Chapter 1 Introduction
1.2 Research Questions
This research attempts to observe the sight translation comprehension
process of experienced interpreters and study the differences between theirs
and the process of novices, in hope to recognize traits that make a delivery by
experienced interpreters better. In Huang’s (2011) study, she had already
collected eye movement data from novice interpreters, and also provided
some insight on the cognitive behavior of novices during sight translation. In
order to be able to compare the collected data from both researches, this study
will also conduct an eye movement experiment and collect eye movement
records of experienced interpreters. Participants will be asked to complete
three tasks: silent reading, read aloud, and sight translation. Eye movements
and vocal output would be recorded for later studies. Output quality of both
groups (novice and experienced interpreters) would also be evaluated in terms
of accuracy and fluency.
This study will observe and study the following areas:
1) Whether experienced interpreters actually in fact require less time in
certain eye movement indices, which would support the hypothesis that
experienced interpreters are more efficient; and
2) Observe if experienced interpreters really do employ specific strategies
during sight translation which are not performed by novices.
Chapter 2
Literature Review
2.1 Expertise
2.1.1 Definitions and criteria of experts
When people mention “an expert”, the image is usually an individual who is
“very good at something”, and are able to provide performances with
consistent good quality (Ericsson, 2000). Glaser (1976) offered a more
detailed description of the general expectations of experts. He pointed out that
when one has achieved expert status, they should be able to constantly deliver
an accurate and complete performance relatively fast, integrate individual
skills and choices, have a more comprehensive perception of the task, and
form new solutions and strategies as required. Efficiency, flexibility, and
consistency are traits that experts should possess. And many studies point out
that experience is crucial to obtaining these traits. For Moser-Mercer (1997),
an expert is, “someone who has attained a high level of performance in a given
domain as a result of years of experience”. Hoffmann (1996) also suggests that
time alone does not make an expert; rather, the key is to accumulate
experience and practice.
As experts accumulate experience, they become more familiar and
comfortable with their skillsets. They can manage, adjust, even develop new
strategies on the spot as the tasks and situations demand, which allows
experts to be able to response and/or react faster than novices when faced
with the same task, as Ericsson and Smith (1993) suggested; and are more
likely to achieve similar levels of quality each time. This “automation” strategy
is also a means of showing one has mastered the skills of the particular field,
and allows experts to utilize production capacities to full efficiency and
shorten reaction time; as opposed to novices who have to consciously manage
all strategies they employ, resulting in more required time and effort and
probably a not very satisfactory outcome (Moser-Mercer, 1997).
Past researchers have found experts or experienced individuals in certain
fields, such as chess masters, would visualize the task in “chunks” as a more
efficient way of understanding the comprehensive situation (de Groot, 1965,
1966; Chase & Simon, 1974). Klein and Hoffman (1993) also mentioned that
experts are able to tell when things are amiss faster, visualize the entire
process and anticipate the possible outcomes because of their experience. This
skill increases the efficiency of experts, as it allows them to figure out the most
appropriate and efficient solution and strategy for the task as early as possible,
decreasing the possibility of employing a wrong solution and failing the task.
Similar judgment skills also assist in the experts’ problem solving and decision
making stages (Klein & Hoffman, 1993). In short, experts have reached a point
where they do not need to spend extra effort to consciously access their
expertise (Anderson, 1995; Dreyfus, 2004), therefore are faster and more
flexible when finding a solution to complete the task at hand.
So what are the exact criteria to define an expert? Traditionally, the emphases
are placed on different strategies and/or larger knowledge bases that experts
possess that allow them to deliver better performances (Klein & Hoffman,
1993). However, so far there has been no consensus on how to scientifically or
objectively evaluate or qualify one as an expert. As Ericsson (2000) points out,
there is the possibility that the individual’s reputation and level of training is
mistakenly used to evaluate their expertise, and these social perspectives of
expertise are usually not consistent with the individual’s performance. He
argued that experts should be able to repeatedly deliver performances of
similar quality anytime; therefore researchers can collect a set of expertise
qualities and evaluate expertise in a scientific way in laboratories (Ericsson,
2000). Ericsson, Prietula, and Cokely (2007) suggested three indicators to
evaluate real expertise: consistent superior performance, concrete results, and
“can be replicated and measured in the lab”. Some may question that in
certain areas, such as creative professions, measuring expertise would run into
many challenges as it is impossible to recreate the performances in a lab, let
alone scientifically measure the results. Nevertheless, according to Ericsson,
Prietula, and Cokely (2007), modified testing methods for these areas, such as
art and writing, still exist, and results accurately reflect the experts’ technical
proficiencies. Therefore, regardless of area and profession, it is still possible to
identify at least the technical strategies and traits of experts.
2.1.2 Developing expertise
Some people may argue that experts are born with special talents, or “gifted”.
Experts possess some kind of innate ability that allows a particular individual
to perform better, to achieve a certain goal faster and easier. On the contrary,
those born without talents have to work harder, and may even never be able to
reach the level of expertise the former group have. Therefore for those who are
not born “with the talent”, any form of expertise training or development
would at most yield limited results. However, according to Ericsson, Prietula
and Cokely (2007), experts are made (trained), not born; in fact, it will take a
person at least 10 years (or 10,000 hours) to become an expert. In their article,
they also mentioned the findings of Bloom (1985). Bloom’s study showed that
individuals who perform exceptionally well “had practiced intensively, had
studied with devoted teachers, and had been supported enthusiastically by
their families throughout their developing years”. Ericsson (2000) also
remarked that so far there have not been any set standards for evaluating the
effects of innate talents on adult achievement. If innate talents do bring
certain advantages for individuals, there is no supporting evidence that others
cannot compensate the gap with extensive training later on in life. The only
exceptions would probably be body size and height, especially for athletes. But
overall, given enough motivation and training, individuals who had already
accumulated substantial experience in the area usually can accomplish
different degrees of improvements later in life.
In order to understand the progress of individuals on their journey to become
experts, Dreyfus (2004) purposed a five-level model of expertise development,
starting with Novice, to Advanced beginner, Competence, Proficiency, and
finally, Expertise. The Dreyfus model has been used to study interpreter
training (汝明麗，2010). According to the study done by 汝明麗 (2010), upon
finishing two years of interpreting training, student interpreters in Taiwan
should have a Competence level skillset. However, the implementation of the
Dreyfus model in interpreting studies is still at its beginning stage (汝明麗，
2010).
In the Dreyfus model, both novices and advanced beginners are placed in
controlled environments where they are given simple basic rules to follow.
Individuals at the Novice level begin by simply follow basic rules given by the
instructor, regardless of the environment and situation. Gradually, the novices
begin to note different situations and start to integrate related context and
information for a better performance. This is when they enter the Advanced
beginner level. At this level, advanced beginners have more experience than
novices, and more understanding of related context; yet the learning at the
level are still based on examples and instructions, and distanced from actual
environments and scenarios. Once advanced beginners enter the Competence
level, they begin to make their own choices. Students at this level learn how to
pick out relevant and important aspects and make decisions during tasks.
Results of the tasks are now controlled by the student’s own choices, which,
understandably, cause emotional stress for the student. Interestingly, if
handled well, stress may actually assist the student to improve, as it pushes
them to improve their performance.
Starting from the Proficient stage, the student is able to conceive goals (as in
what they need to accomplish) and form various strategies to react. However,
proficient individuals lack sufficient experience to anticipate possible
outcomes of different strategies; therefore still require time and effort to
decide which method of solution to use. As they do not have enough
experience to assist their decision, proficient individuals would fall back on
their basic trainings. Here experience becomes the biggest difference between
Proficient and Expertise levels: proficient performers, who have relatively
lesser experience, still need to fall back on basic rules and training to make
decisions, consequently requiring more time and effort to complete the task.
On the other hand, experts are able to form intuitive responses immediately
by leveraging their past experiences, and decide on better and more effective
strategies. Dreyfus (2004) pointed out that after the expert encounters a new
situation, their brain will later categorize the final solution, and form a
database-like storage for the expert to reuse or refer to in the future should
their encounter similar problems. This echoes the findings of Klein and
Hoffman (1993) mentioned earlier which suggested that since experts are
more experienced, they are able to quickly predict possible outcomes of
different strategies; therefore more likely to choose and apply the most
efficient solution within the shortest period of time. Again experience is the
crucial factor that distinguishes experts from other levels of expertise.
However, although experience is an important factor that allows experts to
make decisions faster and more efficiently, Ericsson, Prietula and Cokely
(2007) pointed out that some studies have shown that without continuous
training, expertise actually declines with experience. The training here does
not indicate aimless repetitive practice/exercises, as Klein and Hoffman (1993)
points out; but rather a kind of deliberate practice, which is defined as
“practice that focuses on tasks beyond your current level of competence and
comfort” (Ericsson, Prietula, & Cokely, 2007). It includes two aspects:
stepping out of one’s comfort zone and work on something new and
unfamiliar, and to continuously improve on the skills one already possess.
Deliberate practice also makes great difference in performance. As Ericsson,
Prietula and Cokely (2007) found out in their study, senior experts who
neglect to practice deliberately on a regular basis may be more prone to
dealing with events automatically, or even relying on intuition; therefore are
more likely to run into problems when faced with atypical situations they are
not familiar with.
Dreyfus (2004) did not address the issue of deliberate practice in his model.
Expertise in his model is defined by the ability to make immediate, intuitive
responses according to the situation (Dreyfus & Dreyfus, 2005; Dreyfus,
2004). When faced with atypical situations, experts should be able to
compensate with their vast experience “data-pool”, and still produce quality
performances (Dreyfus, 2004).
Past literature and studies offer general observations on experts in various
fields, such as expertise and quality performance are the results of experience
accumulation (Ericsson & Smith, 1993; Moser-Mercer, 1997; Hoffman, 1996),
and experts employ “chunking” and other strategies during tasks (Klein &
Hoffman, 1993). One phenomenon often used to decide whether an individual
is an expert or not, is their ability to constantly deliver a quality performance
(Glaser, 1976; Ericsson, Prietula, & Cokely, 2007). Although some may say it is
difficult to objectively grade performances in certains fields, the creative arts,
for example, Ericsson, Prietula and Cokely, (2007) point out there are still
methods to grade leves of technical aspects and skills. Experts, according to
Ericsson, Prietula and Cokely (2007), are deliberately trained and developed,
not just individuals natually born with innate talent. In fact, deliberate
practise is very crucial to the making of an expert (Bloom, 1985; Ericsson,
2000; Hoffman, 1996). Since currently there is no other model established to
distinguish different levels of expertise in the field of interpreting, the Dreyfus
model is used in related interpreting studies as guidelines for grouping
interpreters at various skill levels (汝明麗，2010).
2.2 Interpreting
The history of interpreting may be traced back to a time when two people
speaking different languages wanted to understand what the other person was
talking about, so they sought out the help of a person who happened to speak
and understand both languages. Methods of interpreting have evolved and
changed with time and the advance of technology. Interpreting is generally
divided into two major categories: consecutive interpreting and simultaneous
interpreting (Agrifoglio, 2004). During consecutive interpreting, or CI,
speaker and interpreter take turns to speak/interpret. The interpreter delivers
the interpretation after the speaker has spoken a part of the speech (usually no
more than three minutes). In simultaneous interpreting (SI), the interpreter
listens to the original speaker through headphones, and interprets the context
into the target language simultaneously. The delivery is spoken into a
microphone and delivered to the audience’s headphone. Sight translation (ST),
during which the input is visual instead of audio, is often considered a type of
SI; however, since the input during ST is readily available on paper all the
time, the interpreter is able to follow their own pacing, rather than being
controlled by the speaker (Agrifoglio, 2004).
2.2.1 Sight translation
Sight translation (ST) is a task that requires the interpreter to read a text and
simultaneously interpret it into another language. This task may be employed
in judicial situations, such as courtrooms, or scientific and technical academic
conferences, where the speaker may opt to directly read from their papers
(Weber, 1990). In many translation and interpreting training institutes, sight
translation is considered as a preparatory stage for simultaneous interpreting
(Agrifoglio, 2004), and also used as a tool to train interpreting students to
read ahead of their notes and deliver a smoother output. Prior to assignments,
interpreters may also sight translate related text and articles as background
knowledge preparation, and to familiarize themselves with the jargon and
technical terms of the area (Weber, 1990).
During ST, the source text is always visually present, and the interpreter can
process the input according to their own speed; as opposed to SI, during
which the input is audio, and flow and speed is dictated by the speaker.
However, ST should not be considered as easier to accomplish than SI on the
basis that it has no time limitations. Many researches have pointed out that ST
is as difficult as SI, as interpreters mentally process language during both
tasks similarly (Mikkelson, 1995; Agrifoglio, 2004).To further illustrate the
complexity of cognitive loading during various interpreting tasks, Gile (1995)
broke down the components and established effort models to describe how
cognitive efforts are distributed during different interpreting modes.
According to the model, a SI task is composed of Listening and Analysis Effort
(L), Memory Effort (M), Production Effort(P), and Coordination Effort (C),
resulting in a model as follows:
SI = L + M + P + C
Spontaneously listening, comprehending and speaking is one of the main
characteristics of SI, which also implies the importance of coordination during
the task. Furthermore, since the interpreter is required to deliver the
interpretation as the speaker is speaking, the interpreter must not only go
through all efforts at the same time, but also adjust their own processing pace
according to the speaker’s speed. Students or novices of interpreting often find
this task daunting, as the pace and speed of the input is not controlled by the
interpreter themselves. In fact, studies have shown even experienced
professionals may make mistakes during SI (Gile, 1997). Agrifolio (2004) also
concluded that during SI and CI, memory saturation and note-taking
problems could interfere with the final interpretation output, causing failures.
For sight translation, Gile (1995) claimed that during this task, Listening and
Analysis Effort is transformed into a Reading Effort (R), and Production
Effort (P) is still present. But Memory Effort is not required during this task,
as the source text is always present on paper and interpreters do not have to
rely on short-term memory to memorize the beginning of sentences, or
previous information input in order to produce a complete and coherent
sentence. The model is displayed as follows:
ST = R + P
The absence of Memory Effort in Gile’s (1995) is debatable. Gile assumed that
since the source text was always available, there would be no need for extra
short-term memory. He did acknowledge that syntax differences between
languages, and longer sentences with embedded clauses require more time
and effort; however, the interpreter deals with these challenges by rereading
more Translation Units, not by employing any memory-related strategies.
Actually, researchers disagree on whether the always-present visual source
text is more of an interference which could compromise the fluency of delivery,
instead of a visual aid. Lambert (2004) argued that students perform better
during sight translation and simultaneous interpreting with text than during
free simultaneous interpreting, mainly because of having the text which serves
as visual assistance present during the processes (Lambert, 2004). Also, since
the text is a visual input, when combined with audio inputs, it does not cause
much interference to the interpreter (Shaffer, 1975; Viezzi, 1989; Lambert,
2004). On the other hand, some argue that visual interference could be
stronger than that from audio, as mentioned by Agrifolio (2004) and Shreve,
Lacruz and Angelone (2010). Since the source text remains available
throughout the ST process, the attention and gaze of the interpreter may
involuntarily be drawn back to the source text, causing diversions and
increasing the cognitive load (Agrifoglio, 2004). Furthermore, Mikkelson
(1995) also noted that with the text always present, interpreters find it more
difficult to focus on the meaning of the message, instead of the words;
therefore the constant presence of the written text may prove to be a drawback
instead of assistance.
It should also be noted that Gile did not address the Coordination Effort when
describing the model of sight translation; yet it can be assumed that the effort
is still present so that the interpreter can smoothly employ both Reading and
Production efforts. Agrifoglio (2004) also pointed out that one of the main
difficulties of sight translation is the interpreter requires significant
coordination to ensure a fluent, coherent delivery, especially when the two
languages have different grammatical structures. The act of doing many things
simultaneously is not a natural activity for humans, normally people can only
concentrate on one single task (Lambert, 2004). Two tasks may be
manageable if they are related to the same higher-order activity, as the
attention switches rapidly between the different tasks, or at least one of the
tasks can be carried out automatically (Lambert, 2004). However, Lambert
(2004) had also noted that with proper training and practise, it is possible to
(2004) had also noted that with proper training and practise, it is possible to