Results
The
results section is organized into three parts. Part
one presents an overview of the literature on technology
applications in language education. Part two summarizes
how technology has been used to support language
learning and the effectiveness of these usages.
Part three reports the results from the meta-analysis
study intended to assess the overall effectiveness
of technology-supported language learning.
The
review of recent research on technology-supported
language learning reveals a number of interesting
points regarding existing research in this area.
First, the total number of well-designed experimental
studies on the effectiveness of technological applications
in language learning is very limited. For instance,
the four issues in Volume 16 of the CALICO Journal,
which were published in 1998 and 1999, contain 10
feature articles. Only two of the 10 are met the
selection criteria to be included in the meta-analysis.
Of all the 51 feature articles published in Language
Learning and Technology, one met the criteria.
The majority of the articles are either description
of cases of uses of technology in language education
and processes of software development or theoretical
discussions of principles of technological applications.
Some of the limited empirical studies did not measure
learning gains, relied solely on learner self-reports
as measures of effectiveness, or were not well designed.
Second,
the studies were limited to college level language
learners. None of the 9 studies was conducted in
K-12 settings. Only two of the 9 studies were not
about college students—their p participants were
military linguists, who were also adults.
Third,
the target languages under consideration in the
studies were also limited. French and Spanish were
the most studied (10 out 16 or 63%). Other more
commonly studied languages were English as a second
language (ESL), German, and Arabic.
Fourth,
most of the studies were about the application of
a single application instead of systemic large-scale
integration of technology. Only two of the 16 studies
were about long-term technology integration in the
language learning environment. Thus the treatment
reported was also short-term, lasting from a few
hours to a few weeks.
Lastly,
the applications of technology to enhance language
learning have been wide-ranging, both in terms of
the types of technology used and the issues language
education needs to address. The studies investigated
the uses of most available technologies including
video, audio, multimedia, communication, network,
and speech technologies. These technologies have
been applied to support the teaching of various
aspects of the language learning including vocabulary,
grammar, reading, writing, speaking, listening,
and culture.
Uses
and Effectiveness of Technologies in Language Education
The
following paragraphs present detailed discussions
of the specific applications that have been studied
over the past few years. The discussion is categorized
into four groups: access to materials, communication
opportunities, and feedback, and learner motivation.
Providing
Access to Linguistic and Cultural Materials
Access
and exposure to engaging, authentic, and comprehensible
yet demanding materials in the target language is
essential for successful language learning. However for many language learners, whether
in classes or self-study settings, such access is
often limited. Thus language educators have long
looked at information and communication technologies
(ICT) as possible solutions to this problem
(see Egbert, Chao, & Hanson-Smith, 1999; Hanson-Smith,
1999; Salaberry, 2001)
. The uses of ICT to provide better access and exposure
to linguistic and cultural material fall into the
following three areas.
Enhancing
access efficiency through digital multimedia technologies.
Digital multimedia technologies were used
to make access to learning materials more efficiently
than print media or audio recorders because a) multimedia
(visual, audio, and text) presentations can create
stronger memory links than a single medium alone
and b) digital technology allows instant and accurate
playbacks, which helps the learner to access specific
segments much more easily without spending time
to locate them, which can be tedious and a waste
of time
(Hanson-Smith, 1999; Thorton & Dudley, 1996)
. Shea
(2000)
compared the time students needed to complete their
language learning tasks using captioned video versus
interactive video disc(IVD) and found that the students
using IVD completed the tasks significantly faster(p<.05).
Labrie
(2000)
found that although students spent more time learning
a set of French words on paper than those who studied
on computer where they could hear a word pronounced
and see a picture about the word, they did not learn
more words. In another study, Nutta
(1998)
found that after spending the same amount of time
(one hour per day for seven days) learning verb
tenses in English in two conditions: attending a
regular class and receiving instruction from the
teacher vs. using a multimedia (audio, video, recording
capabilities etc.) computer program, the ESL students
using the computer program performed as well or
significantly better (on 3 out of 6 measures, p<.10)
than their counterparts attending the class.
Enhancing
authenticity using video and the Internet. Video
materials can bring natural and context-rich linguistic
and cultural materials to the learner while the
Internet enables the learner to access authentic
news and literature in the target language, which
can reflect current cultural changes more effectively
than printed sources
(Bacon & Finnemann, 1990; Hanson-Smith, 1999;
Herron, Cole, Corrie, & Dubreil, 1999; Herron,
Dubreil, Cole, & Corrie, 2000; Kitajima &
Lyman-Hager, 1998; Lafford & Lafford, 1997;
Lee, 1998; Weyers, 1999)
. Weyers(1999) studied the effectiveness of authentic
video on college Spanish students. He had one class
of students watch a Mexican television show as part
of a second semester Spanish class that met 60 minutes
daily for a total of 8 weeks while the other class
followed the regular curriculum without the video.
He found that the video group’s performance on both
listening comprehension and oral production to be
significantly better than the regular group (p<0.01).
The video group also outperformed their counterparts
on other measures of communicative competence. Herron
(2000)
found that video also helped their first year college
French learners develop significantly better understanding
of the target culture. In another study, Green and
Youngs
(2000)
substituted regular classroom instruction with Web
activities one class period per week for beginning
college French and German students. After a semester,
they found that “the substitution of one class day
for directed, pedagogically sound Web activities
seems to have allowed the treatment groups to continue
to progress toward their personal and professional
goals and allowed them to learn language at a rate
similar to that of their peers in the control groups.
It also appears, in general, that the students had
a positive experience using the Web. . .” (p. 108).
Enhancing
comprehensibility through learner control and multimedia
annotations. Comprehensible input is necessary for language
learning but useful learning materials must also
contain enough unfamiliar materials
(Krashen, 1985)
. For language learners, especially beginning and
intermediate ones, authentic materials are often
beyond their language proficiency and may become
incomprehensible without help. To enhance comprehensibility
of spoken materials, full caption, keyword caption,
or slow-down the speech rate have been found to
be effective
(Shea, 2000; Zhao, 1997)
. Zhao(1997) found that the ESL students who were
able to flexibly slow down or speed up the rate
of speech had significantly better listening comprehension
than those who did not (p<0.05). For reading
materials, glossing or multimedia annotations have
been effective means to enhance comprehension
(Al-Seghayer, 2001; Chun & Plass, 1997; Johnson,
1999; Lyman-Hager, 2000)
. Al-Seghayer (2001) compared ESL students’ vocabulary
learning in different annotation conditions and
found that “a video clip
in combination with a text definition is more effective
in teaching unknown vocabulary than a picture in
combination with a text definition . . . The variety
of modality cues can reinforce each other and are
linked together in meaningful ways to provide an
in-depth experience.”(p<0.001 ) (p. 225).
Providing
Opportunities for Communication
Engaging
in authentic communication in the target language
is another essential condition for successful language
learning yet such opportunities do not exist for
most learners. ICT has again been used in many different
ways to create opportunities for language learners
to communicate in the target language
(see Hanson-Smith, 1999; Kelm, 1998; Muyskens, 1998;
Warschauer & Kern, 2000)
. Efforts in this area can be summarized into two
groups: a) interaction with the computer and b)
interaction through the computer with remote audiences.
Interactions
with the computer. Communicative interactions can occur in either
written or spoken language or a combination of both.
At the simplest level, a computer program can generate
utterances either orally or in writing that require
the learner to respond by selecting an answer with
a mouse click or providing simple writing responses
(Hanson-Smith, 1999)
. With the advancement of speech synthesis and recognition
technologies
(Ehsani & Knodt, 1998)
, the learner can also carry on near natural conversations
with a computer program around pre-selected and
programmed topics
(Jared Bernstein, Najmi, & Ehsani, 1999; Egan,
1999; Harless, Zier, & Duncan, 1999; LaRocca,
Morgan, & Bellinger, 1999; Wachowicz & Scott,
1999)
. The learner can also give either written or spoken
command to a computer program in a simulation and
game environment. The computer program would then
perform the command
(Holland, Kaplan, & Sabol, 1999; LaRocca et
al., 1999)
. Harless et al
(1999)
, for example, tested the effectiveness of a virtual
conversation program in Arabic at the Defense Language
Institute. The program enabled the students to interview
virtual characters of native speakers orally with
speech recognition technology. After interacting
with these virtual characters for at least eight
hours per day for four days, the participants’ reading
and speaking skills increased significantly (p<0.05)
while their listening skill increased “convincingly.”
In another study, Holland and her colleagues (1999)
found a speech-enabled interactive micro-world program
that allowed the learners of Arabic to construct
objects by speaking to the computer improved student
motivation and oral output.
(1999)
.
Interactions
with remote audiences through the computer.
Computer-mediated communication and teleconferencing
technologies have been used to create authentic
communication opportunities for language learners
since the 1980s
(Beauvois, 1997; Pennington, 1996)
. The uses of CMC technologies, such as electronic
mail, bulletin-boards, and chatrooms have been found
to have many benefits for language learners
(Beauvois, 1997; Cahill & Catanzaro, 1997; Kelm,
1998; Salaberry, 2001; Warschauer, 1998)
. CMC brings the much needed audience to the language
learner
(Johnson, 1999)
. It also promotes more equal and better participation,
leading to more output in the target language(Beauvois,
1997)
(Gonzalez-Bueno, 1998)
. It fosters negotiation and form-focused learning
(Pellettieri, 2000)
. CMC was also found to enhance the writing process
and improve student writing
(Schultz, 2000)
. Although CMC communication is, in most cases,
conducted in writing, it has been found to improve
oral proficiency as well. For instance, Beauvois(1997)
found that second year French learners who held
their discussions online achieved better oral proficiency
than those who discussed the texts orally in the
traditional classroom setting (p<0.05).
Providing
Feedback
The
capacity for computers to provide instant and individualized
feedback has long been recognized by educators,
including foreign language educators
(Chao, 1999; Salaberry, 2001)
. While early applications tended to follow the
behaviorist tradition by simply assessing the learner’s
performance and providing simplistic feedback in
a correct-or-wrong fashion, more recent applications
are much more contextualized and pedagogically sound
(Salaberry, 2001)
.
Computer-based
grammar checkers and spell checkers are potentially
powerful ways to provide feedback to students written
output
(Jacobs & Rodgers, 1999)
. Although the feedback provided by current grammar
checkers is not always accurate, albeit immediate,
due to its inability to perform semantic analysis
and process deep-level structures,
(Burston, 2001)
found that advanced students of French benefited
tremendously from a French grammar checker. In this study, the students in the treatment
group used a French grammar checker while writing
their essays while the control group did not. The
results suggest that “the effectiveness of the use
of Antidote in improving morphosyntatic accuracy
in assigned compositions were overwhelmingly positive.”
(p. 507). The treatment group’s first essay scored
on average 70%, compared to 20% of the control group.
The second essay showed similar result: 85% for
the treatment group while 54% for the control.
Automatic
speech recognition technology holds the potential
to provide feedback that would otherwise be impossible.
Pronunciation is a fundamental element of language
learning but to provide feedback that can be easily
accessible and useful is difficult. In traditional
instructional settings, feedback and modeling is
often provided an instructor , who may or may not
be good at judging the student pronunciation in
the first place. The way to provide feedback is
often trying to either repeat the pronunciation
or explain how the sound should be produced, in
a very abstract fashion. With the advancement of
speech recognition technology, the student can receive
feedback in more effective ways
(Dalby & Kewley-Port, 1999; Ehsani & Knodt,
1998; Eskenazi, 1999; Mostow & Aist, 1999)
, according to Aist (1999): visual feedback, template-based,
and model-based. First a computer program can analyze
a student utterance and display the features visually,
perhaps with a comparison to that of a native speaker.
A computer program can also display the position
and movements of the tongue when a student produces
an utterance, which can also be displayed in comparison
to that of native speakers. Second, computer programs
can compare student pronunciation of individual
words or sentences to pre-recorded templates. For example, good agreement (r=0.81 for high quality speech and r-0.76 for telephone-quality speech) was
found between automatic and human grading of the
pronunciation of English sentences produced by Japanese
English learners
(J Bernstein, Cohen, Murveit, Rtischev, & Weintraub,
1990)
. More recent studies found different levels of
correlation between machine and human graders: from
0.44 to 0.85
(J. Bernstein, 1997; Ehsani & Knodt, 1998)
. It was also found that such high correlation can
be achieved at the discourse level
(Coniam, 1998)
. Third, pronunciation can be evaluated against
pronunciation models. In this approach, student
pronunciation is not limited to pre-selected words
because the model is a generalization of a template.
Tracking
and analyzing student errors and behaviors is
another approach language educators have experimented
with so as to provide more helpful feedback. Computer
programs can store student responses, which can
then be analyzed either by a human instructor
(Sinyor, 1997)
or the computer
(Nagata, 1993)
. The effectiveness of this approach is yet to be
determined although Nagata, summarizing her study
findings, suggests “traditional feedback may be
as good as the intelligent feedback for helping
learners to correct word-level errors (e.g., vocabulary
and conjugation errors), while the intelligent feedback
may be more helpful for understanding and correcting
sentence level errors (e.g., particle errors)” (p.
337).
As mentioned before most of the empirical
studies were about a single application used in
a few days, we are fortunate to have found two articles
that evaluated the effectiveness of more comprehensive
uses of technology over a longer period of time
(Adair-Hauk, Willingham-McLain, & Youngs, 2000;
Green & Youngs, 2001)
. These efforts all were carried out at Carnegie
Mellon Univeristy. The first study
(Adair-Hauk et al., 2000)
was conducted in 1996 and the second study took
place in Fall 1998 and Spring 1999
(Green & Youngs, 2001)
. Participants of the first study were second semester
French students and those of the second study were
first semester French students and first and second-semester
German students.
Both studies followed the same format: the
treatment group participated in technology-enhanced
language learning activities while the control group
attended a regular class for one of the class period
each week. The technological applications included
computerized multimedia grammar and vocabulary exercises,
instructional video, online spell-checker, French-English
glossary, and the Web. Measures of listening, reading,
writing, cultural knowledge, and student attitudes
were taken during the course of both studies. Speaking
was assessed in the first study. The findings are
summarized below.
·
For study 1, when change over time was considered,
there was no significant difference between the
treatment group and the control group in cultural
knowledge, speaking or listening. For study 2, there
was not significant difference in any of the skills
measured (cultural knowledge, listening, reading,
and writing) (p<0.05).
·
However
the difference in writing was significant in study
1. The control group’s homework writing scores decreased
while the treatment group’s increased. Writing test scores also indicate a significant
difference between the two groups favoring the treatment
group (p<0.001). The treatment group also scored
significantly better than the control group in reading
(p<0.001).
·
Both studies found that students in the treatment
group spent about the same amount time completing
the tasks as their peers in the control group.
Both
studies concluded that technology-supported independent
language learning is as effective as classroom instruction,
if not more.
In order to gain a better sense of
the overall effectiveness of technology applications
in language learning, a meta-analysis was conducted
of the studies that included enough data for such
an analysis. Meta-analysis is the analysis of analysis—a
statistical technique for aggregating the results
of multiple experimental studies
(Glass, 1976, 1977; Hedges & Olkin, 1985;
Lyons, 1995a)
. The result of each identified study is converted
into a measure called effect size. An effect size
is obtained by transforming the findings from each
study into a standard deviation unit. The effect
size indicates the extent to which experimental
and control groups differ in the means of a dependent
variable at the end of a treatment phase. An effect
size (d)
was calculated is the difference between the means
of the treatment group and the control group divided
by the pooled standard deviation. More than one
effect sizes were calculated for several studies
because they had more than one measures (e.g., listening,
reading, and writing). But in order to satisfy the
independence assumption of
meta-analysis
(Hedges & Olkin, 1985)
, only one effect size per study was entered
into the study. When two or more effect sizes were
calculated, they were averaged. The effect sizes
used in this analyses are weighted ds, which corrected sample size biases
(Hedges & Olkin, 1985)
. The calculation was performed using Meta-analysis
calculator
(Lyons, 1995b)
, a computer program designed for meta-analyses.
Table 1 summarizes the results of the meta-analysis
study.
Table 1: Overall Effect of Technology Applications
in Language Learning
| Analysis* |
K |
N |
Mean Weighted D |
Standard Deviation |
95%Confidence Level
for D |
| Averaged |
9 |
419 |
+1.12 |
o.78 |
0.61 to 1.63 |
| All |
29 |
1045 |
+0.81 |
0.72 |
0.55 to 1.07 |
Notes: *: Averaged shows the result when only one averaged effect
size was include per study while All shows the result
when all effect sizes are included. K
= number of effect sizes. N
= number of subjects. The number of subjects was
repeatedly counted for each effect size for studies
that used multiple measures.
As Table 1 shows, the mean effect size of all
9 studies is quite large, indicating an overwhelmingly
positive effect of technology applications on language
learning. The
confidence interval at the 0.05 level further confirms
this finding. Thus judging from this analysis, it
is reasonable to conclude that technology has been
shown by the published empirical studies to be very
effective in improving student language learning.
What is worth mentioning is that this analysis put
all technologies and their various ways of applications
in language learning together. It did not differentiate
the areas of improvement in the target language
either. In
other words, this is a summary of the empirical
findings of the effects of a variety of technological
applications on virtually all aspects of language
learning (e.g., vocabulary, grammar, reading, listening,
writing, speaking, and cultural understanding.).
Table 2 summarizes the technological applications
and measures under investigation in the 9 studies
consisting the meta-analysis sample.
Table 2: Summary of Technology and Content of Studies
Study
|
Technology |
Content |
D |
Target Language |
| Adair-Hauck et al. 2000 |
Web, video |
listening, reading, writing,
speaking, culture |
0.28 |
German |
| Al-Seghayer (2001) |
Computer, video, image |
vocabulary |
1.11 |
ESL |
| Cahill & Catanzaro (1997)
|
Online/phone/chat |
writing |
1.13 |
Spanish |
| Harless et al. (1999) |
Speech recognition, video |
listening, speaking, reading |
1.44 |
Arabic |
| Herron et al. (1999) |
Video |
culture |
2.82 |
French |
| Herron et al. (1999) |
Video |
culture |
1.61 |
French |
| Labrie (2000) |
Web tutor |
vocabulary |
0.38 |
French |
| Nutta (1998) |
Computer assisted instruction |
grammar |
0.56 |
ESL |
| Weyers (1999) |
Video |
listening, speaking |
0.76 |
Spanish |
Discussions
and Conclusions
This review study was conducted to
achieve three goals: 1) assessing the overall effectiveness
of uses of technology in language education through
meta-analysis, 2) exploring patterns of recent efforts
in using technology to improve language learning,
and 3) identifying effective ways to use technology
in language education. In this final section, I
summarize the findings and discuss their implications
for future research and development efforts in technology
supported language education.
In terms of overall effectiveness of technology
on language learning, there is evidence suggesting
that technology-based language instruction can be
as effective as teacher-delivered instruction. Although
the number of available experimental studies is
limited, a consistent pattern of positive effects
is found across the studies. However, this finding
should be interpreted with extreme caution for a
number of reasons, in addition to the limited number
of studies. First, there may be a tendency for journals
to publish studies that report significant positive
gains. In other words, studies that found less significant
or even negative effect of technology may not have
been published. While there is no simple way to
verify this assumption, it is to some extent supported
by a recent meta-analysis study about the effects
of social contexts on computer uses in learning,
which found that published studies have a bigger
effect size than unpublished studies
(Lou et al., 2001)
. Second, most of the studies had fairly small
sample sizes and employed rarely random sampling.
Third, the fact that all studies were conducted
on college students and adult learners raises questions
about the generalizability of the finding to other
language learners who may differ in motivation,
language background, learning style and ability,
and instructional context. For instance, it is very
likely that college students are generally more
motivated and better learners than K-12 students
as a whole. Lastly, in most cases, the researchers
of these studies were also the instructors who designed,
implemented, and evaluated the technology uses.
It is conceivable that the classical “Pygmalion
effect”
(Rosenthal, 1973)
could affect the results. It is also the case
that most of the instruments were designed by the
researchers, who are also the instructors, instead
of independent standardized instruments. It is possible that these measures might have
a bias in favor of conditions where technology was
applied.
This
review found that recent efforts in applying technology
in language education share three interesting characteristics.
First, many of these efforts were carried out by
individual instructors or small groups of individual
instructors with limited resources. Consequently,
efforts were of smaller scale. Very often only individual
technology was used to affect a very specific part
of language education. The review found a very limited
number of efforts that attempted at comprehensive
applications of multiple technologies to the whole
process of language education. Second, most efforts
involved the development of products, which then
were used in language teaching. Commercially available
language software or tools were rarely used in these
studies. As a result, the review found many publications
describing the development process, while only few
articles reported the effectiveness of these products.
In the meantime, the numerous commercial products
readily available and widely used in classrooms
were not studied. Third, the review found that in
general current attempts to use technology in language
education were not connected ignored the language
learning at the pre-college level. This finding
is very surprising, especially viewed in the context
of technology applications on other content areas,
such as mathematics and science, where a large number
of studies of technology applications were conducted
at the K-12 level.
What are effective uses of technology in language
education? This review shows that the application
of technologies can be effective in almost all areas
of language education. Modern technology can help
enhance the quality of input, authenticity of communication,
and provide more relevant and useful feedback. Particularly
communication technologies such as the Internet
and satellite television have been found to be widely
used as a way to bring authentic materials into
the classroom, involve learners in more authentic
communications with distant audiences, and provide
researchers the opportunity to better examine the
language learning process. Additionally speech technology,
while still not quite ready for full implementation
for language education, has already been shown its
potential for supporting language learning.
Findings from this review study have significant
implications for future work. It is apparent
from the literature review that technology, when
used properly, can have a positive effect on language
learning. It
is also apparent that the availability and capacities
of information technologies have not been fully
taken advantage of by language students or educators.
To truly capitalize on modern information and communication
technologies to significantly improve language learning,
a number of issues must be addressed.
Technology capacities need to be translated
into pedagogical solutions and realized in the forms
of curriculum and content for language learners.
Current uses of technology, as revealed by the literature
review, are fragmented and isolated. There are very
few comprehensive technology-based curricula that
fully takes advantage the power of available technologies.
Thus in the future, what is needed is the development
of full curriculum that is supported by available
technologies instead of individual tools that are
only used infrequently or as a supplement to a primarily
print-material based curriculum.
The effectiveness of technology on language
learning is dependent on how it is used. Certain
technologies are more suitable than others for certain
learning tasks for certain learners. Therefore research
about appropriate ways and contexts of technology
uses is much needed
(Salaberry, 2001)
.
Technology is under utilized in classrooms
(Cuban, 2001)
. The finding that none of the studies found in
the major language education and technology journals
are about technology uses in K-12 classrooms is
shocking because studies of technology applications
in other subject areas (e.g., mathematics, science,
social studies, and language arts) have mainly taken
place in K-12 classrooms. The fact that almost all
the authors of the studies found were also the instructors
in the experiments suggests a possible explanation:
K-12 teachers are not using technology in their
teaching and there is a lack of interest among university
researchers in studying technology applications
in K-12 language classrooms.
This finding raises two issues: a). How to
promote technology uses in K-12 classrooms? And
b). How to encourage more research about technology
uses in K-12 language classes?
There is a clear lack of systematic empirical
evaluation efforts to assess the effectiveness of
large-scale comprehensive uses of technology to
support language learning. This, of course, may
be accounted for by the lack of large-scale implementation
efforts. But it may also be the result of an overall
emphasize on the process rather than result of using
technology in language learning. As mentioned earlier
in this paper, there was a shift among researchers
of language education in the mid 1980s from product-oriented
research to more process-oriented research which
focuses on understanding how student learn instead
if what and how much they learn. For example, many
studies on CMC have been about the nature and patterns
of student participation in online interactions
rather than how much their language skills have
improved. While such research is necessary and important,
we cannot ignore the practical question of how and
in what ways technology uses are effective in improving
language learning.
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