Visual Communication Design for Mobile Learning Apps: User Interface Usability and Learning Engagement
DOI:
https://doi.org/10.58262/V32I78.19Keywords:
Visual Communication, Mobile Learning, Learning Engagement, User Interface Usability, Cognitive LoadAbstract
This study explored the visual communication design for the mobile learning applications through user interface usability and learning engagement. This experiment also observed the mediating impact of cognitive load in the relationship between user interface usability and learning engagement. The method adopted for the study was quantitative method and the data was collected by adopting a questionnaire survey strategy. The data was collected from the higher education institutions in China located at different regions and the target population of the study were the current enrolled students at these institutions. The study tested the research hypotheses through structural equation modelling. CFA was used to evaluate the fitness of the measurement model. The findings of the study indicated that user interface, and student engagement were effective indicators of visual communication design. The study would be a great contribution as it dealt with emerging topic of visual communication design in the educational sector of China, advocating the use of mobile learning applications. The study would also offer significant insights to managers and policy makers. Future researchers could maneuver qualitative research design to analyze the perspectives, viewpoints and subjective opinions in the subject.
References
Ab Hamid, M., Sami, W., & Sidek, M. M. (2017). Discriminant validity assessment: Use of Fornell & Larcker criterion versus HTMT criterion. Journal of Physics: Conference Series, 890(1), 012163. https://doi.org/10.1088/1742-6596/890/1/012163
Adiloglu, F. (2011). Visual communication: design studio education through working the process. Procedia-Social and Behavioral Sciences, 28, 982-991. https://doi.org/10.1016/j.sbspro.2011.11.182
Akbarov, B. (2022). Formation of Professional Motivation of Students in the Educational Process. Galaxy International Interdisciplinary Research Journal, 10(4), 702-704. https://go.revistacomunicar.com/qQbyYC
Aremu, B. V., & Adeoluwa, O. V. (2021). M-learning: A nexus for adult learners’ motivation and readiness to learn in federal universities at Southwest, Nigeria. Journal of Digital Educational Technology, 2(1), e p22 01. https://doi.org/10.21601/jdet/11361
Bateman, K. J., Wilson, S. E., Ingvarsson, E., Doucette, J., Therrien, W., Nevill, R., & Mazurek, M. (2023). Snack Talk: Effects of a Naturalistic Visual Communication Support on Increasing Conversation Engagement for Adults with Disabilities. Behavior Analysis in Practice, 1-15. https://doi.org/10.1007/s40617-023-00775-3
Benden, D. K., & Lauermann, F. (2022). Students’ motivational trajectories and academic success in math-intensive study programs: Why short-term motivational assessments matter. Journal of Educational Psychology, 114(5), 1062-1085. https://doi.org/10.1037/edu0000708
Bernacki, M. L., Greene, J. A., & Crompton, H. (2020). Mobile technology, learning, and achievement: Advances in understanding and measuring the role of mobile technology in education. Contemporary Educational Psychology, 60, 101827. https://doi.org/10.1016/j.cedpsych.2019.101827
Calvo, L., Christel, I., Terrado, M., Cucchietti, F., & Pérez-Montoro, M. (2022). Users’ cognitive load: A key aspect to successfully communicate visual climate information. Bulletin of the American Meteorological Society, 103(1), E1-E16. https://doi.org/10.1175/BA MS-D-20-0166.1
Castro-Alonso, J. C., Ayres, P., & Sweller, J. (2019). Instructional Visualizations, Cognitive Load Theory, and Visuospatial Processing. In J. Castro-Alonso (Ed.), Visuospatial Processing for Education in Health and Natural Sciences ( p p . 111-14 3 ). Springer. https://doi.org/10.1007/978-3-030-20969-8_5
Chen, T., Peng, L., Jing, B., Wu, C., Yang, J., & Cong, G. (2020). The impact of the COVID-19 pandemic on user experience with online education platforms in China. Sustainability, 12(18), 7329. https://doi.org/10.3390/su12187329
Cheung, G. W., & Wang, C. (2017). Current Approaches for Assessing Convergent and Discriminant Validity with SEM: Issues and Solutions. Academy of Management Proceedings, 2017(1), 1270 6. https://doi.org/10.5465/AMBPP.2017.12706abstract
Curum, B., & Khedo, K. K. (2021). Cognitive load management in mobile learning systems: principles and theories. Journal of Computers in Education, 8, 109-136. https://doi.org/10.1007/s40692-020-00173-6
Djeki, E., Dégila, J., Bondiombouy, C., & Alhassan, M. H. (2022). E-learning bibliometric analysis from 2015 to 2020. Journal of Computers in Education, 9(4), 727-754. https://doi.org/10.1007/s40692-021-00218-4
Feldon, D. F., Callan, G., Juth, S., & Jeong, S. (2019). Cognitive Load as Motivational Cost. Educational Psychology Review, 31, 319 -337. https://doi.org/10.1007/s10648-019-09464-6
Fisher, M. J., & Marshall, A. P. (2009). Understanding descriptive statistics. Australian Critical Care, 22(2), 93-97. https://doi.org/10.1016/j.aucc.2008.11.0 03
Fornell, C., & Larcker, D. F. (1981). Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. Journal of Marketing Research, 18(3), 382-388. https://doi.org/10.2307/3150980
Gangaiamaran, R., & Pasupathi, M. (2017). Review on Use of Mobile Apps for Language Learning. International Journal of Applied Engineering Research, 12( 21) , 112 4 2 -112 51. https://go.revistacomunicar.com/svM5TC
Gutiérrez Carreón, G., Daradoumis, T., Jorba, J., & Gomar, C. (2020). A study on the effectiveness of an undergraduate online teaching laboratory with semantic mechanism from a student perspective. Journal of Information Technology Education: Innovations in Practice, 19, 137-155. https://doi.org/10.28945/4624
Hadi, N. U., Abdullah, N., & Sentosa, I. (2016). An easy approach to exploratory factor analysis: Marketing perspective. Journal of Educational and Social Research, 6(1), 215. https://go.revistacomunicar.com/RGRENo
Hammady, R., Ma, M., & Powell, A. (2018). User experience of markerless augmented reality applications in cultural heritage museums:‘museumeye’as a case study. In Augmented Reality, Virtual Reality, and Computer Graphics: 5th International Conference, AVR 2018, Otranto, Italy, June 24–27, 2018, Proceedings, Part II 5 (pp. 349-369). Springer. https://doi.org/10.1007/978-3-319-95282-6_26
Harpur, P., & De Villiers, M. (2015). MUUX-E, a framework of criteria for evaluating the usability, user experience and educational features of m-learning environments. South African Computer Journal, 56(1), 1-21. https://doi.org/10.18489/sacj.v56i1.240
Hermanto, Y. A. L., Pahlevi, A. S., Sutrisno, A. A., & Ibrahim, N. B. (2021). Mega shifts in the business pivot in visual communication design subsector during the COVID-19 pandemic. KnE Social Sciences, 394–402. https://doi.org/10.18502/kss.v5i3.8562
Huang, C. L., Luo, Y. F., Yang, S. C., Lu, C. M., & Chen, A.-S. (2020). Inf luence of students’ learning style, sense of presence, and cognitive load on learning outcomes in an immersive virtual reality learning environment. Journal of Educational Computing Research, 58(3), 596 - 615. https://doi.org/10.1177/0735633119867422
Huang, Z., & Benyoucef, M. (2022). A systematic literature review of mobile application usability: addressing the design perspective. Universal Access in the Information Society, 22, 715 –735. https://doi.org/10.1007/s10209-022-00903-w
Kabrisky, M. (1964). A proposed model for visual information processing in the human brain [Doctoral Dissertation, University of Illinois at Urbana-Champaign]. https://go.revistacomunicar.com/m4tFkS
Ke, P., & Su, F. (2018). Mediating effects of user experience usability: An empirical study on mobile library application in China. The Electronic Library, 36(5), 892-909. https://doi.org/10.1108/EL-04-2017-0086
Klimova, B., & Polakova, P. (2020). Students’ perceptions of an EFL vocabulary learning mobile application. Education Sciences, 10(2), 37. https://doi.org/10.3390/educsci10020037
Krull, G., & Duart, J. M. (2017). Research trends in mobile learning in higher education: A systematic review of articles (2011–2015). International Review of Research in Open and Distributed Learning, 18(7). https://doi.org/10.19173/irrodl.v18i7.2893
Kumar Basak, S., Wotto, M., & Belanger, P. (2018). E-learning, M-learning and D-learning: Conceptual definition and comparative analysis. E-learning and Digital Media, 15(4), 191-216. https://doi.org/10.1177/2042753018785180
Liu, L., Zhang, L., Ye, P., & Liu, Q. (2018). Inf luence factors of satisfaction with mobile learning APP: An empirical analysis of China. International Journal of Emerging Technologies in Learning, 13(3), 87-99. https://doi.org/10.3991/IJET.V13I03.8381
Liu, Y., Al-Atawi, A. A., Khan, I. A., Gohar, N., & Zaman, Q. (2023). Using the fuzzy analytical hierarchy process to prioritize the impact of visual communication based on artificial intelligence for long-term learning. Soft Computing, 27(1), 157-16 8. https://doi.org/10.1007/s00500-022-07556-0
Martin, F., & Borup, J. (2022). Online learner engagement: Conceptual definitions, research themes, and supportive practices. Educational Psychologist, 57(3), 162 -177. https://doi.org/10.1080/00461520.2022.2089147
Nie, R. (2018). Research on dynamic visual communication graphics design under mobile terminal platform. In 2018 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS) (pp. 198-201). IEEE. https://doi.org/10.1109/ICITBS.2018.00058
Paas, F., & van Merriënboer, J. J. (2020). Cognitive-load theory: Methods to manage working memory load in the learning of complex tasks. Current Directions in Psychological Science, 29(4), 394-398. https://doi.org/10.1177/0963721420922183
Park, K., Farb, A., & George, B. (2023). Effectiveness of visual communication and collaboration tools for online GIS teaching: Using Padlet and Conceptboard. Journal of Geography in Higher Education, 47(3), 399- 410. https://doi.org/10.1080/03098265.2022.2065669
Parsazadeh, N., Ali, R., & Rezaei, M. (2018). A framework for cooperative and interactive mobile learning to improve online information evaluation skills. Computers & Education, 120, 75-89. https://doi.org/10.1016/j.compedu.2018.01.010
Pratama, D., Gunarti, W., & Akbar, T. (2017). Understanding visual novel as artwork of visual communication design. Mudra Jurnal Seni Budaya, 32(3), 292-298. https://doi.org/10.31091/mudra.v32i3.177
Prati, E., Peruzzini, M., Pellicciari, M., & Raffaeli, R. (2021). How to include User eXperience in the design of Human-Robot Interaction. Robotics and Computer-Integrated Manufacturing, 68, 102072. https://doi.org/10.1016/j.rcim.2020.102072
Raiyn, J. (2016). The Role of Visual Learning in Improving Students’ High-Order Thinking Skills. Journal of Education and Practice, 7( 2 4 ) , 115 -121. https://go.revistacomunicar.com/sPB6QT
Rice, S., Winter, S. R., Doherty, S., & Milner, M. (2017). Advantages and disadvantages of using internet-based survey methods in aviation-related research. Journal of Aviation Technology and Engineering, 7(1), 5. https://doi.org/10.7771/2159-6670.1160
Saris, B. (2020). A review of engagement with creativity and creative design processes for visual communication design (VCD) learning in China. International Journal of Art & Design Education, 39( 2), 306 -318. https://doi.org/10.1111/jade.12262
Sayibu, M., Jianxun, C., Akintunde, T. Y., Hafeez, R. O., Koroma, J., Amosun, T. S., & Shahani, R. (2021). Nexus between students’ attitude towards self-learning, Tencent APP usability, mobile-learning, and innovative performance. Social Sciences & Humanities Open, 4(1), 10 0 217. https://doi.org/10.1016/j.ssa ho.2021.10 0217
Song, S., Zhao, Y. C., Yao, X., Ba, Z., & Zhu, Q. (2021). Short video apps as a health information source: an investigation of affordances, user experience and users’ intention to continue the use of TikTok. Internet Research, 31(6 ), 2120 -2142. https://doi.org/10.1108/INTR-10-2020-0593
Sun, W., Hong, J.-C., Dong, Y., Huang, Y., & Fu, Q. (2023). Self-directed learning predicts online learning engagement in higher education mediated by perceived value of knowing learning goals. The Asia-Pacific Education Researcher, 32( 3), 3 07-316. https://doi.org/10.1007/s40299-022-00653-6
Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 2 9 5 -312. https://doi.org/10.1016/0959-4752(94)90003-5
Sweller, J. (2020). Cognitive load theory and educational technology. Educational Technology Research and Development, 68(1), 1-16. https://doi.org/10.1007/s11423-019-09701-3
Taherdoost, H., Sahibuddin, S., & Jalaliyoon, N. (2022). Exploratory Factor Analysis; Concepts and Theory. Advances in Applied and Pure Mathematics, 27, 375-382. https://go.revistacomunicar.com/Tgo85Z
Wang, Y., Liu, X., & Zhang, Z. (2018). An overview of e-learning in China: History, challenges and opportunities. Research in Comparative and International Education, 13(1), 195 -210. https://doi.org/10.1177/1745499918763421
Weinstein, C. E., & Mayer, R. E. (1983). The Teaching of Learning Strategies. Innovation Abstracts, 5(32), n32. https://go.revistacomunicar.com/NesUDY
Wijaya, O. P., & Bukhori, I. (2017). Effect of Learning Motivation, Family Factor, School Factor, and Community Factor on Student Learning Outcomes on Productive Subjects. JPBM (Jurnal Pendidikan Bisnis dan Manajemen), 3(3), 192-202. https://doi.org/10.17977/u m 0 03v3i32017p192
Wileman, R. E. (1993). Visual Communicating. Educational Technology. https://go.revistacomunicar.com/phQcYI
Worth, S. (2016). Studying Visual Communication. University of Pennsylvania Press. https://doi.org/10.9783/9781512809282
Wu, H., & Li, G. (2020). Innovation and improvement of visual communication design of mobile app based on social network interaction interface design. Multimedia Tools and Applications, 79, 1-16. https://doi.org/10.1007/s11042-019-7523-6
Yang, C. C. Y., & Ogata, H. (2023). Personalized learning analytics intervention approach for enhancing student learning achievement and behavioral engagement in blended learning. Education and Information Technologies, 28(3), 2509-2528. https://doi.org/10.1007/s10639-022-11291-2
Yu, Z., Gao, M., & Wang, L. (2021). The effect of educational games on learning outcomes, student motivation, engagement and satisfaction. Journal of Educational Computing Research, 59(3), 522-546. https://doi.org/10.1177/0735633120969214
Zhai, X. (2022). ChatGPT User Experience: Implications for Education. Available at SSRN 4312418. https://doi.org/10.2139/ssrn.4312418
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