Feature Article

A Placement Level Study:

Are Students Motivated by Traditionalor Communicative Activities?
David Ockert
Toyo University
This paper reports the findings of an exploratory investigation into first-year Japanese
university students’ (N = 220) preferences among twelve pedagogical activities basedon their English proficiency. Student proficiency levels are pre-intermediate (n = 73),
intermediate (n = 74), and upper-intermediate (n = 73) based on a placement exam. Sixof the twelve activities may be considered traditional, instructivist classroom pedagogicalactivities and six may be considered components of a constructivist communicative language
teaching pedagogy and/or task-based language teaching activities. A principal components
analysis placed the six traditional activity variables into one factor and the communicative/ task-based activity variables into two factors of three variables each. Means comparisons
between the groups show statistically significant differences in the preference for Smallgroup / team activities for the intermediate and upper-intermediate students compared withthe pre-intermediate students. The intermediate students, a sample representing 70% of thestudents in the faculty, prefer Activities where I am moving around in the room more thanthe other two groups. Grammar drills / practice show a statistically significant decline inpreference as ability increases. Finally, all of the communicative / task-based activities areranked higher by the upper-intermediate students compared with the pre-intermediate
students. The results and implications are discussed.
本稿では、英語能力に基づいた12の活動のうち、日本の大学一年生（N = 220）教授法の好み研究成果を報告する。理工系の大学や関西の主要私立大学の入学試験にもっとづいて、準中級(PI; n = 73)、中級(IM; n = 74)、上級(UI; n = 73)である。12活動のうち6つは、伝統的で一番為になる教室での、instructivist教育的活動と考えられるかもしれません、残りは構成主
義コミュニカティブ·ランゲージ·ティーチング教育および/またはタスク·ベ

3Ockertースの言語教育活動の構成要素と考えられるかもしれません。結果は、PIの学生と比較して、IMやUIの学生のためのグループワークの好みにおいて、統計上重要なちがを示している。体を動かしながらの活動は、学生の過半数の典型である、PIとIMの学生の間で統計的有意性を示している。また、文法ド
リル/練習は能力が上がるにつれて、統計上有意な減少を示しています。最後に、コミュニカティブ·ランゲージ·ティーチング教育のすべてはUIグルー
プにより高く位置づけられておりPIグループと比較して統計学的に有意な差を示しています。結果とその結果が暗示することについて議論します。

This paper reports on “the under-researched issue of learners’ motivation to
engage in the task” (Dörnyei & Tseng, 2009, p. 117) and presents the resultsof a study which investigated student preference for pedagogical activities basedon English proficiency level. Previous studies have contrasted communicativeand non-communicative pedagogical approaches for their enjoyment andeffectiveness or perceived usefulness (Burden, 2005; Green, 1993). Others have
explored correlations between motivation and pedagogical approaches ( Jacques,2001) and between motivations, pedagogical approaches and learning strategies(Schmidt & Watanabe, 2001).
In addition, the distinctions between traditional, teacher fronted classroom
activities (TAs) and communicative language teaching methods and/or taskbased activities (C/TBAs) have been reported on theoretically and empirically(Burden, 2005; Ellis, 2003; Green, 1993; Jacques, 2001; Nunan, 1998, 2004;
Ockert, 2006, 2011, 2015; Schmidt & Watanabe, 2001; Willis, 1996). Students’affective response to different pedagogical approaches is well known to classroom
practioners. As Hsu (2005) writes, “some learners like doing grammar andmemorizing, others want to speak and role–play; while still others prefer reading
and writing, but avoid speaking” (p. 55). However, the author is unaware of any
research studies which have investigated student pedagogical preferences basedon English proficiency.
The results presented herein are from students (N = 220) in a single faculty
who were in one of three course levels. The course levels are Pre-Intermediate(PI; n = 73), Intermediate (IM; n = 74) and Upper-Intermediate (UI; n = 73)
as determined by a “TOEIC® -like placement test” (M. Shawback, pers. comm.).
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A Placement Level Study, OnCUE Journal, 8(1), pages 3-34

Students took the placement test at the same time as the entrance exam toenter the College of Science and Engineering at a large private university in the
Kansai area of Japan. Since the students reported on were in the first semester ofuniversity, it should be noted that the results of the activity preferences may reflect
activities from high school (HS) and/or junior high school ( JHS). However, theresults of this research may help educators and curriculum developers make more
informed decisions based on ability level and activity preferences. It is hoped that
this paper will add to the research literature on classroom pedagogical activities
and preferences.

Social Constructivism, ‘Flow’, and Taskmotivation

Over the past several decades, there has been a move toward constructivist
approaches to instruction, reflecting the theories of Vygotsky (1978), Dewey(1963), and Leont’ev (1978). Social constructivist theories involve “engaging
students in problem solving…and co-operative activities” (Felix, 2005, pp. 1920). Social constructivists approach learning tasks that “emphasize interpersonal,
experiential, activity-based learning” (Felix, 2005, p. 29) as opposed to
instructivist approaches, which are generally teacher-fronted.
According to Flow Theory (Csikszentmihalyi, 1991; Csikszentmihalyi,
Abuhamdeh & Nakamura, 2005), there are eight aspects that characterize
an activity or a task that provides enjoyment: First, we must have a chance ofcompleting the task. That is, the task content and time constraints must both
meet student ability level. Second, we must have an opportunity to concentrateon the activity. Third, the task has a clear goal and fourth, immediate feedback
is provided on task progress and completion. Fifth, we are deeply but effortlessly
involved in the task and forget about any worries or frustrations. Sixth, we havea sense of control over our actions. Seventh, concern for the self disappears when
we are engaged in the activity. Finally, our sense of time is altered; we simply
forget about time (in Csikszentmihalyi, 1991, p. 49). Research on Flow Theory
and second language acquisition (SLA) by Egbert (2003) shows “that teachers
can theoretically facilitate the flow experience for students by developing tasks
5Ockertthat might lead to flow” (p. 513). In other words, from the perspective of
SLA, “Flow Theory specifies the task conditions under which Flow can occur”(Dörnyei, 2005, p. 82). Specifically, interactive, problem-solving, and groupbased activities with a clear goal and which require students to focus intently
provide the four aspects that characterize the Flow experience: interest, focused
attention, challenge, and control.
Dörnyei (2007) lists several aspects of teacher practice that are relevant totask-based teaching and the task-motivation of students that are conducive tocreating the Flow experience:
1. Making learning stimulating and enjoyable.
2. Presenting tasks in a motivating way.
3. Setting specific learner goals.
4. Protecting the learners’ self-esteem and increasing their self-confidence.
5. Creating learner autonomy. (p. 728)
Classroom teachers can make learning stimulating and enjoyable in several
ways. Dörnyei and Murphey (2003) write about “the rewarding nature of group
activities” (in Dörnyei, 2007, p.721). They state that the joy that students feel
while performing activities with others and the success in achieving goals (taskcompletion) are affective benefits of working with others. Brophy and Alleman(1991) have written that “(o)ther things being equal, activities that students arelikely to enjoy (or at least find meaningful and worthwhile) are preferable toactivities that students are not likely to enjoy” (p. 18). After more than twenty
years, experts still emphasize the “enjoyable quality” of language learning tasks(Dörnyei, 2009a, p. 18). This paper explores differences of the ‘enjoyable quality’of language learning activities based on the students’ proficiency.
However, there are several classroom pedagogies and overlap amongst them is
to be expected. There are also specific differences (Duffy & Cunningham, 1996)
that can be recognized and preferences amongst them can be explored. Since it iswell known that “(i)nstruction, tasks, and courses have a motivational structure”( Julkunen, 2001, p. 34), preferences amongst them based on their ‘motivational
6

A Placement Level Study, OnCUE Journal, 8(1), pages 3-34

structure’ can be examined.

Classroom Pedagogies
Traditional Approaches
Broadly speaking, when researchers refer to TAs they are referring to a teachercentered classroom with the students as passive receptors. Communicative
approaches, on the other hand, often use tasks involving the students in active,
focused and goal- oriented activities where the outcomes are clear and obtainable.
For example, Nunan (1998) makes rather clear-cut distinctions between
traditional and contemporary communicative task-based language education (pp.
69-91). Naturally, some activities are similar or involve more than one skill. For
example, translation involves reading and writing skills. However, Nunan (1998)
has provided the following guidelines for a traditional approach to pedagogy:
1. Approach to teaching methodology - Traditionally, learners are taught about
the language and its rules in contrast with learners being actively involved inusing the language.
2. Role of the learners - Traditionally, learners spend their time reproducing
language written down by others rather than learning how to use language
creatively by responding to “authentic” communicative situations.
3. Approach to language - Traditionally, grammar and vocabulary are taught asrules or discrete forms to be memorized and reproduced on exams instead ofbeing taught communicatively to express meaning. (pp. 88-89)
Research on Traditional Pedagogical Approaches
Green (1993) was amongst the first researchers in English as a foreign language(EFL) studies to explore student attitudes toward communicative and noncommunicative activities. He has defined the following activities as noncommunicative in nature: looking up words in a dictionary, explaining grammar,
and whole class activities, such as repeating vocabulary words or phrases from atext after the teacher. His research found that the’ non-communicative’ activities
7

Ockertwere rated lower in both ‘enjoyableness’ and ‘usefulness’ by the students surveyed.
Research by Schmidt and Watanabe (2001) and Jacques (2001) on
correlations between motivation and student preferences for different typesof classroom activities found factors comprised of TAs. For example, Jacques’(2001) results contain the items Grammar should be an important focus in thisclass, which grouped with Reading and writing should be an important focus inthis class, forming the factor Traditional Approach (p. 195; 209). In the Schmidt
and Watanabe (2001) study, these two items plus an additional item, Vocabulary
should be an important focus in this class, came under the factor Traditional
Approach (pp. 345-46; 355). Based on these studies, grammar, reading, writing,and vocabulary have been determined to be TAs in the literature.
Communicative Language Teaching & Task-based Activities
Crookes and Schmidt (1991) noted that “communicative approaches arecharacterized by a fairly extensive use of group work” as this has been said
“to result in greater motivation among students” (p. 488). Teachers can help
maintain motivation by enhancing interest and curiosity, which “means using
less orthodox teaching techniques and/or materials” (Crookes & Schmidt, 1991,
pp. 488-489). In order to maintain interest, and in contrast to the traditionalclassroom practices outlined above, Ellis (2003) provides the following featuresof a task in the context of TBL activities in communicative language teaching(CLT):
1. A task is a work plan.
2. A task involves a primary focus on meaning.
3. A task involves real-world processes of language use.
4. A task can involve any of the four language skills.
5. A task engages cognitive processes.
6. A task has a clearly defined communicative outcome. (pp. 9-10)
Willis describes task-based activities to be those in which “...the learner uses
the target language for a communicative purpose in order to achieve an outcome”
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A Placement Level Study, OnCUE Journal, 8(1), pages 3-34

(Willis, 1996, p. 23). She further defines task-based activities under various
categories such as listing, ordering/sorting, comparing, problem solving, sharing
personal experiences, and creative tasks (Willis, 1996, pp. 23-29). In a more recent
article (Willis & Willis, 2009) the relationship between communicative language
and task-based language teaching is contrasted with traditional, teacher-fronted
approaches. Dörnyei (2003) states, “...tasks constitute the basic building blocks
of classroom learning” (p. 14). More specifically, Nation (1991) advocates using
problem-solving tasks since these “have a very important feature that makes themwork well in getting learners involved. This feature is the definite outcome of theactivity. Because of the importance learners place on outcomes, problem-solving
tasks involve a lot of highly motivated goal-directed activity” (p. 8).
Within this activity, according to Dörnyei (2009b), language learning in CLT
comes from “the learners’ communicative competence develops automaticallythrough their active participation in meaningful communicative tasks” (p. 34).
Therefore, C/TBAs are rooted in both a different teaching approach and learnerroles than TAs. Nunan (1998) writes that in C/TBAs “Learners are actively
involved in using language” (p. 89, emphasis added). In other words, learners
actively engage in cooperative learning tasks using the target language to achievea specific outcome – a process which in itself is motivating.
Research on Communicative & Task-based Activities
Green’s (1993) research on communicative and non-communicative activities
included in the former small group work, pair work, and info-seek activities that
require “the students move around the classroom, ask each other questions inEnglish” (p. 9). He has noted that “a striking feature of the enjoyableness ratings
was that, with only one exception, the communicative activities were rated as
more enjoyable than the non-communicative ones” (pp. 4-5). In addition, thecommunicative items as a whole had a higher mean score for ‘effectiveness’ than
the non-communicative items. Green (1993) noted “The general tendency wasfor effectiveness and enjoyment ratings to be highly correlated” (p. 8). Since
Green’s study, several other researchers have investigated pedagogical approaches
using more sophisticated analysis.
9OckertFor example, Jacques (2001, p. 194; 209) and Schmidt and Watanabe (2001,
pp. 345-46; 355) found a factor that they labeled Challenging Approaches. Thisfactor consists of the items I prefer a language class in which there are lots of activities
that allow me to participate actively, plus I prefer to sit and listen and don’t like being
forced to speak in language class (reverse coded), as well as In a class like this, I
prefer activities and material that really challenge me to learn more. In addition,
Jacques (2001, p. 194) and Schmidt and Watanabe (2001, p. 355) found a factor,
Cooperative Learning, that has three items: I like language learning activities inwhich students work together in pairs or small groups, I prefer to work by myself inthis language class, not with other students (reverse coded), and I prefer a language
class in which the students feel they are a cohesive group.
Dörnyei (2002) has reported on action research involving communicative
activities in dyads using an interactive problem-solving activity. The results
showed higher correlations between task attitudes and words spoken and turns
taken with the dyads as compared to the individual data. This indicates “thattask-motivation is, at least partially, co-constructed” (p. 154). In addition, Nationand Hamilton-Jenkins (2000) have shown that group work tasks improve bothspeaking skills and vocabulary acquisition.
Research on Tasks and Motivation in Japan
In the Japanese language literature, Nose (2005) found a relationship between
elementary student interest in learning English and preferred pedagogicalactivities. This two-part study involved answering questions at the beginningand end of an eight month activity intervention research project. Specifically,
61.1% and 68.8% of the students expressed a positive desire to speak English.
For a question on group work or pair work activities, 54% of the respondents
expressed a clear preference for both on the second administration (Nose, 2005,
p. 3). The need for group work involving activity has been made an explicit goalof the Japanese Ministry of Education, Culture, Sports, Science and Technology(MEXT), which recommends to teachers that students “Do not sit still; doactivities which move bodies and minds” (quoted in Watanabe, 2010, p. 5) as
one of the aims of foreign language activities (FLA) in elementary schools. Using
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A Placement Level Study, OnCUE Journal, 8(1), pages 3-34

multi-skill dictation activities as a means to manage, motivate, and activate large
groups of false beginners has been reported (for examples, see Norris, 1993;
Ockert, 2008).
Additional research in the Japanese EFL ( JEFL) environment by Burden(2005) contrasted several TAs (lecture, translation, and grammar exercises)
and C/TBAs (pair-work / group-work) and their perceived enjoyableness andusefulness by university students. The results indicate that several activities
that are perceived as effective were not perceived as enjoyable (e.g. Memorizing
vocabulary lists, p. 7, Table 2). In addition, Ockert (2006, 2011) has founddistinctions between TAs and C/TBAs based on principal components analysis(PCA) and reported on the relationship between activity type and learner EFL
motives. Therefore, students like to engage in specific activities and may also do
so based on EFL motives.
This paper adds to the literature on TAs and C/TBAs by reporting on Japanese
university students’ results for their preferences for pedagogical activities basedon the activities’ motivating aspect or enjoyableness, according to student ability.
The author is unaware of any research into pedagogical preferences of learners ofdiffering English ability level based on a placement exam. The researcher believes
the current study will contribute to the growing body of literature on the topic
of classroom activities and our understanding of student perceptions of specificactivities as enjoyable or motivating based on a placement level analysis.

Research Questions and Hypotheses
Research Questions
The previous studies on TAs and C/TBAs and their motivational qualities/ usefulness guide the present research. However, in this research project,
three groups of first-year university students of differing levels of proficiency
participated. The three levels of proficiency serve as independent variables.
Twelve pedagogical activities serve as dependent variables. The research questions
explored in this study are:
1. Do the students feel that different pedagogical activities are more motivating
11

Ockertthan others? To answer these two research questions, the three groups ofstudents will be treated as a single group (N = 220).
2. 2. Are these twelve activities rated differently based on the student proficiency
levels? In order to answer this research question, the results are presented byproficiency level.
3. Will a principal components analysis show classroom activity factors according
to TA and C/TBA distinctions as described by researchers previously?
Hypotheses
The following two conjectures about this sample are offered:Hypothesis 1: The participants in this survey will indicate differences in
activity preference based on their proficiency level.
Hypothesis 2: A principal components analysis will distinguish between TAs
and C/TBAs.

Methods

The process of operationalizing the affective variable ‘enjoy’ or ‘motivating’is shown in Figure 1. The affective stage asks the respondents how they feel
regarding each activity – negatively, neutrally, or positively. The degree of negative

Figure 1. The conversion of statements of affect into a numerical system for data analysis

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A Placement Level Study, OnCUE Journal, 8(1), pages 3-34

or positive affect is broken into two positive and two negative ratio valuations.
Factor analysis assumes that the data are on an interval scale, but that it iscommon practice to apply factor-analytic methods to Likert-scale data, which
are ordinal. For this research project, the numerical format choices for each item
are the numbers 1 to 5. It is important to remember when viewing means scoresfor each variable that those below ‘3’ are, in fact, representing negative affect forthese respondents.
It is also important to consider that survey use in the JEFL environment has
a rather ‘checkered’ history. According to Reid (1990), students from different
language and cultural backgrounds differ in the ways they respond to surveys. For
example, “NSs used the entire range of the 5-point Likert scale in a reasonably
consistent manner, while the Japanese students tended to respond more toward
the mean: That is, they responded to the Strongly Agree and the Strongly Disagree
categories only rarely” (Reid, 1990, p. 336). As a result, the Japanese student
group did not display clearly defined learning style preferences (while the othergroups surveyed did show learning style preferences). The author developed thescale used for this research before finding out about this phenomenon. However,appropriate measures were taken before analyzing the data (see Procedures).
Respondents
The participants were all first year students (N = 220) in communication classes
in the College of Science and Engineering in a top-tier private university in Japan.
Students in this college take a TOEIC®-like placement test and are streamed into
their respective levels based on their scores relative to other students. The students
who score in the lowest 15 percentile are placed in lower-intermediate (PI; n =73) classes and those in the upper 15 percentile are placed in upper-intermediate(UI; n = 73) classes. Those in the middle 70 percentile are placed in intermediate(IM; n = 74) level classes. Three classes from each level were chosen at random forparticipation with the cooperation of their Communication I teachers. Female
and foreign students account for a very small percentage of the total respondents.

13

OckertInstrument
The author created an English-language instrument for this research under thesupervision of a recognized expert in the field, an approach referred to as the“expert opinion method” (Brown, 2001, pp. 179-180). The scale used in thisresearch was designed with Japanese learners in mind; the items / activities
were selected based on JEFL learners’ classroom and learning situation. The
Classroom Activities Questionnaire lists twelve classroom activities commonlyused in foreign language classrooms. The first six are generally used for instructivist
or teacher-fronted classrooms and are referred to as TAs. The latter six involve amore active student role, are socio-collaborative (group learning based) and arereferred to as C/TBAs. No distinction was made on this survey to indicate to thestudents that the twelve activities were hypothesized to either one or the other.
This questionnaire uses a Likert-type format from 1 to 5, correspondingto (1) strongly dislike, (2) dislike, (3) neutral, (4) like, and (5) strongly
like (please see the Appendix). The Cronbach’s alpha is .76 for the twelve items,
which indicates that it is not a uni-dimensional scale. Rather, there are two or
more sub-scales measuring different constructs.
Procedures
The author’s colleagues administered the surveys to students in three classes
from each level in the fourth week of the first semester. The author was present
to assist in distributing the surveys, answer questions, collect the surveys, andensure that they were filled out. The survey was administered in a paper version
and students were encouraged to ask any questions of their instructor after the
instructions were read aloud. The students were given as much time as necessary
to complete the survey on a voluntary basis. However, no students opted to notfill in the questionnaire. The students were given confidentiality and assured that
their course grade would not be affected in any way for their participation or
non-participation. Due to the issue raised by Reid (1990), above, students fromall three ability levels who chose the ‘3’ option across all items were removed
to create a more robust sample. Therefore, 14, 17, and 15 students’ results were
removed from the PI, IM, and UI groups, respectively, before analysis.
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A Placement Level Study, OnCUE Journal, 8(1), pages 3-34

Statistical Issues
Sample size and subject to item ratio in principal components analysis. Some
researchers claim that using principal components analysis with small numbersof respondents may be inappropriate; however, others disagree. For example,
consider the minimum sample size or subject to variable ratio in several practicalstudies. Fabrigar, Wegener, MacCallum and Strahan (1999) reviewed articles
in the Journal of Personality and Social Psychology and the Journal of Applied
Psychology that used EFA. 18.9% of the articles in the former journal and 13.8%of the articles in the latter had sample sizes of 100 or less. Regarding the ratio of
subject to variable, 24.6% of the papers in the former journal and 34.4% in in
the latter were 4:1 or less. The sample size for the research presented herein has atotal of 220 participants; twelve survey items; therefore, an STV of >18:1. Boththe sample size and subject to variable measures meet the criteria for a principal
components analysis.
Identification of the factors. There are two main points to consider for factor
retention: the minimum items per factor group and the issue of cross-loadings.
The communality between the items of .8 or greater may be ‘ideal’ but numbers
between .40 and .70 are more common. Some (e.g. Costello & Osborne, 2005)
suggest a minimum loading of .32 as a “good rule of thumb for the minimum
loading of an item” (p. 4). However, Tabachnick and Fidell (2007) suggest thiscutoff for N-sizes of 300+ respondents. Stevens (2009) suggests .40 for N-sizes
below 200. Since the sample number for this study was 220, the cut-off of .40
is used to determine the factors. There were no cross-loadings above .40 in the
PCA results. The level of significance was set at .10, which is appropriate for an
exploratory study, according to Cohen (1992).

Results and Discussion
The Activity Rankings, Differences, and Effect Size by
Proficiency Level
The collected data were initially analyzed using the SPSS software, and confirmed
using the MyStat software. The descriptive statistics for the twelve items, minimum/ maximum (from 1 to 5) and rankings are in Table 1. In the column for M, the15

Ockert
Table 1
The Descriptive Statistics for the Twelve Pedagogical Activities (N = 220)
Variable

M

SD

Min

Max

Skewness

Kurtosis

1.

Lecture

3.77

0.86

1

5

-0.31

0.05

2.

Listening exercises (CD, tape or DVD)

3.47

0.92

1

5

-0.03

-0.66

3.

Dialogue / reading practice from the text

3.23

0.86

1

5

-0.25

0.46

4.

Writing exercises

3.14

0.84

1

5

-0.03

-0.20

5.

Translation exercises

3.22

0.68

1

5

-0.13

1.02

6.

Grammar exercises

2.96

0.82

1

5

-0.28

-0.22

7.

Small-group / team activities

3.94

0.76

1

5

-0.72

1.03

8.

Info-seek / finding information activities

3.41

0.70

1

5

-0.05

0.68

9.

Problem-solving activities

3.43

0.65

2

5

0.32

-0.07

10. Activities involving movement

3.43

0.79

2

5

0.37

-0.30

11. Tasks that are intellectually challenging

3.37

0.69

2

5

0.44

0.10

12. Pair-work

3.74

0.80

1

5

-0.52

0.54

lowest score is 2.96 for Grammar exercises. The three highest activity means are
for Lecture (3.77), Small-group / team activities (3.94), and Item 12 Pair-work(3.74). The skewness results indicate that variables 2, 4, and 8 have relatively
normal distributions; variables 9, 10, and 11 are to the right of the mean. This
would be expected since the minimum for each was a ‘2’, indicating that none of
the respondents chose 1 (strongly dislike) for either of these activities.
The twelve activities mean scores and standard deviations rankings are in
Table 2. Lecture, Small-group activities, and Pair-work are ranked highly acrossall three groups. Small-group activities are ranked the highest by the IM and UI
students. However, with the PI students, Lecture is ranked one one-hundredthof a point higher than Small-group activities. In addition, the results show astatistically significant difference in the mean score for Small-group activities for
the IM and UI students compared with the PI students. Activities while moving
show a statistically significance difference between the PI and IM students(who represent approximately 70% of these Science & Engineering majors).
In addition, Grammar drills / practice show a decline as ability increases and16A Placement Level Study, OnCUE Journal, 8(1), pages 3-34
Table 2The Twelve Activity Min / Max and Ranking by English Placement Exam Level
PI (n = 73)

IM (n = 74)

UI (n = 73)

Min / Maxrank

Min / Maxrank

Min / Maxrank1) Lecture

1/5

1

2/5

3

1/5

2

2) Listening exercises

2/5

4

2/5

6

1/5

9

3) Dialogue / reading

1/5

9

1/5

9

1/5

8

4) Writing exercises

1/5

11

1/5

10

1/5

10

5) Translation exercises

1/5

11

1/5

8

1/5

8

6) Grammar drills / practice

1/5

10

1/5

11

1/4

11

7) Small-group activities

1/5

2

2/5

1

2/5

1

8) Info-seek activities

1/5

6

2/5

5

1/5

6

9) Problem solving activities

2/5

7

2/5

5

2/5

4

10) Activities while moving

2/5

8

2/5

4

2/5

7

11) Challenging tasks

2/5

5

2/4

7

2/5

5

12) Pair work

1/5

3

2/5

2

2/5

3

a statistically significant difference between the UI and PI students. Finally,
Challenging tasks are considered more enjoyable by the UI students comparedwith the PI and IM groups, with a statistically significant difference with the IM
group. For comparative purposes, it is worth noting that the lowest ranked items
by mean score for all three groups are TAs.
The ranking of the items based on mean score and the minimum / maximum
for each item by proficiency level reveals the perceived enjoyableness or
motivating aspect of the twelve activities. As can be seen in Table 2, none of the
C/TBAs received a ‘1’ from the IM students and only Info-seek activities receiveda ‘1’ from among the UI students. The mean score differences between the threegroups based on proficiency are compared in Table 3. As can be seen, there areseveral statistically significant differences between the specific activities and the
proficiency levels, notably the lower level of preference for Grammar drills /practice by the UI students compared with the PI students (p < .01), and thepreference for activities while moving by the IM students in comparison with the
PI students (p < .01).
The effect sizes were calculated for the statistically significant differences17

Ockert
Table 3
The Twelve Activity M, SD, and Mean Score Differences by Placement Exam Level
Student level:

PI (n = 73)

IM (n = 74)

UI (n = 73)

Activity:

M (SD)

PI / IM
Difference.

M (SD)

IM / UI
Difference

M (SD)UI / PI
Difference1) Lecture

3.79 (0.87).13

3.66 (0.78).20

3.86 (0.85).072) Listening exercises

3.40 (0.89).02

3.38 (0.93).15

3.23 (0.92).173) Dialogue / reading

3.22 (0.90).08

3.14 (0.75).20

3.34 (0.92).144) Writing exercises

3.15 (0.86).06

3.09 (0.76).07

3.16 (0.90).015) Translation exercises

3.15 (0.66).01

3.16 (0.64).18

3.34 (0.73).196) Grammar drills / practice3.16 (0.71).20

2.96 (0.83).19

2.77 (0.87).39***

7) Small-group activities

3.78 (0.82).25**

4.03 (0.74).02

4.01 (0.70).23**8) Info-seek activities

3.32 (0.66).11

3.43 (0.68).06

3.49 (0.75).179) Problem solving activities

3.30 (0.54).13

3.43 (0.64).12

3.55 (0.73).25**10) Activities while moving

3.26 (0.69).36***

3.62 (0.84).21

3.41 (0.80).1511) Challenging tasks

3.34 (0.69).11

3.23 (0.51).30**

3.53 (0.82).1912) Pair work

3.60 (0.86).22*

3.82 (0.67).03

3.79 (0.85).19Note. ***p < .01; **p < .05; *p < .10

reported in Table 3. According to Field (2009), effect sizes are useful because they
provide an objective measure of the importance of an effect. Therefore, it doesn’t
matter what effect you’re looking for, what variables have been measured, or how
those variables have been measured. For example, we know that a correlation
coefficient of 0 means there is no effect. A coefficient value of 1 means that there
is a perfect effect. Cohen (1988, 1992) has provided suggestions about what
constitutes a small or large effect for differences in mean scores (in Field, 2009):
MM r = .20 (small effect): In this case the effect explains 1% of the total
variance.
MM r = .50 (medium effect): The effect accounts for 9% of the total variance.
MM r = .80 (large effect): The effect accounts for 25% of the variance. (p. 57)
The fact that any statistically significant differences exist amongst the items
based on ability level for samples so small was a surprise. This study did nottest for the effect of any specific pedagogical intervention. Rather, it tested for18

A Placement Level Study, OnCUE Journal, 8(1), pages 3-34

differences in preferences for activities between groups of students based on
ability, not differences of a specific group before and after applying an experiment.
There are several differences between the level of enjoyableness / motivation of
specific activities between the three groups of students. The statistical significancefindings indicate that these differences are not based on chance alone. Therefore,
the effect size was calculated for the six statistically significance differences.
The effect size is calculated by taking the difference in means between two
groups and dividing that number by their combined (pooled) standard deviation.
This tells us how many standard deviations’ difference there is between the means(M) of the two activities for the two groups being compared. For example, aneffect size of .25 indicates that the difference between the two mean scores is aquarter of a standard deviation. In the data analysis for this paper, t-tests wereused to determine what, if any, statistically significant differences exist between
the mean scores for the three groups of students.
The effect size measures for these differences are as follows:
For variable 6 Grammar drills / practice between PI and UI, the Cohen’s d is
0.49.
The variable 7 Small-group activities difference between the PI and IM
students’ effect size measure is 0.32.
In addition, the effect size for the PI and UI students for variable 7 Smallgroup activities is 0.30.
For variable 9 Problem solving activities, the difference between the PI and UI
students has a Cohen’s d of 0.39.
For variable 10 Activities while moving between PI and IM, the Cohen’s d is
0.47.
For variable 11 Challenging tasks between IM and UI, the Cohen’s d is 0.44.
There are several effect size measures that are large enough to warrant
attention. The largest, for Grammar drills / practice between PI and UI (Cohen’s
d 0.49), indicates a medium effect size. Between PI and IM for Small-group
activities (Cohen’s d of .32) and for Activities while moving (Cohen’s d of .30)
19

Ockertare between the cut-off points for small and a medium effect sizes. Finally, for
Challenging tasks, the effect size for the mean difference between IM and UI, theCohen’s d is 0.44. For variable 9 Problem solving activities, the difference between
PI and UI has a Cohen’s d (0.39). Both results are above the threshold of .20 fora small effect size. In addition, the lowest mean score is for variable 6 Grammar
drills / practice for the IM students. The highest mean scores of 4.03 and 4.01 arefor the UI and IM students for variable 7 Small group / team activities. Finally,
the only mean score below a ‘3’ was for the IM students and variable 6 Grammar
drills / practice, indicating that this pedagogical approach was viewed negatively
by these students.
Variable Correlations
The Pearson correlation coefficients for the twelve variables appear in Table 4.
The correlations shed light on the relationships between both the survey sections
and the variables themselves. Recall that items 1-6 are hypothesized to be TAs
and items 7-12 are hypothesized to be C/TBAs. First, the variables on the TAs
scale have correlations amongst themselves and variables 7 and 11 on the C/
TBAs scale. Second, variables 7, 9, 10, and 12 on the C/TBAs scale have goodcorrelations as well as variables 8, 9 and 11. Variable 5 on the TAs scale correlates
well with variables 7, 8, and 11 on the C/TBAs scale, too.
Table 4
The Pearson Correlation Matrix of the Twelve Pedagogical Activities (N = 220)
Var 1

Var 2

Var 3

Var 4

Var 5

Var 6

Var 7

Var 8

Var 9

Var 10 Var 11

Var 2

0.407*

Var 3

0.386* 0.296*

Var 4

0.299* 0.255* 0.362*

Var 5

0.272*

0.143

0.265* 0.348*

Var 6

0.268*

0.138

0.187

0.418* 0.284*

Var 7

0.202

0.079

0.175

0.228*

0.211

Var 8

0.123

0.166

0.189

0.176

0.298* 0.265*

0.192

Var 9

0.147

0.246*

0.174

0.212

0.181

0.175

0.237* 0.344*

Var 10

0.171

0.073

0.094

0.111

0.147

0.208

0.310*

0.122

Var 110.224*

0.194

0.163

0.204

0.284*

0.192

0.094

0.240* 0.340* 0.268*

Var 12

0.192

0.023

0.114

0.107

0.180

0.180

0.456*

0.192

0.289*

Note. *p < 0.01

20

0.165
0.082

0.251*0.173

A Placement Level Study, OnCUE Journal, 8(1), pages 3-34

The PCA Results
SPSS tests of factorability include the Kaiser-Meyer-Olkin (KMO) measureof sampling adequacy and Bartlett’s Test of Sphericity. For the KMO, “values
between 0.5 and 0.7 are mediocre, values between 0.7 and 0.8 are good, values
between 0.8 and 0.9 are great and values above 0.9 are superb” (Hutcheson &Sofroniou, 1999, in Field 2009, p. 647). The results presented in Table 5 show
an acceptable KMO level and also the Bartlett’s Test of Sphericity shows a levelof statistical significance lower than p < 0.001. Both indicate that PCA on thesedata is appropriate.
Table 5
The KMO and Bartlett’s test of Sphericity Results
Kaiser-Meyer-Olkin Measure of Sampling Adequacy
Approx. Chi-Square
Bartlett’s Test of Sphericity.775
465.771

df

66

Sig.

.000

The third Research Question and Hypothesis 2 require a PCA to determine
if the variables will ‘cluster’ into factors / components comprised of TAs or C/
TBAs. The PCA results are presented in Table 6. For these results, 60% or lessexplained variance is satisfactory for the social sciences. The alpha reliability
estimate of .76 indicated inconsistency in the data. However, the PCA resultof three factors indicates the instrument measures three distinct constructs, one
for TAs and two for C/TBAs. Therefore, the PCA results help answer the third
Research Question, Do the respondents’ classroom activity preferences group by factor
analysis according to the TA and C/TBA distinctions made by several authors? In
addition, they help determine if Hypothesis 2: Principal components analysis will
distinguish between C/TBAs and TAs, is supported or not. The six hypothesizedTAs did, in fact, form a single factor, and the hypothesized C/TBAs formed two
factors of three items each.
As can be seen in Table 6, there are no cross-loadings above .40, although thecross-loading of 0.399 for variable 6 Grammar drills / practice is clearly about as21

Ockert
Table 6
Results of Principal Components Analysis of the 12 Activities for all of the Students (N = 220)
Item number and nameFactor 1
Factor 2
Factor 3
Traditional Activities Active Pair / Team work Brains

1. Lecture (Listen to the teacher and stay in my seat)

0.726

0.157

0.030

2. Listening exercises (CD, tape or DVD)

0.621

-0.1800.246

3. Dialogue / reading practice from the text

0.705

0.055

0.067

4. Writing exercises

0.664

0.171

0.134

5. Translation exercises

0.421

0.246

0.328

6. Grammar drills / practice

0.424

0.399

0.178

7. Small-group / team activities

0.167

0.771

0.074

8. Info-seek / finding information activities

0.119

0.175

0.653

9. Problem-solving activities

0.121

0.050

0.763

10. Activities where I am moving around in the room

0.018

0.563

0.258

11. Tasks that are intellectually challenging

0.157

0.114

0.680

12. Pair-work

0.054

0.770

0.033

Eigenvalue

3.394

1.390

1.135

% Total rotated variance explained per factor

19.10715.49414.720Note. Principal components analysis with Varimax rotation, with 49.321% total variance explained.

close as possible to also being included with the variables in factor 2, C/TBAs
Active Pair / Teamwork. Why would grammar drills and practice load with pairand group work? This is a question that deserves further investigation, possiblywith a qualitative approach, in the future. In addition, variable 5, Translation
exercises had a factor loading of 0.328 with factor 3, C/TBAs Brains. The
difficulty of translating from J<=>E makes this relationship rather more obvious
than the previous one.
The three factors are explained in more detail below. However, it should be
noted that the factors are formed by items / variables which are related to eachother as determined by the software algorithms. As such, the factor groupings
themselves do not indicate a ‘preference’ or approval, or disapproval by theparticipants. The three PCA factors, Cronbach’s alpha reliability estimates, andexplanations are as follows:
Factor 1: Traditional Activities (α = .71)
0.726 Item 1: Lecture22

A Placement Level Study, OnCUE Journal, 8(1), pages 3-34

0.621 Item 2: Listening exercises (CD, tape or DVD)
0.705 Item 3: Dialogue / reading practice from the text
0.664 Item 4: Writing exercises
0.421 Item 5: Translation exercises
0.424 Item 6: Grammar drills / practice
The variables loading on this factor consist of activities Lecture and Listening
exercises, which focus on teacher-fronted lessons, audio recordings, movies orlistening to a partner in dialogue practice. In addition, this factor also contains
Writing and Translation exercises, Grammar drills / practice and Dialogue / reading
practice from the text, all traditional approaches to foreign language learning.
With six variables, this factor has the highest alpha reliability score of the three.
Factor 2: C/TBAs Active Pair / Teamwork (α = .61)
0.771 Item 7: Small-group / team activities
0.563 Item 10: Activities where I am moving around in the room0.770 Item 12: Pair-work
The second factor has been labeled C/TBAs Active Pair / Teamwork since
the three variables loading on this factor involve Pair-work, Small-group / team
activities, and Activities where I am moving around in the room.
Factor 3: C/TBAs Brains (α = .57)
0.653 Item 8: Info-seek / finding information activities
0.763 Item 9: Problem-solving activities
0.680 Item 11: Tasks that are intellectually challenging
The variables loading on factor three emphasize task-based activities including
variables 8 Info-seek, finding information activities and 9 Problem-solving activities,
activities that require problem-solving skills and definite outcomes. In theprocess of reviewing this paper, it was suggested that variable 11 Tasks that are
intellectually challenging be dropped from the analysis as it appears based on its
23

Ockertface value to include several activity types. Yet, it loaded with variables 8 and 9
nicely, forming a factor of three items with no meaningful cross-loading.
There are similarities in the results presented in this paper and the results
reported by Jacques (2001) and Schmidt and Watanabe (2001). For example, theresults reported in the Jacques’ (2001) paper contain a factor comprised of items
related to grammar, reading and writing. In Schmidt and Watanabe’s (2001)
research results, vocabulary is also included. The results from both studies havea factor similar to Factor 1 in this study: TAs Listening, Writing & Grammar.
What may be of interest to classroom practitioners is that the IM students, who
are representative of 70% of the first year students, show a greater preference tobe active while learning than the PI and UI students. This is interesting since the
C/TBAs factor which includes variable 10 Activities while moving also includes
variables 7 Small-group activities and 12 Pair work. Therefore, there appears to
be a relationship between working with others and being physically active, too.
An as yet unexplored area of research that this paper investigates is the meanscore differences between the three factors as outlined above, and comparing
the differences between them for each of the three proficiency levels. These
results appear in Table 7 and several differences show a high level of statisticalsignificance, indicating that these differences are highly unlikely to be chancealone.
Table 7The Statistical Significance of the Differences between the Factor Groups by English Ability Level
Factor 1: TAs
Factor 2: C/TBAs
Listening, Writing Stat. Sig. Active Pair / Team Stat. Sig.
Factor groups:& Grammar
F1 vs F2work
F2 vs F3

Factor 3:
C/TBAs Brains

Stat. Sig.
F3 vs F1

All students

M = 3.30 (0.87)

p <.05

M = 3.70 (0.81)

p <.05

M = 3.40 (0.68)

na

PI (n = 73)

M = 3.31 (0.85)

na

M = 3.55 (0.82)

na

M = 3.32 (0.63)na

IM (n = 74)

M = 3.23 (0.82)

p <.01

M = 3.83 (0.77)

p <.01

M = 3.37 (0.62)

na

UI (n = 73)

M = 3.35 (0.93)

p <.10M = 3.74 (0.82)

na

M = 3.53 (0.76)

p <.10Note. The significance level for this analysis was set at p = < .10 as this is an exploratory study (Cohen, 1992).

The effect size measures for the mean statistically score differences between
the three factors are as follows:

24

A Placement Level Study, OnCUE Journal, 8(1), pages 3-34

For all students, the difference between Factors 1 and 2, the Cohen’s d is 0.48.
For all students, the difference between Factors 2 and 3, the Cohen’s d is 0.40.
For the IM students, the difference between Factors 1 and 2, the Cohen’s dis 0.75.
For the IM students, the difference between Factors 2 and 3, the Cohen’s dis 0.66.
For the UI students, the difference between Factors 1 and 2, the Cohen’s dis 0.44.
For the UI students, the difference between Factors 1 and 3, the Cohen’s dis 0.21.
As mentioned previously, the IM students represent approximately 70% of
the students in the faculty. They are also the group of students that shows thelargest (and most statistically significant differences) between Factor 2, C/TBAs
Active Pair / Team work and the first and third factors. Not unexpectedly, theCohen’s d for these two differences (0.75 and 0.66 respectively) are the largest for
any reported difference in the mean scores between the three factors by any groupof students. These results show that the effect sizes are large enough to inform
us that the statistically significant differences in the sampled populations aremeaningful. Therefore, careful consideration should be taken to consider student
ability level when making decisions on pedagogical activities and how they arepresented for use in the classroom.
TAs vs. C/TBAs: Social Constructivism, ‘Flow’, and Taskmotivation
The second research question asked Do the students from the three different
ability levels have different preferences for pedagogical activities? This question leadto Hypothesis 2: The participants in this survey will show differences in activity
preference based on ability level. Before looking at this issue more closely, it is worth
mentioning that none of the C/TBAs received a score of ‘1’ from any of the IM
25

Ockertlevel students, whereas all of the TAs received a ‘1’ from the UI level students.
What can we infer from this? As a classroom teacher with years of experience at
all levels of education in Japan, the author believes that the relationship between
language learning, peer interaction, Flow, and task-motivation accounts forthe relationship of the variables in Factor 2: C/TBAs Active Pair / Teamwork.
Further research including a qualitative segment would help us understand thisrelationship.
Yet, variable 1 Lecture (Listen to the teacher and stay in my seat) also received
a high mean score for enjoyableness and / or motivational aspect(s). What could
account for this? One reason that comes to mind is that the students are simply
apathetic toward learning English. Finally, C/TBAs items 9 Problem solving
activities, 10 Activities where I am moving around in the room, and 11 Tasks thatare intellectually challenging did not receive a ‘1’ for Strongly Dislike from any
student from any ability level.
While all three groups ranked Pair work and Small-group activities in the
top three (with Lecture), the IM students found both slightly more enjoyableor motivating than the PI and UI groups. These results are similar to thosereported previously for two cohorts of IM students (see Ockert, 2006, 2011).
This suggests that educators and curriculum developers should take note of thefact that the more advanced the students, the more they may like or need ‘realworld’ communicative opportunities or in-class scenarios. Of specific interest for
the theories tested is the homogeneity of the sample. While the students may
come from different backgrounds demographically, they are for all intents andpurposes very similar. It would be expected that all three groups answer similarly– yet they did not. The evidence herein demonstrates that students of different
ability levels may need, and therefore desire, different pedagogies. Furthermore,
Dörnyei (2009b) writes that learners should be offered “ample opportunities toparticipate in genuine L2 interaction” (p. 41, emphasis in original). Therefore,
students need at least a partner in order to communicate in any kind of ‘genuine’
L2 interaction. Listening to the teacher, CD, or even watching a movie is not
sufficient to supply the type of communicative opportunities that constitutegenuine L2 interaction. This may be why the more advanced the students, the26

A Placement Level Study, OnCUE Journal, 8(1), pages 3-34

more they seem to favor C/TBAs.

Conclusions
Implications for Placement Testing, Pedagogy, and Curriculum
Development
The results should not lead readers to infer that having students engage in theactivities that the students chose as more motivating / enjoyable will, in fact,increase their motivation to study English. The relationship of effectiveness andenjoyableness / motivating aspect of pedagogical activities has not been firmly
established. In fact, it may not necessarily be a linear relationship but may becircular or even self-reinforcing. What curriculum developers and classroom
educators need to be aware of is “the possibility of problems arising from amismatch of classroom activities with student expectations” (Green, 1993, p. 8).
For example, students who have passed a university entrance exam will almost
certainly have mastered basic grammar. To place such students in a class in which
the teacher places an emphasis on grammatical rules / activities will almost
certainly lead to student frustration, boredom, and burnout.
How are these results to be interpreted? For example, are these results
generalizable to the larger body of university students in Japan in general?
Lazaraton (2005) cautions that using parametric procedures may lead researchers
to overgeneralize their results and to make claims regarding their findings thatexceed what is permitted by their methodologies (p. 219). However, according
to Dörnyei (2011), “researchers should also not to be afraid to extend researchinterpretations to a general class or population if (there are) reasons to assume
that the results apply” (p. 213). In Japanese universities, the vast majority ofstudents who must study English are majoring in subjects other than English.
Therefore, the results presented in this paper may very well apply to university
English students in Japan in general. Teachers may wish to experiment withvarious activities to see what works and what does not work so well in their
specific situation. For example, can we combine activities that students perceive
as enjoyable / motivating with essential activities that are perceived as useful? I.e.
make a vocabulary memorization activity a group activity.
27

OckertLimitations and Future Research
Admittedly, the current study has its limitations. First, several of the activities on
the survey are not exclusive. For example, translation requires a source, a text orother written document as well as writing skills. Furthermore, it is more importantto recognize this study’s sampling limitations. This sample was drawn from thestudents, overwhelmingly male, of a highly ranked university. Therefore, since
the students who answered this survey are a sample of convenience, the results
may not generalize to the population of Japanese university students as a whole(see Brown, 2006). However, these students come from varied demographic
backgrounds and this should be taken into consideration when interpretingthese results for practical applications in the classroom. Yet, this study involved
students from a highly homogenous group and further research is needed todetermine the extent to which their pedagogical activity preferences would be
similar or different to students elsewhere. Gender could play a role in activity
preference; future research should take this into consideration and report theresults accordingly.
There are several questions which could be addressed in future studies.
For example, What could be the reason why some students prefer one pedagogicalapproach over another? Could the reason be the relevance of the material to herlife now, or future goals for language use? Are educators using ‘level appropriate’
pedagogies, materials, and methodologies in the classroom? Is this a ‘chicken andthe egg’ syndrome? In other words, Which comes first, the desire to engage in
specific activities or the level of achievement? Does one cause the other? Using amixed methods approach utilizing open-ended questions would help answer thequestion of why students may prefer certain pedagogical activities. The findingsin this paper of a survey of pedagogical activities are by no means conclusive, andit should not be assumed or inferred from these results that any specific activity inand of itself leads to an increase or decrease in proficiency. The author hopes thatclassroom teachers and curriculum developers may benefit from the information
presented herein. It would be wonderful if other researchers explored survey
differences as well and shared their students’ preferred activities with the broader
community of language researchers and teachers worldwide.
28

A Placement Level Study, OnCUE Journal, 8(1), pages 3-34

Acknowledgements

The author would like to thank David Beglar for his advice and support with theoriginal research project(s); the teachers and students who participated in the
project; and Tim Newfields and the anonymous reviewers for their invaluable
evaluations of an earlier draft of this manuscript. Any errors are the author’s.

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Author Bio

David Ockert has a M.Ed. from Temple University and a Level 2 JLPT certificate.
He presently works for Toyo University. His research interests are in CLT, TBLT,
CALL, motivation and student affect and self-determination theory in educational
contexts. ockert@toyo.jp
Received: February 22, 2013
Accepted: March 10, 201433

OckertAppendix
What classroom activities do you enjoy or find motivating?
Circle the number on the right that best matches your opinion.
1 = strongly dislike, 2 = dislike, 3 = neutral, 4 = like, 5 = strongly like
1. Lecture (Listen to the teacher and stay in my seat)
2. Listening exercises (using a cd, tape or DVD)
3. Dialogue / reading practice from the text
4. Writing exercises
5. Translation exercises
6. Grammar drills / practice
7. Small-group / team activities
8. Info-seek / finding information activities
9. Problem-solving activities
10. Activities where I am moving around in the room
11. Tasks that are intellectually challenging
12. Pair-work34