Introducing artificial intelligence (AI)-based digital writing assistants for teachers in writing scientific articles

Samsul Khabib

doi:10.12928/tefl.v1i2.249

Authors

Samsul Khabib Universitas PGRI Adi Buana Surabaya https://orcid.org/0000-0001-5370-2645

DOI:

https://doi.org/10.12928/tefl.v1i2.249

Keywords:

Artificial intelligence, Digital writing assistant, writing, Scientific article

Abstract

Artificial intelligence (AI) technologies have played essential roles in the development of teachers. In recent years, AI-based digital writing assistants have received increasing attention among teachers. Thus, this study aims to know the use of AI-based digital writing assistants to help teachers write scientific articles. It used a sequential explanatory mixed methods study to gain the research data. Descriptive analysis was completed for the quantitative data, and thematic analysis was used for the qualitative data. The instrument used was surveys, consisting of pre and post-survey. Interestingly, the pre-survey found that teachers are not very familiar with digital writing assistants. Some of the participants had no prior knowledge of AI-assisted writing tools, while others only had limited experience. This means that more people need to be aware of the potential that AI offers in facilitating scientific writing. Furthermore, it is essential to teach teachers how to use this technology, as it can help them save time and effort while they write their articles. The post-survey conducted at the end of the project found that teachers found the process of writing a scientific article to be easier and more enjoyable with the help of AI. The results suggest that AI-based digital writing assistants may be able to provide an alternative method for teachers to compose their scientific articles. This tool could help to reduce errors and enable more efficient writing with greater accuracy. Additionally, the feedback suggests that AI-based tools could aid in improving students’ engagement and interest in writing.

References

Anantrasirichai, N., & Bull, D. (2022). Artificial intelligence in the creative industries: A review. In Artificial Intelligence Review (Vol. 55, Issue 1). Springer Netherlands. https://doi.org/10.1007/s10462-021-10039-7

Barrot, J. S. (2020). Integrating technology into ESL/EFL writing through Grammarly. RELC Journal. https://doi.org/10.1177/0033688220966632

Bautista, R. M., & Pentang, J. T. (2022). Ctrl C + Ctrl V: Plagiarism and knowledge on referencing and citation among pre-service teachers. International Journal of Multidisciplinary: Applied Business and Education Research, 3(2), 245-257. https://doi.org/10.11594/ijmaber.03.02.10

Chen, X., Xie, H., & Hwang, G.-J. (2020). A multi-perspective study on artificial intelligence in education: Grants, conferences, journals, software tools, institutions, and researchers. Computers and Education: Artificial Intelligence, 1, 100005. https://doi.org/10.1016/j.caeai.2020.100005

Cheng, M., Taylor, J., Williams, J., & Tong, K. (2016). Student satisfaction and perceptions of quality: Testing the linkages for PhD students. Higher Education Research & Development, 35(6), 1153–1166. https://doi.org/10.1080/07294360.2016.1160873

Crusan, D., Plakans, L., & Gebril, A. (2016). Writing assessment literacy: Surveying second language teachers’ knowledge, beliefs, and practices. Assessing Writing, 28, 43–56. https://doi.org/10.1016/j.asw.2016.03.001

Dale, R. (2020). Natural language generation: The commercial state of the art in 2020. Natural Language Engineering, 26(4), 481–487. https://doi.org/10.1017/S135132492000025X

Dargan, S., Kumar, M., Ayyagari, M. R., & Kumar, G. (2020). A survey of deep learning and its applications: A new paradigm to machine learning. Archives of Computational Methods in Engineering, 27(4), 1071–1092. https://doi.org/10.1007/s11831-019-09344-w

Egecioglu, D. E., & Chanfreau, G. (2011). Proofreading and spellchecking: A two-tier strategy for pre-mRNA splicing quality control. Rna, 17(3), 383–389. https://doi.org/10.1261/rna.2454711

G.J. Hwang, H. Xie, B.W. Wah, D. Gasevic. (2020). Vision, challenges, roles and research issues of artificial intelligence in education Comput Educ : Artificial Intelligence, 1, 10.1016/j.caeai.2020.100001

Hammad, M. (2022). Publishing a 100% original paper without any plagiarism. Ann Biomed Eng 50, 1017. https://doi.org/10.1007/s10439-022-03031-x

Haustein, S., Peters, I., Bar-Ilan, J., Priem, J., Shema, H., & Terliesner, J. (2014). Coverage and adoption of altmetrics sources in the bibliometric community. Scientometrics, 101(2), 1145–1163. https://doi.org/10.1007/s11192-013-1221-3

Hirvela, A., & Du, Q. (2013). “ Why am I paraphrasing?”: Undergraduate ESL writers’ engagement with source-based academic writing and reading. Journal of English for Academic Purposes, 12(2), 87–98. https://doi.org/10.1016/j.jeap.2012.11.005

Kim, T. (2011). Building student proficiency with scientific literature using the Zotero reference manager platform. Biochemistry and Molecular Biology Education, 39(6), 412–415. https://doi.org/10.1002/bmb.20551

Koltovskaia, S. (2020). Student engagement with automated written corrective feedback (AWCF) provided by Grammarly: A multiple case study. Assessing Writing, 44(September 2019), 100450. https://doi.org/10.1016/j.asw.2020.100450

Liu, G-Z, Lu, H-C, Lin, V, Hsu, W-C. Cultivating undergraduates' plagiarism avoidance knowledge and skills with an online tutorial system. J Comput Assist Learn. 2018; 34: 150– 161. https://doi.org/10.1111/jcal.12223

Nassaji, H. (2012). The relationship between SLA research and language pedagogy: Teachers’ perspectives. Language Teaching Research, 16(3), 337–365. https://doi.org/10.1177/1362168812436903

Nath, R., & Sahu, V. (2020). The problem of machine ethics in artificial intelligence. AI and Society, 35(1), 103–111. https://doi.org/10.1007/s00146-017-0768-6

Noom-Ura, S. (2013). English-teaching problems in Thailand and Thai teachers’ professional development needs. English Language Teaching, 6(11), 139–147. https://doi.org/10.5539/elt.v6n11p139

Poch, A., Hamby, M., & Chen, X. (2020). Secondary teachers’ beliefs about teaching writing to typically achieving and struggling adolescent writers. Reading and Writing Quarterly, 36(6), 497–520. https://doi.org/10.1080/10573569.2019.1666759

Prentice, F. M., & Kinden, C. E. (2018). Paraphrasing tools, language translation tools and plagiarism: An exploratory study. International Journal for Educational Integrity, 14(1), 1–16. https://doi.org/10.1007/s40979-018-0036-7

Sun, Y. C., & Yang, F. Y. (2015). Uncovering published authors’ text-borrowing practices: Paraphrasing strategies, sources, and self-plagiarism. Journal of English for Academic Purposes, 20, 224–236. https://doi.org/10.1016/j.jeap.2015.05.003

Thi, N. K., & Nikolov, M. (2021). How teacher and Grammarly feedback complement one another in Myanmar EFL students’ Writing. Asia-Pacific Education Researcher, 31(6), 767–779. https://doi.org/10.1007/s40299-021-00625-2

Wrigley, S. (2019). Avoiding ‘de-plagiarism’: Exploring the affordances of handwriting in the essay-writing process. Active Learning in Higher Education, 20(2), 167–179. https://doi.org/10.1177/1469787417735611

Writecream. (2022). HypeWrite AI review: Is this tool worth it in 2022? July. https://www.writecream.com/hypewrite-ai-is-this-tool-worth-it/

Zippe, I. (2022). I tried an AI writing tool, and here’s how it went. June. https://ingridzippe.medium.com/i-tried-an-ai-writing-tool-and-heres-how-it-went-6337c560be27