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Weningtyas Parama Iswari
Mulawarman University
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An Investigation of Teaching English Grammar through Distance Learning at SMAN 1 Samarinda Agitha Martha Laura; Weningtyas Parama Iswari; Maria Teodora Ping
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.v1i1.858

Abstract

The purposes of this study were to know how the teacher teaches English grammar through distance learning and investigate the problems during implementation of teaching English grammar through distance learning. The design of this study was qualitative research design which was characterized by a case study. The participant was selected through purposive sampling. The data were analyzed by using the interactive analysis model. The researcher used the triangulation by data source, triangulation by method, and triangulation by theory to check the validity and reliability of this study. The findings revealed that the English teacher applied teaching grammar in context, inductive and deductive approach and integrated grammar with language skills. In addition, the English teacher used flipped-classroom model a form of blended learning that combines synchronous and asynchronous online learning with WhatsApp, Google Meet, and Google Classroom as the teaching platforms. In its implementation, the English teacher faced some problems in the process of teaching English grammar through distance learning. Those problems were student discipline, limited time, teacher’s extra workload, distance between teacher and students, classroom management and technical problem. In conclusion, teaching English Grammar through distance learning can be conducted and maximized by having well preparation on learning activities, well communication and collaboration between the teacher and students in teaching ang learning process to achieve the learning objectives.
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.
Co-Authors Adrianto Ramadhan Agitha Martha Laura Asih, Yuni Utami Bibit Suhatmady Dynda Anastasya Ida Wardani Maria Teodora Ping, Maria Teodora Wahyu Setyo Prihandono