Effect of Categorizing EFL Shaqra University Students' Writing Errors on Writing Improvement

This paper aims at using a strategy of categorizing EFL Shaqra University students' writing errors and identifying its effect in improving students' writing. The study hypothesized that categorizing students' errors into main headings related to the types of error, frequencies of error, examples of errors, and causes of errors will provide precise insight into the nature of students' errors. Moreover, providing students with models to read and extract the difficult vocabularies from them, understanding their meanings, and using them in their writing will improve students' writing. Hence, the researcher gave 65 female students a title to write about in lecture number one as a pre-test. The title was "women driving in Saudi Arabia", and in lecture number eleven, she gave them a post-tester in the same title after applying the hypothesized teaching strategy. The findings of students' essay analysis in the pre-test proved that students had many grammatical and lexical mistakes but in the post-test the students writing improved significantly in terms of style, diction, developing ideas, spelling, and punctuation. Even their errors decreased from 936 errors in the pre-test to 57 errors in the post-test which indicates the success of the teaching strategy adopted by the researcher. Accordingly, the researcher recommended that: firstly, instructors should categorize their students' writing errors to have a clear insight into the nature of their students' errors hence specifying much time in explaining the areas of students' weaknesses. Secondly, instructors should provide students with a well-written model to read; and then ask them to criticize those reading models. The students will learn through criticizing and imitating the style of reading models. Moreover, the instructors of Shaqraa should specify much time explaining morphology since it was the branch that the students make many errors in it.

ERROR ANALYSIS OF USING AUXILIARY VERBS IN WRITING DESCRIPTIVE TEXT

Grammar is complexity in learning English it makes many students often commit errors in learning. Making errors in writing is one of the processes for learning English .The aim of this research was to describe the students’ errors and its causes in using auxiliary verbs in the sentences. In this research, the writer limited the discussion on the error made by the students in using auxiliary verbs. The design of this research was quantitative approach in a form of descriptive analysis (percentage) that included observation, collecting the data the researcher used test as the instrument. The writer conducted the research to 31 students in first semester of English Literature in academic 2021/2022. The data were analyzed by using error analysis method. The error types were classified based on linguistic category, especially surface strategy taxonomy. The writer classified the types of error into omission, addition, misformation, and misordering. Among those four types, the most frequency error was misformation that reached 102 errors or 61.44% . the other finding was the sources of error which are divided into three categories. Those are interlingual errors, intralingual errors, and communicative strategies. Communicative strategies errors is the most common source of error, there were 45.78%

Risky calculations

Drug doses and other forms of patient treatment require detailed calculations. Calculation errors are one of the most common types of error and they could be reduced in many ways. Calculators ignore errors, and should be fixed if they are going to be used in healthcare.

Performance of gender detection tools: a comparative study of name-to-gender inference services

Objective: To evaluate the performance of gender detection tools that allow the uploading of files (e.g., Excel or CSV files) containing first names, are usable by researchers without advanced computer skills, and are at least partially free of charge.Methods: The study was conducted using four physician datasets (total number of physicians: 6,131; 50.3% female) from Switzerland, a multilingual country. Four gender detection tools met the inclusion criteria: three partially free (Gender API, NamSor, and genderize.io) and one completely free (Wiki-Gendersort). For each tool, we recorded the number of correct classifications (i.e., correct gender assigned to a name), misclassifications (i.e., wrong gender assigned to a name), and nonclassifications (i.e., no gender assigned). We computed three metrics: the proportion of misclassifications excluding nonclassifications (errorCodedWithoutNA), the proportion of nonclassifications (naCoded), and the proportion of misclassifications and nonclassifications (errorCoded).Results: The proportion of misclassifications was low for all four gender detection tools (errorCodedWithoutNA between 1.5 and 2.2%). By contrast, the proportion of unrecognized names (naCoded) varied: 0% for NamSor, 0.3% for Gender API, 4.5% for Wiki-Gendersort, and 16.4% for genderize.io. Using errorCoded, which penalizes both types of error equally, we obtained the following results: Gender API 1.8%, NamSor 2.0%, Wiki-Gendersort 6.6%, and genderize.io 17.7%.Conclusions: Gender API and NamSor were the most accurate tools. Genderize.io led to a high number of nonclassifications. Wiki-Gendersort may be a good compromise for researchers wishing to use a completely free tool. Other studies would be useful to evaluate the performance of these tools in other populations (e.g., Asian).

Error Analysis in Students’ Writing Composition

To recognize the students’ difficulties, this research analyzes errors in Students’ writing composition of Passive Voice. This study of error (error analysis) is part of an investigation of the process of English language learning. This research is to find the types of error analysis in students’ writing composition and to find the most dominant types of error analysis in students’ writing composition of passive voice. This research is qualitatively accomplished to look into errors in the second language acquisition. This research focused on the qualitative research by using document analysis to collect empirical data from the students’ writing. This method is applied to get the accurate data collection. The object of the research is students’ writing composition randomly taken from sixteen ESP students of Strata 1 – Arabic Department of STAI Ali bin Abi Thalib Surabaya. The researcher investigates more details by using surface strategy taxonomy to get the result of this error analysis. It is limited on the students’ passive sentences error in writing composition consisting of four error types: omission, addition, misformation, and misordering. Finally, after identifying the entire data and analyzing the research findings, it can be summarized that the types of passive voice errors produced by the students are (1) omission that occurred 24 times or 51,06% of all, (2) addition that occurred 15 times or 31,96% of all, (3) misordering that occurred 5 times or 10,64% of all, and (4) misformation that occurred 3 times or 6,38% of all. According to the research findings, the most dominant type of passive voice error is omission.

An Analysis Of Students’ Sentences With Inverted Subjects And Verbs Error Found In Tmi’s Toefl Preparation Class

The research is to find out the types of error analysis in students’ sentences and the most dominant types of error analysis in students’ sentences. This research uses qualitative method to look into errors in the second language acquisition and to collect empirical data. This method is applied to get the accurate data collection. The object of the research is students’ practice randomly taken from twelve advanced students of TOEFL Preparation Class – The Mushlih Institute (TMI) Surabaya. In acquiring the result of this error analysis, surface strategy taxonomy is applied to investigate more details. It is limited on the students’ sentences with inverted subjects and verbs error in their practice consisting of four error types. In summary, the types of sentences with inverted subjects and verbs errors produced by the students are (1) omission appearing 49 times or 79,03% of all, (2) addition appearing 9 times or 14,52% of all, (3) misordering appearing 3 times or 4,84% of all, and (4) misformation appearing a time or 1,61% of all. According to the research findings, the most dominant type of sentences with inverted subjects and verbs error is omission. Keywords: Error Analysis, Writing Practice, Sentences.

Analysis Grammatical Errors in Using Simple Present Tense in Writing Descriptive Text

One of the English skills which are important to be mastered by the students is writing skill. Writing is a creative and expressive process. Students need to explore their ideas and compose them into a good text. The objectives of this research are to find out types of error and the most dominant error writing using simple present tenses in a descriptive text.

Error Analysis of Using Simple Present Tense on Students’ Descriptive Text Writing

The purpose of the research is to find out the types of error which made by the ninth graders in writing descriptive text using simple present tense at SMPIT Nurul Ihsan. The number of the students is 27 students. This research uses qualitative descriptive as the approach. The researcher directly did the survey and conducted a written test to the students write English descriptive text. The result of the study shows that there are 77 errors from all students’ compositions. The most error made is misformation with the percentage 49,35%. Followed misordering with the percentage 20,78%, then addition with the percentage 18,18%, and the least error made is omission with the percentage is 11,69%. Most students made wrong sentence in misformation category. The cause of that is the interference from mother language or L1. It makes them influenced the way they think about the language they are learning. When they compose a text in English, they follow the rule of L2. Consequently, they should be guided more so that they could understand about simple present tense.

ERRORS IN CONSECUTIVE INTERPRETING: A CASE OF JESSICA KUMALAWONGSO’S COURT

This study aimed to analyze the main types of errors found in the consecutive interpreting (CI) in Jessica Kumalawongso’s trial court and to indicate its causes. The research method used is the descriptive qualitative method by means of the secondary data taken from Kompas TV, uploaded on YouTube in 2016 consisting of three videos of the justifications of Jessica's attorney, toxicologist and forensic pathologist before the interpreter in order to counter the public prosecutor in the courtroom. They were, then, classified into both the source and the target languages by analyzing their types of error leading to the finding of the main types and subtypes of errors. The result of this study is that based on Gonzales theory on the consecutive interpreting, 67 errors with six out of eight main types are found at the entire selected videos. The six main types of errors detected in the court proceedings are non-conservation of paralinguistic features, inadequate language proficiency, addition, omission, distortion and register conservation.

Evolution of Distributed Detection Performance over Balanced Binary Relay Tree Networks with Bit Errors

Target detection based on wireless sensor networks can be considered as a distributed binary hypothesis testing problem. In this paper, the evolution of detection error probability with the increase of network scale is studied for the balanced binary relay tree network with channel noise. Firstly, the iterative expressions of false-alarm probability and missed-detection probability depending on the number of tree network layers are given. Then, the iterative process of two types of error probabilities in the network space is described as a discrete nonlinear switched dynamic system, and the dynamic properties of two types of error probabilities are analyzed in a plane rectangular coordinate system. A globally attractive invariant set of the state of the dynamic system, which is not related to the channel noise, is derived. The switching mode of the system and the total error probability in the invariant set are further analyzed, and a necessary and sufficient convergence condition of the total error probability is provided. Based on this condition the following detection properties of the network are revealed: (1) as long as the channel bit error probability is not zero, the total error probability does not tend to zero with the increasing network size; (2) when the channel bit error probability is greater than 2-/3/ 2 the total error probability will continue to increase with the increase of network size.