The Relationship between Linguistic Intelligence and Computational Thinking among Fifth Grade Students of Elementary School

Idam Ragil Widianto Atmojo, Roy Ardiansyah, Joko Tri Widianto, Dwi Yuniasih Saputri, Maryam Faizah

Abstract


This study aims to determine whether there is a relationship between linguistic intelligence and computational thinking. The research method employed is quantitative, utilizing a correlational research design. The research sample comprised 73 students from 4 elementary schools in the Laweyan District, Surakarta City. Data collection involved a test instrument in the form of a descriptive test to assess both linguistic intelligence and computational thinking. Data analysis included prerequisite tests and hypothesis testing. The results indicate a significant overall relationship between linguistic intelligence and computational thinking, with a significance value of 0.000 (p < 0.05) and a Pearson correlation coefficient of 0.493 with the moderate category. The relationship between each indicator of linguistic intelligence and computational thinking shows significant and positive correlations for the rhetoric, explanation, and metalinguistics indicators, with p < 0.05. In contrast, the mnemonics indicator does not demonstrate a significant relationship, with a p > 0.05.  These findings can serve as a reference for further research. The significant relationship between linguistic intelligence and computational thinking suggests that enhancing linguistic skills, particularly rhetoric, explanation, and metalinguistics, could improve students' computational abilities, guiding future educational strategies.

Keywords


Computational Thinking; Elementary School; Linguistic Intelligence; Relationship; Quantitative Research

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Abdulrasool, A. A., Aljibory, M. W., Abbas, A. K., & Al-Silbi, M. M. (2023). A Computational Study of Perforated Helical Tube Inserted in a Double Pipe Heat Exchanger with Fluid Injection. International Journal of Heat and Technology, 41(1), 35–45. https://doi.org/10.18280/ijht.410104

Aho, A. V. (2020). Computation and Computational Thinking. The Computer Journal, 55(7), 2010–2013. https://doi.org/10.1093/comjnl/bxs074

Alfaro-Ponce, B., Patiño, A., & Sanabria-Z, J. (2023). Components of computational thinking in citizen science games and its contribution to reasoning for complexity through digital game-based learning: A framework proposal. Cogent Education, 10(1). https://doi.org/10.1080/2331186X.2023.2191751

Almelhes, S. A. (2023). A Review of Artificial Intelligence Adoption in Second-Language Learning. Theory and Practice in Language Studies, 13(5), 1259–1269. https://doi.org/10.17507/tpls.1305.21

Aminah, N., Sukestiyarno, Y. L., Cahyono, A. N., & Maat, S. M. (2023). Student activities in solving mathematics problems with a computational thinking using Scratch. International Journal of Evaluation and Research in Education, 12(2), 613–621. https://doi.org/10.11591/ijere.v12i2.23308

Amiri, E. O. (2018). Application of computational experiments based on the response surface methodology for studying of the recirculation zone in the Y-shaped channel. Mathematical Modelling of Engineering Problems, 5(3), 243–248. https://doi.org/10.18280/mmep.050317

Angraini, L. M., Yolanda, F., & Muhammad, I. (2023). Augmented Reality: The Improvement of Computational Thinking Based on Students’ Initial Mathematical Ability. International Journal of Instruction, 16(3), 1033–1054. https://doi.org/10.29333/iji.2023.16355a

Ariffin, K., Husin, M. S., De Mello, G., Ibrahim, M. N. A., Omar, N. H., & Ishak, N. (2024). Meeting students’ needs: teachers’ practice of multiple intelligences in English as second language classrooms. International Journal of Evaluation and Research in Education (IJERE), 13(4), 2707. https://doi.org/10.11591/ijere.v13i4.27797

Arshad, M. H., Sulaiman, Y., & Yusr, M. M. (2024). Influence of innovation on the relationship between market orientation, entrepreneurial orientation, and SME performance in Pakistan. Multidisciplinary Science Journal, 6(5), 1–11. https://doi.org/10.31893/multiscience.2024052

Atmatzidou, S., & Demetriadis, S. (2016). Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robotics and Autonomous Systems, 75, 661–670. https://doi.org/10.1016/j.robot.2015.10.008

Boom, K. D., Bower, M., Arguel, A., Siemon, J., & Scholkmann, A. (2018). Relationship between computational thinking and a measure of intelligence as a general problem-solving ability. Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE, 206–211. https://doi.org/10.1145/3197091.3197104

Boucinha, R. M., Barone, D. A. C., Reichert, J. T., Brackmann, C. P., & Schneider, A. M. (2019). Relationship between the Learning of Computational thinking and the Development of Reasoning. International Journal of Advanced Engineering Research and Science, 6(6), 623–631. https://doi.org/10.22161/ijaers.6.6.71

Cansu, F. K., & Cansu, S. K. (2019). An Overview of Computational Thinking. International Journal of Computer Science Education in Schools, 3(1), 17–30. https://doi.org/10.21585/ijcses.v3i1.53

Chen, P., Yang, D., Metwally, A. H. S., Lavonen, J., & Wang, X. (2023). Fostering computational thinking through unplugged activities: A systematic literature review and meta-analysis. International Journal of STEM Education, 10(1). https://doi.org/10.1186/s40594-023-00434-7

Ching, Y. H., & Hsu, Y. C. (2024). Educational Robotics for Developing Computational Thinking in Young Learners: A Systematic Review. TechTrends, 68(3), 423–434. https://doi.org/10.1007/s11528-023-00841-1

Cırıt, D. K., & Aydemir, S. (2023). Online scratch activities during the COVID-19 pandemic: Computational and creative thinking. International Journal of Evaluation and Research in Education, 12(4), 2111–2120. https://doi.org/10.11591/ijere.v12i4.24938

Colin, S. (2021). International Journal of Heat and Technology: Foreword. International Journal of Heat and Technology, 26(1), 107.

Cusipag, M. N., Oluyinka, S., Bernabe, M. T. N., & Bognot, F. L. (2024). Perceptions toward achieving work-life balance and job satisfaction in online teaching. Multidisciplinary Science Journal, 6(2). https://doi.org/10.31893/MULTISCIENCE.2024012

Denning, P. J., & Tedre, M. (2021). Computational Thinking: A Disciplinary Perspective. Informatics in Education, 20(3), 361–390. https://doi.org/10.15388/infedu.2021.21

Doblon, M. G. B. (2023). Senior High School Students’ Multiple Intelligences and their Relationship with Academic Achievement in Science. Integrated Science Education Journal, 4(1), 01–08. https://doi.org/10.37251/isej.v4i1.298

Fadhli, M., Sukirman, S., Ulfa, S., Susanto, H., & Syam, A. R. (2019). Gamifying children’s linguistic intelligence with the duolingo app: A case study from indonesia. Mobile Learning Applications in Early Childhood Education, December, 122–135. https://doi.org/10.4018/978-1-7998-1486-3.ch007

Fernandes, K. T., Da Silva Aranha, E. H., Lucena, M. J. N. R., & De Souza Fernandes, G. L. (2020). Developing Computational Thinking and Reading and Writing Skills through an Approach for Creating Games. Proceedings - Frontiers in Education Conference, FIE, 2020-Octob. https://doi.org/10.1109/FIE44824.2020.9274065

Fisher, M., & Keil, F. C. (2016). The Curse of Expertise: When More Knowledge Leads to Miscalibrated Explanatory Insight. Cognitive Science, 40(5), 1251–1269. https://doi.org/10.1111/cogs.12280

Garavand, N., Azizifar, A., Gowhary, H., & Welidi, S. (2023). The relationship between linguistic intelligence of EFL learners and their performance on grammar. Journal of Language and Translation, 13(2), 151–161.

Gisborne, N., & Trousdale, G. (2008). Constructional approaches to English grammar. In Constructional Approaches to English Grammar. https://doi.org/10.1515/9783110199178

Gong, D., Yang, H. H., & Cai, J. (2020). Exploring the key influencing factors on college students’ computational thinking skills through flipped-classroom instruction. International Journal of Educational Technology in Higher Education, 17(1). https://doi.org/10.1186/s41239-020-00196-0

Gorai, J., Kumar, A., & Angadi, G. R. (2024). Smart PLS-SEM modeling: Developing an administrators’ perception and attitude scale for apprenticeship programme. Multidiscip. Sci. J, 6(Cii), 2024260.

H05 /B893r(5) /E. (2017). 5.

Halil, N. I. (2017). The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence. International Journal of Education and Literacy Studies, 5(4), 42. https://doi.org/10.7575/aiac.ijels.v.5n.4p.42

Hasbullah, Wahidah, N., & Nanning. (2023). Integrating Multiple Intelligence Learning Approach to Upgrade Students’ English Writing Skills. International Journal of Language Education, 7(2), 199–211. https://doi.org/10.26858/ijole.v7i2.34383

Helsa, Y., Turmudi, & Juandi, D. (2023). TPACK-based hybrid learning model design for computational thinking skills achievement in mathematics. Journal on Mathematics Education, 14(2), 225–252. https://doi.org/10.22342/jme.v14i2.pp225-252

Huang, S. Y., Tarng, W., & Ou, K. L. (2023). Effectiveness of AR Board Game on Computational Thinking and Programming Skills for Elementary School Students. Systems, 11(1). https://doi.org/10.3390/systems11010025

Jauhariyah, M.N.R., Sunarti, T., Wasis, W., Setyarsih, W., Zainuddin, A., Fatimah, S., Syahidi, K., Safitri, N. S. (2021). Scientific Research Trend on Creativity in Physics Learning. International Joint Conference on Science and Engineering 2021 (IJCSE 2021), 209(Ijcse), 560–567.

Jensen, A. R. (2021). Psychometric g: Definition and Substantiation. The General Factor of Intelligence, 51–66. https://doi.org/10.4324/9781410613165-8

Kafi, F. A., & Huda, M. (2023). The Linguistic Intelligence of Students in Applied Classical Arabic Text. Al-Fusha : Arabic Language Education Journal, 5(2), 64–71. https://doi.org/10.62097/alfusha.v5i2.1301

Kurniawan, D. A., Astalini, A., Darmaji, D., & Melsayanti, R. (2019). Students’ attitude towards natural sciences. International Journal of Evaluation and Research in Education, 8(3), 455–460. https://doi.org/10.11591/ijere.v8i3.16395

Kusumawarti, E., Subiyantoro, S., & Rukayah. (2020). The effectiveness of visualization, auditory, kinesthetic (VAK) model toward writing narrative: Linguistic intelligence perspective. International Journal of Instruction, 13(4), 677–694. https://doi.org/10.29333/iji.2020.13442a

Li, Y., Schoenfeld, A. H., diSessa, A. A., Graesser, A. C., Benson, L. C., English, L. D., & Duschl, R. A. (2020). Computational Thinking Is More about Thinking than Computing. Journal for STEM Education Research, 3(1), 1–18. https://doi.org/10.1007/s41979-020-00030-2

Liao, C. H., Chiang, C. T., Chen, I. C., & Parker, K. R. (2022). Exploring the relationship between computational thinking and learning satisfaction for non-STEM college students. International Journal of Educational Technology in Higher Education, 19(1). https://doi.org/10.1186/s41239-022-00347-5

Liu, X., Wang, X., Xu, K., & Hu, X. (2023). Effect of Reverse Engineering Pedagogy on Primary School Students’ Computational Thinking Skills in STEM Learning Activities. Journal of Intelligence, 11(2). https://doi.org/10.3390/jintelligence11020036

Lodi, M., & Martini, S. (2021). Computational Thinking, Between Papert and Wing. Science and Education, 30(4), 883–908. https://doi.org/10.1007/s11191-021-00202-5

Lombrozo, T. (2016). Explanatory Preferences Shape Learning and Inference. Trends in Cognitive Sciences, 20(10), 748–759. https://doi.org/10.1016/j.tics.2016.08.001

Lu, C., Macdonald, R., Odell, B., Kokhan, V., Demmans Epp, C., & Cutumisu, M. (2022). A scoping review of computational thinking assessments in higher education. Journal of Computing in Higher Education, 34(2), 416–461. https://doi.org/10.1007/s12528-021-09305-y

Lubis, A. B., Miaz, Y., & Putri, I. E. (2019). Influence of the Guided Discovery Learning Model on Primary School Students’ Mathematical Problem-solving Skills. Mimbar Sekolah Dasar, 6(2), 253. https://doi.org/10.17509/mimbar-sd.v6i2.17984

Lubis, Y. A., & Sinaga, B. (2021). Development of Macromedia Flash-Assisted Mathematics Learning Media with the Application of Problem Based Learning Models to Improve Computational Thinking Ability and Self-Efficacy of Class X High School Students. Journal of Education and Practice, 12(34), 19–26. https://doi.org/10.7176/jep/12-34-03

Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12? Computers in Human Behavior, 41, 51–61. https://doi.org/10.1016/j.chb.2014.09.012

Marinus, E., Powell, Z., Thornton, R., McArthur, G., & Crain, S. (2018). Unravelling the cognition of coding in 3-to-6-year olds: The development of an assessment tool and the relation between coding ability and cognitive compiling of syntax in natural language. ICER 2018 - Proceedings of the 2018 ACM Conference on International Computing Education Research, 133–141. https://doi.org/10.1145/3230977.3230984

Mubarok, A. (2020). The Correlation Between Students’ Linguistic Intelligence And Their English Speaking Skill Achievement. Sem,Inar Pendidikan, 393–400. http://repository.uinjkt.ac.id/dspace/handle/123456789/33927%0Ahttps://repository.uinjkt.ac.id/dspace/bitstream/123456789/33927/1/SKRIPSI AMIN MUBAROK.pdf

Muhamad, M. Q. B., Doddanavar, I. A., & Chowdhury, S. (2024). Determining youths’ computational thinking skills using confirmatory factor analysis. International Journal of Evaluation and Research in Education (IJERE), 13(4), 2060. https://doi.org/10.11591/ijere.v13i4.28513

Mujiono. (2024). The Mediating Role of Verbal Linguistic Intelligence in the Impact of Self- Efficacy and Academic Engagement on Academic Flow in Academic Writing The Mediating Role of Verbal Linguistic Intelligence in the Impact of Self- Efficacy and Academic Engagement. Journal of Higher Education Theory and Practice, 23(20), 169–183. https://doi.org/10.33423/jhetp.v23i20.6694

Mustahib, Roshayanti, F., & Dewi, E. R. S. (2023). Profil Computational Thinking Siswa Kelas X SMA Negeri Mranggen Tahun 2023. JP3: Jurnal Pendidikan Dan Profesi Pendidikan, 09(01), 18–25.

Muzana, S. R., Jumadi, Wilujeng, I., Yanto, B. E., & Mustamin, A. A. (2021). E-STEM project-based learning in teaching science to increase ICT literacy and problem solving. International Journal of Evaluation and Research in Education, 10(4), 1386–1394. https://doi.org/10.11591/IJERE.V10I4.21942

Ners, P. S., Kesehatan, F., Bangsa, U. C., & Wanita, N. (2021). 3 1,2,3. 6(1), 1–13.

Nouhaila, O., & Hassane, M. (2024). Analyzing the Impact of Cracks on Exhaust Manifold Performance: A Computational Fluid Dynamics Study. International Journal of Heat and Technology, 42(2), 475–480. https://doi.org/10.18280/ijht.420213

Nu, A., Rahmawati, I., Zubaidi, A., Yatin, A., & Dewi, H. R. (2022). Improving Verbal Linguistic Intelligence in Early Childhood Through the Use of Tiktok Media. 6(3), 2316–2324. https://doi.org/10.31004/obsesi.v6i3.2083

Oliver, S. J. (2022). A corpus-based approach to (im)politeness metalanguage: A case study on Shakespeare’s plays. Journal of Pragmatics, 199, 6–20. https://doi.org/10.1016/j.pragma.2022.07.001

Önal, H. (2023). A Comparison of Problem Solving Strategies of Primary School 3rd and 4th Graders. Mimbar Sekolah Dasar, 10(1), 80–91. https://doi.org/10.53400/mimbar-sd.v10i1.46242

Pikhart, M. (2020). Intelligent information processing for language education: The use of artificial intelligence in language learning apps. Procedia Computer Science, 176, 1412–1419. https://doi.org/10.1016/j.procs.2020.09.151

Preston, C. J. (2019). Forthcoming in. 2018–2020.

Purwasih, R., Dahlan, J. A., & Ishartono, N. (2024). Computational thinking on concept pattern number : A study learning style Kolb. 10(January), 89–104.

Razzouki, M., Azdod, M., Lhassan, I. A., Bouayad, M., & Babounia, A. (2024). The effect of differentiation strategy on the organisational performance of companies in the agri-food industry: The mediating role of interactive use of management control system. Multidisciplinary Science Journal, 6(10). https://doi.org/10.31893/multiscience.2024199

Richardo, R., Dwiningrum, S. I. A., Wijaya, A., Retnawati, H., Wahyudi, A., Sholihah, D. A., & Hidayah, K. N. (2023). The impact of STEM attitudes and computational thinking on 21st-century via structural equation modelling. International Journal of Evaluation and Research in Education, 12(2), 571–578. https://doi.org/10.11591/ijere.v12i2.24232

Rodríguez-garcía, J. D., Moreno-León, J., Román-González, M., & Robles, G. (2020). LearningML : A Tool to Foster Computational Thinking Skills Through Practical Artificial Intelligence Projects LearningML : una herramienta para fomentar las habilidades de Pensamiento Computacional mediante proyectos prácticos de Inteligencia Artificial. RED. Revista de Educación a Distancia, 20(63), 37.

Román-González, M., Pérez-González, J. C., Moreno-León, J., & Robles, G. (2018). Extending the nomological network of computational thinking with non-cognitive factors. Computers in Human Behavior, 80, 441–459. https://doi.org/10.1016/j.chb.2017.09.030

Saidi, M. (2020). The Relationship between Iranian EFL Learners’ Linguistic and Logical Intelligences and the Frequency of Fallacies and Evidence in their Argumentative Writing : A Gender-based Study. The Journal of English Languaje Pedagogy, 12(25), 151–169. https://doi.org/10.30495/JAL.2020.675547

Salayev. (2024). Mental Enlightenment Scientific – Methodological Journal Mental Enlightenment Scientific –. Mental Enlightenment Scientific –Methodological Journal, 4(2), 175–184.

Santos, E. C., Macêdo, E. N., Magno, R. N. O., Galhardo, M. A. B., Oliveira, L. G. M., Brito, A. U., & Macêdo, W. N. (2023). Exergetic Assessment and Computational Modeling of a Solar-Powered Directly-Coupled Air Conditioning System: An Application in Library Cooling. International Journal of Heat and Technology, 41(4), 854–868. https://doi.org/10.18280/ijht.410408

Silva, R., Fonseca, B., Costa, C., & Martins, F. (2021). Fostering computational thinking skills: A didactic proposal for elementary school grades. Education Sciences, 11(9). https://doi.org/10.3390/educsci11090518

Sırakaya, D. A. (2020). Investigating computational thinking skills based on different variables and determining the predictor variables. Participatory Educational Research, 7(2), 102–114. https://doi.org/10.17275/per.20.22.7.2

Skills, C. T. (2023). Education sciences computational thinking skills. Education Sciences, 13(433), 1–14.

Song, X. (2022). Testing linearity in semi-functional partially linear regression models. December.

Su, J., & Yang, W. (2023). A systematic review of integrating computational thinking in early childhood education. Computers and Education Open, 4(December 2022), 100122. https://doi.org/10.1016/j.caeo.2023.100122

Suwahyo, B. W. (2020). Problems of Computational Thinking, Teaching, and Learning in a STEM Framework: A Literature Review. 508(Icite), 180–185. https://doi.org/10.2991/assehr.k.201214.233

Syafii, A., Machali, I., Putro, N. H. P. S., Retnawati, H., & ‘aziz, H. (2022). The effects of multiple intelligences theory on learning success: A meta-analysis in social science. International Journal of Evaluation and Research in Education, 11(2), 736–743. https://doi.org/10.11591/ijere.v11i2.22223

Thambu, N., Prayitno, H. J., & Zakaria, G. A. N. (2021). Incorporating Active Learning into Moral Education to Develop Multiple Intelligences: A Qualitative Approach. Indonesian Journal on Learning and Advanced Education (IJOLAE), 3(1), 17–29. https://doi.org/10.23917/ijolae.v3i1.10064

Thomas, P., & Perwez, S. K. (2024). Influence of Hovard Gardner’s Linguistic Intelligence on Effective Communication. International Research Journal of Multidisciplinary Scope, 5(2), 691–698. https://doi.org/10.47857/irjms.2024.v05i02.0609

Triantafyllou, S. A., Sapounidis, T., & Farhaoui, Y. (2024). Gamification and Computational Thinking in Education: A systematic literature review. Salud, Ciencia y Tecnologia - Serie de Conferencias, 3(c). https://doi.org/10.56294/sctconf2024659

Tsarava, K., Moeller, K., Román-González, M., Golle, J., Leifheit, L., Butz, M. V., & Ninaus, M. (2022). A cognitive definition of computational thinking in primary education. Computers and Education, 179(November 2020). https://doi.org/10.1016/j.compedu.2021.104425

Vanisri, K., & Padhy, P. C. (2024). An empirical study on impact of employee green behavior on employee well-being with mediating role of self-esteem in higher educational institutions using PLS SEM. Multidisciplinary Science Journal, 6(3). https://doi.org/10.31893/multiscience.2024032

Verawati, N. N. S. P., Rijal, K., & Grendis, N. W. B. (2023). Examining STEM Students’ Computational Thinking Skills through Interactive Practicum Utilizing Technology. International Journal of Essential Competencies in Education, 2(1), 54–65. https://doi.org/10.36312/ijece.v2i1.1360

Von Ahn, L., & Dabbish, L. (2008). Designing games with a purpose. Communications of the ACM, 51(8), 58–67. https://doi.org/10.1145/1378704.1378719

Wahid, N. A. A., & Hayani, N. (2024). Reslaj : Religion Education Social Laa Roiba Journal Pengaruh Story Reading ( buku bilingual ) Terhadap Reslaj : Religion Education Social Laa Roiba Journal. 6(2), 110–122. https://doi.org/10.47476/reslaj.v6i2.234

Wajiha Kanwal, Quratulain, & Iffat Basit. (2020). Interrelation of Multiple Intelligences and their Correlation with Linguistic Intelligence as Perceived by College Students: A Correlation Study. Journal of Business and Social Review in Emerging Economies, 6(4), 1439–1447. https://doi.org/10.26710/jbsee.v6i4.1468

Wang, F. Y., Yang, J., Wang, X., Li, J., & Han, Q. L. (2023). Chat with ChatGPT on Industry 5.0: Learning and Decision-Making for Intelligent Industries. IEEE/CAA Journal of Automatica Sinica, 10(4), 831–834. https://doi.org/10.1109/JAS.2023.123552

Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215

Wu, T. T., Silitonga, L. M., & Murti, A. T. (2024). Enhancing English writing and higher-order thinking skills through computational thinking. Computers and Education, 213(January), 105012. https://doi.org/10.1016/j.compedu.2024.105012

Xia, J., Ge, Y., Shen, Z., & Najar, M. R. (2024). The Auxiliary Role of Artificial Intelligence Applications in Mitigating the Linguistic, Psychological, and Educational Challenges of Teaching and Learning Chinese Language by non-Chinese Students. 25(3).

Yavich, R., & Rotnitsky, I. (2020). Multiple intelligences and success in school studies. International Journal of Higher Education, 9(6), 107–117. https://doi.org/10.5430/ijhe.v9n6p107

Yilmaz, R., & Karaoglan Yilmaz, F. G. (2023). The effect of generative artificial intelligence (AI)-based tool use on students’ computational thinking skills, programming self-efficacy and motivation. Computers and Education: Artificial Intelligence, 4(April), 100147. https://doi.org/10.1016/j.caeai.2023.100147




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