Intelligent Mobile System for Student Performance Evaluation: Model Testing Using Structural Equation Modeling

Authors

  • Andhika Herayono Universitas Negeri Padang, Padang, Indonesia
  • Muhammad Anwar Universitas Negeri Padang, Padang, Indonesia
  • Elfi Tasrif Universitas Negeri Padang, Padang, Indonesia
  • Qothrun Nada Ma’ruf Batubara Universitas Negeri Padang, Padang, Indonesia; Universitas Negeri Medan, Medan, Indonesia

DOI:

https://doi.org/10.3991/ijim.v20i04.60101

Keywords:

Student Performance Evaluation (SPE), intelligent mobile system, expert system, Structural Equation Modeling (SEM), higher education, evaluation model, technology-based learning

Abstract


Student performance evaluation is a crucial aspect of improving the quality of higher education. This study aims to develop and test an intelligent mobile system based on expert systems for evaluating students’ academic performance. The model is designed to identify key factors influencing student performance and provide more objective, data-driven assessments. Structural equation modeling (SEM) is used to analyze the relationships between variables involved in this evaluation system. Data were collected from students in Universitas Negeri Padang, with students from several departments, and analyzed using SEM to test the validity and reliability of the developed model. The findings indicate that this intelligent mobile system enhances the accuracy of student performance evaluation and provides deeper insights for academic decision-makers. With the implementation of this expert system, educational institutions can optimize learning strategies and academic management more effectively.

References

[1] C. Stöhr, C. Demazière, and T. Adawi, “The polarizing effect of the online flipped classroom,” Comput. Educ., vol. 147, no. December 2019, 2020, doi: 10.1016/j.compedu.2019.103789.

[2] C. Dyah, S. Indrawati, P. Ninghardjanti, C. Huda, and A. Dirgatama, “The effect of practicum learning based audiovisual on students ’ learning outcomes in Indonesian vocational secondary school,” vol. 11, no. 1, pp. 403–408, 2022, doi: 10.11591/ijere.v11i1.21762.

[3] Y. B. Bhakti, B. Tola, and D. D. Triana, “AITPO ( ANTECEDENT , INPUT , TRANSACTION , PRODUCT , OUTCOMES ): MIXED MODEL EVALUASI CIPP DAN COUNTENACE SEBAGAI PENDEKATAN EVALUASI PROGRAM KAMPUS,” vol. 3, no. 1, pp. 11–24, 2022.

[4] R. M. Tawafak, M. N. Mohammed, and A. Arshah, “Review on the Effect of Student Learning Outcome and Teaching Technology in Omani ’ s Higher Education Institution ’ s A cademic Accreditation Process,” pp. 1–5, 2018.

[5] M. Sheikhkhoshkar, F. Pour Rahimian, M. H. Kaveh, M. R. Hosseini, and D. J. Edwards, “Automated planning of concrete joint layouts with 4D-BIM,” Autom. Constr., vol. 107, no. July, p. 102943, 2019, doi: 10.1016/j.autcon.2019.102943.

[6] N. M. Nawi, A. O. Mydin, A. T. Nursal, F. Akmar, A. Nifa, and A. Y. Bahaudin, “Payment issues in Malaysia Industrialised Building System ( IBS ): Literature visit,” vol. 9, no. March, pp. 185–188, 2015.

[7] C. M. Reigeluth and Y. An, Merging the Instructional Design Process with Learner-Centered Theory. Routledge, 2020.

[8] F. M. Talaat, “An improved fire detection approach based on YOLO-v8 for smart cities,” Neural Comput. Appl., vol. 35, no. 28, pp. 20939–20954, 2023, doi: 10.1007/s00521-023-08809-1.

[9] E. Khairani, H. Maksum, F. Rizal, and M. Adri, “Validitas pengembangan modul pembelajaran berbasis project based learning pada mata pelajaran teknologi informasi dan komunikasi,” JRTI (Jurnal Ris. Tindakan Indones., vol. 7, no. 2, p. 71, 2022, doi: 10.29210/30031489000.

[10] S. Abadi et al., “Implementation of fuzzy analytical hierarchy process on notebook selection,” vol. 7, pp. 238–243, 2018.

[11] H. A. Alismail, “Heliyon Teachers ’ perspectives of utilizing distance learning to support 21st century skill attainment for K-3 elementary students during the COVID-19 pandemic era,” Heliyon, vol. 9, no. 9, p. e19275, 2023, doi: 10.1016/j.heliyon.2023.e19275.

[12] M. Anwar, “Prediction of the graduation rate of engineering education students using Artificial Neural Network Algorithms,” Int. J. Res. Couns. Educ., vol. 5, no. 1, p. 15, 2021, doi: 10.24036/00411za0002.

[13] X. Song, Y. Cong, Y. Song, Y. Chen, and P. Liang, “A bearing fault diagnosis model based on CNN with wide convolution kernels,” J. Ambient Intell. Humaniz. Comput., vol. 13, no. 8, pp. 4041–4056, 2022, doi: 10.1007/s12652-021-03177-x.

[14] M. Anwar and A. Herayono, “The Effect of Theory of Planned Behavior ( TBP ) and Creativity-Based Industry Perception on Digital Entrepreneurship : An Innovativeness as Mediator,” vol. 40, pp. 96–105, 2024.

[15] H. Nofrianto, J. Jama, A. Indra, B. Rahim, S. Wardi, and U. Verawardina, “Validity of Cooperative-Discovery Learning Model to Improve Competencies of Engineering Students,” vol. 11, no. 12, pp. 1134–1138, 2020.

[16] A. T. Nursal, M. F. Omar, M. Nasrun, and M. Nawi, “Text Pre-Processing for The Frequently Mentioned Criteria from Online Community Homebuyer Dataset,” vol. 15, no. 06, pp. 171–184, 2021.

[17] I. R. Suwarma and S. Apriyani, “Explore Teachers’ Skills in Developing Lesson Plan and Assessment That Oriented on Higher Order Thinking Skills (HOTS),” J. Innov. Educ. Cult. Res., vol. 3, no. 2, pp. 106–113, 2022, doi: 10.46843/jiecr.v3i2.66.

[18] H. D. Surjono, A. Muhtadi, and N. Trilisiana, “The effects of online activities on student learning outcomes in blended learning environment,” ACM Int. Conf. Proceeding Ser., pp. 107–110, 2019, doi: 10.1145/3345120.3345167.

[19] K. Nuringsih and M. N. Nuryasman, “The role of green entrepreneurship in understanding indonesia economy development sustainability among young adults,” Estud. Econ. Apl., vol. 39, no. 12, pp. 1–13, 2021, doi: 10.25115/eea.v39i12.6021.

[20] S. Ramadhan, R. Sumiharsono, D. Mardapi, and Z. K. Prasetyo, “The quality of test instruments constructed by teachers in bima regency, Indonesia: Document analysis,” Int. J. Instr., vol. 13, no. 2, pp. 507–518, 2020, doi: 10.29333/iji.2020.13235a.

[21] D. Zhang et al., “Psychometric properties of the Coronavirus Anxiety Scale based on Classical Test Theory ( CTT ) and Item Response Theory ( IRT ) models among Chinese front ‑ line healthcare workers,” BMC Psychol., pp. 1–10, 2023, doi: 10.1186/s40359-023-01251-x.

[22] A. Carolus, Y. Augustin, and C. Wienrich, “Computers and Education : Artificial Intelligence Digital interaction literacy model – Conceptualizing competencies for literate interactions with voice-based AI systems,” vol. 4, no. November 2022, 2023, doi: 10.1016/j.caeai.2022.100114.

[23] Surniati Chalid, Nurhayati Tanjung, Yudhistira Anggraini, and Eka Rahma Dewi, “Development of Media Cad Richpeace Grading System for the Making of Home Clothing Pattern in Fashion Education Study Program, Medan State University,” Int. J. Innov. Technol. Soc. Sci., no. 4(36), pp. 0–9, 2022, doi: 10.31435/rsglobal_ijitss/30122022/7933.

[24] S. Michelsen and M. L. Stenström, Vocational Education in the Nordic Countries: The Historical Evolution. 2018.

[25] O. Ibiyemi et al., “Developing an Oral Hygiene Education Song for Children and Teenagers in Nigeria,” Int. Dent. J., vol. 72, no. 6, pp. 866–871, 2022, doi: 10.1016/j.identj.2022.06.008.

[26] W. Yustanti, Y. Anistyasari, and E. M. Imah, “Determining student’s single tuition fee category using correlation based feature selection and support vector machine,” 2017 Int. Conf. Adv. Comput. Sci. Inf. Syst. ICACSIS 2017, vol. 2018-Janua, pp. 172–176, 2018, doi: 10.1109/ICACSIS.2017.8355029.

[27] N. Fatkhi and N. Achyar, “THE NEEDS FOR DEVELOPING THE SABU-SABU METHOD TO INCREASE THE READING INTEREST OF STUDENTS,” vol. 3, no. 1, pp. 14–22, 2024.

[28] R. Darni, L. Mursyida, and A. D. Samala, “Career Exploration System (C-EXSYS) in Era Society 5.0 Based on Expert System,” J. Teknol. Inf. dan Pendidik., vol. 14, no. 2, pp. 131–143, 2021, doi: 10.24036/tip.v14i2.491.

[29] Y. Indarta, A. Ambiyar, F. Rizal, F. Ranuharja, A. D. Samala, and I. P. Dewi, “Studi Literatur : Peranan Model-Model Pembelajaran Inovatif Bidang Pendidikan Teknologi Kejuruan,” Edukatif J. Ilmu Pendidik., vol. 4, no. 4, pp. 5762–5772, 2022, doi: 10.31004/edukatif.v4i4.2721.

[30] A. D. Samala, S. Rawas, S. Criollo-c, O. Bondarenko, A. G. Samala, and D. Novaliendry, “Harmony in Education : An In-Depth Exploration of Indonesian Academic Landscape , Challenges , and Prospects Towards the Golden Generation 2045 Vision,” vol. 13, no. 3, pp. 2436–2456, 2024, doi: 10.18421/TEM133.

[31] R. Ramadhani, N. S. Bina, S. F. Sihotang, S. D. Narpila, and M. R. Mazaly, “Students’ critical mathematical thinking abilities through flip-problem based learning model based on LMS-google classroom,” J. Phys. Conf. Ser., vol. 1657, no. 1, 2020, doi: 10.1088/1742-6596/1657/1/012025.

[32] F. A. Darmawan and A. Jaedun, “Mediation Effect of Assessment as Learning in Mobile-Based Module on Vocational Education Studentâ€TMs HOTS,” J. Educ. Sci. Technol., pp. 32–39, 2020, doi: 10.26858/est.v6i1.11437.

[33] R. A. Madani, “Analysis of Educational Quality, a Goal of Education for All Policy,” High. Educ. Stud., vol. 9, no. 1, p. 100, 2019, doi: 10.5539/hes.v9n1p100.

[34] U. Verawardina, N. Jalinus, F. Rizal, and P. Sudira, “Blended Learning as Instructional Model in Vocational Education : Literature Blended Learning as Instructional Model in Vocational Education : Literature Review,” no. November, 2020, doi: 10.13189/ujer.2020.082214.

[35] S. J. Barnes, A. D. Pressey, and E. Scornavacca, Mobile ubiquity: Understanding the relationship between cognitive absorption, smartphone addiction and social network services, vol. 90. Elsevier B.V., 2019.

[36] M. L. Maciejewski, “Quasi-experimental design,” Biostat. Epidemiol., vol. 4, no. 1, pp. 38–47, 2020, doi: 10.1080/24709360.2018.1477468.

[37] P. J. A. Claro, L. Koivusilta, M. P. Vainikainen, and A. Rimpelä, “Psychosocial reserve capacity, family background and selection of an educational path–a longitudinal study from Finland,” Int. J. Adolesc. Youth, vol. 27, no. 1, pp. 166–180, 2022, doi: 10.1080/02673843.2022.2043916.

[38] T. T. Kiong, M. Azim, and N. Bin, “Employability challenges of vocational college graduates in the state of Johor,” vol. 7, no. 2, pp. 76–90, 2024.

[39] N. Ozdamar-Keskin, F. Z. Ozata, K. Banar, and K. Royle, “Examining Digital Literacy Competences and Learning Habits of Open and Distance Learners,” Contemp. Educ. Technol., vol. 6, no. 1, pp. 74–90, 2020, doi: 10.30935/cedtech/6140.

[40] M. I. Qureshi et al., “A Systematic Review of Past Decade of Mobile Learning : What we Learned and Where to Go,” vol. 14, no. 6, pp. 67–81.

[41] C. Beluce, D. Oliveira, and K. Luciane, “A Motivação dos Estudantes Para Aprender em Ambientes Virtuais de Aprendizagem La Motivación de Estudiantes Para Aprender en Ambientes Virtuales de Aprendizaje,” 2015, doi: 10.1590/1982-43272560201513.

[42] N. Ishartono, A. Desstya, H. J. Prayitno, and Y. Sidiq, “The Quality of HOTS-Based Science Questions Developed by Indonesian Elementary School Teachers,” J. Educ. Technol., vol. 5, no. 2, pp. 236–245, 2021, doi: 10.23887/jet.v5i2.33813.

[43] E. Technology, A. Majmaah, and S. Arabia, “Online and Biomedical Engineering,” vol. 20, no. 7, pp. 163–182, 2024.

[44] G. Supriyanto, I. Widiaty, A. G. Abdullah, and Y. R. Yustiana, “Application expert system career guidance for students,” J. Phys. Conf. Ser., vol. 1402, no. 6, 2019, doi: 10.1088/1742-6596/1402/6/066031.

[45] R. Febrianti, A. Yufrizal, R. P. Putra, and P. Phongdala, “Implementation of project-based learning for improve students ’ critical thinking skills in creative product and entrepreneurship subjects,” vol. 6, no. 4, pp. 240–247, 2023.

Downloads

Published

2026-02-27

How to Cite

Andhika Herayono, Muhammad Anwar, Elfi Tasrif, & Qothrun Nada Ma’ruf Batubara. (2026). Intelligent Mobile System for Student Performance Evaluation: Model Testing Using Structural Equation Modeling. International Journal of Interactive Mobile Technologies (iJIM), 20(04), pp. 23–36. https://doi.org/10.3991/ijim.v20i04.60101

Issue

Section

Papers