Classtime.Com as an Ai-Based Testing Platform: Analysing ESP Students’ Performances and Feedback
DOI:
https://doi.org/10.33394/jollt.v11i3.8286Keywords:
Artificial Intelligence (AI) technology, Online testing platform, English for Specific Purposes (ESP), Classtime.com, Language learning outcomes,Abstract
References
Admiraal, W., Vermeulen, J., & Bulterman-Bos, J. (2020). Teaching with learning analytics:how to connect computer-based assessment data with classroom instruction? Technology, Pedagogy and Education, 29(5), 577–591. https://doi.org/10.1080/1475939X.2020.1825992
Alsharif, D., & Shukri, N. (2018). Exploring Pedagogical Challenges of ESP Teachers at a Saudi Arabian University. International Journal of Asian Social Science, 8(10), 841–855. https://doi.org/10.18488/journal.1.2018.810.841.855
Azad, S., Chen, B., Fowler, M., West, M., & Zilles, C. (2020). Strategies for Deploying Unreliable AI Graders in High-Transparency High-Stakes Exams (pp. 16–28). https://doi.org/10.1007/978-3-030-52237-7_2
Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020). Application and theory gaps during the rise of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
Enesi, M., Vrapi, F., & Trifoni, A. (2021). Challenges of Teaching and Learning English Language for ESP Courses. Journal of Educational and Social Research, 11(4), 213. https://doi.org/10.36941/jesr-2021-0090
Feenstra, H. E. M., Murre, J. M. J., Vermeulen, I. E., Kieffer, J. M., & Schagen, S. B. (2018). Reliability and validity of a self-administered tool for online neuropsychological testing: The Amsterdam Cognition Scan. Journal of Clinical and Experimental Neuropsychology, 40(3), 253–273. https://doi.org/10.1080/13803395.2017.1339017
Fitria, T. N. (2020). Teaching English for Specific Purposes (ESP) to the Students in English Language Teaching (ELT). JET ADI BUANA, 5(01), 55–66. https://doi.org/10.36456/jet.v5.n01.2020.2276
Gayed, J. M., Carlon, M. K. J., Oriola, A. M., & Cross, J. S. (2022). Exploring an AI-based writing Assistant’s impact on English language learners. Computers and Education: Artificial Intelligence, 3, 100055. https://doi.org/10.1016/j.caeai.2022.100055
González-Calatayud, V., Prendes-Espinosa, P., & Roig-Vila, R. (2021). Artificial Intelligence for Student Assessment: A Systematic Review. Applied Sciences, 11(12), 5467. https://doi.org/10.3390/app11125467
Hahn, M. G., Navarro, S. M. B., De La Fuente Valentin, L., & Burgos, D. (2021). A Systematic Review of the Effects of Automatic Scoring and Automatic Feedback in Educational Settings. IEEE Access, 9, 108190–108198. https://doi.org/10.1109/ACCESS.2021.3100890
Hidayati, D. (2019). THE ANALYSIS OF ENGLISH REQUIREMENT FOR SHARIAH ECONOMIC STUDENTS. JARES (Journal of Academic Research and Sciences), 4(2), 32–38. https://doi.org/10.35457/jares.v4i2.840
Huang, J., Saleh, S., & Liu, Y. (2021). A Review on Artificial Intelligence in Education. Academic Journal of Interdisciplinary Studies, 10(3), 206. https://doi.org/10.36941/ajis-2021-0077
Inozemtseva, K. M., Morozova, E. V., & Kolesnikov, I. M. (2022). Assessment of ESP students’ learning outcomes in a digital learning environment. RUDN Journal of Informatization in Education, 19(4), 300–311. https://doi.org/10.22363/2312-8631-2022-19-4-300-311
Isnaini, I., Sunimaryanti, S., & Andre, L. (2021). Assessment Principles and Practices Quality Assessments in A Digital Age. SPEKTRUM: Jurnal Pendidikan Luar Sekolah (PLS), 9(2), 287. https://doi.org/10.24036/spektrumpls.v9i2.112711
Jin, L. (2022). Design of English Writing Assessment System Based on AI Technology in food and agriculture sectors. Journal of Commercial Biotechnology, 25(4). https://doi.org/10.5912/jcb1252
Kakoulli Constantinou, E., & Papadima-Sophocleous, S. (2020). THE USE OF DIGITAL TECHNOLOGY IN ESP: CURRENT PRACTICES AND SUGGESTIONS FOR ESP TEACHER EDUCATION. Journal of Teaching English for Specific and Academic Purposes, 017. https://doi.org/10.22190/JTESAP2001017K
Kester, E. S. (2022). Online Language Assessment of School-Age Students. Topics in Language Disorders, 42(2), 127–139. https://doi.org/10.1097/TLD.0000000000000281
Kiryakova, G. (2021). E-assessment-beyond the traditional assessment in digital environment. IOP Conference Series: Materials Science and Engineering, 1031(1), 012063. https://doi.org/10.1088/1757-899X/1031/1/012063
Langenfeld, T. (2020). Internetâ€Based Proctored Assessment: Security and Fairness Issues. Educational Measurement: Issues and Practice, 39(3), 24–27. https://doi.org/10.1111/emip.12359
Liang, L., Tognolini, J., Hendry, G., & Mantai, L. (2022, June 14). A review of tertiary formative assessment using digital technology in the past decade: what has been facilitated? 8th International Conference on Higher Education Advances (HEAd’22). https://doi.org/10.4995/HEAd22.2022.14371
Mahamatismoyilovna, S. R. (2022). Innovation teaching technology in ESP groups by activities. International Journal of Health Sciences, 3497–3502. https://doi.org/10.53730/ijhs.v6nS5.9400
Mujtaba, D. F., & Mahapatra, N. R. (2020). Artificial Intelligence in Computerized Adaptive Testing. 2020 International Conference on Computational Science and Computational Intelligence (CSCI), 649–654. https://doi.org/10.1109/CSCI51800.2020.00116
Nardi, A., & Ranieri, M. (2019). Comparing paperâ€based and electronic multipleâ€choice examinations with personal devices: Impact on students’ performance, selfâ€efficacy and satisfaction. British Journal of Educational Technology, 50(3), 1495–1506. https://doi.org/10.1111/bjet.12644
Okada, A., Noguera, I., Alexieva, L., Rozeva, A., Kocdar, S., Brouns, F., Ladonlahti, T., Whitelock, D., & Guerreroâ€Roldán, A. (2019). Pedagogical approaches for eâ€assessment with authentication and authorship verification in Higher Education. British Journal of Educational Technology, 50(6), 3264–3282. https://doi.org/10.1111/bjet.12733
Preslavsky, K. (2020). Intelligent Methods for Objective Assessment of Learners in Online Testing.
Reilly, D., Neumann, D. L., & Andrews, G. (2019). Gender differences in reading and writing achievement: Evidence from the National Assessment of Educational Progress (NAEP). American Psychologist, 74(4), 445–458. https://doi.org/10.1037/amp0000356
Saienko, N., & Chugai, O. (2020). Quarantine: Teaching English From Home with Google Classroom, Classtime and Quizlet. Romanian Journal for Multidimensional Education/Revista Romaneasca Pentru Educatie Multidimensionala, 12.
Sillat, L. H., Tammets, K., & Laanpere, M. (2021). Digital Competence Assessment Methods in Higher Education: A Systematic Literature Review. Education Sciences, 11(8), 402. https://doi.org/10.3390/educsci11080402
Sun, Z., Anbarasan, M., & Praveen Kumar, D. (2021). Design of online intelligent English teaching platform based on artificial intelligence techniques. Computational Intelligence, 37(3), 1166–1180. https://doi.org/10.1111/coin.12351
Supendi, R. P. (2020). Analysis of underachieving students’ problems and the given guidance. ProGCouns: Journal of Professionals in Guidance and Counseling, 1(1). https://doi.org/10.21831/progcouns.v1i1.31535
Tran, T. P., Sidhu, L., & Tran, D. (2021). A Framework for Navigating and Enhancing the Use of Digital Assessment. 2021 5th International Conference on E-Society, E-Education and E-Technology, 1–6. https://doi.org/10.1145/3485768.3485803
Vieira Vasconcelos, S., Balula, A., BurkÅ¡aitienÄ—, N., & Stojkovic, N. (2021). V-interESP - Utilização de VÃdeos para Melhorar a Experiência de Aprendizagem dos Estudantes ESP: Ensino e Investigação Conjunta Internacional. Revista de Lenguas Para Fines EspecÃficos, 27.1, 74–96. https://doi.org/10.20420/rlfe.2021.389
Xu, J., Jones, E., Laxton, V., & Galaczi, E. (2021). Assessing L2 English speaking using automated scoring technology: examining automarker reliability. Assessment in Education: Principles, Policy & Practice, 28(4), 411–436. https://doi.org/10.1080/0969594X.2021.1979467
Xu, W., Meng, J., Raja, S. K. S., Priya, M. P., & Kiruthiga Devi, M. (2023). Artificial intelligence in constructing personalized and accurate feedback systems for students. International Journal of Modeling, Simulation, and Scientific Computing, 14(01). https://doi.org/10.1142/S1793962323410015
Zhu, A. (2020). Application of AI Identification Technology in Foreign Language Education. 2020 International Conference on Artificial Intelligence and Education (ICAIE), 71–75. https://doi.org/10.1109/ICAIE50891.2020.00024
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