The Impact of Cognitive Skill, and Individual Innovativeness on Digital Formal Learning Mediated by Attitude to Use Interactive Worksheet Digital




Cognitive skill, individual innovativeness, attitude to use worksheet digital, digital formal learning


This research explores the essence of cognitive skill and individual innovativeness in junior high school students in Bali Province, influencing digital formal learning across a mediator variable. This study proposes to provide the comprehension of digital technology used by students that focus on attitude to use interactive worksheet digital as a mediator for supporting digital formal learning. The study analyzes sampling data from 167 students in the junior high school in Buleleng Regency by partial least square-path modeling. The findings reveal that cognitive skill and individual innovativeness in digital formal learning are partially mediated by attitude to digitally using interactive worksheets. The finding discovers students’ attitudes toward using digital tools that enhance their output, such as accomplishing tasks more effectively and delivering satisfying learning.

Author Biographies

Dessy Seri Wahyuni, Universitas Pendidikan Ganesha

Department of Informatics and Engineering Education

Gede Ariadi, Universitas Kristen Satya Wacana

Department of Management, Faculty of Economics and Business


R. T. Kompen, P. Edirisingha, X. Canaleta, M. Alsina, and J. M. Monguet, “Personal learning Environments based on Web 2.0 services in higher education,” Telemat. informatics, vol. 38, pp. 194–206, 2019.

D. Song and J. Lee, “Has W eb 2.0 revitalized informal learning? The relationship between W eb 2.0 and informal learning,” J. Comput. Assist. Learn., vol. 30, no. 6, pp. 511–533, 2014.

W.-H. D. Huang and E. Oh, “Retaining disciplinary talents as informal learning outcomes in the digital age: An exploratory framework to engage undergraduate students with career decision-making processes,” in Handbook of research on learning outcomes and opportunities in the digital age, IGI Global, 2016, pp. 402–420.

N. N. Chan, C. Walker, and A. Gleaves, “An exploration of students’ lived experiences of using smartphones in diverse learning contexts using a hermeneutic phenomenological approach,” Comput. Educ., vol. 82, pp. 96–106, 2015.

L. M. Ungerer, “Digital curation as a core competency in current learning and literacy: A higher education perspective,” Int. Rev. Res. Open Distrib. Learn., vol. 17, no. 5, 2016.

L. Austen, H. Parkin, S. Jones-Devitt, K. McDonald, and B. Irwin, “Digital capability and teaching excellence: an integrative review exploring what infrastructure and strategies are necessary to support effective use of technology enabled learning (TEL),” 2016.

D. S. Wahyuni, K. Agustini, G. Ariadi, I. N. E. Mertayasa, and N. Sugihartini, “The impact of external knowledge on organization performance with indirect effect of instructional agility and process innovation effectiveness,” in Journal of Physics: Conference Series, 2021, vol. 1810, no. 1, p. 12074.

Y.-M. Cheng, “Exploring the intention to use mobile learning: the moderating role of personal innovativeness,” J. Syst. Inf. Technol., 2014.

C. Lai, Q. Wang, and J. Lei, “What factors predict undergraduate students’ use of technology for learning? A case from Hong Kong,” Comput. Educ., vol. 59, no. 2, pp. 569–579, 2012, doi: 10.1016/j.compedu.2012.03.006.

S. Batra and N. Vohra, “Exploring the linkages of cognitive style and individual innovativeness,” Manag. Res. Rev., 2016.

V. Venkatesh, A.-M. Croteau, and J. Rabah, “Perceptions of effectiveness of instructional uses of technology in higher education in an era of Web 2.0,” in 2014 47th Hawaii international conference on system sciences, 2014, pp. 110–119.

G. M. Troiano et al., “Is my game OK Dr. Scratch? Exploring programming and computational thinking development via metrics in student-designed serious games for STEM,” in Proceedings of the 18th ACM international conference on interaction design and children, 2019, pp. 208–219.

R. Mbarek, “E-Learning Effectiveness: A Survey in Two Tunisian Higher Education Establishments Using an Educational Platform,” in International Conference on Digital Economy, 2018, pp. 153–164.

X. Huang, C.-H. Lin, M. Sun, and P. Xu, “Metacognitive skills and self-regulated learning and teaching among primary school teachers: The mediating effect of enthusiasm,” Metacognition Learn., pp. 1–23, 2022.

D. S. Wahyuni, K. Agustini, and G. Ariadi, “An AHP-Based Evaluation Method for Vocational Teacher‘s Competency Standard,” Int. J. Inf. Educ. Technol., vol. 12, no. 2, pp. 157–164, 2022, doi: 10.18178/ijiet.2022.12.2.1599.

E. Van Laar, A. J. A. M. Van Deursen, J. A. G. M. Van Dijk, and J. De Haan, “The relation between 21st-century skills and digital skills: A systematic literature review,” Comput. Human Behav., vol. 72, pp. 577–588, 2017.

H. McNeill and D. Polly, “Exploring Primary Grades Teachers’ Perceptions of their Students’ Mathematics Self-Efficacy and How they Differentiate Instruction,” Early Child. Educ. J., pp. 1–10, 2021.

G. Naveh and A. Shelef, “Analyzing attitudes of students toward the use of technology for learning: simplicity is the key to successful implementation in higher education,” Int. J. Educ. Manag., 2020.

P. Patil, K. Tamilmani, N. P. Rana, and V. Raghavan, “Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal,” Int. J. Inf. Manage., vol. 54, p. 102144, 2020.

Y. J. Joo, H. W. Lee, and Y. Ham, “Integrating user interface and personal innovativeness into the TAM for mobile learning in Cyber University,” J. Comput. High. Educ., vol. 26, no. 2, pp. 143–158, 2014.

J. D. Jackson, Y. Y. Mun, and J. S. Park, “An empirical test of three mediation models for the relationship between personal innovativeness and user acceptance of technology,” Inf. Manag., vol. 50, no. 4, pp. 154–161, 2013.

O. Oktay, Z. Avcı, and A. I. Sen, “Using digital media through sequential worksheets: an astronomy activity,” Sci. Act., pp. 1–18, 2022.

T. He and C. Zhu, “Digital informal learning among Chinese university students: the effects of digital competence and personal factors,” Int. J. Educ. Technol. High. Educ., vol. 14, no. 1, 2017, doi: 10.1186/s41239-017-0082-x.

A.-M. M. Gasaymeh, A. M. Al-Tawel, K. G. Al-Moghrabi, and A. M. Al-Ghonmein, “University students’ perceptions of the use of digital technologies in their formal learning: a developing country perspective,” Int. J. Learn. Dev., vol. 7, no. 3, pp. 149–164, 2017.

C. Fornell and D. F. Larcker, “Evaluating structural equation models with unobservable variables and measurement error,” J. Mark. Res., vol. 18, no. 1, pp. 39–50, 1981.

J. F. Hair Jr, M. Sarstedt, L. Hopkins, and V. G. Kuppelwieser, Partial least squares structural equation modeling (PLS-SEM), vol. 26, no. 2. 2014.

D. S. Wahyuni, P. Sudira, K. Agustini, and G. Ariadi, “The effect of external learning on vocational high school performance with mediating role of instructional agility and product innovation efficacy in Indonesia,” Manag. Sci. Lett., vol. 10, no. 16, 2020, doi: 10.5267/j.msl.2020.7.017.