Mathematics learning motivated by computer attitude and social media engagement

https://doi.org/10.35912/jshe.v4i2.1575
Published: Feb 1, 2024

Abstract:

Purpose: This study aimed to investigate the impact of computer attitudes and social media engagement on students' motivation to learn mathematics.

Methodology: The study followed a descriptive-correlational approach involving 181 Grade 11 students from three private schools. Questionnaires and statistical tools were used to gather the data.

Results: The results revealed a clear connection between positive computer attitudes and active social media engagement. Moreover, significant evidence has indicated the effectiveness of motivated strategies in improving math learning outcomes. Interestingly, while computer attitudes alone did not significantly influence these strategies, social media engagement had a notable impact.

Limitations: Limited generalizability (specific region, Grade 11 private school focus).

Contribution: Enhances understanding of the link between computer attitude, social media, and motivated strategies in math learning. Emphasize integrating social media to boost motivation and learning outcomes. Valuable for students, teachers, administrators, and officials in shaping effective strategies.

Novelty: One key takeaway is the importance of integrating social media platforms into educational practices to enhance motivation and improve learning outcomes. This study provides valuable insights for students, teachers, administrators, and policymakers as they work together to shape effective learning strategies. Moreover, it offers a unique perspective on the role of technology and social media in fostering motivation and enriching learning experiences.

Keywords:
1. Mathematics
2. Computer Attitude
3. Social media
4. Motivated Strategies
5. Descriptive-Correlational Design
Authors:
1 . Ronald E. Almagro
Sto. Tomas College of Agriculture Sciences and Technology, Philippines
https://orcid.org/0009-0009-9761-807X
2 . MA. Melanie Edig
Davao Del Norte State College, Davao, Philippines
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How to Cite
Almagro, R. E., & Edig, M. M. (2024). Mathematics learning motivated by computer attitude and social media engagement. Journal of Social, Humanity, and Education, 4(2), 79–97. https://doi.org/10.35912/jshe.v4i2.1575
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Issue & Section
Vol. 4 No. 2 (2024): February
Articles
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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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  2. Alabdulkareem, S. A. (2015). Exploring the use and the impacts of social media on teaching and learning science in Saudi. Procedia-Social and Behavioral Sciences, 182, 213-224.
  3. Ayanso, A., & Moyers, D. (2020). Social Media Use in the Public Sector.
  4. Azmidar, A., Darhim, D., & Dahlan, J. (2017). Enhancing students’ interest through mathematics learning. Paper presented at the Journal of Physics: Conference Series.
  5. Barrot, J. S., Llenares, I. I., & Del Rosario, L. S. (2021). Students’ online learning challenges during the pandemic and how they cope with them: The case of the Philippines. Education and Information Technologies, 26(6), 7321-7338.
  6. Begum, F. U., & Hamzah, M. H. (2017). Effect of intrinsic and extrinsic motivation on teachers in secondary schools of Telangana. Pune Research Discovery, 2(2), 1-7.
  7. Boggiano, T. (2017). Modes of interaction in distance education: Recent developments and research questions Handbook of distance education (M. G. Moore & W. G. Anderson ed.): Lawrence Erlbaum Associates Inc.
  8. Burger, A., & Blignaut, P. (2004). A computer literacy course may initially be detrimental to students' attitudes towards computers. Paper presented at the Proceedings of the 2004 annual research conference of the South African institute of computer scientists and information technologists on IT research in developing countries.
  9. Cheah, C. S. (2020). Factors contributing to the difficulties in teaching and learning of computer programming: A literature review. Contemporary Educational Technology, 12(2), ep272.
  10. Chen, C.-H., & Su, C.-Y. (2019). Using the BookRoll e-book system to promote self-regulated learning, self-efficacy and academic achievement for university students. Journal of Educational Technology & Society, 22(4), 33-46.
  11. Chukwuere, J. E., & Bonga, S. O. Y. (2018). An exploration in the influence of social media on university students’ relationships. Paper presented at the WMSCI 2018-22nd World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings.
  12. Chun, J. W., & Lee, M. J. (2017). When does individuals’ willingness to speak out increase on social media? Perceived social support and perceived power/control. Computers in Human Behavior, 74, 120-129.
  13. Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches: Sage publications.
  14. Cuesta, M., Eklund, M., Rydin, I., & Witt, A.-K. (2016). Using Facebook as a co-learning community in higher education. Learning, media and technology, 41(1), 55-72.
  15. Curtis, E. A., Comiskey, C., & Dempsey, O. (2016). Importance and use of correlational research. Nurse researcher, 23(6).
  16. Da?göl, G. D. (2019). The Reasons Of Lack Of Motivation From The Students’and Teachers’voices. The journal of academic social science, 1(1), 35-45.
  17. Daradoumis, T., Marquès Puig, J. M., Arguedas, M., & Calvet Liñan, L. (2022). Enhancing students’ beliefs regarding programming self-efficacy and intrinsic value of an online distributed Programming Environment. Journal of Computing in Higher Education, 34(3), 577-607.
  18. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
  19. de Araujo, Z., Otten, S., & Birisci, S. (2017). Mathematics teachers' motivations for, conceptions of, and experiences with flipped instruction. Teaching and Teacher Education, 62, 60-70.
  20. DeLegge, A., & Wangler, H. (2017). Is this the end for Facebook? A mathematical analysis. Applied Mathematics and Computation, 305, 364-380.
  21. Ekizoglu, N., & Ozcinar, Z. (2010). The relationship between the teacher candidates’ computer and internet based anxiety and perceived self-efficacy. Procedia-Social and Behavioral Sciences, 2(2), 5881-5890.
  22. Garcia, D., & Erlandsson, A. (2011). The relationship between personality and subjective well-being: Different association patterns when measuring the affective component in frequency and intensity. Journal of Happiness Studies, 12, 1023-1034.
  23. Gbollie, C., & Keamu, H. P. (2017). Student academic performance: The role of motivation, strategies, and perceived factors hindering Liberian junior and senior high school students learning. Education Research International.
  24. Gorenko, Y. (2020). The Benefits Of Using Technology In Learning. Retrieved from https://www.teachthought.com/technology/the-benefits-of-using-technology-in-learning-education/
  25. Granito, M., & Chernobilsky, E. (2012). The effect of technology on a student's motivation and knowledge retention.
  26. Gulzar, M. A., Ahmad, M., Hassan, M., & Rasheed, M. I. (2022). How social media use is related to student engagement and creativity: investigating through the lens of intrinsic motivation. Behaviour & Information Technology, 41(11), 2283-2293.
  27. Gwena, C., Chinyamurindi, W. T., & Marange, C. (2018). Motives influencing Facebook usage as a social networking site: An empirical study using international students. Acta Commercii, 18(1), 1-11.
  28. Hannula, M. S., Di Martino, P., Pantziara, M., Zhang, Q., Morselli, F., Heyd-Metzuyanim, E., . . . Jansen, A. (2016). Attitudes, beliefs, motivation and identity in mathematics education: An overview of the field and future directions: Springer Nature.
  29. Harding, S.-M., English, N., Nibali, N., Griffin, P., Graham, L., Alom, B., & Zhang, Z. (2019). Self-regulated learning as a predictor of mathematics and reading performance: A picture of students in Grades 5 to 8. Australian journal of education, 63(1), 74-97.
  30. Hilty, L. M., & Huber, P. (2018). Motivating students on ICT-related study programs to engage with the subject of sustainable development. International Journal of Sustainability in Higher Education, 19(3), 642-656.
  31. Hopper, E. (2021). Understanding Self-Efficacy. Retrieved from https://www.thoughtco.com/self-efficacy-4177970
  32. Hosen, M., Ogbeibu, S., Giridharan, B., Cham, T.-H., Lim, W. M., & Paul, J. (2021). Individual motivation and social media influence on student knowledge sharing and learning performance: Evidence from an emerging economy. Computers & education, 172, 104262.
  33. Ikhsan, R. B., Saraswati, L. A., Muchardie, B. G., & Susilo, A. (2019). The determinants of students' perceived learning outcomes and satisfaction in BINUS online learning. Paper presented at the 2019 5th international conference on new media studies (CONMEDIA).
  34. Kafyulilo, A. C. (2010). Practical Use of ICT in Science and Mathematics Teachers' Training at Dar es Salaam University College of Education: An Analysis of Prospective Teachers' Technological Pedagogical Content Knowledge. Online Submission.
  35. Katz, D. (1964). The motivational basis of organizational behavior. Behavioral science, 9(2), 131-146.
  36. Kukulska-Hulme, A., & Traxler, J. (2013). Design principles for mobile learning Rethinking pedagogy for a digital age (pp. 268-281): Routledge.
  37. Lai, C. (2019). The influence of extramural access to mainstream culture social media on ethnic minority students’ motivation for language learning. British Journal of Educational Technology, 50(4), 1929-1941.
  38. Larbi-Apau, J. A., & Moseley, J. L. (2012). Computer attitude of teaching faculty: implications for technology-based performance in higher education. Journal of Information Technology Education: Research, 11(1), 221-233.
  39. Latif, M. Z., Hussain, I., Saeed, R., Qureshi, M. A., & Maqsood, U. (2019). Use of smart phones and social media in medical education: trends, advantages, challenges and barriers. Acta informatica medica, 27(2), 133.
  40. Lau, W. W. (2017). Effects of social media usage and social media multitasking on the academic performance of university students. Computers in Human Behavior, 68, 286-291.
  41. Lee, J.-A., Nguyen, A. L., Berg, J., Amin, A., Bachman, M., Guo, Y., & Evangelista, L. (2014). Attitudes and preferences on the use of mobile health technology and health games for self-management: interviews with older adults on anticoagulation therapy. JMIR mHealth and uHealth, 2(3), e3196.
  42. Liyanapathirana, V. (2019). Social media use and medical professionals. 28(2).
  43. Madge, C., Meek, J., Wellens, J., & Hooley, T. (2009). Facebook, social integration and informal learning at university:‘It is more for socialising and talking to friends about work than for actually doing work’. Learning, media and technology, 34(2), 141-155.
  44. Mahdizadeh, H., Biemans, H., & Mulder, M. (2008). Determining factors of the use of e-learning environments by university teachers. Computers & education, 51(1), 142-154.
  45. Mahmud, M. M., Ramachandiran, C. R., & Ismail, O. (2018). Social media dependency: The implications of technological communication use among university students. Paper presented at the Redesigning Learning for Greater Social Impact: Taylor’s 9th Teaching and Learning Conference 2016 Proceedings.
  46. Mallem, M., Chavand, F., & Colle, E. (1992). Computer-assisted visual perception in teleoperated robotics. Robotica, 10(2), 93-103.
  47. Mayer, R. E. (2016). The role of metacognition in STEM games and simulations Using games and simulations for teaching and assessment (pp. 207-229): Routledge.
  48. Middleton, J. A., & Spanias, P. A. (1999). Motivation for achievement in mathematics: Findings, generalizations, and criticisms of the research. Journal for Research in Mathematics Education, 30(1), 65-88.
  49. Miller, M. (2005). Teaching and learning in affective domain. Emerging perspectives on learning, teaching, and technology.
  50. Mostafa, R. B. (2015). Engaging students via social media: Is it worth the effort? Journal of Marketing Education, 37(3), 144-159.
  51. Mulenga, E. M., & Marbàn, J. M. (2020). Social media usage among pre-service secondary mathematics teachers in Zambia. Journal of Research and Advances in Mathematics Education, 5(2).
  52. Murthy, D. (2012). Towards a sociological understanding of social media: Theorizing Twitter. Sociology, 46(6), 1059-1073.
  53. Murthy, D. (2018). Introduction to social media, activism, and organizations. Social Media+ Society, 4(1), 2056305117750716.
  54. Musibau, A. A., Oluyinka, S., & Long, C. S. (2011). The relationship between strategic planning and the effectiveness of marketing operations. International Journal of Innovation, Management and Technology, 2(5), 390.
  55. Nickell, G. S., & Pinto, J. N. (1986). The computer attitude scale. Computers in Human Behavior, 2(4), 301-306.
  56. Núñez, J. C., Suárez, N., Rosário, P., Vallejo, G., Cerezo, R., & Valle, A. (2015). Teachers’ feedback on homework, homework-related behaviors, and academic achievement. the Journal of Educational research, 108(3), 204-216.
  57. Ohene-Nyako, M., Persons, A. L., & Napier, T. C. (2018). Region-specific changes in markers of neuroplasticity revealed in HIV-1 transgenic rats by low-dose methamphetamine. Brain Structure and Function, 223, 3503-3513.
  58. Ololube, N. P. (2009). Computer communication and ICT attitude and anxiety among higher education students Encyclopedia of Information Communication Technology (pp. 100-105): IGI Global.
  59. Pajares, F. (2003). Self-efficacy beliefs, motivation, and achievement in writing: A review of the literature. Reading &Writing Quarterly, 19(2), 139-158.
  60. Park, E., Song, H.-D., & Hong, A. J. (2022). The use of social networking services for classroom engagement? The effects of Facebook usage and the moderating role of user motivation. Active learning in higher education, 23(3), 157-171.
  61. Petit, J., & Carcioppolo, N. (2020). Associations between the Dark Triad and online communication behavior: A brief report of preliminary findings. Communication research reports, 37(5), 286-297.
  62. Pintrich, P. R. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ).
  63. Rabinowitz, M. (2017). The interaction between knowledge, strategies, metacognition, and motivation Psychology of learning and motivation (Vol. 67, pp. 35-52): Elsevier.
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