DOI : https://doi.org/10.18517/ijaseit.14.2.19953

Implementation of Relational Database in the STEAM-Problem Based Learning Model in Algorithm and Programming

Des Suryani (1), Ambiyar (2), Asrul Huda (3), Fitri Ayu (4), Erdisna (5), Muhardi (6)
(1) Doctoral Program of Technology and Vocational Education,Universitas Negeri Padang, Air Tawar, Padang, 25171, Indonesia
(2) Department of Technology and VocationalEducation, Universitas Negeri Padang, Air Tawar, Padang, 25171, Indonesia
(3) Department of Technology and VocationalEducation, Universitas Negeri Padang, Air Tawar, Padang, 25171, Indonesia
(4) Department of Electrical Engineering, Sekolah Tinggi Teknologi Pekanbaru, Pekanbaru, 28294, Indonesia
(5) Department of Technology and VocationalEducation, Universitas Negeri Padang, Air Tawar, Padang, 25171, Indonesia
(6) Department of Informatics, Universitas Hang Tuah Pekanbaru, Pekanbaru, 28288, Indonesia
Fulltext View | Download
How to cite (IJASEIT) :
Suryani, Des, et al. “Implementation of Relational Database in the STEAM-Problem Based Learning Model in Algorithm and Programming”. International Journal on Advanced Science, Engineering and Information Technology, vol. 14, no. 2, Apr. 2024, pp. 400-8, doi:10.18517/ijaseit.14.2.19953.
Citation Format :
Currently, digital technology is developing in all fields. The development of this technology certainly has a significant impact on the world of education. A suitable learning model is needed, especially in the Algorithm and Programming course, to face global challenges in the Industrial Revolution 4.0. Students are expected to have skills that include critical and creative thinking in solving problems, communication, and collaboration with the support of technology. The STEAM-Problem Based Learning model can be used in the Algorithm and Programming learning process with seven syntaxes: preparation and knowledge identification; problem identification; plan solution; create and test products; communicate; evaluation and feedback and giving rewards. All activities carried out in the learning process by lecturers and students can be stored in a database. This research attempts to determine the validity of the STEAM-Problem Based Learning database design, which will be implemented in the Algorithm and Programming course. The data analysis technique used is validity analysis, which is based on assessing the data obtained through a questionnaire or a questionnaire using a Likert scale. Data was processed using Aiken’s V validity coefficient formula to test the expert’s judgment. Assessment indicators include correctness, consistency, relevance, completeness, and minimality. The results of the study show that the validity test on the STEAM-Problem Based Learning database design is valid, so it is feasible to implement it in algorithm and programming learning.

D. M. Anggraeni, B. K. Prahani, N. Suprapto, N. Shofiyah, and B. Jatmiko, “Systematic review of problem based learning research in fostering critical thinking skills,” Think. Ski. Creat., vol. 49, no. February, p. 101334, 2023, doi: 10.1016/j.tsc.2023.101334.

R. M. Sari, Sumarmi, I. K. Astina, D. H. Utomo, and Ridhwan, “Increasing Students Critical Thinking Skills and Learning Motivation Using Inquiry Mind Map,” Int. J. Emerg. Technol. Learn., vol. 16, no. 3, pp. 4–19, 2021, doi:10.3991/ijet.v16i03.16515.

C. Ter Chao et al., “Fully digital problem-based learning for undergraduate medical students during the COVID-19 period: Practical considerations,” J. Formos. Med. Assoc., vol. 121, no. 10, pp. 2130–2134, 2022, doi: 10.1016/j.jfma.2021.11.011.

S. A. Seibert, “Problem-based learning: A strategy to foster generation Z’s critical thinking and perseverance,” Teach. Learn. Nurs., vol. 16, no. 1, pp. 85–88, 2021, doi:10.1016/j.teln.2020.09.002.

Y. Kang and I. Lee, “The Effect of Mixed Reality-based HoloPatient in Problem-based Learning Contexts,” Clin. Simul. Nurs., vol. 82, p. 101438, 2023, doi: 10.1016/j.ecns.2023.101438.

C. Lee and C. Lim, “From technological development to social advance: A review of Industry 4.0 through machine learning,” Technol. Forecast. Soc. Change, vol. 167, no. September 2018, p. 120653, 2021, doi: 10.1016/j.techfore.2021.120653.

C. Bulut Ates and H. Aktamis, “Investigating the effects of creative educational modules blended with Cognitive Research Trust (CoRT) techniques and Problem Based Learning (PBL) on students’ scientific creativity skills and perceptions in science education,” Think. Ski. Creat., vol. 51, no. September 2023, p. 101471, 2024, doi:10.1016/j.tsc.2024.101471.

I. Supena, A. Darmuki, and A. Hariyadi, “The Influence of Learning Model on Students’ Learning Outcomes,” Int. J. Instr., vol. 14, no. 3, pp. 873–892, 2021.

J. Miranda et al., “The core components of education 4.0 in higher education: Three case studies in engineering education,” Comput. Electr. Eng., vol. 93, no. February, 2021, doi:10.1016/j.compeleceng.2021.107278.

W. Li, J. Y. Huang, C. Y. Liu, J. C. R. Tseng, and S. P. Wang, “A study on the relationship between student’ learning engagements and higher-order thinking skills in programming learning,” Think. Ski. Creat., vol. 49, no. January, p. 101369, 2023, doi:10.1016/j.tsc.2023.101369.

E. S. Boye and D. D. Agyei, “Effectiveness of problem-based learning strategy in improving teaching and learning of mathematics for pre-service teachers in Ghana,” Soc. Sci. Humanit. Open, vol. 7, no. 1, p. 100453, 2023, doi: 10.1016/j.ssaho.2023.100453.

R. Andersen and M. Rustad, “Using Minecraft as an educational tool for supporting collaboration as a 21st century skill,” Comput. Educ. Open, vol. 3, no. June, p. 100094, 2022, doi:10.1016/j.caeo.2022.100094.

S. He, X. Shi, T. H. Choi, and J. Zhai, “How do students’roles in collaborative learning affect collaborative problem-solving competency? A systematic review of research,” Think. Ski. Creat., vol. 50, no. October, p. 101423, 2023, doi:10.1016/j.tsc.2023.101423.

H. Chai, T. Hu, and L. Wu, “Computer-based assessment of collaborative problem solving skills: A systematic review of empirical research,” Educ. Res. Rev., vol. 43, no. December 2023, 2024, doi: 10.1016/j.edurev.2023.100591.

S. Li, J. Pöysä-Tarhonen, and P. Häkkinen, “Students’ collaboration dispositions across diverse skills of collaborative problem solving in a computer-based assessment environment,” Comput. Hum. Behav. Reports, vol. 11, no. June, 2023, doi: 10.1016/j.chbr.2023.100312.

H. Jiang, D. Turnbull, X. Wang, R. Chugh, Y. Dou, and S. Chen, “How do mathematics interest and self-efficacy influence coding interest and self-efficacy? A structural equation modeling analysis,” Int. J. Educ. Res., vol. 115, no. May, p. 102058, 2022, doi:10.1016/j.ijer.2022.102058.

G. Yi-Ming Kao and C. A. Ruan, “Designing and evaluating a high interactive augmented reality system for programming learning,” Comput. Human Behav., vol. 132, no. June 2021, p. 107245, 2022, doi: 10.1016/j.chb.2022.107245.

J. Cohen and J. Gil, “An entity-relationship model of the flow of waste and resources in city-regions: Improving knowledge management for the circular economy,” Resour. Conserv. Recycl. Adv., vol. 12, no. September, p. 200058, 2021, doi:10.1016/j.rcradv.2021.200058.

S. El Bedewy and Z. Lavicza, “STEAM + X - Extending the transdisciplinary of STEAM-based educational approaches: A theoretical contribution,” Think. Ski. Creat., vol. 48, no. May, 2023, doi: 10.1016/j.tsc.2023.101299.

A. Aslan, “Problem- based learning in live online classes: Learning achievement, problem-solving skill, communication skill, and interaction,” Comput. Educ., vol. 171, no. November 2020, p. 104237, 2021, doi: 10.1016/j.compedu.2021.104237.

R. Lavi, M. Tal, and Y. J. Dori, “Perceptions of STEM alumni and students on developing 21st century skills through methods of teaching and learning,” Stud. Educ. Eval., vol. 70, p. 101002, 2021, doi: 10.1016/j.stueduc.2021.101002.

C. Y. Liu and C. J. Wu, “STEM without art: A ship without a sail,” Think. Ski. Creat., vol. 43, no. September 2020, p. 100977, 2022, doi:10.1016/j.tsc.2021.100977.

Z. Wu, “Understanding teachers’ cross-disciplinary collaboration for STEAM education: Building a digital community of practice,” Think. Ski. Creat., vol. 46, no. October, p. 101178, 2022, doi:10.1016/j.tsc.2022.101178.

T. T. Wu, L. M. Silitonga, and A. T. Murti, “Enhancing English writing and higher-order thinking skills through computational thinking,” Comput. Educ., vol. 213, no. January 2023, p. 105012, 2024, doi: 10.1016/j.compedu.2024.105012.

A. R. Caravalho and C. Santos, “Developing peer mentors’ collaborative and metacognitive skills with a technology-enhanced peer learning program,” Comput. Educ. Open, vol. 3, no. June 2021, p. 100070, 2022, doi: 10.1016/j.caeo.2021.100070.

M. S. Naveed, “Comparison of C++ and Java in Implementing Introductory Programming Algorithms,” Quaid-e-Awam Univ. Res. J. Eng. Sci. Technol., vol. 19, no. 1, pp. 95–103, 2021, doi:10.52584/qrj.1901.14.

T. Erlina, M. Fikri, U. Andalas, and C. Author, “Yolo Algorithm-Based Visitor Detection System For Small Retail Stores Using Single Board Computer,” vol. 4, no. 2, pp. 908–920, 2023.

E. Osaba et al., “A Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problems,” Swarm Evol. Comput., vol. 64, no. August 2020, p. 100888, 2021, doi: 10.1016/j.swevo.2021.100888.

B. Jose and S. Abraham, “Performance analysis of NoSQL and relational databases with MongoDB and MySQL,” Mater. Today Proc., vol. 24, pp. 2036–2043, 2019, doi:10.1016/j.matpr.2020.03.634.

S. Rani and R. Halder, “Comparative Analysis of Relational Database Watermarking Techniques: An Empirical Study,” IEEE Access, vol. 10, no. i, pp. 27970–27989, 2022, doi:10.1109/access.2022.3157866.

B. Lakzaei and M. Shmasfard, “Ontology learning from relational databases,” Inf. Sci. (Ny)., vol. 577, pp. 280–297, 2021, doi:10.1016/j.ins.2021.06.074.

F. Amiraslani, “Analysis of quality of life across Tehran districts based on designated indicators and relational database management system,” Urban Gov., vol. 1, no. 2, pp. 107–114, 2021, doi:10.1016/j.ugj.2021.09.003.

K. J. Fraga et al., “SpecDB: A relational database for archiving biomolecular NMR spectral data,” J. Magn. Reson., vol. 342, p. 107268, 2022, doi: 10.1016/j.jmr.2022.107268.

C. J. F. Candel, D. Sevilla Ruiz, and J. J. García-Molina, “A unified metamodel for NoSQL and relational databases,” Inf. Syst., vol. 104, no. January 2021, p. 101898, 2022, doi: 10.1016/j.is.2021.101898.

A. Gamal, S. Barakat, and A. Rezk, “Standardized electronic health record data modeling and persistence: A comparative review,” J. Biomed. Inform., vol. 114, no. December 2020, p. 103670, 2021, doi:10.1016/j.jbi.2020.103670.

M. Petković, M. Ceci, G. Pio, and B. Škrlj, “Knowledge-Based Systems,” vol. 251, 2022.

T. Connolly and C. Begg, Database systems: A pragmatic approach. 2015. doi: 10.1007/978-1-4842-1191-5.

L. Davidson, Pro SQL Server Relational Database Design and Implementation: Best Practices for Scalability and Performance. 2020. doi: 10.1007/978-1-4842-6497-3.

C. Lettner, R. Stumptner, W. Fragner, F. Rauchenzauner, and L. Ehrlinger, “DaQL 2.0: Measure Data Quality based on Entity Models,” Procedia Comput. Sci., vol. 180, no. 2019, pp. 772–777, 2021, doi: 10.1016/j.procs.2021.01.327.

Lewis. R. Aiken, “Three Coefficients For Analyzing The Reliability And Validity Of Ratings,” Educ. Psychol. Meas., vol. 45, pp. 131–141, 1985.

S. Melzer, O. C. Eichmann, H. Wang, and R. God, “Simulation of database interactions for early validation of digitized enterprise processes,” Procedia Comput. Sci., vol. 219, no. 2021, pp. 658–665, 2023, doi: 10.1016/j.procs.2023.01.336.

Creative Commons License

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

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
    2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
    3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).