Abstract
Previous literature highlights the potential of ICT use to enhance mathematical learning. There are also several theoretical arguments supporting that gifted education benefits from ICT use. However, empirical studies have paid little attention to the relationship between ICT use and gifted students’ mathematics performance. It is also unclear whether and why this relationship differs between gifted students and their peers. For the first time, we tested this relationship by using a large-scale multinational sample of 236,938 adolescents attending 10,213 schools in 44 countries in several contexts from the Programme for International Student Assessment Questionnaire (PISA) 2018. We estimated a hierarchical linear model (HLM) and found that only gifted students benefit from ICT use in mathematics learning. The higher their level of performance, the more beneficial ICT use is for gifted students. This relation is negative in the case of the rest of the students. Based on theoretical arguments, we also explain the likely reasons that lay behind this different relationship between gifted students and their peers. The findings illustrate that policymakers should consider a differentiated approach to ICT use at school depending on the students’ level of performance. Gifted students could benefit more from ICT use in learning and the rest of the students from teaching with more human interaction.
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The OECD explains in detail the sampling process of the participating schools and students. The samples of students in each participating country were obtained using a two-stage stratified procedure. In the first stage, schools, where 15-year-old students may be enrolled, were selected. A minimum of 150 participating schools were selected in each country. The probability of schools being selected was directly proportional to the estimated size of their (eligible) 15-year-old population. In parallel, other schools is chosen to replace those not wishing to participate. In the second step, 42 students were selected to answer the questionnaire in each participating school. All 15-year-old students in the school were selected if fewer than 42 were enrolled, always respecting a minimum of 20 participating students. Data quality standards in PISA required minimum participation rates for schools and students. This ensures that the possible bias resulting from nonresponse was smaller than the sampling error.
The OECD distinguishes seven levels of academic performance. Level 0 is the lowest and, in the case of mathematics, it is composed of the students who obtained a result below 189.33 points. Levels 5 and 6 are considered the levels of excellence. They group students who obtained results between 625.61 and 698.32 (level 5) or above 698.32 points (level 6).
References
Ahmad, M., & Karim, A. A. (2014). The discovery of the traits of gifted and talented students in ICT. International Education Studies, 7(13), 92–101. https://doi.org/10.5539/ies.v7n13p92
Anomal, R. F., Brandão, D. S., Porto, S. B., de Oliveira, S. S., de Souza, R. F. L., de Santana Fiel, J., & Pereira, A. (2020). The role of frontal and parietal cortex in the performance of gifted and average adolescents in a mental rotation task. Plos One, 15(5), https://doi.org/10.1371/journal.pone.0232660
Aubry, A., Gonthier, C., & Bourdin, B. (2021). Explaining the high working memory capacity of gifted children: Contributions of processing skills and executive control. Acta Psychologica, 218, 103358. https://doi.org/10.1016/j.actpsy.2021.103358
Ayhanöz, S. (2022). The place of Intelligence Games in Mathematics Education for Gifted Students. In O. Zahal (Ed.), Current research in Education (pp. 1–216). Ankara, Turkey: Yaşar Hız Genel.
Azimi, E., Jafari, L., & Mahdavinasab, Y. (2023). Using a design-based research methodology to develop and study prompts integrated into GeoGebra to support mathematics learning of gifted students. Education and Information Technologies, (0123456789). https://doi.org/10.1007/s10639-023-11632-9
Bartelet, D., Ghysels, J., Groot, W., Haelermans, C., & van den Brink, H. M. (2016). The differential effect of basic mathematics skills homework via a web-based intelligent tutoring system across achievement subgroups and mathematics domains: A randomized field experiment. Journal of Educational Psychology, 108(1), 1–20. https://doi.org/10.1037/edu0000051
Blair Heald, S. (2016). Curriculum differentiation for Gifted Learners using Instructional Technology: A multiple-case study. Northcentral University.
Bulman, G., & Fairlie, R. W. (2016). Technology and Education: Computers, Software, and the internet. In E. A. Hanushek, S. Machin, & L. Woessmann (Eds.), Handbook of the Economics of Education (5 vol., pp. 239–280). North Holland.
Campbell, J. A., McIntyre, J., & Kucirkova, N. (2021). Gender equality, human development, and pisa results over time. Social Sciences, 10(12), https://doi.org/10.3390/socsci10120480
Chen, J., Dai, Y., D., & Zhou, Y. (2013). Enable, enhance, and transform: How Technology Use can improve Gifted Education. Roeper Review, 35(3), 166–176. https://doi.org/10.1080/02783193.2013.794892
Comi, S. L., Argentin, G., Gui, M., Origo, F., & Pagani, L. (2017). Is it the way they use it? Teachers, ICT and student achievement. Economics of Education Review, 56, 24–39. https://doi.org/10.1016/j.econedurev.2016.11.007
Cooper, L. R. (2018). DIGITAL GAME-BASED LEARNING AND THE MATHEMATICS ACHIEVEMENT OF GIFTED STUDENTS by A Dissertation Presented in Partial Fulfillment Of the Requirements for the Degree Doctor of Education Liberty University.
Cragg, L., & Gilmore, C. (2014). Skills underlying mathematics: The role of executive function in the development of mathematics proficiency. Trends in Neuroscience and Education. Elsevier GmbH. https://doi.org/10.1016/j.tine.2013.12.001
Cresswell, C., & Speelman, C. P. (2020). Does mathematics training lead to better logical thinking and reasoning? A cross-sectional assessment from students to professors. Plos One, 15(7 July), https://doi.org/10.1371/journal.pone.0236153
De Witte, K., & Rogge, N. (2014). Does ICT matter for effectiveness and efficiency in mathematics education? Computers and Education, 75(June), 173–184. https://doi.org/10.1016/j.compedu.2014.02.012
Dunn, T. J., & Kennedy, M. (2019). Technology enhanced learning in higher education; motivations, engagement and academic achievement. Computers and Education, 137(March), 104–113. https://doi.org/10.1016/j.compedu.2019.04.004
Falck, O., Mang, C., & Woessmann, L. (2018). Virtually no effect? Different Uses of Classroom Computers and their Effect on Student Achievement. Oxford Bulletin of Economics and Statistics, 80(1), 1–38. https://doi.org/10.1111/obes.12192
Fernández Batanero, J. M., Rebollo, R., M. M., & Montenegro Rueda, M. (2019). Impact of ICT on students with high abilities. Bibliographic review (2008–2018). Computers and Education, 137(January), 48–58. https://doi.org/10.1016/j.compedu.2019.04.007
Fernández-Gutiérrez, M., Gimenez, G., & Calero, J. (2020). Is the use of ICT in education leading to higher student outcomes? Analysis from the Spanish Autonomous Communities. Computers and Education, 157(July), https://doi.org/10.1016/j.compedu.2020.103969
Gadanidis, G., Hughes, J., & Cordy, M. (2011). Mathematics for gifted students in an arts- and technology-rich setting. Journal for the Education of the Gifted, 34(3), 397–433. https://doi.org/10.1177/016235321103400303
García-Martínez, I., Gutiérrez Cáceres, R., de la Luque, A., & León, S. P. (2021). Analysing educational interventions with gifted students. Systematic review Children, 8(5), 1–15. https://doi.org/10.3390/children8050365
García-Perales, R., & Almeida, L. S. (2019). An enrichment program for students with high intellectual ability: Positive effects on school adaptation. Comunicar, 27(60), 39–47. https://doi.org/10.3916/C60-2019-04
Geake, J. (2009). Neuropsychological characteristics of academic and creative giftedness. International Handbook on Giftedness. Springer Netherlands. https://doi.org/10.1007/978-1-4020-6162-2
Giambona, F., & Porcu, M. (2015). Student background determinants of reading achievement in Italy. A quantile regression analysis. International Journal of Educational Development, 44, 95–107. https://doi.org/10.1016/J.IJEDUDEV.2015.07.005
Gimenez, G., & Vargas-Montoya, L. (2021). Ict use and successful learning: The role of the stock of human capital. Mathematics, 9(14), 1–15. https://doi.org/10.3390/math9141648
Gimenez, G., Martín-Oro, Á., & Sanaú, J. (2018). The effect of districts’ social development on student performance. Studies in Educational Evaluation, 58, 80–96. https://doi.org/10.1016/J.STUEDUC.2018.05.009
Gimenez, G., Barrado, B., & Arias, R. (2019). The role of teachers and the learning environment in academic achievement of costa rican students: An analysis from PISA. Revista Complutense de Educacion, 30(4), 1127–1145. https://doi.org/10.5209/rced.60189
Gimenez, G., Ciobanu, D., & Barrado, B. (2021). A proposal of spatial measurement of peer effect through socioeconomic indices and unsatisfied basic needs. Economies, 9(2), https://doi.org/10.3390/economies9020072
Goodhew, G. (2009). In G. Goodhew (Ed.), Meeting the needs of gifted and talented students. (First). Continuum International Publishing Group.
Gottfredson, L. (1997). Mainstream Science on Intelligence: An Editorial with 52 signatories, history, and bibliography. Intelligence, 24(1), 13–23. https://doi.org/10.1111/j.1432-1033.1976.tb11027.x
Hanushek, E. A., & Woessmann, L. (2011). The Economics of International differences in Educational Achievement. In E. A. Hanushek, S. Machin, & L. Woessmann (Eds.), Handbook of the Economics of Education 3 (pp. 89–200). San Diego: North Holland.
Hanushek, E. A., & Woessmann, L. (2017). School Resources and Student Achievement: A Review of Cross-Country Economic Research. In M. Rosén, K. Yang Hansen, & U. Wolff (Eds.), Cognitive Abilities and Educational Outcomes: A Festschrift in Honour of Jan-Eric Gustafsson (pp. 149–171). Springer. https://doi.org/10.1007/978-3-319-43473-5
Hanushek, E. A., Link, S., & Woessmann, L. (2013). Does school autonomy make sense everywhere? Panel estimates from PISA. Journal of Development Economics, 104, 212–232. https://doi.org/10.1016/j.jdeveco.2012.08.002
Higgins, K., Huscroft-D’Angelo, J., & Crawford, L. (2019). Effects of Technology in Mathematics on Achievement, Motivation, and attitude: A Meta-analysis. Journal of Educational Computing Research, 57(2), 283–319. https://doi.org/10.1177/0735633117748416
Hillmayr, D., Ziernwald, L., Reinhold, F., Hofer, S. I., & Reiss, K. M. (2020). The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific meta-analysis. Computers and Education, 153(April), 103897. https://doi.org/10.1016/j.compedu.2020.103897
Hong, K., & Zimmer, R. (2016). Does investing in School Capital infrastructure improve Student Achievement? Economics of Education Review, 53, 143–158. https://doi.org/10.1016/J.ECONEDUREV.2016.05.007
Housand, B. C., & Housand, A. M. (2014). The role of technology in gifted students’ motivation. Psychology in the Schools, 49, 706–715. https://doi.org/10.1002/pits
Hu, X., Gong, Y., Lai, C., & Leung, F. K. S. (2018). The relationship between ICT and student literacy in mathematics, reading, and science across 44 countries: A multilevel analysis. Computers and Education, 125(June), 1–13. https://doi.org/10.1016/j.compedu.2018.05.021
Jiang, P., & Xiong, B. (2021). Online live teaching of mathematics gifted students on the tablet. In 2021 the 6th International Conference on Distance Education and Learning (ICDEL ’21) (pp. 157–161). New York: ACM. https://doi.org/10.1145/3474995.3475021
John-Steiner, V., & Mahn, H. (1996). Sociocultural approaches to Learning and Development: A Vygotskian Framework. Educational Psychologist, 31(3), 191–206. https://doi.org/10.4324/9781315110592-16
Jones, K. (2005). Using Logo in the teaching and learning of mathematics: a research bibliography. MicroMath, 21(3), 34–36. Retrieved from http://www.atm.org.uk/Micromath/83416%5Cnhttp://eprints.soton.ac.uk/19197/
Jordan, N. C., Glutting, J., & Ramineni, C. (2010). The importance of number sense to mathematics achievement in first and third grades. Learning and Individual Differences, 20(2), 82–88. https://doi.org/10.1016/J.LINDIF.2009.07.004
Kanevsky, L., Lo, C. O., & Marghelis, V. (2022). Individual or collaborative projects? Considerations influencing the preferences of students with high reasoning ability and others their age. High Ability Studies, 33(1), 87–119. https://doi.org/10.1080/13598139.2021.1903842
Kaushik, D. (2019). Role of ICT for better Mathematics Teaching. Shanlax International Journal of Education, 7(4), 19–28. https://doi.org/10.34293/EDUCATION.V7I4.641
Ke, F. (2014). An implementation of design-based learning through creating educational computer games: A case study on mathematics learning during design and computing. Computers & Education, 73, 26–39. https://doi.org/10.1016/j.compedu.2013.12.010
König, J., Jäger-biela, D. J., & Glutsch, N. (2020). Adapting to online teaching during COVID-19 school closure: Teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education, 43(4), 608–622. https://doi.org/10.1080/02619768.2020.1809650
Kontostavlou, E., & Drigas, A. S. (2019). The Use of Information and Communications Technology (I.C.T.) in gifted students. International Journal of Recent Contributions from Engineering Science & IT (IJES), 7(2), 60. https://doi.org/10.3991/ijes.v7i2.10815
Leikin, R. (2018). Giftedness and High Ability in Mathematics. In Encyclopedia of Mathematics Education (pp. 1–11). Springer International Publishing AG. https://doi.org/10.1007/978-94-007-4978-8_65
Leikin, R. (2019). The psychology of high performance: Developing human potential into domain-specific talent. In O. Kubilius & F. Worrell (Eds.), Developing mathematical talent in schoolchildren: Who, What, and How? (pp. 173–192). American Psychological Association. Retrieved from https://www.apa.org/pubs/books/4318157
Leikin, R. (2021). When practice needs more research: The nature and nurture of mathematical giftedness. ZDM - Mathematics Education, 53(7), 1579–1589. https://doi.org/10.1007/s11858-021-01276-9
Leikin, R., Leikin, M., & Waisman, I. (2017). What is special about the brain activity of mathematically gifted adolescents. Undefined, 165–181. https://doi.org/10.1007/978-3-319-38840-3_11
Lim Ping, C. (2002). A theoretical framework for the study of ICT in schools: A proposal. British Journal of Educational Technology, 33(4), 411–421.
Malanchini, M., Engelhardt, L. E., Grotzinger, A. D., Harden, K. P., & Tucker-Drob, E. M. (2019). Same but Different”: Associations between multiple aspects of Self-Regulation, cognition, and academic abilities. Journal of Personality and Social Psychology, 117(6), 1164–1188. https://doi.org/10.1037/PSPP0000224
Manuel, D. (2018). Virtual Learning Communities of Problem Solvers: A potential for developing Creativity in Mathematics? In V. Freiman, & J. L. Tassell (Eds.), Creativity and Technology in Mathematics Education, Mathematics Education in the Digital era (10th ed., pp. 531–557). Springer International Publishing. https://doi.org/10.1007/978-3-319-72381-5_21
Mitten, C., Collier, Z. K., & Leite, W. L. (2021). Online Resources for Mathematics: Exploring the relationship between teacher use and student performance. Investigations in Mathematics Learning, 13(3), 1–18. https://doi.org/10.1080/19477503.2021.1906041
Mrazik, M., & Dombrowski, S. C. (2010). The Neurobiological Foundations of Giftedness, 32(4), 224–234. https://doi.org/10.1080/02783193.2010.508154
Mustafayeva, M. A. (2020). Methods of working with talented students. Theoretical & Applied Science, 83(03), 405–408. https://doi.org/10.15863/TAS
Navas-Sánches, F., Carmona, S., Alemán-Gómez, Y., Sánchez-Gónzalez, J., Guzmán-de-Villoria, J., Franco, C., & Arango, C. (2016). Cortical morphometry in Frontoparietal andDefault Mode Networks in Math-GiftedAdolescents. HumanBrainMapping, 37, 1893–1902.
Neumann, M., Ronksley-Pavia, & Michelle (2021). Leveraging digital technologies for (re)engaging gifted students in the middle years. Australian Journal of Middle Schooling, 20(1), 22–34. Retrieved from https://research-repository.griffith.edu.au/bitstream/10072/401135/2/Neumann457879-Published.pdf
Nguyen, N., & Williams, P. J. (2016). An ICT supported sociocultural approach to improve the teaching of physics. Asia-Pacific Science Education, 2(2), 1–21. https://doi.org/10.1186/s41029-016-0008-2
OECD. (2015). Students, computers and learning: Making the connection. OECD Library. https://doi.org/10.1787/9789264239555-en
OECD. (2019a). PISA 2018 Questionnaire Framework. PISA 2018 Assessment and Analytical Framework (pp. 217–256). OECD Publishing. https://doi.org/10.1787/850d0ef8-en
OECD. (2019b). PISA 2018 results (volume I): What students know and can do (I vol.). OECD Publishing. https://doi.org/10.1787/5f07c754-en
OECD (2021a). 21st-Century Readers: Developing Literacy Skills in a Digital World. Retrieved from www.oecd.org/about/publishing/corrigenda.htm. ©.
OECD (2021b). Scaling procedures and construct validation of context questionnaire data. In PISA 2018 Technical Report (p. na). Paris: OECD Publishing.
OECD (2019c). PISA 2019 Assessment and Analytical Framework. OECD Publishing. Paris: OECD Publishing. Retrieved from https://www.oecd-ilibrary.org/docserver/9789264190511-en.pdf?expires=1569847112&id=id&accname=guest&checksum=08AEA3FD9105123D4555A383BD097B5E.
OECD (2019d). Proficency Scale Construction. In PISA 2018: Technical Report. Paris.
OECD, & First (2016). Socio-economic status, student performance and students’ attitudes toward science. PISA 2015 results (volume I) Excellence and Equity in Education (I vol., pp. 1–239). OECD Publishing. https://doi.org/10.1787/9789264266490-11-en
Palardy, G. J., & Rumberger, R. W. (2008). Teacher effectiveness in first grade: The importance of background qualifications, attitudes, and instructional practices for student learning. Educational Evaluation and Policy Analysis, 30(2), 111–140. https://doi.org/10.3102/0162373708317680
Paz-Baruch, N., Leikin, M., Aharon-Peretz, J., & Leikin, R. (2014). Speed of information processing in generally gifted and excelling-in-mathematics adolescents, 25(2), 143–167. https://doi.org/10.1080/13598139.2014.971102
Periathiruvadi, S., & Rinn, A. N. (2012). Technology in gifted education: A review of best practices and empirical research. Journal of Research on Technology in Education, 45(2), 153–169. https://doi.org/10.1080/15391523.2012.10782601
Peteros, E., Gamboa, A., Etcuban, J. O., Dinauanao, A., Sitoy, R., & Arcadio, R. (2019). Factors affecting Mathematics performance of Junior High School Students. International Electronic Journal of Mathematics Education, 15(1), em0556. https://doi.org/10.29333/IEJME/5938
Pfeiffer, S. I. (2015). In A. S. Kaufman, & N. L. Kaufman (Eds.), Essentials of Gifted Assessment. (First). John Wiley & Sons, Inc.
Plucker, J. A., & Peters, S. J. (2016). Excellence gaps in education: Expanding opportunities for talented students. Harvard Education Press.
Potochnick, S. (2018). The academic adaptation of immigrant students with interrupted schooling. American Educational Research Journal, 55(4), 859–892. https://doi.org/10.3102/0002831218761026
Pyryt, M. C. (2009). Recent developments in technology: Implications for Gifted Education. In L. V. Shavinina (Ed.), International Handbook of Giftedness. Springer US.
Raghubar, K. P., Barnes, M. A., & Hecht, S. A. (2010). Working memory and mathematics: A review of developmental, individual difference, and cognitive approaches. Learning and Individual Differences, 20(2), 110–122. https://doi.org/10.1016/J.LINDIF.2009.10.005
Ravaglia, R., Suppes, P., Stillinger, C., & Alper, T. M. (1995). Computer-based Mathematics and Physics for Gifted Students. Gifted Child Quarterly, 39(1), 7–13. https://doi.org/10.1177/001698629503900102
Reinhold, F., Hoch, S., Werner, B., Richter-Gebert, J., & Reiss, K. (2020). Learning fractions with and without educational technology: What matters for high-achieving and low-achieving students? Learning and Instruction, 65(February 2019), 101264. https://doi.org/10.1016/j.learninstruc.2019.101264
Sheffield, C. C. (2007). Technology and the gifted adolescent: Higher order thinking, 21st century literacy, and the digital native. Meridian, 10(2).
Shi, J., Tao, T., Chen, W., Cheng, L., Wanhg, L., & Zhang, X. (2013). Sustained attention in intellectually gifted children assessed using a continuous performance test. Plos One, 8(2), 1–8.
Spiezia, V. (2010). Does Computer Use Increase Educational Achievements? Student-level Evidence from PISA. OECD Journal: Economic Studies, 2010, 1–22. https://doi.org/10.1787/eco_studies-2010-5km33scwlvkf
Steenbergen-Hu, S., & Cooper, H. (2013). A meta-analysis of the effectiveness of intelligent tutoring systems on K-12 students’ mathematical learning. Journal of Educational Psychology, 105(4), 970–987. https://doi.org/10.1037/a0032447
Sternberg, R. (2003). Giftedness according to the theory of successful intelligence. Handbook of Gifted Education, 3ed, 55–60.
Subani, N., Mohd Nasrul, M. A. S., & Mohamad Shukri, M. Z. (2021). Enhance the Understanding of Gifted and Talented Muslims Student’s on Quadratic Functions Using GeoGebra. In E-Proceeding Insan Junior Researchers International Conference 2021 (pp. 88–94). Retrieved from www.geogebra.org
Subhi, T. (1999). The impact of LOGO on gifted children’s achievement and creativity. Journal of Computer Assisted Learning, 15(2), 98–108. https://doi.org/10.1046/j.1365-2729.1999.152082.x
Tannenbaum, A. J. (2003). Nature and nurture of giftedness. In N. Colangelo, & G. A. Davis (Orgs.) (Eds.), Handbook of gifted education (pp. 45–59). Allyn.
Torrecilla Sánchez, E. M., Olmos Miguélañez, S., & Martínez Abad, F. (2019). Explanatory factors as predictors of academic achievement in PISA tests. An analysis of the moderating effect of gender. International Journal of Educational Research, 96(March), 111–119. https://doi.org/10.1016/j.ijer.2019.06.002
Vaivre-Douret, L. (2011). Developmental and cognitive characteristics of “High-Level Potentialities” (highly gifted) children. International Journal of Pediatrics, 2011, 1–14. https://doi.org/10.1155/2011/420297
Vegas, E., & Coffin, C. (2015). When education expenditure matters: An empirical analysis of recent international data. Comparative Education Review, 59(2), 289–304. https://doi.org/10.1086/680324
Viberg, O., Grönlund, Å., & Andersson, A. (2023). Integrating digital technology in mathematics education: A swedish case study. Interactive Learning Environments, 31(1), 232–243. https://doi.org/10.1080/10494820.2020.1770801
Vogelaar, B., Sweijen, S. W., & Resing, W. C. M. (2019). Gifted and average-ability children’s potential for solving analogy items. Journal of Intelligence, 7(3), https://doi.org/10.3390/jintelligence7030019
Wang, H. Y., Huang, I., & Hwang, G. J. (2016). Comparison of the effects of project-based computer programming activities between mathematics-gifted students and average students. Journal of Computers in Education, 3(1), 33–45. https://doi.org/10.1007/s40692-015-0047-9
Winne, P. H., & Nesbit, J. C. (2010). The psychology of academic achievement. Annual Review of Psychology, 61, 653–678. https://doi.org/10.1146/annurev.psych.093008.100348
Wismath, S. L., & Orr, D. (2015). Collaborative learning in Problem solving: A Case Study in Metacognitive Learning. The Canadian Journal for the Scholarship of Teaching and Learning, 6(3), https://doi.org/10.5206/cjsotl-rcacea.2015.3.10
Youssef, A., Ben, Dahmani, M., & Ragni, L. (2022). ICT Use, Digital Skills and students’ academic performance: Exploring the Digital divide. Information (Switzerland), 13(129), 1–19. https://doi.org/10.3390/info13030129
Yun-Dai, D. (2009). Essential tensions surrounding the Concept of Giftedness. In L. V. Shavinina (Ed.), International Handbook of Giftedness (pp. 39–80). Springer.
Yusof, R., Ismail, M. J., & Radzi, A. M. (2022). Online Distance Learning: A New Learning Approach in the malaysian Gifted Education System. FWU Journal of Social Sciences, 16(1), 28–46. https://doi.org/10.51709/19951272/Spring2022/3
Zhang, L., Khan, G., & Tahirsylaj, A. (2015). Student performance, school differentiation, and world cultures: Evidence from PISA 2009. International Journal of Educational Development, 42, 43–53. https://doi.org/10.1016/j.ijedudev.2015.02.013
Zulnaidi, H., Oktavika, E., & Hidayat, R. (2020). Effect of use of GeoGebra on achievement of high school mathematics students. Education and Information Technologies, 25(1), 51–72. https://doi.org/10.1007/s10639-019-09899-y
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Vargas-Montoya, L., Gimenez, G. & Tkacheva, L. Only gifted students benefit from ICT use at school in mathematics learning. Educ Inf Technol 29, 8301–8326 (2024). https://doi.org/10.1007/s10639-023-12136-2
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DOI: https://doi.org/10.1007/s10639-023-12136-2