La integración de dispositivos móviles en el aula para la enseñanza del álgebra: el caso de la función lineal
Using mobile devices in classroom for algebra teaching: the case of linear function

Barra lateral de artículos

PDF XML
Publicado ene 11, 2022
DOI https://doi.org/10.17081/eduhum.24.42.4044

Contenido principal de artículos

Vladimir Ballesteros-Ballesteros
Fundación Universitaria Los Libertadores, Bogotá, Colombia
Carlos López-Torres
Fundación Universitaria Los Libertadores, Bogotá, Colombia
Marcela Torres-Rodríguez
Fundación Universitaria Los Libertadores, Bogotá, Colombia
Sébastien Lozano-Forero
Fundación Universitaria Los Libertadores, Bogotá, Colombia
https://orcid.org/0000-0002-9551-165X

Resumen

Objetivo: Describir los efectos y las experiencias de la incorporación de la aplicación “Calculadora Gráfica” de GeoGebra para el aprendizaje de la función lineal con estudiantes de undécimo grado a partir de la integración de dispositivos móviles al aula de clase. Método: Desde el paradigma pragmático, se empleó un diseño explicativo secuencial para orientar los esfuerzos investigativos conducentes a validar la hipótesis relacionada con una influencia positiva del aprovechamiento de teléfonos inteligentes y tabletas en el desempeño escolar. En la etapa cuantitativa se realizó un diseño experimental de cuatro grupos de Solomon y durante la etapa cualitativa se empleó un test actitudinal y se aplicaron entrevistas semiestructuradas con estudiantes que participaron del tratamiento con la aplicación móvil. Resultados: Los resultados obtenidos en el postest por los grupos experimentales fueron superiores a los obtenidos por los grupos control que recibieron una intervención mediada por recursos didácticos tradicionales y los estudiantes que recibieron el tratamiento manifestaron mayor interés y motivación por el aprendizaje del tema abordado. Discusión y Conclusiones: La integración de dispositivos móviles en el aula promueve otras formas innovadoras de aprender y desarrolla habilidades en los estudiantes, favoreciendo su motivación e interés.

Descargas

Los datos de descargas todavía no están disponibles.

Detalles de artículo

Número
Vol. 24 Núm. 42 (2022): Enero-Junio
Sección
ARTíCULOS
Creative Commons License

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.

Aquellos autores/as que tengan publicaciones con esta revista, aceptan los términos siguientes:

  1. Los autores/as conservarán sus derechos de autor y garantizarán a la revista el derecho de primera publicación de su obra, el cuál estará simultáneamente sujeto a la Licencia de reconocimiento de Creative Commons que permite a terceros compartir la obra siempre que se indique su autor y su primera publicación esta revista.
  2. Los autores/as podrán adoptar otros acuerdos de licencia no exclusiva de distribución de la versión de la obra publicada (p. ej.: depositarla en un archivo telemático institucional o publicarla en un volumen monográfico) siempre que se indique la publicación inicial en esta revista.
  3. Se permite y recomienda a los autores/as difundir su obra a través de Internet (p. ej.: en archivos telemáticos institucionales o en su página web) antes y durante el proceso de envío, lo cual puede producir intercambios interesantes y aumentar las citas de la obra publicada. (Véase El efecto del acceso abierto).

Licencia de Creative Commons
Este obra está bajo una licencia de Creative Commons Reconocimiento 4.0 Internacional.

Referencias

Citas

  1. Aizikovitsh-Udi, E., & Radakovic, N. (2012). Teaching probability by using geogebra dynamic tool and implemanting critical thinking skills. Procedia-Social and Behavioral Sciences, (46), 4943–4947. https://doi.org/10.1016/j.sbspro.2012.06.364
  2. All, A., Plovie, B., Castellar, E. P. N., & Van Looy, J. (2017). Pre-test influences on the effectiveness of digital-game based learning: A case study of a fire safety game. Computers & Education, (114), 24–37. https://doi.org/10.1016/j.compedu.2017.05.018
  3. Azar, A. S., & Nasiri, H. (2014). Learners’ attitudes toward the effectiveness of mobile assisted language learning (MALL) in L2 listening comprehension. Procedia-Social and Behavioral Sciences, (98), 1836–1843. https://doi.org/10.1016/j.sbspro.2014.03.613
  4. Bano, M., Zowghi, D., Kearney, M., Schuck, S., & Aubusson, P. (2018). Mobile learning for science and mathematics school education: A systematic review of empirical evidence. Computers & Education, (121), 30–58. https://doi.org/10.1016/j.compedu.2018.02.006
  5. Baron, N. S., & Campbell, E. M. (2012). Gender and mobile phones in cross-national context. Language Sciences, 34(1), 13–27. https://doi.org/10.1016/j.langsci.2011.06.018
  6. Bauer, L. B. (2018). A necessary addiction: Student conceptualizations of technology and its impact on teaching and learning. Journal of College Reading and Learning, 48(1), 67–81. https://doi.org/10.1080/10790195.2017.1365668
  7. Benítez Armas, A. F. (2016). Un experimento con GeoGebra (app) para el desarrollo del pensamiento matemático. Revista de Arte y Humanidades, 3(4), 9–22. Retrieved from https://www.upaep.mx/images/revista_artes_humanidades/pdf/AH_4212.pdf
  8. Bokosmaty, S., Mavilidi, M.-F., & Paas, F. (2017). Making versus observing manipulations of geometric properties of triangles to learn geometry using dynamic geometry software. Computers & Education, (113), 313–326. https://doi.org/10.1016/j.compedu.2017.06.008
  9. Braver, M. W., & Braver, S. L. (1988). Statistical treatment of the Solomon four-group design: A meta-analytic approach. Psychological Bulletin, 104(1), 150. https://doi.org/10.1037/0033-2909.104.1.150
  10. Breda, A. M. D., & Santos, J. M. D. S. Dos. (2016). Complex functions with GeoGebra. Teaching Mathematics and Its Applications: An International Journal of the IMA, 35(2), 102–110. https://doi.org/10.1093/teamat/hrw010
  11. Burston, J. (2011). Realizing the potential of mobile phone technology for language learning. IALLT Journal of Language Learning Technologies, 41(2), 56–71. https://doi.org/10.17161/iallt.v41i2.8490
  12. Caligaris, M. G., Schivo, M. E., & Romiti, M. R. (2015). Calculus & GeoGebra, an interesting partnership. Procedia-Social and Behavioral Sciences, (174), 1183–1188. https://doi.org/10.1016/j.sbspro.2015.01.735
  13. Chan, S. W., & Ismail, Z. (2014). Developing statistical reasoning assessment instrument for high school students in descriptive statistics. Procedia-Social and Behavioral Sciences, (116), 4338–4343. https://doi.org/10.1016/j.sbspro.2014.01.943
  14. Cheng Lim, S., Mustapha, F. I., Aagaard-Hansen, J., Calopietro, M., Aris, T., & Bjerre-Christensen, U. (2019). Impact of Continuing Medical Education for Primary Healthcare Providers in Malaysia on Diabetes Knowledge, Attitudes, Skills and Clinical Practices. Medical Education Online, (25), 1–11. https://doi.org/10.1080/10872981.2019.1710330
  15. Cox, M. J., & Marshall, G. (2007). Effects of ICT: do we know what we should know? Education and Information Technologies, 12(2), 59–70. https://doi.org/10.1007/s10639-007-9032-x
  16. Cruz, S., Carvalho, A. A. A., & Araújo, I. (2017). A game for learning history on mobile devices. Education and Information Technologies, 22(2), 515–531. https://doi.org/10.1007/s10639-016-9491-z
  17. Diković, L. (2009). Applications GeoGebra into teaching some topics of mathematics at the college level. Computer Science and Information Systems, 6(2), 191–203. https://doi.org/10.2298/CSIS0902191D
  18. Drijvers, P. (2015). Digital technology in mathematics education: Why it works (or doesn’t). Selected Regular Lectures from the 12th International Congress on Mathematical Education, 135–151. https://doi.org/10.1007/978-3-319-17187-6_8
  19. Göksu, İ., & Atici, B. (2013). Need for mobile learning: technologies and opportunities. Procedia-Social and Behavioral Sciences, 103, 685–694. https://doi.org/10.1016/j.sbspro.2013.10.388
  20. Harley, J. M., Poitras, E. G., Jarrell, A., Duffy, M. C., & Lajoie, S. P. (2016). Comparing virtual and location-based augmented reality mobile learning: emotions and learning outcomes. Educational Technology Research and Development, 64(3), 359–388. https://doi.org/10.1007/s11423-015-9420-7
  21. Heflin, H., Shewmaker, J., & Nguyen, J. (2017). Impact of mobile technology on student attitudes, engagement, and learning. Computers & Education, (107), 91–99. https://doi.org/10.1016/j.compedu.2017.01.006
  22. Hohenwarter, M., & Jones, K. (2007). Ways of linking geometry and algebra, the case of Geogebra. Proceedings of the British Society for Research into Learning Mathematics, 27(3), 126–131. http://eprints.soton.ac.uk/id/eprint/50742
  23. Huang, C. S. J., Yang, S. J. H., Chiang, T. H. C., & Su, A. Y. S. (2016). Effects of situated mobile learning approach on learning motivation and performance of EFL students. Journal of Educational Technology & Society, 19(1), 263–276. https://doi.org/https://www.jstor.org/stable/jeductechsoci.19.1.263
  24. Huang, R., & Price, J. K. (2016). ICT in education in global context. Springer, (10), 973–978. https://doi.org/10.1007/978-3-319-19234-5_5
  25. Hwang, G.-J., & Chang, H.-F. (2011). A formative assessment-based mobile learning approach to improving the learning attitudes and achievements of students. Computers & Education, 56(4), 1023–1031. https://doi.org/10.1016/j.compedu.2010.12.002
  26. İBİLİ, E. (2019). The Use of Dynamic Geometry Software from a Pedagogical Perspective: Current Status and Future Prospects. Journal of Computer and Education Research, 7(14), 337–355. https://doi.org/10.18009/jcer.579517
  27. Ivankova, N. V, Creswell, J. W., & Stick, S. L. (2006). Using mixed-methods sequential explanatory design: From theory to practice. Field Methods, 18(1), 3–20. https://doi.org/10.1177/1525822X05282260
  28. Jeon, Y.-J. (2015). A study on technology embedded english classes using qr codes. International Journal of Contents, 11(1), 1–6. https://doi.org/10.5392/IJoC.2015.11.1.001
  29. Keller, J. M. (2016). Motivation, learning, and technology: Applying the ARCS-V motivation model. Participatory Educational Research, 3(2), 1–15. https://doi.org/10.17275/per.16.06.3.2
  30. Kesharwani, A. (2020). Do (how) digital natives adopt a new technology differently than digital immigrants? A longitudinal study. Information & Management, 57(2), 103170. https://doi.org/10.1016/j.im.2019.103170
  31. Kolář, P. (2019). GeoGebra for Secondary School Physics. Journal of Physics: Conference Series, 1223(1), 12008. https://doi.org/10.1088/1742-6596/1223/1/012008
  32. König, A., & Bernsen, D. (2014). Mobile learning in history education. Journal of Educational Media, Memory, and Society, 6(1), 107–123. https://doi.org/10.3167/jemms.2014.060106
  33. Kösa, T., & Karakuş, F. (2010). Using dynamic geometry software Cabri 3D for teaching analytic geometry. Procedia-Social and Behavioral Sciences, 2(2), 1385–1389. https://doi.org/10.1016/j.sbspro.2010.03.204
  34. Lan, Y.-F., Tsai, P.-W., Yang, S.-H., & Hung, C.-L. (2012). Comparing the social knowledge construction behavioral patterns of problem-based online asynchronous discussion in e/m-learning environments. Computers & Education, 59(4), 1122–1135. https://doi.org/10.1016/j.compedu.2012.05.004
  35. Ljajko, E., & Ibro, V. (2013). Development of Ideas in a GeoGebra-Aided Mathematics Instruction. Online Submission, 3(3), 1-7. https://doi.org/10.13054/mije.si.2013.01
  36. Motiwalla, L. F. (2007). Mobile learning: A framework and evaluation. Computers & Education, 49(3), 581–596. https://doi.org/10.1016/j.compedu.2005.10.011
  37. Mudaly, V., & Fletcher, T. (2019). The effectiveness of Geogebra when teaching linear functions using the iPad. Problems of Education in the 21st Century, 77(1), 55–81. https://doi.org/0.33225/pec/19.77.55
  38. Pachler, N., Bachmair, B., & Cook, J. (2010a). Mobile learning: A topography. In Mobile Learning, 29–72. https://doi.org/10.1007/978-1-4419-0585-7_2
  39. Pachler, N., Bachmair, B., & Cook, J. (2010b). Mobile Learning: Structures, Agency, Practices. https://doi.org/10.1007/978-1-4419-0585-7
  40. Pamungkas, M. D., Rahmawati, F., & Dinara, H. A. (2020). Integrating GeoGebra into Space Geometry in College. 3rd International Conference on Learning Innovation and Quality Education (ICLIQE 2019), 999–1006. https://doi.org/10.2991/assehr.k.200129.123
  41. Pilli, O., & Aksu, M. (2013). The effects of computer-assisted instruction on the achievement, attitudes and retention of fourth grade mathematics students in North Cyprus. Computers & Education, (62), 62–71. https://doi.org/10.1016/j.compedu.2012.10.010
  42. Pimmer, C., Mateescu, M., & Gröhbiel, U. (2016). Mobile and ubiquitous learning in higher education settings. A systematic review of empirical studies. Computers in Human Behavior, (63), 490–501. https://doi.org/10.1016/j.chb.2016.05.057
  43. Radakovic, N., & McDougall, D. (2012). Using dynamic geometry software for teaching conditional probability with area-proportional Venn diagrams. International Journal of Mathematical Education in Science and Technology, 43(7), 949–953. https://doi.org/10.1080/0020739X.2011.633628
  44. Reisa, Z. A. (2010). Computer supported mathematics with Geogebra. Procedia-Social and Behavioral Sciences, (9), 1449–1455. https://doi.org/10.1016/j.sbspro.2010.12.348
  45. Rybanska, V., McKay, R., Jong, J., & Whitehouse, H. (2018). Rituals improve children’s ability to delay gratification. Child Development, 89(2), 349–359. https://doi.org/10.1111/cdev.12762
  46. Schuck, S., Kearney, M., & Burden, K. (2017). Exploring mobile learning in the Third Space. Technology, Pedagogy and Education, 26(2), 121–137. https://doi.org/10.1080/1475939X.2016.1230555
  47. Solomon, R. L. (1949). An extension of control group design. Psychological Bulletin, 46(2), 137. https://doi.org/10.1037/h0062958
  48. Sung, Y.-T., Chang, K.-E., & Liu, T.-C. (2016). The effects of integrating mobile devices with teaching and learning on students’ learning performance: A meta-analysis and research synthesis. Computers & Education, (94), 252–275. https://doi.org/10.1016/j.compedu.2015.11.008
  49. Tomaschko, M., & Hohenwarter, M. (2018). Usability Evaluation of a Mobile Graphing Calculator Application Using Eye Tracking. International Conference on Learning and Collaboration Technologies, 180–190. https://doi.org/10.1007/978-3-319-91743-6_14
  50. Van Landschoot, R., Portzky, G., & Van Heeringen, K. (2017). Knowledge, self-confidence and attitudes towards suicidal patients at emergency and psychiatric departments: A randomised controlled trial of the effects of an educational poster campaign. International Journal of Environmental Research and Public Health, 14(3), 304. https://doi.org/10.3390/ijerph14030304
  51. Vanden Abeele, M. M. P. (2016). Mobile youth culture: A conceptual development. Mobile Media & Communication, 4(1), 85–101. https://doi.org/10.1177/2050157915601455
  52. Wu, W.-H., Wu, Y.-C. J., Chen, C.-Y., Kao, H.-Y., Lin, C.-H., & Huang, S.-H. (2012). Review of trends from mobile learning studies: A meta-analysis. Computers & Education, 59(2), 817–827. https://doi.org/10.1016/j.compedu.2012.03.016
  53. Zazkis, R. (2020). Technology in Mathematics Teacher Education on Trust and Pitfalls. In STEM Teachers and Teaching in the Digital Era (pp. 243–259). https://doi.org/10.1007/978-3-030-29396-3_13
  54. Zengin, Y., Furkan, H., & Kutluca, T. (2012). The effect of dynamic mathematics software geogebra on student achievement in teaching of trigonometry. Procedia-Social and Behavioral Sciences, (31), 183–187. https://doi.org/10.1016/j.sbspro.2011.12.038
  55. 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