STUDENTS' PERCEPTIONS OF USING E-COMICS AS A MEDIA IN MATHEMATICS LEARNING

Yulinar Safitri (1*)
Mailizar Mailizar (2)
Rahmah Johar (3)


(1) Universitas Syiah Kuala
(2) Universitas Syiah Kuala
(3) Universitas Syiah Kuala
(*) Corresponding Author


Abstract


The development of technology in education greatly influences learning strategies. Thus, teachers must adapt and present interesting and technology-based learning, such as e-comics. Therefore, the teacher must see in advance the extent to which students will accept e-comics for use in learning mathematics. This research aimed to determine students' perceptions of the use of e-comics as a media in mathematics learning. This research implemented a quantitative approach with a survey method. The samples were 124 students of Junior High Schools (SMP / MTs) in Aceh. The research data were obtained from questionnaires filled by students which were collected through the TAM (Technology Acceptance Models) framework which was distributed online.  The results showed that students used e-comic as a learning media influenced by their perceived benefits and attitudes towards the use of e-comic. The perceived benefits of students' attitudes have a significant role in their behavioral intention to use e-comic in learning mathematics. This research implies that e-comics has the potential to be used as a media in mathematics learning, especially on material that is considered difficult so that it can attract students' attention.


Keywords


E-Comic; Media; Students Perceptions; TAM

Full Text:

PDF

References


Abdullah, F., & Ward, R. (2016). Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analysing commonly used external factors. Computers in human behavior, 56, 238-256. doi:10.1016/j.chb.2015.11.036

[Article]     [Google Scholar]


Abdullah, F., Ward, R., & Ahmed, E. (2016). Investigating the influence of the most commonly used external variables of TAM on students’ Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) of e-portfolios. Computers in human behavior, 63, 75-90. doi:10.1016/j.chb.2016.05.014

[Article]     [Google Scholar]


Al-Emran, M., Mezhuyev, V., & Kamaludin, A. (2018). Technology Acceptance Model in M-learning context: A systematic review. Computers & Education, 125, 389-412. doi:10.1016/j.compedu.2018.06.008

[Article]     [Google Scholar]


Buchori, A., & Setyawati, R. D. (2015). Development learning model of charactereducation through e-comic in elementary school. International Journal of Education and Research, 3(9), 369-386.

[Article]     [Google Scholar]


Cheng, E. W. (2019). Choosing between the theory of planned behavior (TPB) and the technology acceptance model (TAM). Educational Technology Research and Development, 67(1), 21-37. doi:10.1007/s11423-018-9598-6

[Article]     [Google Scholar]


Chi, T. (2018). Understanding Chinese consumer adoption of apparel mobile commerce: An extended TAM approach. Journal of Retailing and Consumer Services, 44, 274-284. doi:10.1016/j.jretconser.2018.07.019

[Article]     [Google Scholar]


Cigdem, H., & Topcu, A. (2015). Predictors of instructors’ behavioral intention to use learning management system: A Turkish vocational college example. Computers in Human Behavior, 52, 22-28. doi:10.1016/j.chb.2015.05.049

[Article]     [Google Scholar]


Clair, J. S. (2018). Using cartoons to make connections and enrich Mathematics. In Proceedings of the Interdisciplinary STEM Teaching and Learning Conference (Vol. 2, pp. 45-53). doi:10.20429/stem.2018.020112

[Article]     [Google Scholar]


Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 13(3), 319-340. doi:10.2307/249008

[Article]     [Google Scholar]


Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003. doi:10.1287/mnsc.35.8.982

[Article]     [Google Scholar]


Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.

[Article]     [Google Scholar]


Gao, S., Krogstie, J., & Siau, K. (2014). Adoption of mobile information services: An empirical study. Mobile Information Systems, 10(2), 147-171. doi:10.3233/MIS-130176

[Article]     [Google Scholar]


Huang, C. C. (2017). Cognitive factors in predicting continued use of information systems with technology adoption models. Information Research: An International Electronic Journal, 22(2).

[Article]     [Google Scholar]


Huang, Y. M. (2016). The factors that predispose students to continuously use cloud services: Social and technological perspectives. Computers & Education, 97, 86-96. doi:10.1016/j.compedu.2016.02.016

[Article]     [Google Scholar]


Hussein, Z. (2017). Leading to intention: The role of attitude in relation to technology acceptance model in e-learning. Procedia Computer Science, 105, 159-164. doi:10.1016/j.procs.2017.01.196

[Article]     [Google Scholar]


Ibili, E., Resnyansky, D., & Billinghurst, M. (2019). Applying the technology acceptance model to understand maths teachers’ perceptions towards an augmented reality tutoring system. Education and Information Technologies, 24(5), 2653-2675. doi:10.1007/s10639-019-09925-z

[Article]     [Google Scholar]


Joo, Y. J., Park, S., & Shin, E. K. (2017). Students' expectation, satisfaction, and continuance intention to use digital textbooks. Computers in Human Behavior, 69, 83-90. doi:10.1016/j.chb.2016.12.025

[Article]     [Google Scholar]


Khor, E. T. (2014). An analysis of ODL student perception and adoption behavior using the technology acceptance model. International Review of Research in Open and Distributed Learning, 15(6), 275-288. doi:10.19173/irrodl.v15i6.1732

[Article]     [Google Scholar]


Kristanto, A., Mustaji, M., & Mariono, A. (2017). The development of instructional materials e-learning based on blended learning. International Education Studies, 10(7), 10-17. doi:10.5539/ies.v10n7p10

[Article]     [Google Scholar]


Lazarinis, F., Mazaraki, A., Verykios, V. S., & Panagiotakopoulos, C. (2015). E-comics in teaching: Evaluating and using comic strip creator tools for educational purposes. In 2015 10th International Conference on Computer Science & Education (ICCSE) (pp. 305-309). IEEE. doi:10.1109/ICCSE.2015.7250261

[Article]     [Google Scholar]


Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & management, 40(3), 191-204. doi:10.1016/S0378-7206(01)00143-4

[Article]     [Google Scholar]


Liao, S., Hong, J. C., Wen, M. H., & Pan, Y. C. (2018). Applying technology acceptance model (TAM) to explore users’ behavioral intention to adopt a performance assessment system for E-book production. EURASIA Journal of Mathematics, Science and Technology Education, 14(10), em1601. doi:10.29333/ejmste/93575

[Article]     [Google Scholar]


Lew, S. L., Lau, S. H., & Leow, M. C. (2019). Usability factors predicting continuance of intention to use cloud e-learning application. Heliyon, 5(6), e01788. doi:10.1016/j.heliyon.2019.e01788

[Article]     [Google Scholar]


Mamolo, L. (2019). Analysis of senior high school students' competency in general mathematics. Universal Journal of Educational Research, 7(9), 1938-1944. doi:10.13189/ujer.2019.070913

[Article]     [Google Scholar]


Masrom, M. (2007). Technology acceptance model and e-learning. In 12th International Conference on Education (pp. 1-10). Sultan Hassanal Bolkiah Institute of Education Universiti Brunei Darussalam.

[Article]     [Google Scholar]


McFarland, D. J., & Hamilton, D. (2006). Adding contextual specificity to the technology acceptance model. Computers in human behavior, 22(3), 427-447. doi:10.1016/j.chb.2004.09.009

[Article]     [Google Scholar]


Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, 2(3), 192-222. doi:10.1287/isre.2.3.192

[Article]     [Google Scholar]


Nagy, J. T. (2018). Evaluation of online video usage and learning satisfaction: An extension of the technology acceptance model. International Review of Research in Open and Distributed Learning, 19(1), 160-185. doi:10.19173/irrodl.v19i1.2886

[Article]     [Google Scholar]


Nikou, S. A., & Economides, A. A. (2017). Mobile-based assessment: Investigating the factors that influence behavioral intention to use. Computers & Education, 109, 56-73. doi:10.1016/j.compedu.2017.02.005

[Article]     [Google Scholar]


Nikou, S. A., & Economides, A. A. (2019). Factors that influence behavioral intention to use mobile‐based assessment: A STEM teachers’ perspective. British Journal of Educational Technology, 50(2), 587-600. doi:10.1111/bjet.12609

[Article]     [Google Scholar]


Özdemir, E. (2017). Humor in elementary science: Development and evaluation of comic strips about sound. International Electronic Journal of Elementary Education, 9(4), 837-850.

[Article]     [Google Scholar]


Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students' behavioral intention to use e-learning. Journal of Educational Technology & Society, 12(3), 150-162.

[Article]     [Google Scholar]


Pituch, K. A., & Lee, Y. K. (2006). The influence of system characteristics on e-learning use. Computers & Education, 47(2), 222-244. doi:10.1016/j.compedu.2004.10.007

[Article]     [Google Scholar]


Rafique, H., Almagrabi, A. O., Shamim, A., Anwar, F., & Bashir, A. K. (2020). Investigating the acceptance of mobile library applications with an extended technology acceptance model (TAM). Computers & Education, 145, 103732. doi:10.1016/j.compedu.2019.103732

[Article]     [Google Scholar]


Revythi, A., & Tselios, N. (2019). Extension of technology acceptance model by using system usability scale to assess behavioral intention to use e-learning. Education and Information technologies, 24(4), 2341-2355. doi:10.1007/s10639-019-09869-4

[Article]     [Google Scholar]


Sánchez-Prieto, J. C., Olmos-Migueláñez, S., & García-Peñalvo, F. J. (2017). MLearning and pre-service teachers: An assessment of the behavioral intention using an expanded TAM model. Computers in Human Behavior, 72, 644-654. doi:10.1016/j.chb.2016.09.061

[Article]     [Google Scholar]


Saroia, A. I., & Gao, S. (2019). Investigating university students’ intention to use mobile learning management systems in Sweden. Innovations in Education and Teaching International, 56(5), 569-580. doi:10.1080/14703297.2018.1557068

[Article]     [Google Scholar]


Song, Y., & Kong, S. C. (2017). Investigating students’ acceptance of a statistics learning platform using technology acceptance model. Journal of Educational Computing Research, 55(6), 865-897. doi:10.1177/0735633116688320

[Article]     [Google Scholar]


Taat, M. S., & Francis, A. (2020). Factors influencing the students' acceptance of e-learning at teacher education institute: An exploratory study in Malaysia. International Journal of Higher Education, 9(1), 133-141. doi:10.5430/ijhe.v9n1p133

[Article]     [Google Scholar]


Taherdoost, H. (2018). Development of an adoption model to assess user acceptance of e-service technology: E-Service Technology Acceptance Model. Behaviour & Information Technology, 37(2), 173-197. doi:10.1080/0144929X.2018.1427793

[Article]     [Google Scholar]


Tarhini, A., Hone, K., & Liu, X. (2013). Factors affecting students’ acceptance of e-learning environments in developing countries: a structural equation modeling approach. International Journal of Information and Education Technology (IJIET), 3(1), 54-59. doi:10.7763/IJIET.2013.v3.233

[Article]     [Google Scholar]


Tarhini, A., Hone, K., & Liu, X. (2014). The effects of individual differences on e-learning users’ behaviour in developing countries: A structural equation model. Computers in human behavior, 41, 153-163. doi:10.1016/j.chb.2014.09.020

[Article]     [Google Scholar]


Teeroovengadum, V., Heeraman, N., & Jugurnath, B. (2017). Examining the antecedents of ICT adoption in education using an extended technology acceptance model (TAM). International Journal of Education and Development Using ICT, 13(3), 4-23.

[Article]     [Google Scholar]


Toh, T. L., Cheng, L. P., Ho, S. Y., Jiang, H., & Lim, K. M. (2017). Use of comics to enhance students’ learning for the development of the twenty-first century competencies in the mathematics classroom. Asia Pacific Journal of Education, 37(4), 437-452. doi:10.1080/02188791.2017.1339344

[Article]     [Google Scholar]


Tsai, T. H., Chang, H. T., Chen, Y. J., & Chang, Y. S. (2017). Determinants of user acceptance of a specific social platform for older adults: An empirical examination of user interface characteristics and behavioral intention. PLoS ONE, 12(8), e0180102. doi:10.1371/journal.pone.0180102

[Article]     [Google Scholar]


Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204. doi:10.1287/mnsc.46.2.186.11926

[Article]     [Google Scholar]


Wingo, N. P., Ivankova, N. V., & Moss, J. A. (2017). Faculty perceptions about teaching online: Exploring the literature using the technology acceptance model as an organizing framework. Online Learning, 21(1), 15-35. doi:10.24059/olj.v21i1.761

[Article]     [Google Scholar]


Wu, B., & Zhang, C. (2014). Empirical study on continuance intentions towards E-Learning 2.0 systems. Behaviour & Information Technology, 33(10), 1027-1038. doi:10.1080/0144929X.2014.934291

[Article]     [Google Scholar]


Yeou, M. (2016). An investigation of students’ acceptance of Moodle in a blended learning setting using technology acceptance model. Journal of Educational Technology Systems, 44(3), 300-318. doi:10.1177/0047239515618464

[Article]     [Google Scholar]


Zain, F. M., Hanafi, E., Don, Y., Yaakob, M. F. M., & Sailin, S. N. (2019). Investigating student's acceptance of an EDMODO content management system. International Journal of Instruction, 12(4), 1-16. doi:10.29333/iji.2019.1241a

[Article]     [Google Scholar]

 




DOI: https://doi.org/10.22460/infinity.v10i2.p319-330

Article Metrics

Abstract view : 369 times
PDF - 251 times

Refbacks

  • There are currently no refbacks.




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