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Ida Wardani
Mulawarman University
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Computational Thinking for Primary School Teachers: Building Problem-Solving and Literacy Skills Maria Teodora Ping; Yuni Utami Asih; Ida Wardani
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.v1i1.838

Abstract

Problem-solving is one of the skills that is crucial to equip students to face a variety of challenges in the future as well as related to the development of their lifelong literacy skills. One of the potential solutions for promoting students’ problem-solving skills is introducing Computational Thinking. However, in the context of schools in East Kalimantan, both teachers and students have not been familiar with Computational Thinking. Therefore, this current pilot study aimed at introducing Computational Thinking to teachers, especially primary school teachers, by developing a workshop and a module suitable to the local contexts and needs. This study involved 22 primary school teachers from Kutai Kartanegara Regency who had no prior knowledge and experience concerning Computational Thinking. The teachers were trained the basic concepts of CT and how to implement CT in the class especially in relation to literacy aspects. Afterwards, the teachers were assigned to develop a CT-infused lesson and did a self-reflection on the process. The findings from the post-workshop questionnaires indicated that most teachers showed positive attitudes towards CT and implementing CT in their lessons. Furthermore, they also voiced out that they would like to learn further about CT, particularly related to Literacy and the Minimum Competency Assessment (AKM).
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 Asih, Yuni Utami Bibit Suhatmady Dynda Anastasya Maria Teodora Ping, Maria Teodora Weningtyas Parama Iswari