ERROR ANALYSIS OF CONDITIONAL SENTENCES

Making mistakes when using conditional sentences is common for foreign language learners. Errors in this study are in accordance with the error classification surface strategy taxonomy, namely omission, addition, misform ation and misordering. The purposes of this study are to identify and to classify the types of error and to find the factors causing errors in the use of conditional sentences. The research method used is descriptive qualitative research method that is a case study with taxonomic analysis. Data collection techniques were carried out using test and interview. The research subject was third semester students of the English Language Education Study Program 2018/2019 of Pamane Talino College of Education in Landak Regency, West Kalimantan. The results show that 30.27% of students make omission errors, 21.11% addition errors, 34.86% misformation errors and 13.76% misordering errors. The factors that cause errors are found from the system's own target language (intralingual). The main error factors classified as intralingual errors in this study are: incomplete knowledge in verb forms, incomplete application of rules and false concept hypothesis.

An Analysis of Students’ Pronunciation Errors

This study deals with students’ pronunciation errors in English consonants. It was conducted under the consideration that pronouncing English words played an important role. A descriptive qualitative was used as the research method. The subject of this research was forty seven students of first year of English Language Education Study Program at Pamane Talino College of Education, Landak Regency, West Kalimantan. Pronunciation test and interview were used to collect data. The result reveals that the students got difficulties in pronouncing /θ/, /ð/, /ʃ/, /ʒ/, /tʃ/ and /dʒ/. Then, the factors affecting the students’ pronunciation are interference, phonological system and motivation.

AN ANALYSIS ON THE DIFFICULTIES LEVEL OF THREE ONLINE WRITTEN TEXTS

This research aims to elaborate the difficulty levels of three different texts that bring the same topic. This research is a discourse analysis which was done by analyzing the lexical density, nominalization, and the finiteness of the texts. The three texts that have been analyzed were taken online from Wikipedia and two personal blogs for English research. The results show that the first text can be taken as the most complex text for high level readers, the second text for the intermediate level readers, and the third text for the elementary or low level readers. In terms of lexical density, the first text gains very high percentage which is up to 60%, this shows that the text is the most informative of all. Whereas, the second text and the third text’s lexical density are both 50%, which indicates that there are lack of contents in them. Regarding to nominalization, the first text is still on the highest level with 12 nominalizations, the second text is on the intermediate level with 10 nominalizations, and the third text is on the lowest level, without any nominalization. The last is from the finiteness side. The first text has the lowest number of finiteness; the second text has the second highest number of finites, whereas the third text has the highest number of finites of all. This is the result of the highest number of lexical density and nominalization of the first text that decreases the frequency of sentences in it. The results of this research can be useful for online readers to decide what kind of reading materials which are suitable for their English levels.

The Effectiveness of Teachers’ Corrective Feedback in Enhancing Students’ Ability to Recount Text Writing

Most junior high school students get some difficulties in recount text writing. The purpose of this research is to explain the kind of corrective feedback that is more effective for high achievers’, for low achievers, and for mixed groups of high and low achievers in enhancing their ability in recount text writing and explain the interaction between corrective feedback, students’ prior achievement, and ability in recount text writing. The samples are eighth-graders of SMP Agus Salim. The experiment group receives direct corrective feedback while the control group receives indirect corrective feedback. And from both groups, the researcher divides again into two groups of high and low achievers. Finally, direct feedback is more effective for mixed groups of high and low achievers. The sum of means score of the experimental group is 63.75. While the total means score of the control group is 63.50. The mean score of the high achievers that received direct corrective feedback is 62.00, while the low achievers were 65.5. And from the control group, the high achiever group mean is 66.00 while the low achiever group means is 61.00. So direct corrective feedback is better used for low achievers.