EXPLORING THE CORRELATION BETWEEN STUDENTS' PERCEPTIONS AND ACHIEVEMENTS ON ENGLISH ONLINE HOMEWORK

 Tiara Vagari, Slamet Asari, Nirwanto Maruf

Abstract


This research investigates the correlation between students' perceptions of English online homework and their corresponding achievements, aiming to shed light on the interplay between these variables. A correlational research design was employed, involving 187 secondary school students from SMP YIMI 'FDS' Gresik. Data on perceptions and achievements exhibited normal distribution and significance levels (2-tailed) below 0.05, affirming the robustness of the study. The Spearman correlation test unveiled a very strong correlation between students' positive perceptions of online homework and their English achievements. The findings align with previous studies, emphasizing the pivotal role of attitudes in shaping academic outcomes. The outcomes resonate with Self-Determination Theory, suggesting that fostering favorable perceptions can enhance intrinsic motivation and learning outcomes. The study underscores the significance of user-friendly instructional design and a balanced approach to learning. It also recognizes limitations related to sample and cross-sectional design. In conclusion, the research contributes to understanding the impact of students' perceptions on their achievements in the digital learning era, urging educators to prioritize not only technological integration but also the psychological dimensions of education.

Full Text:

PDF

References


Al-Bataineh, A., Anderson, S., Toledo, C., & Wellinski, S. (2008). A Study of Technology Integration in the Classroom. International Journal of Instructional Media, 35(4).

Alshammari, H., & Rosli, S. (2020). A Review of Technology Acceptance Models and Theories. In A Review of Technology Acceptance Models and Theories. Innovative Teaching and Learning Journal (Vol. 4, Issue 2).

Arifin, S., Arifani, Y., Maruf, N., & Helingo, A. (2022). A Case Study of EFL Teacher Scaffolding of an ASD Learner’s Shared Reading with a Storybook App. Journal of Asia TEFL, 19(4). https://doi.org/10.18823/asiatefl.2022.19.4.6.1234

Bai, S., Hew, K. F., & Gonda, D. E. (2021). Examining Effects of Different Leaderboards on Students’ Learning Performance, Intrinsic Motivation, and Perception in Gamified Online Learning Setting. 2021 IEEE International Conference on Educational Technology, ICET 2021. https://doi.org/10.1109/ICET52293.2021.9563130

Barianty, T. N., Arifani, Y., Ma'ruf, N., & Setiawan, S. (2022). L2 ASD Learners’ Scaffolding Development after Long Interaction with The Mobile Story-Sharing Application. Language Related Research, 13(3), 87-110.

Cai, J. (2021). A Design of Interactive Online English Translation System Based on Deep Learning. Proceedings - 2021 International Conference of Social Computing and Digital Economy, ICSCDE 2021. https://doi.org/10.1109/ICSCDE54196.2021.00011

Chiu, T. K. F. (2022). Applying the self-determination theory (SDT) to explain student engagement in online learning during the COVID-19 pandemic. Journal of Research on Technology in Education, 54(S1). https://doi.org/10.1080/15391523.2021.1891998

Darsih, E., Suherdi, D., & Safrina, S. (2019). Technology Integration in Public Speaking Classroom: Is It Effective? https://doi.org/10.4108/eai.19-10-2018.2281323

de Jong, T. (2010). Cognitive load theory, educational research, and instructional design: Some food for thought. Instructional Science, 38(2). https://doi.org/10.1007/s11251-009-9110-0

Gilakjani, A. P. (2017). A Review of the Literature on the Integration of Technology into the Learning and Teaching of English Language Skills. International Journal of English Linguistics, 7(5). https://doi.org/10.5539/ijel.v7n5p95

Gunuç, S., & Babacan, N. (2017). Technology integration in English language teaching and learning. The Journal of Teaching English for Specific and Academic Purposes, 5(2).

Kirschner, P. A. (2002). Cognitive load theory: Implications of cognitive load theory on the design of learning. In Learning and Instruction (Vol. 12, Issue 1). https://doi.org/10.1016/S0959-4752(01)00014-7

Kozan, K. (2013). Cognitive load theory. Turkish Online Journal of Distance Education, 14(2). https://doi.org/10.26537/rebules.v0i28.1024

Liu, B. (2022). Design of English Online Learning Platform Based on Deep Learning Technology. World Automation Congress Proceedings, 2022-October. https://doi.org/10.23919/WAC55640.2022.9934238

Maruf, N., & Anjely, A. M. R. (2020). Utilizing Cooperative Integrated Reading and Composition (CIRC) with mobile Learning to Enhance Students’ Reading Comprehension. British (Jurnal Bahasa Dan Sastra Inggris), 9(2), 10–19.

Mathieson. (1991). Comparing The Technology Acceptance Model with The Theory of Planned Behaviour. Information Systems Research, 2, 3(3).

Mohammed, M. A. A. A. A. (2020). Utilizing Technology in ELT Classrooms. OALib, 07(01). https://doi.org/10.4236/oalib.1106016

Palazón-Herrera, J., & Soria-Vílchez, A. (2021). Students’ perception and academic performance in a flipped classroom model within Early Childhood Education Degree. In Heliyon (Vol. 7, Issue 4). https://doi.org/10.1016/j.heliyon.2021.e06702

Pangaribuan, C. H., Hidayat, D., Prihatma, O., Putra, B., Aguzman, G., & Febriyanto, R. (2020). DIGITAL BADGE FROM THE PERSPECTIVE OF SELF- DETERMINATION THEORY. Palarch’s Journal Of Archaeology Of Egypt/Egyptology, 18(1).

Peng, N. (2022). Research on the effectiveness of English online learning based on neural network. Neural Computing and Applications, 34(4). https://doi.org/10.1007/s00521-021-05855-5

Plass, J. L., Moreno, R., & Brünken, R. (2010). Cognitive load theory. In Cognitive Load Theory. https://doi.org/10.1017/CBO9780511844744

Purwantoro, A., Asari, S., & Maruf, N. (2021). The Effectiveness of E-Learning Madrasah in English Teaching and Learning. BIRCI-Journal, 4(3).

Rejali, S., Aghabayk, K., Esmaeli, S., & Shiwakoti, N. (2023). Comparison of technology acceptance model, theory of planned behavior, and unified theory of acceptance and use of technology to assess a priori acceptance of fully automated vehicles. Transportation Research Part A: Policy and Practice, 168. https://doi.org/10.1016/j.tra.2022.103565

Salikhova, N. R., Lynch, M. F., & Salikhova, A. B. (2020). Psychological aspects of digital learning: A self-determination theory perspective. Contemporary Educational Technology, 12(2). https://doi.org/10.30935/cedtech/8584

Shaigerova, L., Almazova, O., Vakhantseva, O., & Shilko, R. (2022). Positive and negative affects in university students at the beginning of the COVID-19 pandemic and a year after it was announced. European Psychiatry, 65(S1). https://doi.org/10.1192/j.eurpsy.2022.1293

Shin, J., Ly, J., Polikoff, D., & Reyes, K. (2022). Student perceptions and academic performance in a remote flipped classroom. Pharmacy Education, 22(1). https://doi.org/10.46542/pe.2022.221.436444

Sulaiman, R., & Ermianti, E. (2021). The Effectiveness of Online Learning at English Education Students. Didaktika: Jurnal Kependidikan, 10(4). https://doi.org/10.58230/27454312.119

Trujillo, F. S., Salvadores, C. M., & Gabarrón, Á. P. (2019). Technology for teaching and learning foreign languages: a literature review. RIED-Revista Iberoamericana de Educacion a Distancia, 22(1). https://doi.org/10.5944/ried.22.1.22257

Venkatesh, V. (2015). Technology Acceptance Model And The Unified Theory Of Acceptance And Use Of Technology. In Wiley Encyclopedia of Management. https://doi.org/10.1002/9781118785317.weom070047

Xu, J., Liu, Y., Liu, J., & Qu, Z. (2022). Effectiveness of English Online Learning Based on Deep Learning. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/1310194

Yaghoubi, N.-M., & Bahmani, E. (2010). An Integration of Technology Acceptance Model and Theory of Planned Behavior. International Journal of Business and Management, 5(9).

Zaineldeen, S., Hongbo, L., Koffi, A. L., & Hassan, B. M. A. (2020). Technology acceptance model’ concepts, contribution, limitation, and adoption in education. Universal Journal of Educational Research, 8(11). https://doi.org/10.13189/ujer.2020.081106

Zambrano, R. J., Kirschner, P. A., & Kirschner, F. (2019). HOW COGNITIVE LOAD THEORY CAN BE APPLIED TO COLLABORATIVE LEARNING: Collaborative cognitive load theory. In Advances in Cognitive Load Theory: Rethinking Teaching. https://doi.org/10.4324/9780429283895-3

Zeng, X.-F., & Wang, S. (2020). An Investigation and Research on the Effectiveness of College English Online Learning. https://doi.org/10.2991/assehr.k.201214.038


DOI: http://dx.doi.org/10.31314/british.12.2.%25p.2023

Article metrics

Abstract views : 226 | views : 53

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Publisher : Program Studi S1 Sastra Inggris, Fakultas Ilmu Budaya, Universitas Muhammadiyah Gorontalo

Web Analytics View British (Jurnal Bahasa dan Sastra Inggris) Stats