An Analysis of Students’ Attitudes by Using Word Frequency and Word Cloud Visualization
Keywords:
word cloud, qualitative data, thai languageAbstract
This research aims to investigate the use of word frequency and word cloud visualization to analyze qualitative data in Thai, and to examine the students’ attitudes towards the training course of developing English language skills for teaching in English program, Faculty of Education, Rajabhat Rajanagarindra University. The samples in this study were the second- to the fourth-year university students in digital technology for education. These 51 participants (7 male and 44 female) were selected by using convenience sampling. The research instrument used for data collection was open-ended questionnaire asking the students’ attitudes towards participating in the training course, divided into two parts: the first part included general information, and the second part concerned feedback on the training course of developing English language skills, knowledge application of English language skills, problems, and suggestions. The data obtained from the questionnaire were prepared and analyzed by using “WordItOut”, which was compatible to Thai. The results of the study showed that word frequency and word cloud analysis could be used for Thai to summarize an overall students’ attitudes. The participants with positive attitude enjoyed learning and were aware the importance of English language for TOEIC test preparation and future careers. The students also added that the English language training should be extended longer.
References
ไทยโพสต์. (2564, 9 ธันวาคม). 'ตรีนุช' ชะลอใช้'หลักสูตรฐานสมรรถนะ'อย่างเต็มระบบ ใช้วิธีแบ่งระยะทดลองนำร่องออกเป็น 3 ปี (2565-67). ไทยโพสต์. https://www.thaipost.net/general-news/113184/
สำนักงานคณะกรรมการการศึกษาขั้นพื้นฐาน. (2564). หลักสูตรสมรรถนะ. https://cbethailand.com/about-cbe/
สำนักงานเลขาธิการสภาการศึกษา. (2562). แนวทางการพัฒนาสมรรถนะผู้เรียนระดับการศึกษาขั้นพื้นฐาน. กลุ่มมาตรฐานการศึกษา สำนักมาตรฐานการศึกษาและพัฒนาการเรียนรู้. http://backoffice.onec.go.th/uploads/Book/1727-file.pdf
Aroonmanakun, W. (2002). Word Segmentation (Version 2.03) [Computer Software]. Department of Linguistics, Faculty of Arts, Chulalongkorn University. https://www.arts.chula.ac.th/ling/resources/
Bromley, K. (2013). Using word clouds in the classroom. The Utah Journal of Literacy, 16(1), 39-41. https://utahreading.org/index.php/UJOL/article/view/7/7
Calle-Alonso, F., Cuenca-Guevara, A., de la Mata Lara, D., Sánchez-Gómez, J. M., Vega-Rodríguez, M. A., & Sánchez, C. J. P. (2018). Neurok: A Collaborative e-Learning platform based on Pedagogical Principles from Neuroscience. CSEDU, 1, 550-555. https://www.scitepress.org/Papers/2018/66489/66489.pdf
Chi, M. T., Lin, S. S., Chen, S. Y., Lin, C. H., & Lee, T. Y. (2015). Morphable word clouds for time-varying text data visualization. IEEE Transactions on Visualization and Computer Graphics, 21(12), 1415-1426. https://doi.org/10.1109/TVCG.2015.2440241
DePaolo, C. A., & Wilkinson, K. (2014). Get your head into the clouds: Using word clouds for analyzing qualitative assessment data. TechTrends, 58(3), 38-44. https://doi.org/10.1007/s11528-014-0750-9
Haruechaiyasak, C., Kongyoung, S., & Dailey, M. (2008, May). A comparative study on Thai word segmentation approaches. In Proceedings of the 5th International Conference on Electrical Engineering, Electronics, Computer, Telecommunications and Information Technology (pp. 125-128). IEEE. https://doi.org/10.1109/ECTICON.2008.4600379
Kabir, A. I., Ahmed, K., & Karim, R. (2020). Word Cloud and Sentiment Analysis of Amazon Earphones Reviews with R Programming Language. Informatica Economica, 24(4), 55-71. https://doi.org/10.24818/issn14531305/24.4.2020.05
Khamngoen, S., Seehamat, L., & Khongjaroen, K. P. (2020). The Knowledge Synthesis of English Teaching Based on Content and Language Integrated Learning Approach (CLIL). Journal of Roi Et Rajabhat University, 14(1), 249-260. https://ph01.tci-thaijo.org/index.php/RERU/article/view/242427
McNaught, C., & Lam, P. (2010). Using Wordle as a supplementary research tool. Qualitative Report, 15(3), 630-643. https://doi.org/10.46743/2160-3715/2010.1167
Milum, J. (2018). SAS® Visual Analytics: Text Analytics Using Word Clouds. SAS. https://www.sas.com/content/dam/SAS/support/en/sas-global-forum-proceedings/2018/1687-2018.pdf
Ratanapitakdhada, C., Charuenkul, N., & Siribanpitak, P. (2020). Academic Management Strategies Based on Content and Language Integrated Learning and English Competency of Secondary Students. Journal of Education Studies, 49(2), 1-14. https://so02.tci-thaijo.org/index.php/EDUCU/article/view/238714
Sellars, B. B., Sherrod, D. R., & Chappel-Aiken, L. (2018). Using word clouds to analyze qualitative data in clinical settings. Nursing Management, 49(10), 51-53. https://doi.org/10.1097/01.NUMA.0000546208.18770.97
Uitdenbogerd, A. L. (2019). World cloud: A prototype data choralification of text documents. Journal of New Music Research, 48(3), 253-263. https://doi.org/10.1080/09298215.2019.1606829
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