Digital Literacy Stratification: Analyzing how Prior Technology Experience Moderates Intrinsic Motivation on Mobile Gaming
Keywords:
digital literacy stratification; technology acceptance model; self-determination theory; mobile gaming adoption; multi-group analysisAbstract
This study investigates how digital literacy moderates the relationships among intrinsic motivation, Technology Acceptance Model (TAM) perceptions, and mobile gaming adoption among African university students, addressing whether technology acceptance pathways operate uniformly across users with varying technological backgrounds. Combining TAM with Self-Determination Theory, the research conceptualized digital literacy as a fundamental moderator shaping how competency, relatedness, and autonomy influence perceived usefulness, perceived ease of use, behavioral intention, and actual usage. Using a quantitative cross-sectional design, data were collected from 310 Nigerian university students and analyzed through multi-group structural equation modeling. Participants were classified into high (34.8%), moderate (45.2%), and low (20.0%) digital literacy groups based on technology experience profiles across seven platforms. The findings reveal substantial literacy-contingent variation in adoption pathways. Competency effects on perceived ease of use were markedly stronger among low-literacy users, while autonomy significantly predicted perceived usefulness only among digitally experienced users. Perceived ease of use consistently dominated the formation of behavioral intention across all literacy levels. However, actual usage remained constrained by infrastructure and economic barriers, irrespective of user expertise. These findings challenge foundational assumptions within TAM and Self-Determination Theory about the universal applicability of adoption processes, demonstrating instead that motivational hierarchies are conditional on users’ digital proficiency. Hence, the results foreground the need for literacy-sensitive theoretical models and adaptive technology designs that align competency scaffolding, autonomy features, and social integration with users’ digital capacities and proficiency level. Policy interventions that address structural constraints are also necessary to translate adoption intentions into sustained usage within African higher education settings.
https://doi.org/10.26803/ijlter.25.3.16
References
Ajani, O. A., Govender, S., & Gamede, B. T. (2025). Challenges of Learning Management Systems in Enhancing Teaching and Learning: A Study of Undergraduate Students at a Rural University. E-Journal of Humanities, Arts and Social Sciences, 6(10), 2232–2248. https://doi.org/10.38159/ehass.20256101
Ajzen, I. (2011). The theory of planned behaviour: Reactions and reflections. Psychology & Health, 26(9), 1113-1127. https://doi.org/10.1080/08870446.2011.613995
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Prentice-Hall.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Akbulut, Y., Dönmez, O., Ceylan, B., & Firat, T. (2025). Effect of pre-training on cognitive load and achievement in a computer-based learning environment. Journal of Computing in Higher Education. https://doi.org/10.1007/s12528-024-09420-6
Akakpo, M. G., Ahardy, D. O., & Kumankumah, S. S. (2025). Towards digital information literacy guidelines for African libraries: A survey of the relationship between digital and information literacy of university students in Ghana. The Journal of Academic Librarianship, 51(3), 102863. https://doi.org/10.1016/j.acalib.2025.103067
Baidoo-Anu, D., Gyamerah, K., & Munezhi, M. (2023). Digital divide in higher education in Sub-Saharan Africa: evidence from online learning during the COVID-19 pandemic. SN Social Sciences, 3(8), 122. https://doi.org/10.1007/s43545-023-00717-4
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173
Chasubuta, A. R., Ndibalema, P. M., & Loisulie, P. (2024). Technological literacy in using learning management system among students in higher education institutions Tanzania: The case of two selected universities. Educational Technology Quarterly, 2024(1), 76–96. https://doi.org/10.55056/etq.695
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211. https://doi.org/10.2307/249688
Conway, A. R. A., Kane, M. J., & Engle, R. W. (2003). Working memory capacity and its relation to general intelligence. Trends in Cognitive Sciences, 7(12), 547-552. https://doi.org/10.1016/j.tics.2003.10.005
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Dwivedi, Y. K., Rana, N. P., Tamilmani, K., & Raman, R. (2020). A meta-analysis based modified unified theory of acceptance and use of technology (meta-UTAUT): A review of emerging literature. Current Opinion in Psychology, 36, 13-18. https://doi.org/10.1016/j.copsyc.2020.03.008
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
Leila Kajee and Robert Balfor (2011). Students' access to digital literacy at a South African university: Privilege and marginalisation. Southern African Linguistics and Applied Language Studies, 29(2), 185–194. https://doi.org/10.2989/16073614.2011.633365
GSMA. (2023). The mobile gender gap report 2023. GSMA Connected Women. Retrieved from https://www.gsma.com/r/wp-content/uploads/2023/07/The-Mobile-Gender-Gap-Report-2023.pdf
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2019). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage Publications.
Kabakus, A. K., Bahcekapili, E., & Ayaz, A. (2023). The effect of digital literacy on technology acceptance: An evaluation on administrative staff in higher education. Journal of Information Science, 51(4), 930–941. https://doi.org/10.1177/01655515231160028
Krönke, M. (2020). Africa's digital divide and the promise of e-learning (Afrobarometer Policy Paper No. 66). Afrobarometer. Retrieved from https://www.afrobarometer.org/wp-content/uploads/2022/02/pp66-africas_digital_divide_and_the_promise_of_e-learning-afrobarometer_policy_paper-14june20.pdf
Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one's own incompetence led to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121-1134. https://doi.org/10.1037/0022-3514.77.6.1121
Li, L., Hew, K. F., & Du, J. (2024). Gamification enhances student intrinsic motivation, perceptions of autonomy and relatedness, but minimal impact on competency: A meta-analysis and systematic review. Educational Technology Research and Development, 72, 521-555. https://doi.org/10.1007/s11423-023-10337-7
Marakas, G. M., Yi, M. Y., & Johnson, R. D. (1998). The multilevel and multifaceted character of computer self-efficacy: Toward clarification of the construct and an integrative framework for research. Information Systems Research, 9(2), 126–163. https://doi.org/10.1287/isre.9.2.126
Mavutha, W., & Mabotja, T. (2024). Digital literacy: A foreign language for students from rural areas in South Africa. International Journal of Business and Social Science, 13(5), 784–793. https://doi.org/10.30845/ijbss.v13n5p1
Moller, A. C., Kornfield, R., & Lu, A. S. (2024). Competition and digital game design: A self-determination theory perspective. Interacting with Computers, iwae023. https://doi.org/10.1093/iwc/iwae023
Ndibalema, P. (2025). Digital literacy gaps in promoting 21st century skills among students in higher education institutions in Sub-Saharan Africa: A systematic review. Cogent Education, 12(1), Article 2452085. https://doi.org/10.1080/2331186X.2025.2452085
Oluwajana, D., Idowu, A., Nat, M., Vanduhe, V., & Fadiya, S. (2019). The adoption of students' hedonic motivation system model to gamified learning environment. Journal of Theoretical and Applied Electronic Commerce Research, 14(3), 156–167. https://doi.org/10.4067/S0718-18762019000300109
Oni, A. A., Ajayi, D., & Randle, O. A. (2025). Critical factors influencing the adoption of mobile games in African students: Case of an extended technology acceptance model. Educational Process: International Journal, 19, e2025546. https://doi.org/10.22521/edupij.2025.19.546
Papadakis, S., Kalogiannakis, M., & Zaranis, N. (2018). Educational apps from the Android Google Play for Greek preschoolers: A systematic review. Computers & Education, 116, 139–160. https://doi.org/10.1016/j.compedu.2017.09.007
Pierce, G. L., & Cleary, P. F. (2024). The persistent educational digital divide and its impact on societal inequality. PLoS ONE, 19(4), e0286795. https://doi.org/10.1371/journal.pone.0286795
Randle, O. A. (2024). The roles of riddles, puzzles, and narratives as pedagogy in video games: A case of African-themed video games. Journal of Black Studies, 55(8), 661–683. https://doi.org/10.1177/00219347241278383
Randle, O. A., & Ajayi, D. (2025). Influence of computer self-efficacy, socio economic status, and facilitating conditions on the learning abilities of digital arts students. International Journal of Learning, Teaching and Educational Research, 24(7), 1–17. https://www.ijlter.org/index.php/ijlter/article/view/13356
Randle, O. A., Ajayi, D., & Kaka, F. (2025). Adoption of technology in the promotion of translanguaging in African higher education. International Journal of Learning, Teaching and Educational Research, 24(12), 1-17. https://www.ijlter.org/index.php/ijlter/article/view/15049
Randle, O. A., & Kayode, O. (2025). Examining the factors influencing undergraduate students' use of digital arts playrooms in South African university game studies programs. African Perspectives of Research in Teaching and Learning, 9(1), 60–71. https://doi.org/10.70875/v9i1article5
Rosli, M. S., & Saleh, N. S. (2022). Technology enhanced learning acceptance among university students during Covid-19: Integrating the full spectrum of Self-Determination Theory and self-efficacy into the Technology Acceptance Model. Current Psychology, 43, 5684-5703. https://doi.org/10.1007/s12144-022-02996-1
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68-78. https://doi.org/10.1037/0003-066X.55.1.68
Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, Article 101860. https://doi.org/10.1016/j.cedpsych.2020.101860
Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Press.
Sarstedt, M., Hair, J. F., Cheah, J.-H., Becker, J.-M., & Ringle, C. M. (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian Marketing Journal, 27(3), 197-211. https://doi.org/10.1016/j.ausmj.2019.05.003
Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review, 84(1), 1-66. https://doi.org/10.1037/0033-295X.84.1.1
Schwartz, B. (2004). The paradox of choice: Why more is less. Harper Perennial.
Shi, Y.-D., Feng, H.-X., Liu, J., Ma, Y.-L., & Xiao, Q. (2024). Mobile online game experience and community interaction: Mechanisms affecting user satisfaction. Acta Psychologica, 251, 104591. https://doi.org/10.1016/j.actpsy.2024.104591
Thompson, R. L., Compeau, D. R., & Higgins, C. A. (2006). Intentions to use information technologies: An integrative model. Journal of Organizational and End User Computing, 18(3), 25–46. https://doi.org/10.4018/joeuc.2006070102
Turner, M., Kitchenham, B., Brereton, P., Charters, S., & Budgen, D. (2010). Does the technology acceptance model predict actual use? A systematic literature review. Information and Software Technology, 52(5), 463–479. https://doi.org/10.1016/j.infsof.2009.11.005
UNESCO. (2018). A global framework of reference on digital literacy skills for indicator 4.4.2. UNESCO Institute for Statistics. Retrieved from http://uis.unesco.org/sites/default/files/documents/ip51-global-framework-reference-digital-literacy-skills-2018-en.pdf
Vansteenkiste, M., Ryan, R. M., & Soenens, B. (2020). Basic psychological need theory: Advancements, critical themes, and future directions. Motivation and Emotion, 44, 1-31. https://doi.org/10.1007/s11031-019-09818-1
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
World Bank. (2020). The African digital economy: Opportunities and challenges. World Bank Group. Retrieved from https://www.worldbank.org/en/region/afr/publication/the-african-digital-economy
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 David Ajayi, Aderonke Oni, Olu Randle
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All articles published by IJLTER are licensed under a Creative Commons Attribution Non-Commercial No-Derivatives 4.0 International License (CCBY-NC-ND4.0).
