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International Journal of Learning, Teaching and
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VOLUME 11 NUMBER 1 April 2015
Table of Contents
Using Natural Language Processing Technology to Analyze Teachers’ Written Feedback on Chinese Students’
English Essays ........................................................................................................................................................................1
Ming Liu, Weiwei Xu, Qiuxia Ran and Yawen Li
Using Particle Swarm Optimization Approach for Student Engagement Measurement............................................ 12
Ming Liu, Yuqi Wang, Hua Liu, Shujun Wu and Chang Li
A Study of the Development of Courseware and Students’ Learning Effectiveness in Primary Education: Using
Three Teaching Techniques as an Example....................................................................................................................... 22
Fang-Chun Ou
A Comparative Examination of Teacher Candidates’ Professional Practicum Experiences in Two Program Models
.................................................................................................................................................................................................36
Nancy Maynes, Anna-Liisa Mottonen, Glynn Sharpe and Tracey Curwen
A Study of Formative Assessment Strategies in Teachers‘ School-Based In-Service Training...................................53
Eva Nyberg and Mona Holmqvist Olander
Designing and using interactive e-books in Vietnam .....................................................................................................75
Ngoc-Giang Nguyen
Impact Investigation of using a Digital Literacy Technology on a Module: Case Study of Tophat .......................... 99
Xue Zhou and Stella-Maris Orim
Implementation of the 2006 Education Amendment Act on Indigenous Languages in Zimbabwe: A Case of the
Shangaan Medium in Cluster 2 Primary Schools in the Chiredzi District .................................................................117
Webster Kododo and Sparky Zanga
The Concept of In Situ Lecturing...................................................................................................................................... 128
Joachim R. R. Ritter and Ellen Gottschämmer

The Mathematics Problem and Mastery Learning for First-Year, Undergraduate STEM Students ...................... 141
Layna Groen, Mary Coupland, Tim Langtry, Julia Memar, Beverley Moore and Jason Stanley
Teaching Culture through Language: Exploring Metaphor and Metonymy in Chinese Characters ..................... 161
Hu, Ying-Hsueh
Coaches‟ Perceptions of how Coaching Behavior affects Athletes: An Analysis of their Position on Basic
Assumptions in the Coaching Role .................................................................................................................................180
F. Moen, R. Giske and R. Høigaard
Regional Educational Development Research and School Improvement: A Systematic Literature Review of
Research ............................................................................................................................................................................... 200
Associate Professor Lena Boström
The Value-Added Assessment of Higher Education learning: The case of Nagoya University of Commerce and
Business in Japan ............................................................................................................................................................... 212
Hiroshi Ito Surname and Nobuo Kawazoe

1
© 2015 The authors and IJLTER.ORG. All rights reserved.
International Journal of Learning, Teaching and Educational Research
Vol. 11, No. 1, pp. 1-11, April 2015.
Using Natural Language Processing Technology
to Analyze Teachers’ Written Feedback on
Chinese Students’ English Essays
Ming Liu, Weiwei Xu, Qiuxia Ran and Yawen Li
Southwest University
Beibei District, Chongqing, China
Abstract. Writing an essay is a very important skill for students to
master, but a difficult task for them to overcome. It is particularly true
for English as Second Language (ESL) students in China. It would be
very useful if students can receive timely and effective feedback about
their writing. In order to build an automatic feedback system, we need
to understand the relationship between textual features and human
teacher feedback, and how well those features were used for predicting
feedback rating. In this study, we analyzed 105 Chinese English majors’
essays with teachers’ feedback and used Coh-Metrix, a computational
linguistic tool, to extract features from their writing. The study results
showed some feedback was moderately correlated to some textual
features (e.g. text easability cohesion and lexical diversity were related
to coherence feedback) and those feedback are more predictable, such as
spelling, grammar, supporting ideas and coherence. This finding has
important implications for building automated writing feedback tool.
Keywords: Writing Feedback, Text Analysis, Natural Language
Processing.
1. Introduction
With the coming of the 21st century and the globalization of English, English
essay writing, as one of the four basic skills of language learning, has become a
more and more important skill. It not only requires some basic writing skill,
such as spelling and grammar, but also asks some high competency of writing,
such as coherence, structure and reasoning. Thus, it is also a difficult task to
overcome. It is particularly so in China. Statistics show that the number of
college students in China has soared to twenty-six million in 2013 (Bureau of
Statistis of China, 2013), accounting for the largest proportion of ESL learners
worldwide. Since 1987, the writing test has become one important aspect of the
College English testing in China. As for college students in China, college
English has been an obligatory course to take. In a typical English course,

2
students have to do 2-3 essay writing assignments and take 1 essay writing test
in order to pass national English tests, such as College English Test (CET) 4 or
Test for English-Major (TEM) 4. Essay writing is the last part of these tests.
Novice writers need feedback to develop their writing skills; however,
providing timely and meaningful feedback is time-consuming and expensive.
Since the early 1980s, researchers have investigated feedback on students’
writing (Brannon & Knoblauch, 1982). These study results showed that written
feedback provided a potential value in motivating students to revise their draft
and improving their writing (Leki, 1991). As a result, written feedback is the
most popular method among various feedback delivery modes (oral feedback,
audiotaped and writing conference) that teachers use to interact and
communicate with students. Straub (Straub, 2000) suggested that the effective
teacher feedback should be written in complete sentences, avoid abstract,
technical language and abbreviations, relate their comments back to specific
words and paragraphs from the students’ text, by viewing students’ writing
seriously, as part of a real exchange. In addition, an increasing number of
studies have also been conducted to see whether certain types of feedback are
more likely than others to help ESL students improve the accuracy of their
writing, such as direct and indirect feedback (Lee, 2004). Direct or explicit
feedback occurs when the teacher identifies an error and provides the correct
form, while indirect strategies refer to situations when the teacher indicates that
an error has been made but does not provide a correction, thereby leaving the
student to diagnose and correct it.
With the advanced development of information technology and natural
language processing techniques, various numbers of automatic essay scoring
(AES) systems have been proposed. Haswell (Haswell, 2006) reviewed systems
for automated feedback tracing back to the 1950s. These systems focused more
on assessment of end products, and less on providing formative feedback
(Shermis & Burstein, 2003; Williams & Dreher, 2004) The Writer Workshop
(Anderson, 2005) and Editor (Thiesmeyer & Theismeyer, 1990) both focus on
grammar and style. Sourcer’s Apprentice Intelligent Feedback system (SAIF)
(Britt, Wiemer-Hastings, Larson, & Perfetti, 2004) is a computer assisted essay
writing tool used to detect plagiarism, uncited quotations, lack of citations, and
limited content integration problems. The Glosser system (Villalon, Kearney,
Calvo, & Reimann, 2008) aims to support reflection in writing through trigger
questions. It uses text mining algorithms to help learners think about issues such
as coherence, topics, and concept visualization. However, Glosser only provides
generic trigger questions. Liu et al. (Liu, Calvo, & Rus, 2014; Liu, Calvo, & Rus,
2010) investigated an automatic trigger question generation system which could
support critical review writing.
The aim of this study is to investigate the frequent type of feedback used by
human teachers and the relationship between the feedback and the textual
features extracted by using the natural language processing techniques.

3
The rest of this paper is constructed as follows: Section 2 presents related work
on feedback classification. Section 3 describes the study and discusses the
results. Finally, Section 4 concludes this paper.
2. Related Work
Recent development in natural language processing techniques has made it
possible for researchers to develop a wide range of sophisticated techniques that
facilitate text analysis. Some tools, such as Coh-Metrix (Graesser, McNamara,
Louwerse, & Cai, 2004), LIWC (Pennebaker & Francis, 1999) and Gramulator
(Rufenacht, McCarthy, & Lamkin, 2011), are useful in this respect, and have
certainly contributed to ESL knowledge (S．A. Crossley & McNamara, 2012).
Coh-Metrix is a powerful computational tool that provides over 100 indices of
cohesion, syntactical complexity, connectives and other descriptive information
about content (Graesser et al., 2004). Coh-Metrix has extensively been used to
analyze the overall quality of writing (S．A. Crossley & McNamara, 2012) and
one important aspect of writing quality, such as coherence (Scott a. Crossley &
McNamara, 2011a). For example, Crossley and McNamara found that
computational indices related to text structure, semantic coherence, lexical
sophistication, and grammatical complexity best explain human judgments of
text coherence. This study focused on using Coh-Metrix to analyze more aspects
of writing quality including, Supporting Ideas, Conclusion and Sentence
Diversity.
The AES systems, such as Criterion (Burstein, Chodorow, & Leacock, 2004), can
provide feedback on some aspects of writing including grammar, usage,
mechanics, style, organization, development, lexical complexity and prompt-
Table 1: Criterion Category
Criterion Category Examples
Grammar Fragments, Run-on Sentences
Subject-verb agreement, Ill-formed verbs
Pronoun Error, Missing Possessive Error
Usage Wrong article, Missing article
Confusing words, Wrong form of word
Preposition Error
Mechanics Spelling, Capitalize Proper Nouns
Missing Question mark, Missing final punctuation
Missing Apostophe, Missing Comma
Style Repetition of words, Inappropriate words or
phrases
Too many short sentences, Too many long
sentences
Organization Background, Thesis, Main-point
Supporting ideas, Conclusion

4
specific vocabulary usage (See Table 1). The Criterion categories are more
relevant to our case since we aim to generate corrective feedback on different
aspects of ESL student writing.
3. Study
We conducted an empirical study in analyzing Chinese ESL college student
essays with teachers’ comments and the relationship between the teacher
feedback and textual features. Section 3.1 describes the annotation process,
where each essay is scored in different aspect, such as Grammar, Spelling,
Coherence, Organization and Supporting Ideas. Section 3.2 shows the textual feature
extraction process. Section 3.3 illustrates the relationship between the textual
features and each feedback category, while section 3.4 examines the predictive
strength of the features in explaining the score variance in the each feedback
score.
3.1 Proposed Feedback Taxonomy
Table 2: Feedback Frequency and Pearson Correlations between Raters
Our dataset containing 105 English majors’ essays with teachers’ feedback was
collected from a large university in China. Two experienced English teachers
volunteered to rate the quality of the essays. They had at least five years of
teaching composition course for English majors. Their first task was to identify
the most frequent feedback type adapted from the standardized rubric used for
grading college English. 9 frequent feedback categories were found, including
Grammar, Spelling, Word Count, Sentence Diversity, Conclusion, Supporting Ideas,
Organization, Coherence and Chinglish (See Appendix I). Table 2 shows that
Supporting Ideas and Organization categories were more frequent than others,
while Spelling and Chinglish Expression and word count were less frequent. We
observed some feedback categories were similar to the Criterion categories, such
as Grammar, Spelling and Supporting Ideas. But, the Chinglish Expression and
Conclusion categories only appeared in our dataset.
The teachers’ second task was to give a score to each feedback category
regarding to the rubric (See Appendix I) on a scale of 3. 1 means negative
Feedback Category Frequency r
Grammar 48 .824
Spelling 12 .504
Word Count 24 .707
Sentence Diversity 40 .454
Conclusion 44 .747
Supporting Ideas 98 .632
Coherence 40 .716
Chinglish Expression 24 .352
Organization 89 .534

5
feedback on the category while 3 means positive feedback on the category. The
Correlations between the raters are located in Table 2. The raters had the highest
correlations for judgments of Grammar, Word Count, Conclusion and
Supporting Ideas and the lowest correlations for Chinglish and Sentence
Diversity.
For further analysis, the dataset was randomly divided into training set (n=70)
and testing set (n=35). A training set was used to identify which of the textual
features most highly correlated with each feedback score. Moreover, the training
set was used to train a multiple regression model to examine the amount of
variance explained by each writing feature. The model was then applied to a test
set to calculate the accuracy of the analysis.
3.2 Textual Feature Extraction
We used Coh-Metrix 3.0, which could retrieve 108 scores of textual features.
More information can be found on the website
(http://cohmetrix.Memphisedu/cohmetrixpr/index.html).
Descriptive indices: It includes the number of paragraphs, number of sentences,
number of words, number of syllables in words, mean length of paragraphs etc.
Cohesion: Cohesion is a key aspect of understanding language discourse
structure and how connections within a text influence cohesion and text
comprehension(Kintsch & van Dijk, 1978). Coh-Metrix employs referential
cohesion including noun overlap, argument overlap, stem overlap, and LSA-
based semantic overlap.
Sentence Complexity: The grammatical structure of a text is also an important
indicator of human evaluations of text quality. Difficult syntactic constructions
(syntactic complexity) include the use of embedded constituents, and are often
dense, ambiguous, or Ungrammatical (Graesser et al., 2004). Syntactic
complexity is also informed by the density of particular syntactic patterns, word
types and phrase types.
Lexical sophistication: Lexical sophistication refers to the writer’s use of advanced
vocabulary and word choice to convey ideas. Lexical sophistication is captured
by assessing the type and amount of information provided by the words in a
text. Words are assessed in terms of rarity (frequency), abstractness
(concreteness), evocation of sensory images (imagability), salience (familiarity),
and number of associations (meaningfulness). Words can also vary in the
number of senses they contain (polysemy) or levels they have in a conceptual
hierarchy (hypernymy).
Moreover, we propose and extract 8 new features that are not available in Coh-
Metrix. These features refer to characteristics of ESL learners’ writing style and
reflect on the importance of the introduction section, conclusion section and
mechanics in errors including spelling errors and grammatical errors. In the
database, each essay is stored as a plain text, where each line is a paragraph. We

6
use Java API to extract the first line and last line text, as introduction and
conclusion section respectively. For checking spelling errors, an open source
spelling error checker, called LanguageTool (http://www.languagetool.org/), is
employed to scan each word. For checking grammatical errors, the Link
Grammar Parser (Lafferty, Sleator, & Temperley, 1992) is used to check the
grammar of a sentence based on natural language processing technology. If the
link grammar could not generate links (relations between pairs of words) after
parsing a sentence, this sentence would be considered as ungrammatical.
Number of words in Introduction: the total number of words in the first paragraph
considered as the introduction section.
Number of words in Conclusion: the total number of words in the last paragraph
considered as the conclusion section.
Introduction Portion: the ratios of number of words in introduction to the total
number of words in the document.
Conclusion Portion: the ratios of number of words in conclusion to the total
number of words in the document.
Spelling errors: the number of spelling errors. We employ an open source spelling
error checker called LanguageTool (http://www.languagetool.org/), which is
part of the OpenOffice suite.
Grammatical errors: the number of sentences with grammatical errors. We use the
Link Grammar Parser (Lafferty et al., 1992) to check the grammar of a sentence,
which is also widely used in ESL context.
Percentage of spelling errors: the ratios of the number of word spelling errors to the
total number of words in the document.
Percentage of grammatical errors: the ratios of the number of sentence with
grammatical errors to the total number of sentences in the document.
Therefore, there are totally 116 features extracted from each essay.

7
3.3 Pearson Correlation
Based on the system producing feature scores and the human annotators’ score
on each category, we used IBM SPSS for evaluating the Pearson correlation
between textual features and each category. Over 30 textual features
demonstrated significant correlations with the human ratings of each feedback
category. Table 3 shows the Chinglish was more related to the number of Gerund
used, the paragraph length and the first person singular pronoun incidence. The
Coherence was correlated to Text Easability PC Deep cohesion, consistent with
Crossley and McNamara’s study result (S. Crossley & McNamara, 2010). As
expected, the Conclusion was more related to the features of Conclusion Portion
and Lexical Diversity. We have not defined specific features which can detect the
Supporting Ideas. However, some features, such as Intentional verbs and
Adjective incidence, have shown their moderate correlations with the category
of Supporting Ideas. As we had expected, the Grammar and Spelling were
negatively related to the features of grammar error and spelling error. The Word
Count was correlated to the number of words in an essay. Organization was
correlated to the number of paragraphs since the essays with only 1 or 2
paragraphs were given lower scores by human annotators since they did not
have a clear essay structure, introduction, body and conclusion. Crossley and
MacNamara (Scott a. Crossley & McNamara, 2011b) got the similar study
results, where six features including the total number of paragraphs were
significant predictors in the regression to the raters’ organization evaluations.
Table 3: Correlations between Textural Features Scores and Raters’
feedback scores
Feedback Category Features R P
value
Chinglish
Gerund incidence .415 <0.05
paragraph length .459 <0.05
first person singular pronoun
incidence
.493 <0.01
Coherence
Text Easability Cohesion .433 <0.05
Lexical diversity .402 <0.05
Conclusion Conclusion Portion .477 <0.05
Lexical diversity .394 <0.05
Supporting Ideas
Intentional verbs incidence .496 <0.05
Adjective incidence .503 <0.05
CELEX Log minimum frequency
for content words
.541 <0.01
Grammar Grammar errors -.606 <0.01
Sentence Variety
Hypernymy for verbs .506 <0.01
Standard deviation of Sentence
length
.413 <0.05
Spelling Spelling Errors -.617 <0.05
Organization Number of paragraphs .507 <0.01
Word Count Word count .666 <0.01

8
3.3 Test Set Model
We used the training set to train a regression model for each feedback category
and evaluated the model in testing set. Table 4 shows the performance of each
regression model for predicting essay feedback ratings. It has been found that
Grammar (r2=.881) and Spelling feedback (r2=.886) were easier for prediction,
since some textual features were highly related to those feedbacks. It also
demonstrated that the combination of the textual features accounted for 88.1% of
the variance in the grammar evaluation of the 35 essays comprising the test set.
On the other hand, organization and conclusion were difficult to predict since
r2=.223 and r2=.380 respectively since the textual features were not correlated to
those feedback ratings.
Table 4: Linear Regression Analysis to Predict Essay Feedback Ratings in Testing Set
Feedback R R2 S.E.
Chinglish
Expression
.764 .584 .349
Coherence .790 .624 .472
Conclusion .616 .380 .486
Supporting
Ideas
.745 .555 .407
Grammar .939 .881 .260
Sentence
Variety
.735 .540 .423
Spelling .941 .886 .242
Organization .475 .223 .473
Word Count .756 .572 .535
Notes: S.E. is standard error
4. Conclusion
Human teachers’ written feedback is very useful for students to revise their draft
and improve writing. A great number of researches has been conducted to
investigate the theoretical foundation of feedback in terms of feedback mode,
feedback strategies and feedback classification. With the development of
information technologies, automated essay scoring tools have been proposed,
which can extract textual features and generate corrective feedback on the traits
of writing including grammar, usage, style, mechanics and organization.
However, these AES systems are mainly designed for international ESL
students, who take TOFEL test. Those students can only represent a small
portion of ESL students, because they obviously possess a higher English
competency. Thus, we conducted an empirical study to investigate the frequent
feedback types and examine the feasibility of using existing natural language
processing tools to automatically measure the feedback.
In the study, we collected 105 essays written by English majors and some
teachers’ comments at a large university in China. Two English teachers first
found 9 frequent feedback categories based on the teachers’ comments. Some
feedback categories are consistent with the Criterion category. Then, they gave a

9
score on a scale of 1 to 3 to each feedback category of each student essay. The
study results showed that the feedback had moderate correlations with some
features extracted by using Coh-Metrix, a computational writing analysis tool,
and some proposed new features. For example, coherence feedback was highly
related to Text Easability Cohesion and Lexical diversity, while Supporting Ideas
was related to Intentional verbs incidence and Adjective incidence. Moreover, it
has been found that some feedback, such as supporting ideas, coherence,
grammar and spelling, were more predictable. It indicated the feasibility of
using existing NLP tools to measure the quality of feedback.
Our future work will examine teachers’ comments in detail and collect non-
English major student essays for analysis. In addition, we will focus on building
an automatic essay feedback generation system. Specifically, we will investigate
the feedback generation mechanism by using association rule mining
algorithms. In addition, we will look at how to incorporate effective feedback
strategies, such as formative feedback theory, into feedback generation
templates.
Acknowledgment
The authors would like to thank those teachers and student participants. This
work is partially supported by Chongqing Social Science Planning Fund
Program under grant No. 2014BS123, Fundamental Research Funds for the
Central Universities under grant No. SWU114005, No. XDJK2014A002 and No.
XDJK2014C141 in China.
Appendix A
Table 5: Nine Traits Rubric for Essay Writing
Category Scoring
Organization 1 Rudiment of organization apparent, but may be illogical,
ineffective or different to understand the sequencing of ideas
2 Satisfactory organization of sections, but the sequencing of
paragraphs within sections may be problematic.
3 Effective method of organization for both section and for
paragraphs within sections.
Supporting Ideas 1 Minimal use of examples and facts to support the writer’s
idea.
2 using some examples and facts to discuss
strengths/weakness of some opinions, but may have difficulties
(1) choosing appropriate facts; (2) sufficiently explaining those
facts; (3) connecting them to present thing.
3 Effective supports the strengths and weakness of one’s
opinion; Generally effective use of choice of examples and facts,
although some material may be extraneous or not adequately
explained
Grammar 1 Uses simple sentence constructions, but there are still
numerous errors (greater than 7).

10
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Williams, R., & Dreher, H. (2004). Automatically Grading Essays with Markit©. Issues in
Informing Science and Information Technology, 1, 693-700.

12
Vol. 11, No. 1, pp. 12-21, April 2015
Using Particle Swarm Optimization Approach
for Student Engagement Measurement
Ming Liu, Yuqi Wang, Hua Liu, Shujun Wu and Chang Li
Southwest University
Beibei, Chongqing, China
Abstract. Measuring Student Engagement is a difficult task. Previous
research has used a cloud-based writing platform, Google Docs, which
can store a number of document revisions with timestamps.
Engagement measurement algorithm has taken the advantages of each
timestamp in a revision and calculated how much time the student
spent on a writing task. However, the parameters passed to the
algorithm were fixed and hard to determine, for example, how much
time means fully engaged or partially engaged. In this paper, we
proposed a new student engagement measurement algorithm based on
a computational intelligence approach, Particle Swarm Optimization
technique, to find the optimized parameters for the engagement
measurement algorithm. In the study, the proposed algorithm measures
the engagement of two groups of students in two different writing
activities (long-term and short term writing activities) carried out in our
cloud-based writing platform. The study results show that the
correlations between the engagement measurement and student self-
report are high. In addition, it indicates that this approach is robust to
measure student engagement in both long-term and short term
activities.
Keywords: Student Engagement Measurement, Advanced Educational
Technologies, Particle Swarm Optimization.
Introduction
Student engagement plays an important role in a learning activity. Studies
(Fredricks, Blumenfeld, & Paris, 2004) show that a student who is engaged and
intrinsically motivated in a task is more likely to learn from an activity and
models of school engagement identify three core dimensions: behavioral,
cognitive and emotional engagement. ‘Behavioral engagement’, which is the
focus of the present study, refers to student participation in school related
activities and involvement in any learning tasks such as those being done online
(Fredricks et al., 2004). ‘Cognitive engagement’ refers to motivation,
thoughtfulness and willingness to make an effort to comprehend ideas and

13
master new skills. ‘Emotional engagement’ includes emotions and interest, such
as affective reactions in the classroom towards teachers. These three aspects are
interrelated and helpful to understand engagement as a whole.
The measurement of behavioral engagement is more obvious because behavioral
patterns can be defined, observed and interpreted. Traditionally, student
engagement is measured by teachers’ observation (Bulger, Mayer, Almeroth, &
Blau, 2008; Martin, 2007). But, this approach is time consuming and subjective. In
the era of ‘big’ data, a large amount of student data about their behavior being
harnessed to improve learning interactions and to personalize the learning
experience can be collected by the system (Tanes, Arnold, Selzer King, & Remnet,
2011). For instance, when a student participates in an activity that is technology
mediated, a detailed collection of behavioral events can be recorded. Computer
keystroke-logging (Leijten & Van Waes, 2013) or screen capturing (Latif, 2008)
allow a detailed account of the behavior of a writer including actions such as
starting a new paragraph or deleting a text portion and these are all considered
indicators of behavioral engagement. Thus, new computer technology permits the
observation and identification of learning events, which can then be examined in
relation to other indices of engagement. However, these technologies require
specialized setups and often hardware.
In the recent year, with the development of the cloud-based online writing
platform, such as Google Doc or Wiki, it is possible to capture student’s writing
behavior easily by utilizing document revision history (Cole, 2009; Liu et al.,
2013). However, the engagement measurement algorithm requires so many
predefined parameters, such as the time threshold for full engagement or for
partial engagement. Previously, the thresholds are determined by educational
experts, which is too subjective. If the thresholds are set too high or too low, it
would affect the accuracy of engagement measurement and effect of engagement
visualization.
Particle swarm optimization (PSO) is a population-based metaheuristics used for
stimulating social behaviour such as fish school to a promising position (S. W.
Lin, Ying, Chen, & Lee, 2008). PSO is a subset of swarm intelligence which was
occurred in the late 1980s to relate to cellular robotic systems, where a number of
agents in an environment interact based on local rules. Over the past years,
particle swarm optimization technique has lately been illustrated to have the
ability to solve complex problems, such as automatic group composition(Y.-T.
Lin, Huang, & Cheng, 2010), e-learning problems(Huang, Huang, & Cheng,
2008), automatic test sheets generation (Yin, Chang, Hwang, Hwang, & Chan,
2006). These studies suggested that swarm intelligence is useful for providing
high scalability and robust computation. In our study, we use PSO to optimize
the engagement measurement algorithm.
Behavioural Engagement
Studies of behavioural engagement in learning environments typically use
evidence collected by human observers, such as teachers or students (Lane, 2009;
Martin, 2007). For example, using scales such as the Student Engagement

14
Walkthrough Checklist, observers such as administrators, instructional
supervisors or teachers, have examined the degree to which students exhibit
engagement in the classroom, by measuring behaviors such as positive body
language, consistency of focus, spoken participation (Jones, 2009). The observer
ratings are then compared to simultaneous and anonymous ratings by students
of their level of engagement according to the extent to which the work is
interesting and challenging, and the degree to which they understand why and
what they are learning.
Jones (2009) have defined the models of general engagement including
behavioral, emotional and cognitive engagement as consisting of three
dimensions; intensity, consistency and breadth. Intensity relates to the level of
engagement of each student. Consistency refers to how long students remain
engaged at high levels throughout the class period and breadth refers to how
broadly the class as a whole is engaged. Measuring dimensions of engagement
allows teachers to provide differentiated feedback. For example, if the
engagement intensity is low, teachers can focus on adding rigor and relevance to
expectations and lessons.
To date, most of the research on student engagement has occurred in classrooms
(Sheldon & Biddle, 1998), yet researchers are increasingly exploring learning
theories in web-based activities (Chena, Lambertb, & Guidryb, 2010), social
software (2009), smart interactive devices (Blasco-Arcas, Buil, Hernández-
Ortega, & Sese, 2013) and virtual environments (Bouta, Retalis, & Paraskeva,
2012). ‘Clickers’ (Blasco-Arcas et al., 2013) allowed students to quickly answer
questions presented in class. Responses can be anonymized or identified and
software programs are usually used to summarize responses and present
visualizations in the form of charts. Technology-based tools such as Wiki
technology (2009) have been used to support learning engagement. Cole (2009)
tested Wikis in a third year undergraduate course to examine the degree to
which they supported student knowledge construction, peer interaction and
group work. However given the optional nature of this form of technology in
the course, students did not contribute to the Wiki as was intended. Thus focus
groups were used to examine barriers to uptake rather than the effects of Wikis
on student engagement per se. However, a limitation of previous studies is that
they have not addressed how to automatically track and analyze student
behaviour patterns and present them in a way that is understandable. Given the
difficulties identified by previous studies (2009) related to student use of web-
based techniques the present study was conducted within a laboratory
environment rather than as part of a course.

15
Engagement Visualization and Measurement
Engagement is critical to the success of learning activities such as writing, and
can be promoted with appropriate feedback. Tracer is a learning analytic system
(Liu et al., 2013) which derives behavioral engagement measures and creates
visualizations of behavioral patterns of students writing on a cloud-based
application. Figure 1 shows that the Line-based Visualization uses a line to
connect the points and the thickness of a line indicates the intensity of the user’s
behavior during a period of time. This information is derived from Intensity-
based engagement measurement algorithm (IbA), where a series represents a
line and its weight represents a line thickness. Therefore, the whole graph is
made of lines. The weighting process is defined as follows:
1. A hashmap is predefined, where each entry contains a time threshold and a
corresponding weight value. For example, (0.5h, 0.8) indicates that the time
threshold is 0.5h and its corresponding weight is 0.8.
2. If the duration between neighboring events is less than the shortest time
threshold, we assign that corresponding weight to the series. For example, in
one month project proposal writing assignment, the following
combinations/hashmap: (0.5h, 1), (1h, 0.8), (3h, 0.4) and (12h, 0.2) is considered
based empirical experience. For example, if the duration of an activity is 2 hours,
we assigned 0.4 as a weight to the series because 3h is the shortest time defined
in the hashmap that is longer than 2h.
Thus the total engagement score is calculated as the following weighted sum:
Engagement= si ∗ wi
n
i (1)
where i is the index of a series, Si is the duration of the series i and Wi is the
weight assigned to i.
Figure 1: Line-based Visualization: green lines with different thickness show that
a user has done several intensive writing in the drafting process.
Graphs are copied from (Liu, Calvo, & Pardo, 2013).

16
Particle Swarm Optimization
PSO looks through a collection of individual solutions called particles that update
iteratively. Each particle at iteration t can be represented by a D-dimensional state
vector as 𝑥𝑖
𝑡
= 𝑥𝑖1
𝑡
, 𝑥𝑖2
𝑡
, … , 𝑥𝑖𝐷
𝑡
. Then, to obtain the optimal solution, we define D-
dimensional velocity vectors 𝑉𝑖
𝑡
= 𝑉𝑖1
𝑡
, 𝑉𝑖2
𝑡
, … , 𝑉𝑖𝐷
𝑡
for each particle and
determined by its own best previous experience, denoted as pbest, and the best
experience of all the particles, denoted as gbest. Particles change velocity based
on the pbest and gbest as follows:
   1
1 1 2 2
t t t t t t
id id id id id idV V c r pbest X c r gbest X
    
,d=1,2,3…D (2)
Where 𝑐1 𝑎𝑛𝑑 𝑐2 are the learning factors which are commonly set to 2 and 𝑟1, 𝑟2
are random numbers distributed uniformly in the range [0, 1]. Then, each particle
updates to a new potential answer based on the velocity as:
𝑋𝑖𝑑
𝑡+1
= 𝑋𝑖𝑑
𝑡
+ 𝑉𝑖𝑑
𝑡
(3)
When the iteration number reaches a pre-determined maximum iteration
number, the update process is terminated and the best individual of the last
generation is the final solution to the target problem.
PSO enhanced Engagement Measurement Algorithm
In this section, we describe the proposed PSO-EM algorithm for predicting the
total time a student spent on the writing task. The aim of this study is to optimize
the accuracy of the engagement prediction by estimating the best values of an
engagement measurement function parameters described above. We used the
Matlab to implement this algorithm. The evaluation matrix for SVR is MSE (mean
square error).
MSE =
1
𝑛
(𝑓 𝑥𝑖 − 𝑦𝑖)2𝑛
𝑖=1 (4)
MSE is a common evaluation measurement for numeric value prediction, which
has been adapted in education (Tang & Yin, 2012).
In our study, PSO starts with 20-randomly chosen particles and looks for the
best particle iteratively. Each particle is a 6-dimensional vector including three
time thresholds and three weights represents a candidate solution. The
engagement measurement algorithm is constructed for each candidate solution
to estimate its performance. The procedure describing proposed PSO-SVR
approach is as follows.

17
Function PSO-EM () {
Initializing PSO with 20 particles and each engagement measurement algorithm with
each particle.
Evaluating the fitness (MSE) of each particle.
For each iteration in 200
For each particle in 20
Calculating the particle velocity and updating the particle
Calculating the fitness of the particle by passing the parameters to
engagementMeasurement()
Comparing the fitness values and updating the local best and global best
particle.
End
End .
}
Study
In order to evaluate the feasibility of the proposed engagement measurement
algorithm, we have conducted a study, where 120 students were writing an
individual document in a web-based writing system. This system is developed
based on etherpad (http://etherpad.org/), which is an online real-time text
editor, letting authors to write a text document, and look all the revision history
of the document. Each document revision history has been recorded in a textual
database. We need to extract the timestamp of each revision as an input to the
engagement algorithm.
Participants and Procedure
A total of 120 university students participated in this study. The participants’
age ranged from 20 to 30 years (M: 25, SD: 5) and there were 61 males and 59
females. Those student participants came from different disciplines, including
computer engineering and education. They had no prior knowledge of the
system and did not participated in any previous related study. We arranged a
separate one hour writing activity for 60 education majors (writing a personal
best travel experience) while one month writing activity (writing a project
proposal) for 60 engineering students. We conducted this study in a controlled
environment so that each participant could only write in our system (see Figure
2), thus avoiding the ‘copy-and-paste’ issues. Once the writing activity was
finished, each participant was asked to estimate their engagement time in the
writing session. The dataset was divided into the training set (n=30) and testing
set (n=30) for each activity. We used the training set to train the parameters of the
engagement algorithm and testing set to evaluate the performance of the
algorithm.

18
Results
The correlation among participants and engagement measurement functions is
presented in Table 1. This study results show that correlations between the
proposed engagement algorithm (PSO-EM) and human are highly correlated
(r=.73 and r=.81) in both writing activities. This algorithm outperformed IbA
which has moderate correlation (r=.49 and r=.59) with student self-report
(Human). We also observed that the student engagement time in the one-hour
writing activity is more predictable than in the one month writing activity,
because the one-hour writing activity produced less document revisions.
Figure 2: the user interface in the online writing system

19
After 200 iterations, PSO-EM converges. Table 2 shows that PSO-EM algorithm
(MSE:15.88 in one hour;MSE:31.89 in one month) gets lower MSE scores than
traditional IbA (MSE:16.13 in one hour;MSE:64.95 in one month) in both writing
tasks (one hour and one month writing tasks).
In the one hour writing task, PSO-EM finds the best parameters for this dataset
include Threshold1 as 3.30, Threshold2 as 4.20 and Threshold3 as 5.12 minute,
and Weight1 as 1.09, Weight2 as 2.34 and Weight 3 as 2.89.
In addition, in the one month writing task, the best parameters for threshold are
different from those parameters in one hour writing task and the unit is hour.
This result indicates that the PSO-EM algorithm is robust to automatically adjust
its parameter values based on the dataset or the nature of the task. It also
suggests that PSO-EM outperformed the traditional method.
Table 2: Performance of PSO-EM Algorithm and Its best parameters. T1 means 1
Time Threshold1 Parameter while W1 means weight1 Parameter
Writing
Task
Parameters
Evaluation
Measure
T1 T2 T3 W1 W2 W3 MSE
One
Hour
IbA
0.5 m 1.0 m 2.0 m 0.33 0.66 1 16.13
PSO
-EM
3.30m 4.20 m 5.12m 1.09 2.34 2.89 15.88
One
Month
ibA
0.5h 1.0h 2.0h 0.33 0.66 1 64.95
PSO
-EM
3.3h 4.20h 5.12h 1.09 2.34 2.89 31.89
Table 1: Correlation of engagement time
One month writing One hour writing
PSO-EM IbA Human PSO-EM IbA Human
PSO-EM 1 1
IbA 0.67 1 0.69 1
Human
Self-Report
0.73 0.49 1 0.81 0.59 1

20
Conclusion and Future Work
In this paper, we introduce a novel algorithm, called PSO-EM for engagement
measurement, particularly student engagement in a writing activity. This
algorithm is based on a computational intelligence approach, called Particle
Swarm Intelligence, to find the best parameters for engagement measurement
algorithm. Our study result indicates that this algorithm outperformed the
traditional engagement measurement method and can automatically adjust the
function parameters based on the writing task. We also found that the short-time
writing activity (one-week) was more predictable than the long-time writing
activity (one-month), since the short-time writing activity produced less revision
data for analysis. However, PSO-EM can still perform well in complex revision
data due to its robust capability. Our future work will focus on generating real
time visualizations based on the engagement algorithm to support individual
and collaborative writing.
Acknowledgements
This work is partially supported by Chongqing Social Science Planning Fund
Program under grant No. 2014BS123, Fundamental Research Funds for the
Central Universities under grant No. XDJK2014A002 and No. XDJK2014C141
and No. SWU114005 in China.
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21
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22
© 2015 The author and IJLTER.ORG. All rights reserved.
Vol. 11, No. 1, pp. 22-35, April 2015
A Study of the Development of Courseware and
Students’ Learning Effectiveness in Primary Education:
Using Three Teaching Techniques as an Example
Fang-Chun Ou
Overseas Chinese University
Taichung, Taiwan
Abstract. As Taiwan has carried on its educational reform, many
problems have emerged over the past ten years. These issues have to be
solved as soon as feasible. Specifically, primary education is facing
severity in competition and stern challenges in a fast globalizing world.
This study aims to explore Taiwan’s English education so as to find out
new approaches to revision and innovation. In Taiwan, most students
have to learn English since elementary school. English teachers usually
adopt different methods to teach students so as to achieve teaching
excellence. Three groups of primary school students participated in a
study with three teaching methods involved for learning English as a
foreign language (EFL). TPR (Total Physical Response) was employed
with the first group, giving instruction and then students responding
with body movement. CLT (Communicative Language Teaching) was
adopted with the second group, which emphasized interaction and
communication genuinely. Conventional teaching method was used
with the third group, in which students learned from what teachers
taught in class. The pre- and post-test were carried out to investigate
which teaching method was the most significant. The present study
indicates under controlled conditions that TPR & CLT, proven beneficial
in TPR & CLT context, can yield a positive outcome. In contrast, the
traditional teaching method has the least progress among the three
teaching methods. In addition, the findings of the study support that the
participants enhanced in the vocabulary and picture matching of the
posttest. The result of this study could be a good demonstration for
teachers to provide more options in English learning. Through the

23
curriculum, teachers could promote the ability to devise a flexible
variety of activities in order to stimulate pupils’ learning as well as make
them better interested in English. This study has set up a great value for
other similar researches and should be replicated with students at
various English proficiency levels.
Keywords: TPR (Total physical response), CLT (Communicative
language teaching), Conventional teaching method, EFL (English as a
foreign language).
Introduction
English is one of the indispensable languages in modern society, which can be
employed to do a great deal of trades between countries as well as spoken to
interact with foreigners. It is also an essential bridge that connects people from
variety of events. In response to the requirement of international society,
strengthening English ability has become an important issue of education.
Moreover, with English learning, learners can blend into social and cultural
activities in English-speaking countries in good time. Language learners should
understand and respect multiculturalism in order to be cosmopolite.
Nowadays, being capable of speaking English fluently has become one of the
basic requirements in the global village. The purpose of English teaching and
learning is to build up learners’ ability of communication, increase the
motivation and interest of English learning, and develop a global perspective.
Additionally, language learners are expected to enhance the ability of handling
international matters and conflicts.
It has been a quite normal phenomenon cultivating English capability since a
very young age, particularly in Taiwan. In line with the government policy to
improve international competitiveness, MOE (Minister of Education) stipulates
English teaching and learning should be implemented in Grade1-9 Curriculum.
According to MOE, the teaching methods should be active and interactive. The
content of teaching material should be related to daily life, practical and
interesting. By means of diverse teaching materials and activities participation,
the four skills including reading, listening, speaking, and writing can be built up
gradually, and then be put into practice.

24
In order to break the myth of grades, the aims of 12-year compulsory education
are leading students toward creative learning on the initiative, having
knowledge from the learning process, experiencing pleasure, cultivating their
own characteristics, and communicating with English. However, the major
problem of English education is teaching too much and too difficult. Teachers
usually make students remember vocabularies and grammars compulsorily.
Therefore, the mechanical drills kill students’ learning motivation toward
English. As a consequence, the policies of 12-year compulsory education are set
up to teach efficiently, blend information technology into teaching, and
encourage students to think and express creatively. In light of this, English
ability and practicality are more important than they used to. Additionally, in
2010, Attar and Chopra pinpoint the teaching methodology and approach
should keep changing in order to meet the needs of language learning. Namely,
how to design effective teaching modes and cultivate students' communicative
competence have become the major concerns in English teaching and research.
Tracking back to the early period, English teaching mostly put emphasis on
Grammar Translation Method and Audio-Lingual Method. The traditional
teaching method is drill-oriented, which introduces and practices language
knowledge and skills in details. Worse still, students tend to be bored and
punctilious gradually. Until 1994, Ministry of Education started highlighting
Communication Language Teaching, which aims at meaningful interactions,
language skills, genuine material, language ability development, and English
communication under different social situations properly. As a consequence,
designing diverse teaching techniques as well as appealing activities and
courseware should be taken into consideration so as to benefit students by
increasing achievement and learning outcomes.
Research Questions
1. Does the intervention in the use of teaching methods help improve
elementary school students’ English proficiency?
2. Which type of question (vocabulary, picture matching, and reading
comprehension) was influenced most after exposed to these three teaching
methods?

25
Literature Review
The advantages of Communicative Language Teaching have been proved and
employed successfully in ESL/EFL (English as a Second Language/ English as a
Foreign Language) classrooms around the world (Kelch, 2011). Chang (2011)
explores to compare the feasibility of Grammar Translation Method and
Communicative Language Teaching in English grammar teaching as well as tries
to find out which on is more appropriate in Taiwan. In his study, the result
shows students benefit more from grammar instruction with Grammar
Translation Method (GTM) adoption. With contrast to GTM, Communicative
Approach focuses on fluency rather than accuracy. The teacher corrects errors
immediately if the scope of the classroom activity is accuracy, but if the scope of
the activity is fluency the errors will be corrected later on. As a result, combining
both methods might be the best way to improve circumstances in English
grammar teaching. Wei (2010) reviews the advantages of Communicative
Language Teaching method and analyzes the obstacles of implementation in
EFL classroom context. In his study, it provides guidelines for compromising
CLT with the conventional teaching approach. Additionally, it recommends
some techniques and principles for English teaching implementation in EFL
environment.
Teacher Training
The main purpose of language education is to enhance the quality of teachers as
well as the quality of education. The English teachers should possess
professional knowledge related to ELT (English Language Teaching) and be
capable of employing varieties of teaching methods. Regarding mid- and
long-term teacher training (MOE, 1999), MOE encourages normal universities to
establish departments of English education. Besides, school should provide
English subgroups, English minors or second specialty students a twenty-credit
course of ELT.
Teaching Methods
TPR (Total Physical Response) was originally developed by James Asher. In the
1960s, TPR makes good use of physical movements and associates with the
theoretical framework of mother tongue. Most importantly, teachers can check
young learners’ comprehension through their reactions linked to body
movements, which reinforce their comprehension ability.

26
CLT (Communicative Language Teaching) emphasizes interaction and
communication in classrooms. In fact, it was a response to Chomsky’s theory
(Chomsky, 1965). Chomsky showed linguistic competence is not the mastery of
structures, but communication competence in real situation. Teachers should
create a wide variety of authentic situations for students to interact with their
classmates. Then students have the opportunity to share their individual
experience in target language. Most importantly, students gain more
self-confidence through practices and keep enthusiastic toward language
learning.
Methodology
Subjects
The target subjects were an unselected convenience sample. Thirty 5th and 6th
elementary school students voluntarily participated in this study. They were
asked to take the identical pre- and post-test to evaluate the appropriateness of
three different teaching techniques (TPR, CLT, conventional teaching) in
different classroom settings.
Course Material
The researchers created an innovative story that students have never read before.
In addition, ten sentences and vocabulary cards were made to emphasize
grammar instructions and practices.
Instruction and Testing Procedure
Three groups of subjects were administered the pretest to obtain initial scores of
the students’ English proficiency. There are three parts in the test. Part one is
multiple-choice questions of vocabularies, part two is matching correct pictures
according to the story, and the last part is reading comprehension. The actual
instruction lasted three hours with three different teaching methods adopted in
three different classroom settings, respectively. After the instruction, a posttest
was implemented to investigate the differences among the three different
teaching methods. The students completed both the pre- and posttest as the
requirement. All subjects were given the same test used in pre-test as a post-test.
Results
Analyses
The test contains twenty questions. Among these twenty questions, ten are

27
vocabulary, five are picture matching, and the remaining five are reading
comprehension. The result of the test focuses on which teaching technique was
the most suitable for primary school students.
Table 1 (Test Question Distribution)
Question Categories Numbers Percentage
Vocabulary 10 50 %
Picture matching 5 25 %
Reading comprehension 5 25 %
Results
The means and standard deviations of the pre-test and post-test scores for the
conventional teaching method were presented in Table 2.
Table 2 Descriptive Statistics of Pretest and Posttest (Conventional)
N=20
Conventional M SD
Pretest 25 11.055
Posttest 57 6.770
A paired-samples T test was conducted to evaluate whether the conventional
teaching method increases students’ scores. The results indicated the mean
scores for posttest (M= 57, SD= 6.770) was not significantly greater than the
mean scores for pretest (M= 25, SD= 11.055), t(9) = -8.677, p= .12 (Table 3). The
results revealed there is no effect of the conventional teaching method
adoption.
Table 3 Results of Paired Samples T Test
The means and standard deviations of the pre-test and post-test scores for Total
Physical Response method were presented in Table 4.
Table 4 Descriptive Statistics of Pretest and Posttest (TPR)
N=20
TPR M SD
Pretest 25 7.45356
Posttest 76 10.28753
Pair 1
Conventional
Mean Std.
Deviation
t df Sig.
Pretest-posttest -32.50 11.844 -8.677 9 .12

28
A paired-samples T test was conducted to evaluate whether TPR increases
students’ scores. The results indicated the mean scores of posttest (M= 76, SD=
10.28753) was significantly greater than the mean scores of pretest (M= 25, SD=
7.45356), t(9) = -11.057, p= .000 (Table 5). The results confirmed the effectiveness
and appropriateness of the total physical response adoption.
The means and standard deviations of the pre- and post-test scores of the
communicative language teaching method were presented in Table 6.
Table 6 Descriptive Statistics of Pretest and Posttest (CLT)
N=20
CLT M SD
Pretest 32 15.12907
Posttest 90 5.77350
A paired-samples T test was conducted to evaluate whether the communicative
language teaching increases students’ scores. The results indicated the mean
scores for posttest (M= 90, SD= 5.77350) was significantly greater than the mean
scores for pretest (M= 32, SD= 15.12907), t(9) = -16.900, p= .000 (Table 7). The
results confirmed the effect and appropriateness of the communicative language
teaching adoption.
The second question of the present study was the following “Which type of
question (vocabulary, matching, and reading comprehension) was influenced
most after exposed to these three teaching techniques?” A multivariate analysis
of variance (ANOVA) was performed on the data with the three scores (scores of
vocabulary questions, matching questions, and comprehension questions) used
as dependent variables and Group as the independent variable. The three
dependent variable scores were calculated by subtracting test scores of each
question type obtained at the beginning of the instruction (pre-test scores) from
Pair 2
TPR
Mean Std.
Deviation
t df Sig.
Pair 3
CLT
Mean Std.
Deviation
t df Sig.

29
those obtained at the completion of the instruction (post-test scores).
The ANOVA for the Group main effect was found to be significant, F (6,50)=
25.515 (Wilks’ Λ = .061), p < .001. As a result, the univariate ANOVAs on each
dependent variable were conducted as follow-up tests to the MANOVA. Using
Bonferroni method, each ANOVA was tested at the .0167 level (.05/3). There
was a significance in the vocabulary question scores, F (2, 27) = 63.224, p < .001,
eta squared = .824. The difference in the picture matching questions scores was
significant as well, F (2, 27) = 8.113, p = < .001, eta squared = .375. The difference
in the reading comprehension questions scores was nonsignificant, F (2, 27) =
25.317, p= .159, eta squared = .652. (Table 8)
Table 8 Results of Comprehension Difference Scores by Question Types
Note: adjusted Alpha = 0.0167
Findings
The first important finding of this study suggests that the teaching methods,
TPR and CLT do enhance elementary students’ English proficiency. The present
study demonstrates under controlled conditions that TPR& CLT, proven
beneficial in TPR & CLT context, can yield a positive outcome. In contrast,
traditional teaching method has the least progress among the three teaching
methods.
Moreover, the research evidence indicates that explicit, overt physical
movements can greatly increase the positive outcome of instruction. To students
who just listen to teachers and repeat after them do not possess much
comprehension because they do not really understand the context of the course,

30
nor do they know how to apply them to the real life. The teaching methods, TPR
and CLT can help students become more confident and have more involvement
in class.
Overall, the findings of the study support that the participants enhanced in the
vocabulary part (requiring respondents to select the best word according to the
picture) and picture matching (requiring respondents to choose the best sentence
describes the pictures) of the posttest. The second important finding of this
study deals with the question that which type of test questions was influenced
most after the instruction of these three teaching methods. It was found that the
participants in this study in fact did tend to use the physical movements to link
the meaning of the vocabularies. Besides, the pictures cards do assist them to
have better understanding of plots of the story.
Discussion
The first results show students achieve better improvement in TPR and CLT
classrooms. The reasons are provided as follow. Firstly, during the instruction of
TPR, instructors gave a lesson in target language, and students responded with
whole body actions. Students were not forced to speak, and instructors waited
until students acquire enough language input through listening comprehension,
then they would speak out without any fear. Namely, language learning should
not involve any stress and the lively interaction could impress the physical
response upon students’ mind.
Secondly, during the instruction with CLT teaching method, students were
taught the story along with picture cards, and they were asked to communicate
with instructors. By means of these, more interactions were expected. As a result,
students could keep the story in mind easier and more efficient.
Lastly, during the instruction with the conventional teaching method, instructors
taught by simply reading aloud the story lines and made explicit translation.
Compared to TPR and CLT, the conventional teaching method was not lively
that the students only sat tediously and sometimes did not catch what were
taught thoroughly.
The second results indicate that students achieve better toward vocabularies and
picture matching than reading comprehension. The reasons are explained in

31
detail.
Vocabulary
Vocabulary picture cards were created to employ during the instruction.
Students saw the picture at the first glance and were encouraged to guess the
meaning of the vocabulary. Then, vocabulary card was revealed and students
were requested to repeat after the instructors and sounded it out. Moreover, an
exciting game was designed for students to play in class. As a consequence,
students learned through the action and memorized novel words more easily
and efficiently.
Picture Matching
The story picture cards were used to associate and connect the pictures with the
content. Through viewing picture cards, students found the key words from
story lines, which enhanced their visual-mental correspondence. While having
an exam, students were easier to reason the story and match the right pictures.
Reading Comprehension
Instructors invented the story taught in class, and it has never been heard before.
Although students learned with the visual aid of picture cards and some exciting
games were set up especially for them, most of the students still had difficulties
reading as well as comprehending long paragraphs. As a consequence, while
having a test, students expressed they guessed instead of answering
conscientiously.
When it comes to TPR method, some recommendations are provided as follow.
First of all, realia is a good choice. Teachers can make good use of objects from
the real life to make the instruction more clearly and attract more attentions. In
addition to real objects, picture cards and posters are helpful as well. In fact,
students are able to associate the images of picture cards with new vocabularies
easily, which makes them have less pressure when memorizing new words.
Secondly, physical movement is strongly recommended. In class, the actions
demonstrated by instructors make the commands or instructions more
meaningful and clear. Moreover, students, especially young children, have more
interests in learning when they leave their seats and do some actions around.
Thirdly, instead of using a long sentence to direct students’ behaviors, teachers
can use combinations of commands. For instance, teachers give one command

32
first, and then do the action spontaneously. Gradually, when students are
familiar with the commands, teachers can add more commands at one time.
However, do
not add more than three commands at one time because students might get
confused while receiving the signals. Most importantly, teachers can observe
students’ comprehension easily and directly. If students can correctly do the
action after the command, then they do really comprehend what teachers teach
in class, which makes them feel confident and self-achieved.
With regard to CLT, there are some suggestions provided as follow. Situational
Language Teaching (SLT) can motivate students’ interests in learning. When
teachers introduce a new target language in words or phrases, instead of
translating them into students’ native language, teachers can demonstrate the
lessons through the use of realia, pictures or pantomime. Teachers may also use
intonation, rhythm, and concert pseudo-passiveness to get students’ attention
and motivate their interests in the lesson. Initially, students are really dependent
on their teachers. After teachers’ questions, students tend to make themselves
understand first, and then they are encouraged to answer in front of the whole
class. Gradually, with more practices, they may be more independent and have
greater security. Meanwhile, students can also listen to other’s opinions, and
learn from each other little by little. In fact, the interaction goes both ways, from
teachers to students and from students to teachers. Although students might
make mistakes, teachers usually employ various techniques to get students to
self-correct. Namely, the feeling of security is enhanced by many opportunities
of the cooperative interactions with their fellows and teachers. By means of this,
teachers evaluate not only students’ accuracy, but also their fluency. Teachers act
as advisors or co-communicator. Rardin (1988) mentioned language learning is
neither student-centered, nor teacher-centered, but rather teacher-student
centered. The CLT method makes students feel proud to use the knowledge to
express in different languages.
Two reasons are provided to explain why these three teaching methods were
chosen in the first place. First, TPR and CLT are the most popular teaching
methods adopted in educational institutions. Most instructors consider students’
interest in learning foreign languages is the priority. When students feel
interested in English, they will feel more comfortable and easy to communicate
with others by using a foreign language. Next, the traditional teaching method is

33
still employed now and then. Under the circumstance, most language learners
deem memorizing vocabularies a rather tough task; needless to say, speaking
English causes pressure and anxiety. Worse still, it surely lessens learners’
motivation toward English learning.
Teacher Training
During the past decade, the communicative language teaching approach has
been recommended especially for language teachers because of the essential and
emphasis of language use in foreign/second language classrooms (Mangubhai
et al., 2005). In addition, Li and Yu (2001) have identified the communicative
language teaching method has improved communicative ability of language
learners in which the conventional teaching approach has been demonstrated
unsuccessfully. However, due to the lack of sufficient teacher training in CLT,
teachers usually do not know how to implement CLT as well as do not possess
confidence in English speaking capabilities to carry out the communicative
approach (Butler, 2011). Specifically, most language teachers lack of this kind of
training and they are often afraid of “losing face” or feel embarrassed when
making errors or when they are not capable of answering students’ questions
promptly (Park, 2012). In light of the significance, Carrier (2003) points out the
different teaching approaches should be demonstrated and highlighted through
direct explanation, explicit teacher modeling, and extensive feedback in teacher
training programs in terms of the implementation in language classrooms.
Specifically, in the environment of English as a foreign language in Taiwan, the
supply of language input and practice opportunities are insufficient for the
learners to become immersed. Therefore, teachers should value process-oriented
instruction more highly than content-oriented or grammar-oriented instruction
because it is beneficial for students to become independent learners.
The language teacher should also bear in mind that elementary school children
are not mature enough to take full responsibilities for their own language
learning. Therefore, children’s proficiency levels and their cognitive maturity
would determine the types of activities (strictly-controlled ones, semi-guided
ones, or free communicative ones) the teacher puts into practice in a
communicative classroom.

34
Limitation
The sample size is small, which causes the effect of the experiments was not
statistically significant, so the results cannot be completely generalized to young
EFL learners from other areas. In addition, time duration of each class is two
hours. Within this short period of instruction, it was at time difficult for the
instructors to circle around the classroom while the activities were conducted
since the instruction involved observing the class and providing assistance.
Consequently, language learners would benefit from the instruction with
sufficient guiding period.
Pedagogical Implication
The result of this study could be a good demonstration for teachers to provide
more options in English learning. Through the curriculum, teachers could
promote the ability to devise a flexible variety of activities in order to stimulate
pupils’ learning as well as make them better interested in English. This study
has set up a great value for other similar researches and should be replicated
with students at various English proficiency levels. For instance, in addition to
TPR and CLT, The Direct Method, Community Language Learning, and
Reciprocal teaching are strongly recommended as the integrated teaching
method to promote the teaching process.
This study explores Taiwan’s education to find out new approaches to revision
and innovation. According to Jarvis and Atsilarat (2004), new teaching
approaches have been addressed so as to diversify the approaches in existence to
accomplish global innovation. As for the future investigation, more
breakthroughs in curriculum and instruction need to be put into consideration,
in order to gain an overall picture of the optimal outcomes of education.
References
教育部 (1999). 國小英語師資培育檢核相關報導。 Retrieved from
http://content.edu.tw/junior/english/scedu/rimage/r04.htm.
教育部 (1999). 培訓國小英語師資完整計畫方案。 Retrieved from http://
npl.ly.gov.tw/npl/report/880517/14.pdf.
Attar, M. & S. S. Chopra (2010). “Task-Based Language Teaching in India”. MJAL 2:4.

35
Butler, Y. G. (2011). The implementation of communicative and task-based language
teaching in the Asia-Pacific region. Annual Review of Applied Linguistics, 31, 36-57.
Carrier, K.A. (2003). NNS teacher in Western-based TESOL programs. ELT Journal, (3),
57- 242.
Chang , Shih-Chuan. (2011) “A Contrastive Study of Grammar Translation Method and
Communicative Approach in Teaching English Grammar” English Language
Teaching, Vol. 4, No. 2. Published by Canadian Center of Science and Education.
Chomsky, N. (1965). Aspects of the Theory of Syntax. Cambridge, MA: MIT Press.
Jarvis, H & Atsilarat, S. (2004). Shifting paradigms: from a communicative to a
context-based approach. Asian EFL Journal, (6), 4-8.
Kelch, K. (2011). Curriculum development in English language teaching: Innovations
and challenges for the Asian context. International Journal of
Organizational Innovation (Online), 3(3), 22-42.
Li, D. (1998). It's always more difficult than you plan and imagine: Teachers' perceived
difficulties in introducing the communicative approach in South Korea. TESOL
Quarterly, 32 (2), 677-703.
Mangubhai, F., Marland, P., Dashwood, A., & Son, J. B. (2005). Similarities and
differences in teachers' and researchers' conceptions of communicative language
teaching: Does the use of an educational model cast a better light? Language
Teaching Research, 9(1), 51-86.
Park, S. M. (2012). Communicative English Language Teaching in Korea. Humanising
language teaching, 14(6), 1-6.
Wei, H. (2010). Communicative Language Teaching in the Chinese Environment. US-
China Education Review, 7(6), 78-82. Retrieved March 15, 2011, from
http://eric.ed.gov/PDFS/ED511286.pdf.
Yu, L. (2001). Communicative Language Teaching in China: Progress and Resistance.
TESOL Quarterly, 35(1), 194-198

36
Vol. 11, No. 1, pp. 36-52, April 2015
A Comparative Examination of Teacher
Candidates’ Professional Practicum Experiences
in Two Program Models
Nancy Maynes, Anna-Liisa Mottonen, Glynn Sharpe and Tracey Curwen
Nipissing University, North Bay, Ontario
Abstract. This paper reports on one aspect of a larger study, examining
the relationship between teacher candidates’ self-reports of knowledge
and confidence related to many key areas of professional practice.
Survey information was provided by concurrent and consecutive
bachelor of education students. Perceptions of professional gains
through the practicum were examined. Students who are studying
education through a concurrent program feel that they have acquired
significantly more professional background about teaching through
practicum experiences than students acquiring a comparable degree
though a consecutive route. As the practical applied knowledge that
students acquire through practicum experiences is essential for teacher
development, this finding is relevant, especially as each of these
programs is undergoing structural changes as a reflection of new
provincial directions about teacher education. The results of this study
demonstrate that the amount and placement over time of practicum
provided in a teacher’s pre-service program matters to the level of
professional expertise they feel that they have acquired overall.
Keywords: practicum, consecutive education programs, concurrent
education programs.
Introduction
This paper reports on a study regarding whether or not pre-service teacher
candidates feel knowledgeable and confident in the acquisition of skills they
need to teach in their own classrooms at the completion of their respective
teacher preparation programs. The study contrasted responses from teacher
candidates who completed their teacher preparation programs in different
models. One group graduated through an eight month program, involving 13
weeks of classroom practicum time; the second group graduated with a 5 year
concurrent education degree, including 19 weeks of classroom practicum. The
focus of this study is on teacher candidates’ perceptions of what is gained
through practicum experiences in the classroom. We investigated how effective

37
in some tasks new teachers perceive themselves to be as a direct result of what
they have learned through practicum experiences.
Background
Theories may provide the knowledge that teacher candidates require to work
effectively with students in the classroom. However, without opportunities to
apply these theories to practice during practicum time, candidates may lack the
necessary confidence to address new contexts with equal effectiveness, and they
may lack the pedagogical content knowledge to determine strategy efficacy as
they encounter new situations early in their career. Practicum time in a teacher
education program is typically designed as a professional internship of short
duration, strategically placed in the teacher candidates’ professional program.
The practicum allows the teacher candidate to try out ideas that they have
learned in courses in the context of a classroom where a certified teacher can act
as a mentor for them.
However, not all teacher preparation programs provide the same amount of
classroom practicum experience for teacher candidates. In the jurisdiction where
this study took place, teacher candidates are required by their accreditation body
to acquire a minimum of 12 weeks of successful practicum experience. Success in
the practicum is assessed by the professional judgment of the mentor teacher,
who is referred to as an associate teacher (AT) in this jurisdiction. In this study,
however, two paths to acquiring the professional teacher accreditation are
examined in relation to the perceived impact of the practicum on knowledge and
confidence of the new teacher. Students acquiring their accreditation through a
consecutive program route in this jurisdiction engage in 13 weeks of practicum
(i.e., one week more than required by the local accreditation body), while those
who acquire their accreditation through the concurrent program route acquire
19 weeks of practicum (i.e., 7 weeks more than required by the local
accreditation body). Additionally, the 19 practicum weeks in the concurrent
program are distributed across the 5 years of the program, while the 13 weeks of
the consecutive degree route are spread across 8 months.
While we acknowledge that the quality of the practicum experience each teacher
candidate may experience can be vastly different due to many circumstances,
our study focuses solely on examining perceptions related to how the length and
placement of the experience may have an instructional impact. As teacher
candidates, prospective teachers enter the professional arena through practicum
experiences; however, they are often unequally exposed to many learning
opportunities (Beck, Kosnik & Rowsell, 2007). It is logical to assume that more
time in a practicum context would allow more exposure to a greater variety of
learning opportunities. Many of the learning opportunities that a pre-service
teacher candidate may have during any practicum may be wholly dependent on
the skills and resources of the teachers to whom they are assigned for their
practicum. Additional practicum time may allow new teachers to have
otherwise unavailable exposure to strategies utilized by experienced teachers,
and they may lack contextualized opportunities to apply their course-based
knowledge in contexts that would allow the teacher candidate to develop

38
confidence in their ability to use these strategies if they have little or no time to
see them in operation and to adapt theoretical ideas to pragmatic contexts.
Therefore, the current study provides us with a benchmark of current reports of
knowledge and confidence acquired through practicum experiences on which to
base program design decisions for this aspect of teacher preparation.
Additionally, in the jurisdiction where this study is taking place, the government
has recently made significant changes to accreditation criteria, which will come
into effect in fall of 2015. In response to the demands for new program designs in
the accreditation program for teacher certification in this jurisdiction, many
accrediting institutions are considering the elimination of the concurrent
program route and retaining the single option of a 2-year consecutive program.
This study may shed some light on the efficacy of this decision as it relates to
decreased opportunities for longer program embedded practica.
Teacher preparation programs include a combination of course work in a
university setting, and internship style practicum placements in classroom
settings. In the jurisdiction where this study was completed, practicum
placements are arranged in any of 52 school boards in the province. Teacher
candidates are able to identify any three of these school boards as areas where
they might ultimately apply for a teaching position. Then, program placement
officers approach school boards to arrange the number of placments required in
their area. Usually, school boards have employees who are then responsible for
placing the teacher candidate in a specific classroom for a specific placement
block.
As this university offers two routes to the completion of the same bachelor of
education (B.Ed.) degree, with two approaches to the placement and differences
in the total amount of time provided for the practicum, we identfied the need to
compare teacher candidates’ perceptions of the relative value of these
differences in providing them with the skills and strategies needed to support
their developing professional skills to prepare to be successful with the role of
teacher. The skills that were identified for this aspect of the larger study were
selected because, while some theory for each skill can be provided in the context
of their courses, each skill could reasonably be expected to develop more fully if
teacher candidates had contextualized opportunities in schools to use these skills
and to consider the impact of their practices in relation to the outcomes they
achieved.
Six skills were identified by researchers in this category of professional practice.
They include: the ability to manage a classroom; the knowledge and confidence
to interact with parents; the knowledge and confidence to interact with school
and board administrators; the ability to manage difficult student behaviours; the
ability to deal with difficult situations; and the knowledge and confidence to
address the learning needs of all children.

39
Literature Review
During the past 15 years there has been a considerable amount of intensive
investigation into the value and learning afforded to teacher candidates whose
professional preparation program provides opportunities for them to hone their
theoretical course knowledge by participating in classroom placements, usually
referred to as practicum experiences, or collectively as practica. While we were
able to find many studies related to the perceived value of teacher practicum
experiences, there seems to be an absence in the professional literature regarding
investigations of the relative perceived value of different approaches to
providing the practicum experience and the perceived value of different
amounts of practicum experience. It seems reasonable to assume that more time
in a classroom practicum placement is likely to provide more opportunities for
the teacher candidate to gain a wider variety of professional skills, but there is a
dirth of literature about existing programs to support this contention.
Much of the existing research literature about teacher practicum placements
addresses perceptions of how effective this experience is as a contributor to the
overall professional preparation of a new teacher. A study by Brouwer &
Korthagen (2005) confirmed the role of the practicum in the overall development
of competent teachers. While both classroom theory and practicum experiences
were found to be contributors to a new teacher’s development, the practicum in
a school context was more influential than the course components of the teacher
education program on the development of teaching competence. However, the
nature of the practicum has also been found to matter when teacher competency
are the desired outcome. In a study by Beck, Kosnik, and Rowsell (2007),
researchers identified the need for more focus in the practicum on practical
issues related to the daily tasks of functioning in a classroom. In this study,
teacher candidates identified six characteristics or skills needed to be provided
and developed in their preparation programs to prepare them to teach,
including: theoretical understanding, practical knowledge and skills,
comprehensive program planning ability, knowledge of what must be done in
the first few weeks of school, understanding and skill in assessment and
evaluation, and knowledge of how to implement effective group work. It is
interesting to note that five of these six characteristics relate to implementation
practices that might be expected to develop in teacher candidates during their
practicum placements, even though the participants in the study also identified
the need to have theoretical understanding.
It seems clear from this study that prospective teachers recognize and value the
theoretical aspects of the preparation program to help them understand what
they should do, but they value the practical experiences of the practicum to
show them how and when to do these things. The Brouwer and Korthagen
(2005) study also demonstrated that by gradually increasing student teaching
activity complexity, by increasing cooperation among students (triads of student
teachers), cooperating teachers, and university supervisors, and by alternating
between student teaching and college (in-class) sessions, teacher education
programs allowed student teachers to relate theory and practice. This need for
balance between the course theory and the practicum experiences is supported

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