Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Educational Studies: Conference Series

Plagiarism Awareness and Academic Writing Ability: The Relationship with the EFL Students' Plagiarism Practice Maulidya Namira; Maria Ping; Bibit Suhatmady
Educational Studies: Conference Series Vol 1 No 1 (2021)
Publisher : Faculty of Teacher Training and Education, Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/escs.v1i1.867

Abstract

Plagiarism is considered as the writing difficulty and has been a topic among researchers in the past ten years. Many studies explored plagiarism perceptions and the reasons behind plagiarism. Some studies also attempted to find an association between the elements that might contribute to plagiarism such as writing skills, language level, studying behavior, etc. However, most of the studies does not include the plagiarism rate or similarity index as one of the research variables. To fill this gap, this study aimed to find out whether there is any relationship between plagiarism awareness and academic writing ability towards the students’ actual plagiarism practice. The 30 respondents are students of the English Department in Mulawarman University who has written an academic paper namely a Mini research proposal. This study design is quantitative-correlational design with a Multiple regression data analysis technique. The study three main findings are; (1) there is no significant relationship between plagiarism awareness and plagiarism rate; (2) there is a significant negative relationship between academic writing ability and plagiarism rate; and (3) there is a simultaneous relationship between plagiarism awareness and academic writing ability with plagiarism rate. Additionally, academic writing ability has more influence on plagiarism rate than plagiarism awareness.
Investigating Gender Differences in Senior High School Students’ Motivation to Learn English Online During The COVID-19 Pandemic Wahyu Setyo Prihandono; Bibit Suhatmady; Weningtyas Parama Iswari
Educational Studies: Conference Series Vol 1 No 1 (2021)
Publisher : Faculty of Teacher Training and Education, Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/escs.v1i1.880

Abstract

A lot of research has been conducted to examine the effect of gender differences on language learning motivation in various learning environment, yet the outcomes remain contradictory. This study investigates gender differences in 568 Indonesian senior high school students’ motivation to learn English online during the COVID-19 pandemic. In this quantitative enquiry, the data were collected using a motivational questionnaire containing a number of items indicating motivational components. One-way MANOVA was performed to examine not only the students’ overall motivation, but also the effect of gender differences on three motivational variables, namely instrumental orientation, self-efficacy beliefs, and self-regulation. The findings revealed that the students’ overall motivation differs by gender. Furthermore, it was indicated that, in general, female students possessed higher levels of motivation than male students in learning English online. The results support the growing stereotype claiming that female learners tend to outperform their male peers in language learning. The analyses on the motivational variables indicated that female students had higher level of instrumental orientation and they were more self-regulated compared to male students. In terms of their self-efficacy beliefs, no significant differences detected between male and female students in learning English online during the COVID-19 pandemic.
Using Concordance Software to Generate Academic Words in Applied Linguistics Weningtyas Parama Iswari; Bibit Suhatmady; Yuni Utami Asih; Ida Wardani; Adrianto Ramadhan; Dynda Anastasya
Educational Studies: Conference Series Vol 1 No 1 (2021)
Publisher : Faculty of Teacher Training and Education, Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/escs.v1i1.882

Abstract

Academic words include words that are not commonly encountered in formal circumstances and specific to particular fields of study. Undergraduate students of the English Department are required to acquire academic words in applied linguistics for academic reading and writing research articles. This paper reports on generating the academic word list for the students of the English Department by using AntConc, a concordance software application. In this study, corpus linguistic research was adopted, in particular the corpus-based analysis category. Data were gathered from approximately one thousand credible Applied Linguistics journal articles published from 2008 to 2021. AntConc software played a significant role in processing these data to get the intended corpus, which was then classified and categorized based on the frequency of occurrences. The results include an academic word list and its word family. These clusters of academic words are intended for undergraduate students of the English Department in the first up to fourth academic semesters to prepare them to participate in international academic discourse, such as writing and publishing research articles. This list can also be used as a basis for further research related to academic vocabulary. Academic words include words that are not commonly encountered in formal circumstances and specific to particular fields of study. Undergraduate students of the English Department are required to acquire academic words in applied linguistics for academic reading and writing research articles. This paper reports on generating the academic word list for the students of the English Department by using AntConc, a concordance software application. In this study, corpus linguistic research was adopted, in particular the corpus-based analysis category. Data were gathered from approximately one thousand credible Applied Linguistics journal articles published from 2008 to 2021. AntConc software played a significant role in processing these data to get the intended corpus, which was then classified and categorized based on the frequency of occurrences. The results include an academic word list and its word family. These clusters of academic words are intended for undergraduate students of the English Department in the first up to fourth academic semesters to prepare them to participate in international academic discourse, such as writing and publishing research articles. This list can also be used as a basis for further research related to academic vocabulary.