AI-Based Teaching Using Bing Image Creator (AI Art Generator): Teaching English Writing a Descriptive Text Illustrated by 3D Animation Design Style

Tira Nur Fitria

doi:10.29040/ijcis.v6i4.255

AI-Based Teaching Using Bing Image Creator (AI Art Generator): Teaching English Writing a Descriptive Text Illustrated by 3D Animation Design Style

Tira Nur Fitria

Abstract

Recently, posters or images with designs similar to Disney Pixar have been circulating on various social media platforms, such as Instagram and TikTok. With a design that is quite adorable, it is no wonder that the image design created using artificial intelligence (AI) has attracted the attention of people. Seeing the popularity of posters via Bing Image Creator, people can try to create character descriptions according to their favourite cartoons/ animations, such as Disney, via Bing Image Creator. This research simulated the use of Bing Image Creator to teach writing an English descriptive text to be illustrated into an animation or a cartoon. The analysis shows that the Bing Image Creator AI application is currently entertaining to create/produce the images they want without having design or drawing skills. This research is descriptive qualitative research. Teachers/lecturers can ask students to visit or access Bing Image Creator at https://www.bing.com/create. Students need to have a Microsoft account, but if they do not have one, they can create an account first. They sign in using a Microsoft account. After logging in, type the character description into the column provided. They can enter character descriptions as desired. To create a Disney AI cartoon, students can add the words "Disney Pixar style" to the beginning of the character description. They can create more specific commands to turn photos into Disney cartoons. The order may include descriptions such as 1) gender, male or female. 2) character shape, such as face shape, eyes, jaw, nose, cheeks, hair, clothes, position of body parts, and others. 2) certain poses/styles and accessories used. 3) objects worn on body parts, for example, types of clothing, colors, motifs/patterns. 4) objects used or around 5) expression, facial expression, or feeling. 6) activities carried out. 7) shooting angle. 8) surrounding background. To get accurate animated image results, students can write detailed and specific descriptions. Finally, wait for the image to finish and download it. Further research still needs to be carried out to determine students' perceptions of the use of Binh Image Creator in illustrating their written character descriptions of a desired cartoon.
Keywords: AI-based teaching, Bing Image Creator, teaching writing, descriptive text,

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References

Adru, S. L., Johnson, S., & Hemalatha, M. (2023). AI and Blockchain-Based Platform for Empowering Content Creators: Enabling NFT – Driven Content Sharing, Inspiration Generation, and Collaborative Interaction. 2023 4th International Conference on Smart Electronics and Communication (ICOSEC), 666–673. https://doi.org/10.1109/ICOSEC58147.2023.10276305

Agnese, J., Herrera, J., Tao, H., & Zhu, X. (2020). A survey and taxonomy of adversarial neural networks for text-to-image synthesis. WIREs Data Mining and Knowledge Discovery, 10(4), e1345. https://doi.org/10.1002/widm.1345

Anna, N. E. V., Novian, R. M., & Ismail, N. (2023). Enhancing virtual instruction: Leveraging AI applications for success. Library Hi Tech News, ahead-of-print(ahead-of-print). https://doi.org/10.1108/LHTN-09-2023-0175

Ary, D., Jacobs, L. C., Irvine, C. K. S., & Walker, D. (2018). Introduction to Research in Education. Cengage Learning.

Attard-Frost, B. (2023). Generative AI Systems: Impacts on Artists & Creators and Related Gaps in the Artificial Intelligence and Data Act (SSRN Scholarly Paper No. 4468637). https://doi.org/10.2139/ssrn.4468637

Bankar, S. A., & Ket, S. (2021, May 25). An Analysis of Text-to-Image Synthesis. Proceedings of the International Conference on Smart Data Intelligence (ICSMDI 2021). https://doi.org/10.2139/ssrn.3852950

Bellaiche, L., Shahi, R., Turpin, M. H., Ragnhildstveit, A., Sprockett, S., Barr, N., Christensen, A., & Seli, P. (2023). Humans versus AI: Whether and why we prefer human-created compared to AI-created artwork. Cognitive Research: Principles and Implications, 8(1), 42. https://doi.org/10.1186/s41235-023-00499-6

Biddix, J. P. (2018). Research Methods and Applications for Student Affairs. John Wiley & Sons.

Chesher, C., & Albarrán-Torres, C. (2023). The emergence of autolography: The ‘magical’ invocation of images from text through AI. Media International Australia, 189(1), 57–73. https://doi.org/10.1177/1329878X231193252

Darmawan, A. J., Yoo, P. M. H., & Hartawan, R. A. (2024). Teknik Prompt ANVS Progresif untuk Bing Image Creator dan Interpretasi Kesenjangan Gambar AI. Visualita: Jurnal Online Desain Komunikasi Visual, 13(1), 112–130. https://doi.org/10.34010/visualita.v13i1.13967

Drianto, L. A., Valentino, M. N., Wibowo, S. I., & Setiawan, S. B. (2023). Inovasi Teknologi Kecerdasan Komputer. SIEGA Publisher.

Enjellina, Beyan, E. V. P., & Rossy, A. G. C. (2023). A Review of AI Image Generator: Influences, Challenges, and Future Prospects for Architectural Field. Journal of Artificial Intelligence in Architecture, 2(1), 53–65. https://doi.org/10.24002/jarina.v2i1.6662

Fitria, T. N. (2021). The Use Technology Based on Artificial Intelligence in English Teaching and Learning. ELT Echo : The Journal of English Language Teaching in Foreign Language Context, 6(2), 213–223. https://doi.org/10.24235/eltecho.v6i2.9299

Fitria, T. N. (2023). Artificial intelligence (AI) technology in OpenAI ChatGPT application: A review of ChatGPT in writing English essay. ELT Forum: Journal of English Language Teaching, 12(1), 44–58. https://doi.org/10.15294/elt.v12i1.64069

Hanafy, N. O. (2023). Artificial intelligence’s effects on design process creativity: “A study on used A.I. Text-to-Image in architecture.” Journal of Building Engineering, 80, 107999. https://doi.org/10.1016/j.jobe.2023.107999

Kim, D., Joo, D., & Kim, J. (2020). TiVGAN: Text to Image to Video Generation With Step-by-Step Evolutionary Generator. IEEE Access, 8, 153113–153122. https://doi.org/10.1109/ACCESS.2020.3017881

Kompas, C. M. (2023, November 2). 10 Contoh Deskripsi Bing Image Creator untuk Membuat Poster Disney AI yang Viral Halaman all. KOMPAS.com. https://tekno.kompas.com/read/2023/11/01/16150087/10-contoh-deskripsi-bing-image-creator-untuk-membuat-poster-disney-ai-yang

Lakomy, M. (2023). Artificial Intelligence as a Terrorism Enabler? Understanding the Potential Impact of Chatbots and Image Generators on Online Terrorist Activities. Studies in Conflict & Terrorism, 0(0), 1–21. https://doi.org/10.1080/1057610X.2023.2259195

Lee, Y.-H., & Chiu, C.-Y. (2023). The Impact of AI Text-to-Image Generator on Product Styling Design. In H. Mori & Y. Asahi (Eds.), Human Interface and the Management of Information (pp. 502–515). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-35132-7_38

Liu, V., Vermeulen, J., Fitzmaurice, G., & Matejka, J. (2023). 3DALL-E: Integrating Text-to-Image AI in 3D Design Workflows. Proceedings of the 2023 ACM Designing Interactive Systems Conference, 1955–1977. https://doi.org/10.1145/3563657.3596098

Miles, M. B., Huberman, A. M., & Saldana, J. (2018). Qualitative Data Analysis: A Methods Sourcebook. SAGE Publications.

Mori, H., & Asahi, Y. (2023, July 8). Human Interface and the Management of Information. HCI International Conference, Copenhagen, Denmark.

Narayanaswamy, A. (2024). Working with Image Creator. In A. Narayanaswamy (Ed.), Microsoft Copilot for Windows 11: Understanding the AI-Powered Features in Windows 11 (pp. 149–161). Apress. https://doi.org/10.1007/979-8-8688-0583-7_8

Oppenlaender, J. (2022). The Creativity of Text-to-Image Generation. Proceedings of the 25th International Academic Mindtrek Conference, 192–202. https://doi.org/10.1145/3569219.3569352

Pakniany, Y., Latue, P. C., & Rakusa, H. (2023). Utilization of Bing Image Creator to Design Learning Media with the Theme of Natural Disasters in the Form of Artificial Intelligence-Based Animation. Journal Education Innovation (JEI), 1(1), 87–97. https://jurnal.ypkpasid.org/index.php/jei/article/view/28

Primasari, D., Kamilah, N., Hermawan, E., Riana, F., Laxmi, G. F., Yanuarsyah, I., Hadjimartsu, S. A., & Eosina, P. (2025). Artificial Intelligence Application Usage Training: ChatGPT, Gamma, and Bing Image Creator In SMK Taman Siswa Bogor Students. Jurnal Pengabdian Masyarakat Inovatif, 3(1), 30–38.

Qiao, H., Liu, V., & Chilton, L. (2022). Initial Images: Using Image Prompts to Improve Subject Representation in Multimodal AI Generated Art. Proceedings of the 14th Conference on Creativity and Cognition, 15–28. https://doi.org/10.1145/3527927.3532792

Rahayu, R. A. S., & Santoso, H. (2023). Analisis Gambar Wajah Palsu: Mendeteksi Keaslian Gambar Yang Dimanipulasi Menggunakan Metode Variational Autoencoder Dan Forensics Deep Neural Network. SIBATIK JOURNAL: Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, Dan Pendidikan, 2(9), 2701–2726. https://doi.org/10.54443/sibatik.v2i9.1312

Sandoval-Martin, T., & Martínez-Sanzo, E. (2024). Perpetuation of Gender Bias in Visual Representation of Professions in the Generative AI Tools DALL·E and Bing Image Creator. Social Sciences, 13(5), 250. https://doi.org/10.3390/socsci13050250

Saroh, S., & Nurhamidah, D. (2024). Kolaborasi Classcraft dan Bing Image Creator (AI) Sebagai Media Pembelajaran Bahasa Indonesia. Jurnal Metamorfosa, 12(2), 126–139. https://doi.org/10.46244/metamorfosa.v12i2.2437

Suryadevara, C. K. (2020). Generating Free Images with Openai’s Generative Models. International Journal of Innovations in Engineering Research and Technology, 7(3), 49–56. https://repo.ijiert.org/index.php/ijiert/article/view/3653

Zhang, H., Zhu, H., Yang, S., & Li, W. (2021). DGattGAN: Cooperative Up-Sampling Based Dual Generator Attentional GAN on Text-to-Image Synthesis. IEEE Access, 9, 29584–29598. https://doi.org/10.1109/ACCESS.2021.3058674

DOI: https://doi.org/10.29040/ijcis.v6i4.255