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Mobile Sensor Interfaces for Learning Science

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Learning and Collaboration Technologies (HCII 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14723))

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Abstract

In the context of science education, studies frequently highlight experimental practices employing diverse mobile device sensor interfaces for data collection and analysis. Despite the benefits, there is unclearness on sensor integration within science teaching. This study aims to propose a comprehensive model for understanding the interaction between students and mobile device sensors in science education. The model introduces a nested curricular integration approach, focusing on developing scientific skills through stages like observation, research planning, data processing, evidence analysis, and results communication. It also aligns these processes with three levels of technology presence: readiness, use, and integration. The evaluation revealed substantial positive changes in students’ expectations of enhanced science learning support, their attitudes toward classroom integration, and intentions to utilize the educational resources. Significant improvements were observed in Expectation of Performance, Attitude, and Intention to use. No significant changes were found in Anxiety-related aspects.

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References

  1. Sánchez, J.: Aprendizaje Visible, Tecnología Invisible. Dolmen Ediciones (2001)

    Google Scholar 

  2. Sánchez, J.: Integración curricular de TICS conceptos y modelos. Revista Enfoques Educacionales 5(1), 51–65 (2017)

    Google Scholar 

  3. Sánchez, J.: Bases constructivistas para la integración de TICs. Revista Enfoques Educacionales 6(1), 75–89 (2018)

    Article  Google Scholar 

  4. Cope, B., Kalantzis, M.: Multiliteracies: new literacies, learning, pedagogies. Int. J. 4(3), 164–195 (2009)

    Google Scholar 

  5. Gros, B., Kinshuk, Maina, M.: The future of ubiquitous learning: learning designs for emerging pedagogies. In: Gros, B., Kinshuk, Maina, M. (eds.). LNET, vol. 1, pp. 3–271. Springer, Heidelberg (2016)

    Google Scholar 

  6. McQuiggans, S., McQuiggans, J., Sabourin, J., Kosturko, L.: Mobile Learning: A Handbook for Developers, Educators, and Learners. Wiley and SAS Business Series (2015)

    Google Scholar 

  7. Kuhn, J., Vogt, P.: Analyzing spring pendulum phenomena with a smart-phone acceleration sensor. Phys. Teacher 50(8), 504–505 (2012)

    Article  Google Scholar 

  8. Monteiro, M., Cabeza, C., Martí, A.: Acceleration measurements using smartphone sensors: dealing with the equivalence principle. Revista Brasileira de Ensino de Física, 37(1), 1303 (2015)

    Google Scholar 

  9. Monteiro, M., Cabeza, C., Martí, A.: The atwood machine revisited using smartphones. Phys. Teacher 53(6), 373–374 (2015)

    Article  Google Scholar 

  10. Pili, U., Violanda, R., Ceniza, C.: Measurement of g using a magnetic pendulum and a smartphone magnetometer. Phys. Teacher 56(4), 258–325 (2018)

    Article  Google Scholar 

  11. Pili, U., Violanda, R., Ceniza, C.: Measuring a spring constant with a smartphone magnetic field sensor. Phys. Teacher 57(3), 198–199 (2019)

    Article  Google Scholar 

  12. Becker, S., Klein, P., Kuhn, J.: Video analysis on tablet computers to investigate effects of air resistance. Phys. Teacher 54(7), 440–441 (2016)

    Article  Google Scholar 

  13. Kuhn, J., Vogt, P., Hirth, M.: Analyzing the acoustic beat with mobile devices. Phys. Teacher 52(4), 248–249 (2014)

    Article  Google Scholar 

  14. Schwarz, O., Vogt, P., Kuhn, J.: Acoustic measurements of bouncing balls and the determination of gravitational acceleration. Phys. Teacher 51(5), 312 (2013)

    Article  Google Scholar 

  15. Silva-Alé, J.: Determination of gravity acceleration with smartphone ambient light sensor. Phys. Teacher 59(3), 2018 (2021)

    Article  Google Scholar 

  16. Wang, T.H., Lim, K.Y.T., Lavonen, J., Clark-Wilson, A.: Maker-centred science and mathematics education: lenses, scales and contexts. Int. J. Sci. Math. Educ. 17, 1–11 (2019)

    Article  Google Scholar 

  17. Sánchez, J.: Successful IT Curriculum Integration: Concepts and Cases. In: Proceedings of ECIS IT Conference, pp. 7–9 (2003)

    Google Scholar 

  18. UNESCO. Guidelines for ICT in Education Policies and Masterplans. UNESCO (2022)

    Google Scholar 

  19. UNESCO. The International Science and Evidence based Education (ISEE) Assessment: 2.6 Education Technology. UNESCO (2023)

    Google Scholar 

  20. The Organization for Economic Co-operation and Development: OECD Future of Education and Skills 2030 OECD Learning Compass 2030 a Series Of Concept Notes. OECD (2020)

    Google Scholar 

  21. UNESCO: UNESCO ICT Competency Framework for Teachers. UNESCO (2018)

    Google Scholar 

  22. World Economic Forum. Schools of the Future: Defining New Models of Education for the Fourth Industrial Revolution. World Economic Forum (2020)

    Google Scholar 

  23. Livingstone, K.: The Place of Information and Communication Technologies in Curriculum Design and Development. Int. J. Educ. Developm. Inf. Commun. Technol. 15(4) (2019)

    Google Scholar 

  24. UNESCO. Global Education Monitoring Report, 2023: Technology in Education: A Tool on Whose Terms? UNESCO (2023)

    Google Scholar 

  25. Bogiannidis, N., Southcott, J., Gindidis, M.: An exploration of the possible educational opportunities and the challenges at the intersection of the physical and digital worlds occupied by 10–14-year-old students. Smart Learn. Environ. 10(26) (2023)

    Google Scholar 

  26. Jagust, T., Boticki, I., So, H.-J.: A review of research on bridging the gap between formal and informal learning with technology in primary school contexts. J. Comput. Assist. Learn. 34(4), 417–428 (2018)

    Article  Google Scholar 

  27. Rasheed, R., Kamsin, A., Abdullah, N.: Challenges in the online component of blended learning: a systematic review. Comput. Educ. 144, 103701 (2020)

    Google Scholar 

  28. Chen, X., Xie, H., Zou, D., Hwang, G.J.: Application and theory gaps during the rise of artificial intelligence in education. Comput. Educ. 1, 100002 (2020)

    Google Scholar 

  29. Tang, K.Y., Chang, C.Y., Hwang, G.J.: Trends in artificial intelligence-supported e-learning: a systematic review and co-citation network analysis (1998–2019). Interact. Learn. Environ. 1–19 (2021)

    Google Scholar 

  30. Aslan, A., Zhu, C.: Investigating variables predicting Turkish pre-service teachers’ integration of ICT into teaching practices. Br. J. Edu. Technol. 48(2), 552–270 (2016)

    Article  Google Scholar 

  31. Aslan, A., Zhu, C.: Influencing factors and integration of ICT into teaching practices of pre-service and starting teachers. Int. J. Res. Educ. Sci. 2(2), 359–370 (2016)

    Article  Google Scholar 

  32. Suleimen, N.: Appraising the attitude towards information communication technology integration and usage in Kazakhstani higher education curriculum. J. Inf. Technol. Educ. Res. 18(1), 355–378 (2019)

    Google Scholar 

  33. Li, S., Yamaguchi, S., Takada, J.: Understanding factors affecting primary school teachers’ use of ICT for student-centered education in Mongolia 14(1), 103–117 (2018)

    Google Scholar 

  34. Hammou, Y., Elfatihi, M.: Moroccan teachers’ level of ICT integration in secondary EFL classrooms. Int. J. Lang. Literary Stud. 1(3) (2019)

    Google Scholar 

  35. Aksal, F., Gazi, Z.: Examination on ICT integration into special education schools for developing countries. TOJET: The Turkish Onl. J. Educ. Technol. 14(3), 124–130 (2015)

    Google Scholar 

  36. Dong, C., Newman, L.: Ready, steady … pause: integrating ICT into Shanghai preschools. Int. J. Early Years Educ. 24(2), 224–237 (2016)

    Article  Google Scholar 

  37. Xiao, J., Cao, M., Li, X., Hansen, P.: Assessing the effectiveness of the augmented reality courseware for starry sky exploration. Int. J. Distance Educ. Technol. 18(1), 19–35 (2020)

    Article  Google Scholar 

  38. Chun, K.: Pedagogical Innovation Through Mobile Learning Implementation: An Exploratory Study on Teachers’ Extended and Emergent Use of Mobile Learning Systems. ProQuest Dissertations Publishing (2019)

    Google Scholar 

  39. Lai, C.: Trends of mobile learning: a review of the top 100 highly cited papers. Br. J. Educ. Technol. 1–22 (2019)

    Google Scholar 

  40. Laine, T.: Mobile educational augmented reality games: a systematic literature review and two case studies. Computers 7(1), 19 (2018)

    Article  Google Scholar 

  41. Baran, B., Yecan, E., Kaptan, B., Pasayigit, O.: Using augmented reality to teach fifth grade students about electrical circuits. Educ. Inf. Technol. 25, 1371–1385 (2020)

    Article  Google Scholar 

  42. Ozdemir, M., Sahin, C., Arcagok, S., Demir, M.K.: The effect of augmented reality applications in the learning process: a meta-analysis study. Eurasian J. Educ. Res. 18(74) (2018)

    Google Scholar 

  43. Bos, A., et al.: Educational technology and its contributions in students’ focus and attention regarding augmented reality environments and the use of sensors. J. Educ. Comput. Res. 57, 1832–1848 (2019)

    Article  Google Scholar 

  44. Coimbra, M., Cardoso, T., Mateus, A.: Augmented reality: an enhancer for higher education students in math’s learning? Procedia Comput. Sci. 67 (2015)

    Google Scholar 

  45. Guncaga, J., Janiga, R.: Virtual labs and educational software as a tool for more effective teaching STEM subjects. In: The Third International Conference on Computer Science, Computer Engineering, and Education Technologies (2016)

    Google Scholar 

  46. Ewais, A., Troyer, O.: A usability and acceptance evaluation of the use of augmented reality for learning atoms and molecules reaction by primary school female students in Palestine. J. Educ. Comput. Res. 57(7), 1643–1670 (2019)

    Article  Google Scholar 

  47. Donhauser, A., et al.: Making the invisible visible: visualization of the connection between magnetic field, electric current, and Lorentz force with the help of augmented reality. Phys. Teacher 58(6), 438–439 (2020)

    Article  Google Scholar 

  48. Bodensiek, O., Sonntag, D., Wendorff, N., Albuquerque, G., Magnor, M.: Augmenting the fine beam tube: from hybrid measurements to magnetic field visualization. Phys. Teacher 57(4), 262–263 (2019)

    Article  Google Scholar 

  49. Heafner, J.: Astronomical apps for teaching astronomy. Phys. Teacher 57(7), 504–505 (2019)

    Google Scholar 

  50. Lincoln, J.: Augmented reality Moon for astronomy lessons. Phys. Teacher 56(7), 492–493 (2018)

    Article  Google Scholar 

  51. Silva-Alé, J.: Learning volcanism through school projects: a pedagogical design using technology in pandemic context. Revista Saberes Educativos 7, 111–130 (2021)

    Article  Google Scholar 

  52. MacIsaac, D.: NYT virtual tour of CERN’s Large Hadron Collider. Phys. Teacher 57(2), 126 (2019)

    Google Scholar 

  53. MacIsaac, D.: Perseverance: the new Rover on Mars. Phys. Teacher 59(4), 303 (2021)

    Google Scholar 

  54. Lauer, L., et al.: Real-time visualization of electrical circuit schematics: an augmented reality experiment setup to foster representational knowledge in introductory physics education. Phys. Teacher 58(7), 518–519 (2020)

    Article  Google Scholar 

  55. Kapp, S., et al.: Augmenting Kirchhoff’s laws: using augmented reality and smart glasses to enhance conceptual electrical experiments for high school students. Phys. Teacher 57(1), 52–53 (2019)

    Article  Google Scholar 

  56. Chandrakar, M., Bhagat, K., Kumar: Development of an augmented reality-based game for projectile motion. Phys. Teacher 58(9), 668–669 (2020)

    Google Scholar 

  57. Monteiro, M., Cabeza, C., Martí, A.: Acceleration measurements using smartphone sensors: dealing with the equivalence principle. Phys. Teacher 37(1), 1303 (2015)

    Google Scholar 

  58. Silva-Alé, J.: Determination of gravity acceleration with smartphone ambient light sensor. Phys. Teacher 59(3), 218–219 (2021)

    Article  Google Scholar 

  59. Chamizo, J.: Una tipología de los modelos para la enseñanza de las ciencias. Revista Eureka Enseñanza y Divulgación de las Ciencias 7(1), 26–41 (2010)

    Article  Google Scholar 

  60. Chamizo, J.: A new definition of models and modeling in chemistry’s teaching. Sci. Educ. 22(7), 1613–1632 (2011)

    Article  Google Scholar 

  61. Soto, M., Couso, D., López, V., Hernández, M.: Promoviendo la apropiación del modelo de energía en estudiantes de 4º de ESO a través del diseño didáctico. Revista de Educación Científica 1(1) (2017)

    Google Scholar 

  62. Hernández, M., Couso, D., Pintó, R.: Analyzing students’ learning progressions throughout a teaching sequence on acoustic properties of materials with a model-based inquiry approach. J. Sci. Educ. Technol. 24(2–3), 356–377 (2015)

    Article  Google Scholar 

  63. Greca, M., Moreira, M.: Modelos mentales y aprendizaje de física en electricidad y magnetismo. Enseñanza de las ciencias: revista de investigación y experiencias didácticas 16(2) (1998)

    Google Scholar 

  64. Justi, R.: La enseñanza de la ciencia basada en la elaboración de modelos. Enseñanza de las ciencias 24(2), 173–184 (2006)

    Google Scholar 

  65. Schwarz, C., Gwekwerere, Y.: Using a guided inquiry and modeling instructional framework (EIMA) to support preservice K-8 science teaching. Sci. Educ. 91(1), 158–186 (2007)

    Google Scholar 

  66. Couso, D., Garrido, A.: Models and modelling in elementary school pre-service teacher education: why we need both. In: Cognitive and Affective Aspects in Science Education Research. Springer International Publishing 1(3), 245–261 (2017)

    Google Scholar 

  67. Tünnermann, C.: Modelos Educativos y Académicos. Brevarios Universitarios (2008)

    Google Scholar 

  68. Sierra, R.: Técnicas de Investigación Social: Teoría y Ejercicios (2001)

    Google Scholar 

  69. Davis, F.: Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989)

    Article  Google Scholar 

  70. Venkatesh, V., Davis, F.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46(2), 186–204 (2000)

    Google Scholar 

  71. Venkatesh, V., Morris, M., Davis, G., Davis, F.: User acceptance of information technology: toward a unified view. MIS Q. 27(3), 425–478 (2003)

    Article  Google Scholar 

  72. Venkatesh, V., Bala, H.: Technology acceptance model 3 and a research agenda on interventions. Decis. Sci. 39, 273–315 (2008)

    Article  Google Scholar 

  73. Fogarty, R.: Ten ways to integrate the curriculum. Educ. Leadersh. 49(2), 61–65 (1991)

    Google Scholar 

  74. Fogarty, R.: The Mindful School: How to Integrate the Curricula: Training Manual. IRI/Skylight Publishing (1993)

    Google Scholar 

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Acknowledgments

This work was funded by Chilean National Agency for Research and Development (ANID), Basal Funding for Scientific and Technology Centers of Excellence, project FB0003.

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Correspondence to Jhon Alé .

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Alé, J., Sánchez, J. (2024). Mobile Sensor Interfaces for Learning Science. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. HCII 2024. Lecture Notes in Computer Science, vol 14723. Springer, Cham. https://doi.org/10.1007/978-3-031-61685-3_10

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  • DOI: https://doi.org/10.1007/978-3-031-61685-3_10

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