sample had vowel insertion while pronouncing the English words with
initial or final consonant clusters and if yes, whether the amount of vowel
insertion was the same in such clusters. The statistics performed on this test
could help the researcher accept or reject the first hypothesis. Moreover,
comparing the number of times the students had vowel insertion in the initial
consonant clusters against those in the final consonant clusters and performing
statistics on these numbers could help the researcher decide whether the
students' native language (Persian) had any effect on their pronunciation of the
initial or final consonant clusters, thereby accepting or rejecting the second
hypothesis. The test included 50 words, half of which contained different initial

8
consonant clusters and the other half covered different final consonant clusters.
The words chosen for the students to pronounce were those they already were
familiar with; therefore, the researcher was sure that the words' level of
difficulty is in accordance with the participants' knowledge of the English
language. The students were asked to read the words aloud while they were
voice-recorded. The test was by no means difficult for the students to read as no
word was new and unfamiliar to them. In fact, the words in the test were chosen
from their own textbook so that the researcher could make sure that the words'
level of difficulty is appropriate to the students' level of English knowledge.
However, before each test was given to them, they were asked to carefully scan
the words to see whether or not they knew the meanings of all words. In the test
the researcher listened to how each student read the words, giving a score to
that student based on the way he pronounced initial or final consonant clusters.
For the scores to be reliable, two other English teachers analyzed the students'
pronunciations and scored them, counting their errors in pronouncing different
consonant clusters. It is worth mentioning that the three scorers had attended
teacher training periods, and thus were highly experienced and skilled in doing
so. In this study, they were asked to score the students only based on their
pronunciation of consonant clusters, and to pay no attention to other aspects of
pronunciation, such as stress. This way the scores given by the three scorers
could be reliable. The scales used for rating the results of the tests were interval.
Data Analysis
Since the two hypotheses dealt with frequencies, and also because the variables
in them were nominal (i.e. categorical) in nature, the number of times the
students inserted vowels in the initial and final consonant clusters in the test
were counted and the percentages of such vowel insertions were calculated. The
results could show whether or not Persian learners of English insert vowels in
the initial or final consonant clusters.
Using a chi square (x2), the frequencies of the vowel insertions in the initial
consonant clusters were then compared with those in the final consonant
clusters. The results would show whether or not Persian learners of English
would have the same amount of vowel insertion in the initial consonant clusters
with those in the final ones. The significance level for the chi square (x2) was set
at .01 (p < .01). Moreover, counting the number of times the participants had
vowel insertion in the initial or final consonant clusters could show whether the
syllable structure of the Persian language would have any effect on the learning
of each cluster (initial or final).
Results
First Hypothesis
H1: Persian learners of English have the same number of vowel insertions in the
initial and final consonant clusters.
Table 1 shows how many vowel insertions the samples had for the initial
consonant clusters in the test. It is worth mentioning that there were 50 words in
the test 25 of which contained initial consonant clusters and the remaining 25
contained final consonant clusters.

9
Table 1: Number and Percentage of Vowel Insertions for the Initial Consonant
Clusters
Words
containing initial
consonant
clusters
Number of words
pronounced with
undue vowel
insertion
Number of words
pronounced
without vowel
insertion
Percentage of
vowel insertion
25 22 3 88%
As Table 1 shows, in 88% of the cases the sample inserted vowels in the initial
consonant clusters. Thus, it can be concluded that Persian learners of English
highly add vowels in the initial consonant clusters. Table 2 shows how many
vowel insertions the sample had for the final consonant clusters in the pre-test.
Table 2: Number and Percentage of Vowel Insertions for the Final Consonant Clusters
Words
containing final
consonant
clusters
Number of words
pronounced with
undue vowel
insertion
Number of words
pronounced
without vowel
insertion
Percentage of
vowel insertion
25 4 21 16%
As Table 2 shows, only in 16% of the cases the sample inserted vowels in the
final consonant clusters. Thus, it can be concluded that Persian learners of
English do not have much vowel insertion in the final consonant clusters.
Since the first hypothesis deals with frequencies and because both the
independent and the dependent variables in the hypothesis were nominal (i.e.
categorical), the chi square (x2) was used to compare the frequencies and to
determine whether the number of times the samples had vowel insertion in the
initial and final consonant clusters were the same. The results of the chi square
analysis, based on Table 3, shows that there is a significant relationship between
having the same or different number of vowel insertions in the initial and final
consonant clusters at the alpha level of .01 (x2:23.12; df:1; p<.01). In other words,
Persian learners of English do not have the same number of vowel insertions for
the initial and final consonant clusters. Based on the findings illustrated in Table
3, the first hypothesis is rejected at the alpha level of .01.
Table 3: Chi Square Tests
Value Df Asymp. Sig.
(2-sided)
Exact Sig.(2-
sided)
Exact Sig.(1-
sided)
Pearson chi square
Continuity
correction a
Likelihood ratio
Fisher's Exact test
Linear-by-Linear
25.962b
23.157
28.905
25.442
50
1
1
1
1
.000
.000
.000
.000
.000 .000

10
Association
N of valid cases
a. computed only for a 2x2 tables
b. 0 cells (.0%) have expected count less than 5. the minimum expected count is
12.50.
Second Hypothesis
H2: The phonological system of the Persian students' mother tongue has no
effect on their learning the pronunciation of the initial or final consonant
clusters.
Like the first hypothesis, this hypothesis also dealt with frequencies. In fact, the
aim of the second hypothesis was to decide whether or not the syllable structure
of the Persian language has any effect on the pronunciation of the English words
containing the initial and final consonant clusters. Again, as the dependent
variable was nominal in nature dealing with frequencies and with respect to the
results acquired from the first hypothesis, only descriptive statistics were needed
and the only thing the researcher had to do was to compare the percentages of
the times the samples inserted vowel in each kind of consonant cluster.
As Tables 1 and 2 show, because in 88% of the times the selected sample made a
mistake in pronouncing the initial consonant clusters, the conclusion is that it is
the syllable structure of the Persian language that is causing them to add extra
vowels to the English words containing initial consonant clusters. This outcome
agrees with the findings of the recent researches saying initial consonant clusters
do cause great difficulty for Persian learners of English since such clusters are
not allowed in Persian language (Keshavarz, 2008b). However, with respect to
the words containing the final consonant clusters, it cannot be claimed that the
Persian syllable structure is deterring them from learning the rule because in
only 16% of the cases they made a mistake in pronouncing the words with the
final consonant clusters while the test showed that they were unaware of the
rule.
Thus, the second hypothesis can be rejected because Persian language does
really affect the learning of consonant clusters. Actually, with regard to initial
consonant clusters, the effect is negative (i.e. the Persian syllable structure is
preventing them from learning the rule) while regarding final consonant clusters
the effect is positive (i.e. it is not preventing them from learning the rule).
Discussion & Conclusion
The goal of the present study was to find out whether initial or final consonant
clusters are more difficult for Persian students to pronounce correctly, i.e.
without vowel insertion. The other secondary aim was to investigate whether
other factors such as the phonological system of the students' mother tongue
have any effect on the learning of the rule. The study was conducted inside an
educational environment and under real conditions pervasive in language
institutes so that the findings could be applicable in Iranian schools.

11
Moreover, the reason why some consonant clusters, such as those starting with
stops followed by approximants (as in the words 'dress', 'tree', 'green' and 'blue'),
were difficult for the participants to pronounce correctly, i.e. without vowel
insertion could be the existence of a gap between explicit knowledge and use. In
fact, as discussed by DeKeyser (2003), it takes a long time and needs much
practice for the explicit declarative knowledge to develop into fully implicit,
automatized procedural knowledge. That is why the participants' being aware of
the English consonant cluster rules did not guarantee their correct production of
such clusters. Thus, the only thing that can gradually bridge the gap between
explicit knowledge and use is practice. In other words, more time, more practice
and also more exposure are needed for the automatic processing to occur.
Regarding the objectives of the study, the participants' performances on the test
were analyzed and the finding showed that Persian learners of English do not
have the same number of vowel insertions in the two kinds of consonant
clusters. It was also found that the problem was much more severe with initial
consonant clusters as some of such clusters were too difficult for the students to
pronounce correctly. The differences between the phonological systems of the
two languages were found to be the source of a great number of participants'
mistakes in correctly pronouncing the words containing initial consonant
clusters. As Persian does not allow initial consonant clusters, Persian learners of
English would face serious problems in accurately pronouncing such clusters.
However, the problem was not found to be so serious for final consonant
clusters where the participants had nearly no vowel insertion. In fact, and based
on the results, only in 16% of the times, the sample inserted vowels in final
consonant clusters. This percentage is too low to conclude that the participants
have vowel insertion in final consonant clusters. This is because Persian syllable
structure allows two consecutive consonant clusters in the final position. Thus, it
can be said that they are familiar with such clusters in their own mother tongue,
causing them to have no problem pronouncing the words containing two final
consonant clusters (as in the words 'bend, pant, cold') and even to tolerate those
containing longer final clusters (i.e. to have no undue vowel insertion) (as in the
words 'texts, words, girls, things, crafts). Even when a word, containing long
final consonant clusters, was too difficult to articulate without vowel insertion,
they resorted more to 'elision' rather than 'vowel insertion', the act which is also
common to native English speakers themselves.
Actually, it is noticeable in English that in casual conversational speech, large
consonant clusters, especially those occurring in final position, are frequently
reduced as they are usually difficult for even native speakers to pronounce
(Keshavarz, 2008a). Thus, it is not surprising to hear them pronounce the word
'depths' as /dɛps/, and similarly the word 'acts' as /æks/. Sometimes, the
participants also managed to avoid elision without having undue vowel
insertion by reducing the speed of pronunciation, leading them to having
artificial articulations. In fact, reducing the speed of articulation is one of the
solutions through which foreign speakers of a language manage to keep their
accuracy. But this way they lose their fluency (i.e. the effect of accuracy on

12
fluency). Therefore, explicit knowledge about language rules can affect learners'
fluency.
The only final consonant clusters for which the participants couldn't help
inserting vowels were those containing dental fricatives such as /ɵ/ and /ð/
followed by /s/ and /z/, respectively (as in the words 'strengths', 'depths',
'twelfths', 'truths', 'breathes'). The combination of affricates such as /ʤ, ʧ/
followed by /d/ was also difficult for them to pronounce at first, but again the
participants managed to solve the problem by reducing the speed of articulation
(as in the word 'changed').
Nearly all of the words containing initial consonant clusters in the test were
found to be difficult for the participants to pronounce correctly. The fact that in
88% of the words, the participants inserted vowel in initial consonant clusters is
suggestive of the depth of their difficulty regarding such clusters. However, the
problem was not the same with all such clusters. In other words, the participants
did not have the same degree of vowel insertion in all initial consonant clusters.
The problem was found to be more severe in clusters with three consonants in
the initial position beginning with /s/, such as 'spring, strong, stress'. However,
in the words containing two clusters in the initial position, the combinations of
fricatives such as /f/ or /ɵ/ and approximants /r/ or /l/ in the words 'fresh,
flash, throw' were the easiest for the participants to learn (i.e. although they had
vowel insertion at the beginning, they learned such clusters sooner than the
others). However, the combination of /k/ and /l/ in the word 'class' (especially
when /l/ was followed by /ɒ/ in the word 'clock') was a little more difficult for
the participants to learn. The most difficult combinations were those of /dr/,
/tr/, /gr/ and /bl/ (i.e. the combinations of stops and approximants) in the
words 'dress', 'tree', 'green' and 'blue'.
The findings of the research are highly consistent with the CA hypothesis, based
on which the degree of difference between learners' native language and the
target language can bring about greater difficulty. According to this hypothesis,
the more different the two languages are, the more difficult it will be for learners
to learn the target language. Therefore, initial consonant clusters must be much
more difficult for Persian learners to learn than their final counterparts as the
degree of difference between English and Persian is greater in such clusters. In
fact, based on the CA hypothesis, they will need much more practice and
exposure to such clusters to be able to learn the true articulation of English
words containing initial consonant clusters.
Furthermore, it was found that Persian language's syllable structure does really
affect the learning of consonant clusters. In fact, based on the results of the first
hypothesis, it can be concluded that it is transfer from mother tongue, rather
than over generalization, that affects the students' learning of consonant cluster
rules. To explain, because the phonological system of Persian students' mother
tongue is completely different from that of English language with respect to
initial consonant clusters, negative transfer happens in such clusters. However,
because the two systems of Persian and English are not so different in final
consonant clusters, positive transfer occurs for such clusters. In fact, due to the

13
fact that Persian language's syllable structure is not so restrictive with respect to
the final consonant clusters, its speakers, being familiar with such clusters in
their mother tongue, do not find it so difficult to pronounce the English words
containing such clusters. Therefore, the conclusion is that the pronunciation
system and patterns of the learners' mother tongue strongly influence the
learning of those of the target language, and learners probably make more
mistakes in areas in which the two systems do not match.
The study also showed that language transfer plays a highly fundamental role in
the early stages of phonological development. With respect to the teaching of
English consonant clusters to Persian learners, the study proved that Persian
learners highly use their knowledge of L1 of syllable structure to pronounce the
English words containing such clusters. It also showed that due to the rule's
being semantically redundant, the students are unable to learn the syllable
structure of English regarding consonant clusters by themselves. Thus, they
need to be explicitly instructed.
Moreover, the fact that many advanced learners of English can also be observed
inserting vowels in consonant clusters can verify the results. To explain, due to
the fact that the rules underlying English consonant clusters are not salient,
Persian learners of English continue inserting vowels unless they are instructed
by the teacher in the classroom or unless their errors are corrected by native
speakers in naturalistic settings. Thus, the authorities in charge of planning the
educational strategies in Iran should reconsider their perspectives on the issue of
pronunciation.
References
Brown, H.D. (2000). Principles of language learning and teaching (Fourth edition). White
Plains: Longman.
Cook, V. (1991). Second language learning and language teaching. New York: Edward
Arnold.
DeKeyser, R. (2003). Implicit and explicit learning. In Doughty & Long, The handbook of
second language acquisition. Oxford: Blackwell Publishing.
Eckman, F. R. (1977). Markedness and the contrastive analysis hypothesis. Language
learning, 27, 315-330.
Flege, J. (1987). A critical period for learning to pronounce second languages? Applied
linguistics, 8, 162-177.
Hudson, G. (2000). Essential introductory linguistics. Massachusetts, USA: Blackwell
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James, C. (1980). Contrastive analysis. Bangor, Wales.
Jones, R. H., & Evans, S. (1995). Teaching pronunciation through voice quality. Retrieved
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Keshavarz, M. H. (2008a). Contrastive analysis and error analysis. Tehran: Rahnama Press.
Keshavarz, M. H. (2008b). A practical course of English phonetics and phonology. Tehran:
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Morley, J. (1991). The pronunciation component in teaching English to speakers of other
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Piske, T., Mackey, I. R. A. & Flege, J. E. (2001). Factors affecting degree of foreign accent
in an L2: A review. Journal of phonetics, 29, 191-215.
Prator, C. H. (1967). Hierarchy of difficulty. University of California, Los Angelos.
Richards, J.C. & Renendya, W.A. (2002). Methodology in Language Teaching. Cambridge:
Cambridge University Press.
Tarone, E. (1978). The phonology of interlanguage. In J.C. Richards (Ed.), Understanding
second and foreign language learning (pp.15-33). Rowley, MA: Newbury House.
Ziahosseiny, S. M. (2006). Questions and answers on contrastive analysis and error analysis.
Tehran: Rahnama Press.

15
Vol. 10, No. 4, pp. 15-27, March 2015
Do Emotional-Social Intelligence, Caring, Moral
Judgment and Leadership of Physical Therapy
Students Predict their Clinical Performance?
Hélène Larin
Ithaca College
Ithaca, NY, U.S.A.
Jean Wessel
McMaster University
Hamilton, ON, Canada
Abstract. Although non-cognitive characteristics are increasingly valued
in physical therapists, their contribution to the development of physical
therapy students has not been well established. The purpose of this
study was to ascertain whether measures of emotional-social intelligence
(ESI), caring, moral judgment and leadership predict clinical
performance of physical therapy students. Sixty physical therapy
students, mean age 21.4 years, from two Masters entry-level programs,
volunteered to participate in the study. At the beginning of their
professional studies (entry), before and after 2 clinical affiliations, and at
the end of their academic programs, the students completed four self-
report questionnaires (independent variables): the Caring Ability
Inventory (CAI), the Defining Issues Test (DIT-2) for moral judgment,
the Self-Assessment Leadership Instrument (SALI), and the Bar-On
Emotional Quotient Inventory Short (EQ-i:S) for ESI. For each
instrument, higher scores represent higher levels of the construct being
measured. The students were evaluated at each clinical affiliation by
means of the Clinical Performance Instrument (CPI) (dependent
variable). Correlations and regressions were performed to determine the
relationship between the independent variables and the scores on the
CPI. Results indicated that the EQ-i:S Total at entry was the only
independent variable significantly correlated (r=0.25-0.43) with the
average CPI scores (total and selected performance criteria) from the
first two clinical affiliations. The CPI from the final affiliation could not
be used in the analyses because most scores were close to the maximum
score of 100 (mean=98.8). In conclusion, ESI was significantly correlated
to clinical competence, but the non-cognitive measures of ESI, caring,
moral judgment and leadership could not adequately predict the clinical
performance of physical therapy students.
Keywords: emotional-social intelligence; caring; moral judgment;
leadership; clinical performance

16
Introduction
Over the course of their studies, physical therapy students in North America are
expected to develop competencies in the cognitive, psychomotor and affective
domains. Professional knowledge and clinical skills are continuously measured
and graded against standards of practice. Attitudinal competencies are often
inferred although there is also a need to assess them through observations of the
students‟ actions and interactions (Danielsen & Cawley, 2007). The attitudinal
aspects of professionalism are associated with the core values of physical
therapy (Ries, 2013). Students are expected to develop as „caring‟ and „ethical‟
health care professionals with „leadership‟ qualities and skills (American
Physical Therapy Association, 2004a; American Physical Therapy Association,
2004b; Gersh, 2006; Schafer, Lopopolo, & Luedtke-Hoffmann, 2007). Moreover
the American Physical Therapy Association (APTA) has developed continuing
education modules in emotional intelligence and ethics, and increasingly
encourages students to participate in various leadership programs (American
Physical Therapy Association, 2013).
Not only do educators want to instill these core values in their students, but they
would like to be able to measure these attributes and determine whether they
can predict success in the profession. Academic scores such as grade point
average (GPA) and Graduate Record Examination (GRE) have been correlated
with clinical performance of occupational and physical therapy students
(Balogun, 1988; Howard & Jerosch-Herold, 2000; Tan, Meredith, & McKenna,
2004; Watson, Barnes, & Williamson, 2000). However, other investigators have
found no relationship or weak correlations between GPA and clinical
performance (Balogun, 1988; Opacic, 2003; Thieman, Weddle, & Moore, 2003).
Few non-cognitive variables have been researched. Balogun (1988) reported that
an interview accounted for a greater percentage of the variance (34.6%) in
clinical performance of physical therapy students than GPA (7.5%). More
recently, Opacic (2003) found „self-efficacy‟ of physician assistant students,
measured at the beginning of their clinical year, to be significantly correlated
(r=0.16, p˂0.01) with their second-year clinical performance, while GPA and
previous experience were not. Nearly all authors suggested that non-cognitive
variables might assist in predicting students‟ clinical performance.
Review of Literature
Emotional-social intelligence (ESI), a relatively new, non-cognitive construct in
physical therapy has been investigated for its potential role in students‟
academic and clinical performance (Lewis, 2010; Lewis, 2011). Bar-On defined
ESI as “a multi-factorial array of emotional and social competencies that
determine how effectively we relate with ourselves and others and cope with
daily demands and pressures.” (Bar-On, 2002, p31). Boyce (2001) studied the ESI
of master‟s level physical therapy students using the Multifactor Emotional
Intelligence Scale. He reported low correlations between ESI and general
cognitive ability (on the Wonderlic Personnel Test), and between ESI and
academic success (GPA). Lewis (2010) showed no relationship between ESI
measured on the Mayer-Salovey-Caruso Emotional Intelligence Test and success
on the Clinical Performance Instrument (CPI) of 56 students enrolled in 4
different physical therapist entry-level education programs (2 at doctoral and 2

17
at master‟s levels). It appears from the study description that ESI was measured
after the CPI scores were obtained, and therefore could not be evaluated as a
predictor of clinical performance. In another study, Lewis (2011) found that the
ESI of 87 physical therapy students did not change over the course of their 3-
year education programs and had a low correlation with the CPI scores at the
end of the first and third years of study. However, Lewis did not provide
correlation coefficients between ESI and CPI for the various time periods.
Therefore, the potential of ESI as a predictor of future clinical performance could
not be determined from this study.
Caring is viewed as a critical component of physical therapy and also as a
dynamic, ethical relationship (Resnik & Jensen, 2003; Romanello & Knight-
Abowitz, 2000). It includes being client-centered and manifests itself in
communication (including listening), organization of infrastructure, and
advocacy for clients (Greenfield, Anderson, Cox, & Tanner, 2008; Resnik &
Jensen, 2003; Ries, 2003). Greenfield and colleagues (2008) conducted a
qualitative study of physical therapists in their first year of clinical practice. The
therapists valued caring, but struggled in providing „caring‟ services because of
difficult clients, stress, fatigue, time constraints and interdisciplinary issues.
These investigators (Greenfield et al., 2008) recognized that the attitudes and
skills required for caring accrue over time. They recommended that these
elements be developed during the physical therapy studies through the
integration of simulated patient cases followed by reflection and targeted clinical
experiences.
Moral Judgment is the reasoning process used to determine the moral thing to
do and the ability to behave in a moral manner (Bebeau, 2002; Rest, Thoma,
Narvaez, & Bebeau, 1997; Rest & Narvaez, 1994). Moral judgment has been said
to include three levels of functioning: codes of conduct imposed on the
individual, ethical concepts serving as guides of behavior of members of a
profession, and values broadly held by society (Thoma, 2006). Mature moral
reasoning measured on the Defining Issues Test (DIT) has been labeled
„principled‟ reasoning (Rest et al., 1997) represented initially as a P index and in
the DIT-2 as the N2 index. The few studies conducted on the DIT scores of
physical therapy practitioners or students have produced inconsistent findings.
Swisher (2010) reported lower P scores in practicing therapists compared to
other health professional practitioners and students. Dieruf (2004) found no
change in the P score of physical therapy students over the course of their
educational programs while Larin, Geddes and Eva (2009) and Geddes, Salvatori
and Eva (2009) described a significant increase in the N2 scores.
Moral judgment has been found to be predictive of clinical performance in
several health care professionals including physical therapists. Sisola (2000)
studied 58 physical therapy students in three programs and reported a
significant relationship (r=0.28) between the P scores at entry to the programs
and scores on the Clinical Competence Scale at the end of their first clinical
affiliation.
Leadership has been defined as “the means through which the content of practice
is professionally applied to the problems facing the physical therapist.” (Schafer

18
et al., 2007, p2). Although the physical therapy literature has described
philosophies and skills of leadership, little research has been conducted on the
effect of leadership on clinical performance. Gersh proposed Greenleaf‟s
philosophy of „servant-leadership‟ as a “unifying matrix for the enhancement of
professionalism and the focus of professional behaviors in physical therapy.”
(Gersh, 2006, p13). Using Delphi method and a national survey, investigators
(Lopopolo, Schafer, & Nosse, 2004; Schafer et al., 2007) have identified
leadership, administration, management and professionalism skills that
practitioners believe entry-level therapists should have. However, no studies
have examined the relationship of leadership ability and clinical performance
(Lopopolo et al., 2004; Schafer et al., 2007).
There are some associations among the variables of ESI, caring, moral judgment
and leadership. In an investigation of physical therapy and nursing students
entering their programs, ESI was correlated to two subscales of the Caring
Ability Inventory (CAI): Knowing (CAI_K) and Courage (CAI_C) (Wessel et al.,
2008). Leadership has been correlated with ESI in the field of administration
(Goleman, Boyatzis, & McKee, 2013), and in health science students (including
those in physical therapy) (Wessel et al., 2008). In the latter study, no
relationship was found between ESI and the N2 score of the DIT-2 (Wessel et al.,
2008).
The physical therapy profession views non-cognitive concepts as extremely
important, but few studies have measured these concepts and their ability to
predict the clinical competence of students. The purpose of this study was to
determine if ESI, caring, moral judgment and leadership of physical therapy
students are predictors of their clinical performance.
Participants
Physical therapy students from Ithaca College, Ithaca, New York and McMaster
University, Hamilton, Ontario were recruited to participate in the study.
Students in the Ithaca program were in the third year of an undergraduate
program but in the first year of their 3-year professional studies leading to an
entry-level master‟s degree in physical therapy. The McMaster students had
completed an undergraduate degree and were enrolled in the first year of a 2-
year (22 months) entry-level master‟s degree. The students were informed about
the study by e-mail or through an announcement in a class session. They were
offered a pizza snack or a $5.00 food voucher for their participation. The
interested students contacted the research assistant of their respective program.
Methods
Design: The data for this study was taken from a longitudinal investigation of
ESI, caring, moral judgment and leadership of physical therapy students as they
progress through their professional education program (Larin, Wessel, &
Williams, 2009; Larin, Benson, Wessel, Martin, & Ploeg, 2014). In the main
study, physical therapy students completed measures of ESI, caring, moral
judgment and leadership at entry to the program, following their first two
clinical placements (post-clinical) and at the end of their academic program. An
additional ESI measure was obtained just prior to their first clinical experience
(pre-clinical). Data were obtained from their performance in their first two and

19
their final clinical affiliations. Figure 1 illustrates the measures and time points of
interest in the present study.
Figure 1: Flow chart showing time points of data collection in the two physical
therapist education programs. T1-T4: Time 1 to T4; EQ-i:S: Emotional Quotient
Inventory Short; CAI: Caring Ability Inventory; SALI: Self-Assessment Leadership
Inventory; DIT-2: Defining Issues Test-2; CPI: Clinical Performance Inventory.
At entry, 60 students (39 from Ithaca College and 21 from McMaster University)
volunteered to participate in the study. The groups of students and their
characteristics at the beginning of the study are illustrated in Table 1. The project
received ethical approval from the ethics review boards of both institutions
involved in the study, and all subjects provided written informed consent.
Table 1: Characteristics of Subject Groups at Entry to their Programs.
Program N Class
Size
% of
Class
Male/Female
Subjects
Age
Mean (SD)
Ithaca Physical Therapy 39 67 58 7/32 20 (2.1)
McMaster Physical Therapy 21 59 36 1/20 24 (4.0)
Total 60 126 47.6 8/52 21

20
Educational Programs: The concepts of ESI, caring, moral judgment and
leadership are covered to some extent in both physical therapy programs.
Within the Ithaca College conventional curriculum, the subject of caring was
addressed during the discussion of the professional code of ethics and core
values in pre-clinical courses. Students delved into the topic further in a course
on psychosocial aspects of patient care, in the semester following their second
clinical affiliation. A set of professional behaviors was also outlined for the
students at the beginning of their program. Knowledge related to leadership was
found in two administration courses. At McMaster University, the subjects of
caring, moral judgment and leadership were intricate parts of the case scenarios
discussed during the problem-based tutorial sessions and were addressed in a
series of seminars on professional issues. Professional behaviors were explored
by the students in their tutorials and in the professional issues seminars. The ESI
topic, however, was not a primary focus of either program.
Instruments: The four independent variables were measured with self-report
instruments: the Bar-On Emotional Quotient Inventory Short (EQ-i:S) (Bar-On,
2002), the Caring Ability Inventory (CAI) (Nkongho, 2003), the Self-Assessment
Leadership Instrument (SALI) (Smola, 1988), and the Defining Issues Test (DIT-
2) (Bebeau & Thoma, 2003). These instruments are described in detail in a
previous publication (Larin et al., 2014).
In summary, the EQ-i:S is a measure of emotional and social intelligent
behaviors (Bar-On, 2004; Bar-On, 2006). The instrument comprises 51 items in
the form of short sentences that the respondents rate from 1 (very seldom or not
true of me) to 5 (very often or true of me). Standard scores, based on a mean of
100 and SD of 15, are reported for a total EQ-i:S and 5 subscales: Intrapersonal,
Interpersonal, Stress Management, Adaptability, and General Mood. A higher
score indicates greater ESI. Standard scores of 85-115 are considered „effective
functioning‟, greater than 115 „enhanced skills‟ and less than 85 „area for
enrichment‟. The CAI is a questionnaire designed to measure the degree of a
person‟s ability to care for others (Nkongho, 2003). It comprises 3 sub-scales:
Knowing (understanding of self and others), Courage (ability to cope with the
unknown) and Patience (tolerance and persistence). Respondents rate, on a scale
of 1 to 7, how much they agree or disagree with 37 statements (14, 13, 10
respectively per subscale) reflecting their thoughts and feelings about other
people in general. After reverse scoring of some items, the subscale scores are
calculated by summing the items in each subscale. Higher scores indicate a
greater degree of caring. The DIT-2 is a measure of moral judgment (Bebeau,
2002). Persons are presented with moral dilemmas. They must rank, on a 5-point
Likert scale, the relative importance of a series of 12 statements in determining
the appropriate action. The N2 score was used in the present study. Lastly, the
SALI is a measure of leadership characteristics (Smola, 1988). Respondents rate,
on a 5-point scale (0 to 4), how frequently they behave in the manner described
in each of 40 statements for a possible total range of 0 to 160. A higher total score
indicates higher self-assessment of leadership characteristics.
The dependent variable was measured using the first version of the APTA CPI
(American Physical Therapy Association, 1997) which was available at the time
this study was conducted and used by most programs. This tool comprises 24

21
performance criteria; each criterion is evaluated on a 100-mm visual analog scale
representing the span from novice to entry-level to practice. A total score for
each clinical affiliation is the mean of all criteria that are scored. Inter-rater
reliability of the total score has been reported as good (intraclass correlation
coefficient=0.87), and construct validity supported by various correlations
(American Physical Therapy Association, 2002). The CPI scores show significant
change as students progress through clinical placements, but tend to plateau
(with less variance) during the senior placements (Adams, Glavin, Hutchins,
Lee, & Zimmermann, 2008; Proctor, Dal Bello-Haas, McQuarrie, Sheppard, &
Scudds, 2010).
Analysis: Previous analyses of our data indicated minimal difference between
the scores of the two groups of students (Larin et al., 2009). Therefore, analyses
were performed using the total cohort of students. Pearson or Spearman‟s
coefficients were used to examine the correlation of all the variables. If
correlations with the CPI were at least 0.2, the variable would be included in a
regression equation to predict clinical performance. Regression equations were
originally planned as follows:
1) independent variables: EQ-i:S, CAI, SALI, DIT-2 at entry; dependent
variable: mean of CPI 1 and 2
2) repeat with dependent variable CPI final
3) independent variable EQ-i:S pre-clinical; dependent variable: mean of
CPI 1 and 2
4) repeat with dependent variable CPI final
5) independent variables: EQ-i:S, CAI, SALI, DIT-2 after first 2 clinical
experiences; dependent variable: CPI final.
Results
A total of 59/60 students (Ithaca 38, McMaster 21) completed the study from
entry to the end of their first two clinical placements. Two additional students
dropped out of the Ithaca program before the final clinical placement. The
clinical placement of another student was delayed. The means and SD of the
variables at all time-points are listed in Table 2 and the correlations in Table 3.
Some analyses were omitted or changed due to the nature of the data and the
results of the correlations. The variance of the final CPI scores was small among
the students, and therefore, correlations and regressions involving this variable
(intended analyses #2, #4, #5) were not performed. Because predictor variables
had weak or no correlation with the total score of the CPI, individual
performance criteria of the CPI were considered for analyses. It was thought that
questions relating to the students‟ manner of behavior in clinical interactions
(rather than technical skills or knowledge) might be better predicted from the
non-cognitive variables. The chosen performance criteria concerned professional
behavior (#3), ethical practice (#4), appropriate communication (#6), and respect
for individual differences (#8). The scores for each criterion were the average of
CPI 1 and 2. Only EQ-i:S Total was significantly correlated with these variables
(r=0.43, 0.35, 0.35 and 0.38, respectively). No regression analyses were performed
because only one independent variable, EQ:i-S Total at entry, was significantly
correlated with CPI scores.

22
Table 2: Scores of emotional social intelligence, leadership, caring, moral judgment
and clinical performance.
Entry to
Program
n=59
Before
Clinical
n=59
Average of Placements
1 and 2
n=59
Final Clinical
Placement
n=56
Mean SD Mean SD Mean SD Mean SD
CPI 81.7 10.7 98.8 2.5
EQ-i:S
Total
102.6 10.6 100.6 11.9 105.0 12.6
SALI 102.9 16.1
CAI_K 78.6 5.4
CAI_C 67.9 8.5
CAI_P 61.9 4.7
DIT-2 N2 45.1 12.8
CPI: Clinical Performance Instrument
EQ-i:S: Bar-On Emotional Quotient Inventory Short
SALI: Self-Assessment Leadership Inventory
CAI_K: Caring Ability Inventory Knowledge subscale
CAI_C: Caring Ability Inventory Courage subscale
CAI_P: Caring Ability Inventory Patience subscale
DIT-2 N2: N2 score from the Defining Issues Test

23
Table 3: Correlation of scores of emotional social intelligence (ESI), caring, moral
judgment and leadership at entry to the physical therapist education program and
(ESI) immediately before first clinical placement with average of scores of first two
clinical placements (CPI 1 and 2).
Average of
CPI 1 and 2
n=59
EQ-i:S Total
(entry)
SALI CAI_K CAI_C CAI_P
EQ-i:S Total
(entry)
.25*
EQ-i:S Total
(pre-clinical)
.14 .78
SALI -.05 .35*
CAI_K .05 .50* .36*
CAI_C .06 .63* .36* .39*
CAI_P -.07 -.03 .07 -.02 -.16
DIT-2 N2 -.04 -.01 -.02 -.02 .21 -.03
CPI: Clinical Performance Instrument
EQ-i:S: Bar-On Emotional Quotient Inventory Short
SALI: Self-Assessment Leadership Inventory
CAI_K: Caring Ability Inventory Knowledge subscale
CAI_C: Caring Ability Inventory Courage subscale
CAI_P: Caring Ability Inventory Patience subscale
DIT-2 N2: N2 score from the Defining Issues Test
*correlations significant at p<0.05
Discussion
This study was the first longitudinal examination of the ability of a group of
non-cognitive variables (ESI, caring, moral judgment and leadership) to predict
the clinical performance of physical therapy students. The variables were not
found to be strong predictors. Only one independent variable, EQ:i-S Total at
entry, was significantly correlated with the CPI scores (total and selected
performance criteria) from the first two clinical affiliations. However, these
correlations were weak.
Similarly to Lewis (2010; 2011) we found little change in ESI over the course of
the physical therapist education programs and a low correlation between ESI
and the total CPI score. Although the correlation between ESI and CPI was
significant at the p<0.05 level, ESI accounted for less than 7% of the variance in
CPI. Our study included additional non-cognitive variables (caring, moral
judgment and leadership), but these variables failed to predict clinical
performance. In spite of differences in the ESI measurement tool and the timing
of the measurements, our study and Lewis‟ study had similar results.
Some properties of the CPI contributed to the results obtained in the present
study. As indicated in the Results section, we were unable to use the final CPI
scores because of low variance. Even the average score of the first two clinical
placements was high (81.7 out of a possible 100), suggesting that the clinical
educators used only a small range of the scales. The 1997 version of the CPI
(American Physical Therapy Association, 1997) was the most recognized and

24
utilized clinical assessment tool at the time of this study. Roach et al. (2012)
summarized several problems that could account for the low variance in scores.
These include: a lower completion rate for certain performance criteria and
difficulty discriminating performance on the visual analog scale. In addition,
clinical therapists likely evaluated students against the expected performance for
the clinical level of the student rather than against expected performance at
entry to the profession.
The latest version of the CPI has attempted to address these issues (American
Physical Therapy Association, 2008). This version could not be used in the
present study because it was introduced after the completion of data collection.
Changes to the CPI included combining criteria, modifying wording, providing
additional examples of behavior for rating, and placing more anchors along the
visual analogue scale. Perhaps higher correlations will be found between
predictor variables and the revised CPI.
The outcomes of this study reinforce the point that ESI, caring, moral judgment
and leadership remain attributes that are not well understood, are difficult to
measure, and have yet to be found predictive of clinical performance. The
delivery method of the two physical therapist educational programs (problem-
based and conventional) did not differentiate students‟ outcomes. The ideal
approach to maximize the desired non-cognitive attributes has yet to be
established. Would students in entry-level doctoral programs produce different
results from students in entry-level master‟s programs? Rigorous research of
non-cognitive attributes of physical therapy students remains scarce, although
educators continue to underline the value of these variables. Current measures
of these characteristics do not detect significant changes nor predict clinical
performance. Development of more sensitive tools should be considered.
Investigators also need to pursue the scholarship of teaching, and study the
impact of psychosocial courses on clinical practice.
The clinical educators‟ role in determining the level of performance of physical
therapy students remains invaluable. While the profession has offered training
in the use of the CPI, only a small percentage of therapists have participated.
Clinical educators need training to ensure a standardized, valid and reliable
method of clinical evaluation. More low-cost training and use of media such as
webinars should be considered.
Limitations
The selection process of physical therapist education programs might contribute
to the high scores (and low variance) obtained on the CPI and the independent
variables. The programs may attract students that already have well-developed
non-cognitive and cognitive skills. Furthermore, all participants were volunteers
who may have had a special interest in the concepts evaluated in this study. One
additional factor was the self-report nature of the tools used for the independent
variables. Use of performance measures of these variables might have resulted in
different outcomes. However, Lewis (2011) had similar correlations between ESI
and CPI using an ability-based ESI measure.

25
It is possible that the measures of caring, moral judgment and leadership
changed from entry to pre-clinical as a result of the physical therapist education
programs. If so, students with low scores at entry may have improved prior to
their first two clinical affiliations, thus minimizing any potential correlation with
CPI. These constructs were not measured immediately prior to the first two
clinical affiliations. However, as reported previously (Larin et al., 2011; Larin et
al., 2014), there were no substantial changes in these variables later in the
programs.
Conclusion
The present study examined the combined effect of four non-cognitive variables
as potential predictors of clinical performance of physical therapy students. ESI
was significantly correlated to clinical competence, but the non-cognitive
measures of ESI, caring, moral judgment and leadership could not adequately
predict the clinical performance of physical therapy students. Further studies are
needed to deepen our knowledge of non-cognitive variables that forecast the
ability of the physical therapist to provide high quality patient care.
Acknowledgements
We wish to thank all the students who volunteered to participate in this study.
This project was supported by two grants from Ithaca College (Seed Research
Fund, School of Health Sciences and Human Performance; Small Grant for
Faculty Research, Office of the Provost).
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© 2015 The author and IJLTER.ORG. All rights reserved.
Vol. 10, No. 4, pp. 28-39, March 2015
Integrating Teaching Resources and Assessment
Tasks to Enhance Student Experience
Dr Sujana Adapa
University of New England
UNE Business School, Armidale NSW Australia
Abstract. This paper outlines the importance of integrating teaching resources
with assessment tasks and continuous feedback in creating a unique student
experience through effective student engagement and interactive learning. These
activities are undertaken in two undergraduate services marketing and strategic
marketing units offered in an off campus teaching mode in a regional Australian
university. The resultant impact upon the overall student satisfaction, academic
performance, retention rates and attrition rates has been studied. Results indicate
that student engagement increased and, also, that students focused on deeper
learning approaches because of the integration of technology-enabled teaching
resources with authentic assessment tasks. Continuous feedback provided by the
academic staff member acted as a feed forward element that gauged students’
deep interest in the unit offerings.
Key words: student experience; student engagement; student learning; interactive
resources; authentic assessment; feedback
1. Introduction
Rapid changes are evident in teaching and assessment related activities in the
higher education sector throughout the world due to forces such as
globalisation, privatisation, technological evolution and migration. The higher
education sector is significantly influenced by processes of rapid globalisation,
frequent policy changes and international movement of students (Kirkwood &
Price, 2014). The changes in the higher education sector are evident in many
areas including the internationalisation of classrooms, changes in teaching and
study modes, changes in unit offerings and changes to assessment and grading
methods. Technology has an undeniable impact on these changes and so
contemporary educational institutions are embracing technology to a greater
extent in their service offerings (HEFCE, 2009).

29
On the other hand, modern day students cannot be expected to access higher
education institutional offerings without any knowledge of the subject content.
Students have information at the forefront of their concerns and go to tertiary
institutions with greater knowledge than before. Students are also increasingly
looking for unique experiences from tertiary institutions rather than just aiming
for degrees or awards. These students’ expectations place immense pressure on
teaching staff and tertiary institutions in outlining their curriculum, courses and
unit offerings. Coupled to this, modern students’ attention span is less (Coates,
2007) and academic staff have to design unit content and assessment tasks
differently to maintain student engagement throughout the unit offering, to offer
an authentic learning experience and to create a unique study experience
(Coates, 2007).
This paper outlines the importance of aligning teaching resources with authentic
assessment tasks and continuous feedback to promote unique study experiences
through better engagement and learning strategies for distance education
students in two marketing units offered in a higher education institution in
Australia. These intervention strategies not only improved students’ academic
performance but also had an impact upon the students’ deep learning processes,
as well as student retention and attrition rates.
2. Literature Syntheses
2.1. Teaching Resources
Pedagogical changes in the contemporary higher education sector cannot be
ignored. Technology now plays a pervasive role in the enhancement of teaching
resources that further student engagement and the overall student experience.
Technology Enhanced Learning (TEL) commonly is used in many countries to
foster student learning (Kirkwood & Price, 2014). TEL promotes efficiency of
existing processes, enhances learning outcomes and the transformation of
existing processes (HEFCE, 2009). Technology supported interventions have
been used in the higher education sector to improve teaching resources that
generate inherent interest in subject content, making the learning process
interesting, informative and useful for students (Kirkwood & Price, 2014).
TEL is often linked to learning outcomes and defined graduate attributes in
order to foster deeper learning among students. As contemporary students are
well equipped and connected to various technologies, TEL is widely used by
many higher education institutions to foster active student learning. TEL
promotes interactive student learning and facilitates student deeper engagement
with the subject content.
2.2. Assessment Tasks

30
Assessment tasks are important components of active student learning.
Assessment tasks may be divided into formative and summative tasks.
Formative assessment tasks include a set of tools to effectively monitor students’
progress during learning (Dunn & Mulvenon, 2009). Such tasks are oriented
towards the provision of continuous feedback to students through various
activities while instruction is under way. They are directed towards
understanding the students’ viewpoint and further preparing them towards
achieving higher grades and improved learning (Heritage, 2007). Thus,
formative assessment is considered an ongoing activity to enhance students’
participation and active learning (Perie et al., 2007).
Inclusion of formative assessment tasks will engage students in continuous
learning. However, summative assessment tasks remain important tools for
grading the performance of the students (Knight, 2002). Gradable summative
assessment tasks motivate students to progress further in their learning activities
and foster achievement-oriented academic learning. Students’ academic
performance is measured through the inclusion of summative assessment tasks
in the curriculum.
2.3. Student Engagement
Student engagement has attracted considerable attention since the 1990s. It has
been a topic of interest in North America, UK and Australasia due to
collaborative efforts between government bodies and the higher education
sector and the commissioning of large-scale national surveys on an annual basis
(Trowler, 2010) in order to gather student related data. As such, student
engagement is related to student representation, student feedback, learning
spaces and learning development. Student engagement has been linked with
sense making, belonging and feelings (Harper & Quaye, 2009a). The three most
important dimensions of student engagement relate to behavioural engagement,
emotional engagement and cognitive engagement (Fredricks, Blumenfield &
Paris, 2004). In behavioural engagement terms, students tend to comply with
acceptable positive behavioural norms and tend to score less on disruptive and
negative behaviour. Emotional engagement refers to the students’ affective
reactions such as enjoyment, interest in the subject matter, sense of belonging
etc. Cognitive engagement relates to students’ deeper involvement with the
learning activities and students’ interest in taking on challenging work. Student
engagement is an important concept and is attracting global attention in the
higher education sector in order to improve retention and avoid student attrition
and withdrawals (Trowler, 2010).
Coates (2007) outlined four types of student engagement styles on the basis of
academic and social patterns. These student engagement styles refer to intense,
independent, collaborative and passive forms. Students having an intense form

31
of engagement are deeply involved in their academic studies and view learning
environments as supportive, responsive and challenging. An independent style
of engagement scores high within an academic context but less in terms of social
orientation and these students generally are less interested in collaborative
forms of study. Collaborative engagement is characterised by involving students
in activities that fall beyond a formal higher education context. Passive
engagement reflects a lack of interest in productive learning and as well as
general inertia in educational terms (Coates, 2007). Student engagement is linked
to student learning and how the process of learning and learning activities are
influenced by a student’s active participation in educationally meaningful
activities (Coates, 2005).
2.4. Student Learning
The traditional models of student learning have undergone several changes in
order to suit current pedagogical approaches. There seems to be an upsurge in
embedding online or virtual learning environments into curricula to suit
different study modes, and also to enhance the level of student interaction and
engagement (Dale & Lane, 2007). Many higher education institutions are
focusing on creating stimulating learning environments through the
incorporation of technology in their learning and teaching strategies (Graham et
al., 2007). Debates related to online versus offline study modes, and criticisms
oriented towards low levels of student participation in these study modes,
spurred interest among higher education institutions and teachers to embrace
interactive online resources in order to foster student learning oriented towards
the development of high order critical thinking and problem solving skills
(Trowler, 2010).
Students’ learning differs widely. Distance students additionally have family
and work commitments meaning that they often have to pace their learning
differently to the traditional face-to-face students. Enhancing student learning
through effective engagement has been widely debated (Graham et al., 2007).
Similarly, the existing literature on student engagement is linked directly or
indirectly to improving students’ learning (Coates, 2005). However students are
further classified into active versus passive and/or surface versus deep learners.
In order to transfer the skills and competencies acquired through higher
educational learning to the work environment, students need to be active,
achievement-oriented and deep learners. The impact of student learning is
directly reflected in their academic achievements and performance and is
indirectly reflected through metrics such as student retention rates, student
attrition rates and their enrolment in other unit offerings. Therefore, it is normal
to expect that students’ learning will have an impact on the overall student
experience gained within the higher educational context.

32
2.5. Student Experience
Higher educational institutions are increasingly moving away from the
traditional model of just offering educational services to students. While
students are viewed as the most important stakeholders, the notion that they are
‘consumers’ of service offerings is losing popularity. In contrast, the
contemporary focus within educational institutions is not only to foster students’
academic success, but also to embrace overall student experiences beyond the
university setting in order to create value for their service offerings. Students are
also increasingly focusing on matching their experiences with their educational
expectations in order to enhance their deeper learning capabilities.
3. Methodology
This paper is based on the interactive teaching resources developed for distance
students enrolled in Marketing units at a regional Australian university. The
information presented reports the teaching interventions undertaken by the
researcher, who is an academic staff member coordinating Marketing related
units for undergraduate students. The staff member focused on developing
interactive resources to foster student engagement and student learning in order
to create an enhanced overall student experience in two third year
undergraduate units (Strategic Marketing [MM316] and Services Marketing
[MM314]). The staff member, who is also the unit coordinator, deliberately
focused on the weekly release of interactive teaching resources as a way of
simplifying the content included within these units.
These particular units were offered only to the distance students. This specific
mode of offering made it difficult for the unit coordinator (initially, at least), to
fully understand the needs and expectations of those enrolled in the courses.
These students lacked the advantage of having physical contact with the staff
member and focused on learning the subject content on their own at their own
pace. This setting seemed to provide a passive delivery of the unit with minimal
or no interaction between some students with their peers and/or the unit
coordinator. The latter focused upon utilising available technology and
developed resources that gauged student interaction with peers and the teacher,
and motivated students to engage in online interactive discussions. A number of
formative and summative assessment strategies were linked to the interactive
resources and these were supplemented with feedback on both kinds of
assessment tasks that indicated students’ interest and self-regulated learning
skills.

33
4. Results and Discussion
Strategically, course development was focused upon the provision of weekly
interactive resources and aligning these resources to assessment tasks (see
Figure 1). Initially teaching resources were updated and rewritten, incorporating
real life examples, with an emphasis upon the provision of appropriate readings.
Later, module-based and topic-based interactive resources were developed for
release to learners on a weekly basis. Module-based resources consisted of
interactive case scenarios and concept maps that provided an overview of the
topics in that particular module. Topic-based resources presented related
information to learners in various interactive formats such as concept maps,
power point slides, activities, audio podcasts, summaries, and case studies on a
weekly basis. In doing so, unit supervisor focused upon simplifying subject
content and presentation within interactive formats for easy access by learners.
In unit evaluations completed by students, these were appreciated as ‘excellent
resources, which were of great assistance’; other students stated that ‘content
guidance and resources made this subject a pleasure to study!’ (MM314 2012);
‘the material content is relevant and very applicable to marketing strategies’
(MM316 2012); and the reworked course material ‘provided great resources, in
particular the audio summaries’ (MM314 2013). The unit supervisor also focused
on integrating technology enabled learning through the development of the
interactive teaching resources.
Students also commented on the relevance of the resources. Their comments
included the ‘learning material seemed very relevant and useful for a future
career in marketing’, providing scenarios ‘really like the real life case studies’
(MM316 2012); others noted the ‘excellent resources’ and the ‘interesting and
diverse subject matter’ (MM314 2012). In the second step of the overhaul of the
courses under discussion, the focus was upon developing assignments in the
form of ‘Marketing Plans’ and ‘Strategic Marketing Plans’, whereby students
needed to apply critical thinking skills to problem-solving and draw logical
conclusions. This was further supplemented with ‘assignment tips’ that
provided an overview of the entire assignment. Learners appreciated that ‘the
assignments were highly relevant’ (MM316 2013) allowing them to ‘create our
own marketing plan… rather than spend assessments simply reciting
definitions’ (MM316 2011). These revised weekly interactive resources and
assessment tasks were complemented by a feedback system in order to develop
distance learners’ core competencies and their ongoing development; in this
respect a student noted that the academic staff member ‘provided thorough and
timely feedback to enquiries and assessment submissions’ (MM316 2011); other
comments included ‘feedback provided areas for improvement’ (MM314 2013);

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