The Role of Attitude Toward Learning, Interest in Learning and Digital Literacy in Inventive Thinking Skill: SEM Approach

Eka Ad'hiya, Rodi Edi, Fitrah Amini, Deika Zhillan Fatharani, Diah Kartika Sari, Maefa Eka Haryani

Abstract


The urgency of this research stems from a follow-up to previous research that mapped the level of inventive thinking among chemistry education students at Sriwijaya University, which was found to be at a moderate level. Therefore, it is necessary to conduct further analysis of the factors that influence inventive thinking. This study aims to determine the relationships among Attitude toward Learning, Interest in Learning, and Digital Literacy and Inventive Thinking among Chemistry Education Students at Sriwijaya University. This research is a quantitative, cross-sectional study. Data were collected through a survey. The instrument used was a 59-item Likert-type questionnaire with 4 points on the scale. The questionnaire included 23 items on inventive thinking, 18 on attitude toward learning, 8 on interest in learning, and 10 on digital literacy. The sample for this study consisted of students in the Chemistry Education study program at Sriwijaya University. The research data were analyzed using Structural Equation Modeling (SEM). The results of the measurement model test indicated 26 indicators that were valid and reliable. The results of the structural model evaluation showed no multicollinearity problems, and the model explained 61.1% of the variance in the inventive thinking variable, which was classified as high. The results of the path coefficient significance test showed that only Hypothesis 3 had a t-statistic greater than 1.96 and a p-value less than 0.05, indicating that only digital literacy had a positive and significant effect on inventive thinking. Then the results of this research will have implications for the development of learning designs/learning environments that can support the inventive thinking of chemistry education students by integrating learning with digital literacy.

Keywords


Attitude toward Learning; Interest in Learning; Digital Literacy; Inventive Thinking; SEM.

Full Text:

DOWNLOAD [PDF]

References


Ab Hamid, M. R., Sami, W., & Mohmad Sidek, M. H. (2017). Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT Criterion. Journal of Physics: Conference Series, 890(1), 1–5. https://doi.org/10.1088/1742-6596/890/1/012163

Ad'hiya, E., Haryani, M. E., Edi, R., Sari, D. K., & Savitri, N. N. (2025). Assessing Inventive Thinking Using Rasch Model. SPEKTRA: Jurnal Kajian Pendidikan Sains, 11(1), 1-10. https://doi.org/10.32699/spektra.v11i1.8009

Ad’hiya, E., Haryani, M. E., Edi, R., & Sari, D. K. (2024). Analysis Of The Relationship Of Inventive Thinking And Science-Related Attitude. ALOTROP, 8(2), 1–8. https://doi.org/10.33369/alo.v8i2.37518

Ad’Hiya, E., & Laksono, E. W. (2018). Students’ analytical thinking skills and chemical literacy concerning chemical equilibrium. AIP Conference Proceedings, 2021. https://doi.org/10.1063/1.5062824

Afandi, ’Alia Nur Husna, Kusumaningrum, S. R., Dewi, R. S. I., & Pristiani, R. (2024). Digital Literacy Questionnaire Instrument: Based on the Integration of Elementary School Students’ Characteristics. International Journal of Elementary Education, 8(2), 344–353. https://doi.org/10.23887/ijee.v8i2.76773

Amora, J. T. (2021). Convergent validity assessment in PLS-SEM: A loadings-driven approach. Data Analysis Perspectives Journal, 2(1), 1–6. https://scriptwarp.com/dapj/2021_DAPJ_2_3/Amora_2021_DAPJ_2_3_ConvergentValidity.pdf

Anggraini, L., Maison, & Syaiful. (2022). Attitude and Understanding of Concepts: It’s Influence in Science Learning. Journal of Education Research and Evaluation, 6(3), 423–430. https://doi.org/10.23887/jere.v6i3.45991

Ardhiani, O., Noor, M., Hadjam, R., & Fitriani, D. R. (2023). Digital Literacy and Student Academic Performance in Unversities: A Meta-analysis. Journal Of Psychology And Instruction, 7(3), 103–113. https://doi.org/10.23887/jpai.v5i2

Cheng, C. L., Shalabh, & Garg, G. (2014). Coefficient of determination for multiple measurement error models. Journal of Multivariate Analysis, 126(1), 137–152. https://doi.org/10.1016/j.jmva.2014.01.006

Cheung, G. W., Cooper-Thomas, H. D., Lau, R. S., & Wang, L. C. (2024a). Reporting reliability, convergent and discriminant validity with structural equation modeling: A review and best-practice recommendations. Asia Pacific Journal of Management, 41(2), 745–783. https://doi.org/10.1007/s10490-023-09871-y

Cheung, G. W., Cooper-Thomas, H. D., Lau, R. S., & Wang, L. C. (2024b). Reporting reliability, convergent and discriminant validity with structural equation modeling: A review and best-practice recommendations. Asia Pacific Journal of Management, 41(2), 745–783. https://doi.org/10.1007/s10490-023-09871-y

Feyza, N. E., & Seyda, S. Y. (2023). 21st Century Skills and Learning Environments: ELT Students Perceptions. Educational Research and Reviews, 18(6), 114–128. https://doi.org/10.5897/err2023.4332

Firdaus, E., Andrikasmi, S., Hermita, N., & Wijaya, T. T. (2025). Investigating factors influencing bullying behavior reduction and gender differences in higher education: A structural equation modeling approach. Acta Psychologica, 253(1), 1–11. https://doi.org/10.1016/j.actpsy.2025.104747

Hair, J., & Alamer, A. (2022a). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 1–16. https://doi.org/10.1016/j.rmal.2022.100027

Hair, J., & Alamer, A. (2022b). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 1–16. https://doi.org/10.1016/j.rmal.2022.100027

Hair, J., Hult, G., Ringle, C., Sarstedt, M., Danks, N., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. Springer. https://link.springer.com/book/10.1007/978-3-030-80519-7

Haji-Othman, Y., & Yusuff, M. S. S. (2022). Assessing Reliability and Validity of Attitude Construct Using Partial Least Squares Structural Equation Modeling (PLS-SEM). International Journal of Academic Research in Business and Social Sciences, 12(5), 378–384. https://doi.org/10.6007/ijarbss/v12-i5/13289

Hasanati*, A., & Purwaningsih, E. (2021). Influence of Interest In Learning and How to Learn on Understanding Concepts: Work and Energy Cases. Indonesian Journal of Science Education, 9(2), 305–316. https://doi.org/10.24815/jpsi.v9i2.19203

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8

Ihsan Khairi, M., & Susanti, D. (2021). Study on Structural Equation Modeling for Analyzing Data. International Journal of Ethno-Sciences and Education Research, 1(3), 52–60. https://journal.rescollacomm.com/index.php/ijeer/article/view/295/240

Lestari Pasaribu, R., Mirza, A., Aldila Afriansyah, E., Hadari Nawawi, J. H., & Kalimantan, W. (2023). Students’ Scientific Attitudes and Creative Thinking Skills. Mosharafa: Journal of Mathematics Education, 12(2), 315–326. http://journal.institutpendidikan.ac.id/index.php/mosharafa

Lim, Y. W., Darmesah, G., Pang, N. T. P., & Ho, C. M. (2023). A bibliometric analysis of the structural equation modeling in mathematics education. Eurasia Journal of Mathematics, Science and Technology Education, 19(12), 1–9. https://doi.org/10.29333/ejmste/13838

Listiani, I., Susilo, H., & Sueb, S. (2022). Relationship between Scientific Literacy and Critical Thinking of Prospective Teachers. AL-ISHLAH: Journal of Education, 14(1), 721–730. https://doi.org/10.35445/alishlah.v14i1.1355

Maier, C., Thatcher, J. B., Grover, V., & Dwivedi, Y. K. (2023). Cross-sectional research: A critical perspective, use cases, and recommendations for IS research. In International Journal of Information Management (Vol. 70, Issue 1, pp. 1–6). Elsevier Ltd. https://doi.org/10.1016/j.ijinfomgt.2023.102625

Marwati, Jasruddin, & Arafah, K. (2024). The Influence of Learning Interest, Emotional Intelligence and Achievement Motivation on the Critical Thinking Ability of Physics of Class XI Students at UPT SMAN 4 Bantaeng. Journal of Science Education Research, 10(12), 10076–10082. https://doi.org/10.29303/jppipa.v10i12.8891

Megasafitri, * R, Roesminingsih, M. V, & Jacky, M. (2023). The Influence of Digital Literacy in Online Learning on Student Learning Outcomes. Studies in Philosophy of Science and Education, 4(2), 88–03. https://doi.org/10.46627/sipose

Miah, M. S., Singh, J. S. K., & Rahman, M. A. (2023). Factors Influencing Technology Adoption in Online Learning among Private University Students in Bangladesh Post COVID-19 Pandemic. Sustainability, 15(4), 1–12. https://doi.org/10.3390/su15043543

Mulyamti, H. S., & Tarumingkeng, R. C. (2025). The Influence Of Interest In Learning And Student Discipline ON Learning Outcomes Mediated By Learning Motivation (Study In Smpn 197 West Jakarta). Journal of Islamic Social and Religious Research, 22(1), 46–60. https://doi.org/10.19105/nuansa.v18i1.xxxx

Nursiwan, W. A., & Hanri, C. (2023). Relationship between level of scientific creativity and scientific attitudes among prospective chemistry teachers. International Journal of Evaluation and Research in Education, 12(1), 174–179. https://doi.org/10.11591/ijere.v12i1.22852

Primastami, R. J., & Insani, N. H. (2024). Investigating the Impact of Learning Interest on Student Achievement in Javanese Language Courses at State Senior High Schools. AL-ISHLAH: Journal of Education, 16(4). https://doi.org/10.35445/alishlah.v16i4.5669

Putu Gede Subhaktiyasa. (2024). PLS-SEM for Multivariate Analysis: A Practical Guide to Educational Research using SmartPLS. EduLine: Journal of Education and Learning Innovation, 4(3), 353–365. https://doi.org/10.35877/454ri.eduline2861

Saifulkhair Omar, M., & Isha Awang, M. (2021). The Relationship Between Attitude And Higher Order Thinking Skills (Hots) Among Secondary School Students. Article in Turkish Journal of Computer and Mathematics Education, 12(7), 82–90. https://turcomat.org/index.php/turkbilmat/article/view/2547/4235

Salma, A., Fitria, D., & Syafriandi, S. (2020). Structural Equation Modelling: The Affecting of Learning Attitude on Learning Achievement of Students. Journal of Physics: Conference Series, 1554(1). https://doi.org/10.1088/1742-6596/1554/1/012056

Samad, N. A., Osman, K., & Nayan, N. A. (2023). Learning chemistry through designing and its effectiveness towards inventive thinking. Eurasia Journal of Mathematics, Science and Technology Education, 19(12), 1–15. https://doi.org/10.29333/ejmste/13883

Sappaile, B. I., Abeng, A. T., & Nuridayanti, N. (2023). Exploratory Factor Analysis as a Tool for Determining Indicators of a Research Variable: Literature Review. International Journal of Educational Narratives, 1(6), 304–313. https://doi.org/10.55849/ijen.v1i6.387

Setyaedhi, H. S., & Pramana, A. (2025). The influence of Digital Literacy and Learning Independence on Learning Outcomes in Statistics Courses. Journal of Education Technology, 9(1), 51–63. https://doi.org/10.23887/jet.v9i1.822

Shopia, K., & Fadhil, M. R. (2025). Teachers’ Feedback in Integrating Ways of Thinking and ICT Competences in Learning Activity English. In International Journal Of Humanities Education And Social Sciences (IJHESS) E-ISSN (Vol. 5, Issue 1). https://ijhess.com/index.php/ijhess/

Sokol, A., Oget, D., Sonntag, M., & Khomenko, N. (2008). The development of inventive thinking skills in the upper secondary language classroom. Thinking Skills and Creativity, 3(1), 34–46. https://doi.org/10.1016/j.tsc.2008.03.001

Sujati, H., Sajidan, Akhyar, M., & Gunarhadi. (2020). Testing the construct validity and reliability of curiosity scale using confirmatory factor analysis. Journal of Educational and Social Research, 10(4), 229–237. https://doi.org/10.36941/JESR-2020-0080

Syed Hassan, S. S. (2018). Measuring attitude towards learning science in Malaysian secondary school context: implications for teaching. International Journal of Science Education, 40(16), 2044–2059. https://doi.org/10.1080/09500693.2018.1518614

Taber, K. S. (2018). The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2

Turiman, P., Osman, K., & Wook, T. S. M. T. (2020a). Inventive thinking 21st century skills among preparatory course science students. Asia Pacific Journal of Educators and Education, 35(2), 145–170. https://doi.org/10.21315/APJEE2020.35.2.9

Turiman, P., Osman, K., & Wook, T. S. M. T. (2020b). Inventive thinking 21st century skills among preparatory course science students. Asia Pacific Journal of Educators and Education, 35(2), 145–170. https://doi.org/10.21315/APJEE2020.35.2.9




DOI: https://doi.org/10.31764/ijeca.v8i3.36302

Refbacks

  • There are currently no refbacks.


Copyright (c) 2025 Eka Ad'hiya, Rodi Edi1, Fitrah Amini, Deika Zhillan Fatharani, Diah Kartika Sari, Maefa Eka Haryani

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

IJECA (International Journal of Education and Curriculum Application) already indexed:

            

___________________________________________________________________

  
   https://doi.org/10.31764/ijeca.

   Creative Commons License
   IJECA (International Journal of Education and Curriculum Application)
   is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

 View IJECA Stats

____________________________________________________________________

 IJECA Publisher Office: