January 1997 -- Volume 2, Number 3
Computer Generated Error Feedback and Writing Process: A Link
Judy F. Chen
Business English Instructor
The Overseas Chinese College of Commerce,
Taichung, Taiwan, ROC
This study examines a possible link between computer
generated feedback and changes in Taiwan EFL business
writing students' writing strategies. By using computer
software that measured details of students' writing,
including: time spent on a document, amount of editing
on a document, specific errors made in the document,
and the amount of text copied from resource material,
the author was able to perform numerous detailed analyses.
Students were randomly assigned to test and control groups
with control students receiving a placebo computer feedback
and the test group receiving real computer generated
feedback on their errors. While the majority of feedback
was teacher based and exactly the same for the two groups,
different writing strategies were evident in the two groups
by the third assignment.
Conclusions point to the important impact computer
generated feedback appears to have on students, including
the encouragement of a more process oriented approach in
their writing. Such a finding has the potential of allowing
Teachers to incorporate more process writing in their
classrooms where they once though impossible, due to the
large EFL class sizes so common in Asia.
English business writing skills have been shown to be important
to Taiwanese businesspeople (Tsui, 1992; Liao, 1990). Across Asia,
the educational emphasis on English reflects the importance attached
to English skills in international business. In Taiwan, however, the
emphasis placed on English does not lead to a very conducive
learning environment. The normal class size in Taiwan ranges from
forty to eighty students (with numbers rarely falling below forty
and occasionally going over one hundred. Remuneration for teachers
is largely based on hours in class, rather than number of students
in class. This leads teachers to question the amount of effort that
should be expended in supplying students with feedback on writing
Searching for possible solutions to some of these problems, I
began to study how computer-generated feedback may play a role in
relieving teachers' burden, while supplying students with more
Application of grammar-checking software is a logical step in
CALL; however, due to shortcomings in software and the lack of
hardware in most EFL settings, such application has not become
widespread. Numerous programs that claim to check grammar errors in
English writing are commercially available. Bolt (1992) has
described most of these programs in detail, including: Correct
Grammar, Right Writer, Grammatik, CorrecText, Reader, Power Edit and
LINGER. While these programs have different demands on hardware,
most run on a personal computer. Bolt points out the very important
characteristic of transparency, which he defines as the degree to
which the program's underlying functions and logic can be seen and
changed. Grammatik offera the greatest access to its rule base and
allows changes to rules or addition of new rules(this is the case in
the present study).
Healey (1992, p. 14) also examined such programs and attempted
to add some new rules to Grammatik but found that such an exercise
required considerable work on the part of the teacher. Healey
observed that while a grammar checker may not find every error, its
work in "consciousness raising" can be very helpful for language
learners. Brock (1990), teaching in Hong Kong, also found that
modifying Grammatik was helpful when rules were programmed for some
common errors of Cantonese speakers learning English.
Garton and Levy (1994), using a later version of Grammatik,
version 5, found it to be much improved over earlier versions.
Although at first use Grammatik5 seems to be very inaccurate, after
modification, it improves greatly. In their study, Garton and Levy
gathered a large database of students' writing. They then ran some
documents through the Grammatik grammar/style checking software. The
results directed them towards what rules to turn off because such
rules were not accurate or did not apply to EFL students. It also
led towards the creation of new rules to find errors in the
students' writing that the program had missed. After making
changes, the database could again be used to verify the accuracy of
new rules programmed into Grammatik. While the computer could not
replace a teacher or even a tutor, it was found to be a useful tool
in helping to raise the awareness of students.
Liou (1991, 1992, 1993, 1994) has performed a number of
experiments using Grammatik as well as custom-designed software to
find their impact on EFL students in Taiwan. Although the studies
usually include a small number of subjects, the results tend to be [-2-]
positive in showing that groups using CALL perform somewhat better
than those not using it.
When grammar-oriented CALL was applied in a process-oriented
class setting, Liou (1993) found that the CALL group was able to
rectify more of their errors during redrafts and made fewer errors
than the non-CALL group:
It is evident that subjects [non-CALL] were not able to correct
most of their mistakes by themselves even after some devices to
raise their consciousness as to form, such as marks, were used (p.
The inability of EFL students to overcome some errors has also
been observed by Dalgish (1991) when he wanted to find the common
errors of students learning English in Sweden. The same topic was
pursued by Brehony and Ryan (1994) with the understanding that EFL
learners' mistakes often reflect the usage or structure of their
native languages. These interlingual errors can be affected by CALL
simply because they can be easily identified and then codified in
software. Simple matching procedures can be used to flag such
This study builds on previous studies using the custom built
software QBL TOOLS (Warden & Chen, 1995; Warden 1995; Yao & Warden,
1996). These studies attempted to uncover details of why computer-
generated error feedback does appear to help in the Taiwan EFL
writing context. The software used is QBL Student Version for
student use and QBL TOOLS for teacher use. While QBL TOOLS has
continued to improve with more custom rules specific to the Chinese
EFL context, the main parsing engine continues to be Grammatik5 for
Windows. Previous results of supplying students with detailed
computer-generated error feedback included: lower error rates for
the test groups, time savings for the teachers, and detailed data on
the types of errors made by students.
General Approach Of QBL System
A text editor (QBL, Quick Business Letters) for use in the DOS
environment is supplied to each student on a floppy disk and can be
taken home or used in any open computer lab. Students' disks are
clearly labeled so that a student uses the same floppy disk
throughout the study. The student program guides students through
the creation of correctly formatted business letters and memos for
business writing classes, or essays, for normal English classes.[-3-]
When an assignment is completed, each student prints out his/her
work and hands it into the teacher for normal review and grading.
Students also send the completed files over a local area network to
the teacher's directory for automated correction.
After receiving the students' files over a network, the teacher
then runs the teacher software (QBL TOOLS) that creates detailed
feedback on grammar, style, and mechanical errors for each student.
The custom developed software automates the process of accessing
students' files, running them through the Grammatik program and
collecting and summarizing data.
The Grammatik parsing engine was programmed to find 45 error
types (see Table 1,) including a class of errors and custom errors
(with over 300 customized rules) programmed specifically for EFL
writing students in Taiwan (a similar approach to that followed by
Levy and Garton (1994)). This completed system can automatically
find hundreds of errors in minutes and print them out with no input
from the teacher. Charts and graphs can be printed to track class
or individual student progress.
Data Categories Of This Study
For this study, the student letter writing program was modified
to collect data on the number of keystrokes completed by the user.
This measurement includes two parts: one for actions that add
characters to a document (such as typing the letters of a word) and
one for actions that remove characters from a document (such as the
backspace or delete keys). The characters removed from a
document divided by the number of characters added to a document is
here referred to as an "editing ratio."
All measurements are taken in units of keystrokes. For
example, a student typing "ships before" would be reported as having
added twelve keys. If the student then goes back and removes an s,
resulting in "ship before," the number of characters removed would
be one while the number of keys added remains twelve. The editing
ratio of this example is thus .08333 (1/12) or 8.33 percent. All
measurements begin at zero when a new assignment is given and are
cumulative over a single assignment no matter how many times, or in
what locations, the program is run.
Error rates and error types are the other data types gathered
for this study. The error feedback for the students is made up of
45 specific writing error types (see Table 1). [-4-]
Table 1 The Error Types Found (See Appendix A for explanation)
Abbrev. |Adjective |Adverb
Archaic |Article |Capitalization
Clause |Colloquial |Comma Splice
Comparative |Conjunction |Custom
Double Neg. |Ellipsis |Ending Prep.
Incomplete Sen.|Infinitive |Jargon
Long Sen. |Noun Phrase |Number
Overstated |Pejorative |Poss. Form
Preposition |Pron. Number |Pronoun Case
Punctuation |Ques. Usage |Redundant
Rel. Pronoun |Repeated |Run-on
S/V Agreement |Sent. Variety |Similar Words
Spelling |Split Infin. |Split infinitive
Subordination |Tense Shift |Trademark
Vague Adv. |Verb Form |Verb Object
Rather than using separate classes (intact groups) to form
control and test groups, this study used randomly selected students.
After selection, both groups stayed mixed together in already
existing classes so that each class contained both test and control
Approximately ten percent of students in each class were
randomly selected to receive (unknowingly) feedback that was not
actually produced by the computer system, i.e., a placebo. The
computer-generated feedback given to these students resembled the
true feedback; however, any errors found by the computer would not
be reported as errors. The computer printout given back to them
would simply report zero errors found. Other feedback from the
teacher, such as handwritten corrections, comments on content
and corrections to formatting (layout of heading, opening, closing,
etc.) were given to all students irrelevant of the experimental
group they were in. The test group students were randomly selected
from the remaining students.
The experiment was performed during the 1995-96 fall semester
at The Overseas Chinese College of Commerce (Chiao Kwang) located in
central Taiwan. Students from three departments participated:
International Trade, Business Administration, and Banking &
Insurance. Two instructors taught the eight participating sections
of Business English, which was required for these students in their
senior year. The total number of students (see Table 2) using the
QBL computer system was 363. The control group (receiving dummy
feedback) contained 38 students while the test group numbered 42
Table 2. Participating students
All teaching material was unified, and assignment topics,
scheduling, and other class characteristics were agreed upon before
the semester began. Numerous assignments were completed over the
semester (which began in September), with three requiring students
to use their QBL program disks (see Table 3). Each assignment
required a minimum of 150 words in the body of the letter, with no
restriction over 150. The first assignment was not a business
letter, but geared towards familiarizing students with the computer
system and the correct format of a business letter.
Missing assignments could be caused by a student not performing
the assignment, late completion of the assignment or an error in
successfully completing any part of turning in the assignment over
Table 3. Assignments & students successfully turning in files
|Assignment Topic | Date | Control Students| Test Students|
|Summer Vacation | Oct. 3, 95| 33 | 35 |
|Job Application | Nov. 6, 95| 36 | 36 |
|Business Inquiry | Dec. 7, 95| 37 | 42 |
Files were turned in over a network and printouts turned in by
hand. Redrafts were not required by the instructors. Thus any
changes observed reflect students' behaviors before submitting the
relative assignment. The teaching strategy for the class can best
be described as a combination of process and product. This approach
is a practical combination of process and product, as has been
pointed out by Hutchinson and Waters (1987) and applied to large
technical writing classes by Okoye (1994),referred to as SDPA
(Self-Directed Process Approach). Upon return of assignments to
students, the teachers spent time in class reviewing the most common
error types found by the computer. At no time, however, did
teacher-directed redrafting take place. [-6-]
Differences In Means
Changes Between Assignments
As in previous studies using computer generated error feedback,
error rates quickly declined(see Table 4).
Table 4. Error mean and rate of decline
|Group | Control | Test |
|Assignment 1 | 15.32 | 15.67 |
|Assignment 2 | 7.81 | 7.69 |
|Assignment 3 | 5.16 | 5.00 |
|Rate of Decline | -5.08 | -5.33 |
Figure 3. Decline in mean errors
15| # @
14| # @ # Control
13| # @ @ Test
12| # @
11| # @
10| # @
9 | # @
8 | # @ # @
7 | # @ # @
6 | # @ # @
5 | # @ # @ # @
4 | # @ # @ # @
3 | # @ # @ # @
2 | # @ # @ # @
1 2 3
What is most striking about this decline is that it is equally
exhibited by both the control and test groups. Such a similar
decline in both groups runs counter to previous QBL Tools studies
that used intact and separated classes as control and test groups.
Overall, each specific error type followed a downward trend through
the three assignments. Between the first and third assignments, the
control group was able to statistically significantly reduce eight
of its error types, while the test group was able to reduce fifteen
(two error types showed a significant increase). Table 5 clearly
shows that both groups were reducing a range of error types. Of
special interest in Table 5 are the different types of errors
Previous studies have shown that spelling errors are the error
type most sensitive to computer generated feedback. In this case,
however, we observe that spelling errors are quickly reduced for
The obvious explanation is that these students, of the control
group, are mixed with students receiving feedback. They were
exposed to the errors common to their classmates, while also
cooperating on completing assignments (a behavior quite normal for
Taiwanese students) and receiving the same input from a teacher
during class from instruction.
Table 5. Reduction in specific error types
(all changes shown are significant on a modified LSD [Bonferroni]
test at P<.05)
Assignments 1-3 || Assignments 1-3 |
|Control 1| Control 3|| Test 1 |Test 3 |
| Mean | Mean || Mean | Mean |
Adjective: | .2647 | .0526 || .1284 | .0373 |
Adverb: | | || .1588 | .0466 |
Capitalization: | | || .1757*| .3727*|
Comma Splice: | | || .2466 | .0870 |
Custom: | 4.1176 | .7105 || 4.4932 | .7298 |
Incomplete Sen.:| | || .3041 | .1180 |
Infinitive: | | || .0338 | .0062 |
Noun Phrase: | 1.9412 | .5789 || 1.3176 | .6335 |
Poss. Form: | | || .0946*| .1708*|
Pronoun Case: | | || .1554 | .0435 |
Punctuation: | .6176 | .1316 || 1.2230 | .3634 |
Repeated: | | || .1047 | .0155 |
S/V Agreement: | | || .6417 | .4161 |
Sent. Variety: | | || .6014 | .3634 |
Spelling: | 3.3529 | 1.1842 || 3.5236 | 1.7702 |
Subordination: | .4706 | .0789 || .3243 | .0404 |
Verb Form: | .3824 | .1053 || | |
Verb Object: | .5000 | .1316 || .4662 | .1801 |
* Showed an increase between first and third assignments
Differences Between Groups
From the measurements centering on editing ratio, it is
apparent that feedback had differing impact on the two groups.
Editing ratios begin with no statistical difference in the first
assignment and quickly show a significant difference in the second
and third assignments (see Table 6). Clearly, the feedback is
having an impact on editing behavior. This measure shows that for
an equal number of keystrokes put into a document, feedback is
causing the test group to delete more from the document than the
control group. [-8-]
Table 6. Differences in editing ratio (percentage)
|Group | Control |t-test | Test |
|Assignment 1 | 17.91 | NS | 18.02 |
|Assignment 2 | 16.20 | .046 | 23.20 |
|Assignment 3 | 13.94 | .018 | 22.00 |
|Trend | -1.99 | | 1.99 |
Figure 4 graphically shows that not only is there a significant
difference, but the two groups are actually showing trends in
opposite directions. While the test group shows a positive trend
(using linear trend analysis) of 1.99 (F=1.17, NS), the control
group shows a negative trend of 1.99 (F=158.99, P<.01).
Figure 4. Differences in editing ratio
22| @ @
20| @ @ # Control
18| # @ @ @ @ Test
16| # @ # @ @
14| # @ # @ # @
12| # @ # @ # @
10| # @ # @ # @
8 | # @ # @ # @
6 | # @ # @ # @
4 | # @ # @ # @
1 2 3
Keystrokes added (see Table 7) show no statistical difference
with a general upward increase for both groups. The control group
is very steady in its trend of 46.48 (F=1693.93, P<.025), meaning
that this group types about 46 more keystrokes into each new
Table 7. Differences in keystrokes added
|Group | Control |t-test | Test |
|----------------|---------|P value |---------|
|Assignment 1 | 1205.06 | NS | 1226.46 |
|Assignment 2 | 1253.5 | NS(.08)| 1390.44 |
|Assignment 3 | 1298.03 | NS | 1266.19 |
In contrast, the test group shows much more variation among the
students, possibly showing differing individual reactions to the
very specific feedback from the computer. The test group has an
overall average increase in keystrokes added of 19.87 (F=.0570, NS).
Table 7 clearly shows how the test group exhibits much more
variation over the second and third assignments, although none of
the differences are statistically significant.
The keystrokes deleted measurement also shows differences
between the two groups. Although none of the differences are
significant at the P<.05 level (see Table 8), the trends of the
groups are very similar to the trends of the editing ratios. This
similarity shows that the edit ratio is rising or declining not due
to how much is being put into a document, but mostly due to how much
is being changed.
Table 8. Differences in keystrokes deleted
|Group | Control | t-test | Test |
|----------------|---------| P value |---------|
|Assignment 1 | 262.30 | NS | 266.37 |
|Assignment 2 | 240.81 | NS(.060)| 386.42 |
|Assignment 3 | 202.92 | NS(.068)| 321.07 |
|Trend | -29.69 | | 27.35 |
In total, the additional keystrokes being used to delete
characters means that the test group is typing more. In fact, the
test group is typing (keystrokes added plus keystrokes deleted)
nearly 11 percent more keystrokes (see Table 9) than the control
group in the second and third assignments (only examining
assignments after the first feedback was received). The control
group stays steady in its keystroke activity throughout the three
assignments, in contrast to changes in the test group's activity.
Table 9. Total keystrokes
|Group | Control |% Difference| Test |
|Assignment 2 | 1494.31 | 15.9016 | 1776.86 |
|Assignment 3 | 1500.95 | 5.4377 | 1587.26 |
|Total | 2995.26 | 10.9645 | 3364.12 |
The test group is increasing editing and reducing errors. The
control group is decreasing editing and also reducing errors at a [-10-]
rate equal to the test group's. One would suspect that increased
editing leads to lower errors and that decreased editing leads to
increased errors. Cooperation among students, thus a mixing of test
and control groups, can explain some error reductions by the control
group, but surely that could not fully compensate for real editing
being done by the test group. It seems that differing mechanisms
are at work that bring down error rates by assignment three. The
question is how the control group manages to reduce errors.
While the fields of EFL and ESL present numerous pedagogical
theories, the lack of actual information concerning cognition and
operation of learning strategies makes it difficult to advance
teaching techniques (Holland et al., 1993). Real teachers work in
the real world and are confronted with real students. More detailed
information gathered about what is actually going on with students'
learning strategies (in this case writing strategies) means better
teaching and increased learning. Such information is vital to the
development of CALL since programs must be modeled on some
underlying assumptions. This study has been able to begin to
quantify different strategies brought about simply through
differences in computer generated error feedback.
By exposing students to the existence of specific errors, they
are able to reduce their own errors even though they have not
received personalized and accurate feedback on their own writing.
Simultaneously, receiving personalized and accurate feedback
encourages students to reduce a wider range of error types and to
increase editing activity in their writing. Such activity does
support the concept that a student's writing is a work in progress.
Students receiving the personalized feedback appeared to review and
changed their documents more. This increase in writing modification
might have the drawback of actually introducing errors, thus
resulting in the equal error rates of the test and control groups.
As the data show, the test group was not able to lower spelling
errors as much as the control group, while the test group even
increased capitalization and possessive errors. Students who do not
see their own specific errors, but are aware of the errors
commonly found in classmates' writings, may take a preventative
approach to errors. Control group students may be using resource
material more, copying examples, or simply taking measures such as
avoiding the common errors like spelling by using dictionaries
before typing into the computer. Test group students may also use
these strategies; however, their increased editing introduces new
Clearly, the very presence of feedback raises all students'
awareness and increases behaviors that reduce errors. Previous
studies with isolated control groups receiving no computer feedback
showed that students reduced their errors at a much slower rate than
those receiving the feedback. One can conclude that Taiwanese
students are slow to implement any strategies to improve their
English writing and reduce errors when no specific feedback is
available, an assertion that is confirmed by other teachers'
observations (Levy and Garton, 1994; Liou, 1993).
The process writing class does offer some types of motivation,
mostly in the form of guidance through the different stages and
steps of creating a composition. Difficulties with such a process
in the EFL setting become evident in large classes with unmotivated
students. What is a teacher to do when the majority of his/her
students move through the many stages of writing, only to end up
with documents that show little or no improvement over a semester?
This study has shown that with no other input from the teacher,
students decrease errors in the presence of error feedback, and
increase editing behavior when individualized feedback is provided.
Future Directions: Investigating Issues of Quality
A further topic of interest is much more difficult to quantify,
the issue of writing quality from a holistic perspective. Liou
(1992) used teachers who were native English speakers to
holistically review writing from CALL and non-CALL groups and found
that the CALL group performed somewhat better. My own informal
observations also find students using CALL do have better content
and structure, although it seems to me that such things are mostly
influenced by the teacher, as Hyland (1993) and Pennington (1991)
pointed out in their own CALL research. Quantifying this on a large
scale presents many difficulties, which explains why it has not been
widely attempted. [-12]
Bolt, P. (1992). An evaluation of grammar-checking programs as
self- help learning aids for learners of English as a foreign
language.Computer Assisted Language Learning, 5(1-2) 49-91.
Brehony, T., & Ryan, K. (1994). Francophone stylistic grammar
checking (FSGC) using link grammars.Computer Assisted
Language Learning, 7(3) 257-269.
Brock, M. N. (1990). Customizing a computerized text analyzer
for ESL writers: Cost versus gain.CALICO Journal, 8 51-60.
Dalgish, G. (1991). Computer-assisted error analysis and
courseware design: Applications for ESL in the Swedish context.
CALICO Journal, 9(2) 39-56.
Garton, J., & Levy, M. (1994). A CALL model for a writing
advisor.CAELL Journal, 4(4) 15-20.
Healey, D. (1992). Where's the beef? Grammar practice with
computers.CAELL Journal, 3(1) 10-16.
Holland, V.M., Maisano, R., Alderks, C., & Martin, J. (1993).
Parsers in tutors: What are they good for?CALICO, 11(1)
Hutchinson, T., & Waters, A. (1987).English for specific
purposes: A learner centered approach Cambridge, UK:
Cambridge University Press.
Hyland, K. (1993). ESL computer writers: What can we do to
help?System, 21(1) 21-30.
Levy, M., & Garton, J. (1994). Adapting a grammar checker for
learner writers.ReCALL, 6(2), November 3-8.
Liao, Chao-chih (1990).A needs analysis for improving
instruction of business English in Taiwan Taipei: The Crane
Liou, H. (1991). Development of an English grammar checker a
progress report.CALICO Journal 9(2) 57-70. [-13-]
Liou, H. (1992). An automatic text-analysis project for EFL
writing revision.System, 20(4) 481-492.
Liou, H. (1993). Integrating text-analysis programs into
classroom writing revision.CAELL Journal, 4(1) 21-27.
Liou, H. (1994). Practical considerations for multimedia
courseware development: an EFL IVD experience.CALICO Journal
Okoye, I. (1994). Teaching technical communication in large
classes.English for Specific Purposes, 13(3) 223-237.
Pennington, M. (1991). An assessment of the value of word
processing for ESL writers.City Polytechnic of Hong Kong
research report, No. 7
Tsui, C. (1992). English business communication skills training
needs of non-native English-speaking managers: a case in
Taiwan.The Bulletin of the Association of Business
Communication, 55(1) 40-41.
Warden, C. (1995). Expert system impact on writing errors in
Taiwanese business English classes.CAELL Journal, 6(2)
Warden, C., and Chen, J. (1995). Improving feedback while
decreasing teacher burden in R.O.C. ESL business English
writing classes, In: Bruthiaux, P., Boswood, T., & Du-Babcock,
B. (Eds.), Explorations in English for professional
communications (pp.125-137). Hong Kong: City University of
Yao, Y., and Warden, C. (1996). Process writing and computer
correction: Happy wedding or shotgun marriage?CALL Electronic
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Return to Table 1
Explanation of error types found in this study.
Note: These error types are based on the error definitions from
the software package Grammatik 5.0 for Windows. However, for this
study, the rule base was modified and in some places heavily
extended (as in the case of custom errors which was programmed to
include common errors of Chinese EFL learner). (Grammatik5 User's
Guide, 1992, Reference Software International)
Abbreviation Abbreviations follow rules, such as the use of
periods and commas before and after the abbreviations.
Additionally, in more formal writing, such as business
communication, abbreviations should be avoided and all words written
out to assure better understanding on the part of the reader. e.g.,
Mr. Smith Ph.D. can't come next week.
Adjective Incorrect adjective used to modify noun or pronoun.
e.g., This is an interested story.
Adverb An adjective was used to modify a verb instead of an
adverb. e.g., She certain is smart, but she is also stubborn.
Archaic The use of words that are out of date or not in common
use. e.g., We can all go, albeit we must go separately.
Article Incorrect use of: a, an and the. Many words require the
use of an article preceding them; Chinese EFL students often forget
articles or use them incorrectly. e.g., A teachers had already
distributed the tests to the class. e.g., The student claimed it was
a honest mistake. e.g., We sell our products in North American
Capitalization Letters at the beginning of a sentence and the
personal pronoun 'I' are checked for correct capitalization. e.g.,
THere was a book on the bed. e.g., Tomorrow, i want to visit Bill.
Clause Subject and verb must together form a complete thought.
A dependent clause that is not a complete thought must begin with a
subordinating conjunction. e.g., James went to the tennis match.
Even though it was raining.
Colloquial Colloquial phrases are often used in spoken English
but are not appropriate in business writing. e.g., The director will
make a decision when he is good and ready.[-15-]
Comma Splice Two or more independent clauses, or complete
thoughts, are joined by only a comma. e.g., He smokes when he is
working overtime, it keeps him awake.
Comparative/Superlative The incorrect use of comparatives like
'more' and 'most.' e.g., It would be even more better if we all
Conjunction A conjunction is used as a coordinating or a
subordinating conjunction. e.g., We had to choose between English or
Custom These errors are the expanded data base, including
common errors of Chinese students. e.g., I have ever been to
America. e.g., Go in and open the light. e.g., I learn English every
Double Negative Two negative words together is not acceptable
in most written English e.g., There was not never any doubt that he
Ellipsis The correct usage of ellipsis between words is: ' . .
. ' and at the end of a sentence is: ' . . . .' Spaces are required
before, between and after each period. e.g., They are white, red,
Ending Preposition The use of a preposition at the end of a
sentence should be avoided. e.g., He moved to an office near the
people he works with.
Incomplete Sentence Usually, a sentence needs a subject and a
verb; this error is when one of those is missing. e.g., Our
wonderful president who devoted many years of service.
Incorrect Verb Form The incorrect form of the verb e.g., I will
bought it next week.
Infinitive The incorrect use of the present tense of a verb in
its infinitive form. e.g., I hope graduate in June.
Jargon Jargon is not known to a general audience and should be
avoided when possible. This error often occurs when the writer uses
an electronic dictionary for a translation from Chinese to English.
e.g., Let us interface next week over lunch.
Long Sentence Sentences longer than that specified amount in
the software (often set at 30). Shorter sentences are easier to
understand and have less chance of containing errors. e.g., There
are tables for scuba divers showing how fast a diver may ascend
safely, but these tables make the assumption that the diver [-16-]
descends, remains at the same depth for some time, and then comes to
the surface, which is not necessarily so.
Noun Phrase Words missing from a phrase or a number
disagreement with the phrase. e.g., He drove motorcycle. e.g., I
purchased nine magazines and book.
Number Usage Numbers should be spelled out when: smaller than
11 or at the beginning of a sentence. Numbers that are degrees,
percentages, times, dates, page numbers, money, should be written as
Arabic numerals. e.g., 5 years are required to graduate. e.g., It is
made of one hundred percent cotton.
Overstated Wordy sentences that are vague and difficult to
understand. e.g., At the conclusion of the meeting, everyone in
attendance departed for their homes.
Possessive Form Possessives are words that show ownership,
usually of a thing. Possessives are often followed by a noun. It is
often the case that if a plural noun is followed by another noun,
the plural noun should be a possessive. e.g., The secretarys desk
was covered with work.
Preposition Normal usage dictates which prepositions are used
with which words or phrases. Although a preposition may appear to
follow all grammatical rules, if it is not normally used then it
should be revised. e.g., Everyone in our office must comply
to the new regulations.
Pronoun Case Incorrect use of pronouns when being used as
subjects or objects in the sentence. Also found in this group are
incorrectly used possessive pronouns. e.g., Everyone has their own
goal. e.g., The television is for you and I.
Pronoun Number Pronouns take the place of nouns in a sentence.
They must agree in number with any verbs in the sentence. e.g., This
error is caused when the number of the verb and pronoun are not in
agreement. e.g., They was going to the fair
Punctuation Common punctuation errors such as commas and
semicolons as well as incorrect use of spaces before and after
punctuation (a very common error for Chinese EFL students). e.g.,
While most would agree Chinese is a difficult language to learn, it
is useful if you want to do business in Asia.
Redundant Words that repeat the same meaning, e.g., raise up,
past history, cash money. e.g., Once you use a computer, you will
never revert back to using a typewriter.
Relative Pronoun Relative pronouns introduce restrictive and
non-restrictive clauses (which, that, who). This error is the [-17-]
incorrect use of the relative pronoun. e.g., Her green coat, that
she bought in February, has a tear.
Repeated Words Or Punctuation This error is most often caused
by typing error. Punctuation, in English, does not repeat. One
period at the end of a sentence is always enough. e.g., We all like
to travel to to Canada, South America, the United States, etc..
Run-on Sentence A run-on sentence is simply too long or is
actually two sentences together. The overuse of commas or
conjunctions causes this error. As a general rule, shorter sentences
are easier to understand. e.g., My name is Chaur-Sheng Jan, I went
to the National Tax Bureau, which is in Jang-Huah County, and had an
internship during my summer vacation.
Sentence Variety Starting many sentences with the same words or
structures gives a bad impression. Change some sentences so that the
sentences do not seem monotone. e.g., I would like you to ship
before June 20. I could open a letter of credit in your favor within
the week. I will wait for your decision.
Similar Words Some words are often used wrong because they have
the similar spellings or sounds to other words. e.g., We got the
book form her mother. e.g., The words sited are from Shakespeare.
Spelling Spelling or typing errors are easy to correct, yet
make an important impression on the reader. e.g., The acter, who is
a techer, had the leading part
Split Infinitive A word, phrase or clause that comes between
the infinitive 'to' and the verb. Avoid the split infinitive
structure because it makes the main idea harder to understand. e.g.,
Steve wants to quickly finish this project.
Split Words As English changes, words often merge together,
e.g., basketball. A modern dictionary will help to avoid splitting
words that belong together. e.g., The quality of this product is out
Subject/Verb Agreement Verbs must agree with their subjects in
voice and number. e.g., The overcoat in the market are very heavy.
e.g., My mother always encourage me.
Tense Shift A change in the verb tense, in one sentence, that
makes the sentence difficult to understand. e.g., As long as a
person could concentrate his attention, he will be successful in
whatever he did.
Trademark Trademarks often follow unconventional
capitalization. The writer should make sure of the specific [-18-]
capitalization, such as: WordPerfect, Band-Aid, etc. e.g., He bought
some scotch tape while listening to a walkman.
Vague Adverb Vague adverbs are commonly used in spoken English
but make written English weak. Words such as: for example, awfully,
pretty, really, kind of, etc., all hurt formal writing. e.g., He
found her speech pretty interesting.
Verb Object A verb object is a noun or pronoun that comes after
a transitive verb. An error occurs when the object of a verb is
missing. e.g., She fixed up.
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