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Digital Learning Technologies in Chemistry Education: A Review

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Digital Technologies: Sustainable Innovations for Improving Teaching and Learning

Abstract

This study is a systematic review of empirical research on digital learning technologies and their educational applications in primary and secondary Chemistry Education, during the period 2002–2016. Despite the importance of digital learning technologies in Chemistry Education, this review comes to light because of the current lack of similar works, in that it outlines and organizes the existing literature highlighting the technologies and pedagogical approaches adopted. Forty-three related studies published in peer-reviewed scientific journals were identified and reviewed. Results show that most researchers are interested in chemistry topics related to the particulate nature of matter and use digital learning technologies, to mainly create and present visualizations of simulations and models of structural elements of matter and their phenomena. Researchers are interested overall in assessing digital technologies’ contribution to learning and the main technologies used include multimedia and simulations. Most studies are designed as quasi-experiments, and the assessment of learning outcomes is mostly done through questionnaires. The review emphasizes the pedagogical value of digital learning technologies in Chemistry Education. Meta-analyses of the empirical studies could contribute to further understand the pedagogical added value digital learning technologies offer in Chemistry Education.

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References

  1. Dalgarno, B., & Lee, M. J. W. (2010). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41(1), 10–32.

    Article  Google Scholar 

  2. Jonassen, D. H. (2000). Computers as mindtools for schools. Upper Saddle River: Prentice Hall.

    Google Scholar 

  3. Mikropoulos, T. A., & Bellou, I. (2010). Senária didaskalías me ypologistí (Educational scenarios with ICT). Athens: Kleidarithmos.

    Google Scholar 

  4. Tsaparlis, G. (1991). Thémata Didaktikís Phisikís kai Khimías sti Mési Ekpaídefsi (Topics in Physics and Chemistry didactics in secondary education). Athens: M. P. Grigori.

    Google Scholar 

  5. O’Haver, T. C. (1991). Applications of computers and computer software in teaching analytical chemistry. Analytical Chemistry, 63(9), 521–534.

    Article  Google Scholar 

  6. Osborne, J., & Hennessy, S. (2003). Report 6: Literature review in science education and the role of ICT: Promise, problems and future directions. Bristol: Futurelab Series.

    Google Scholar 

  7. Randolph, J. J., Julnes, G., Bednarik, R., & Sutinen, E. (2007). A comparison of the methodological quality of articles in computer science education journals and conference proceedings. Computer Science Education, 17(4), 263–274.

    Article  Google Scholar 

  8. Ferk, V., Vrtacnik, M., Blejec, A., & Gril, A. (2003). Students’ understanding of molecular structure representations. International Journal of Science Education, 25(10), 1227–1245.

    Article  Google Scholar 

  9. Gregorius, R. M., Santos, R., Dano, J. B., & Gutierrez, J. J. (2010). Can animations effectively substitute for traditional teaching methods? Part I: Preparation and testing of materials. Chemistry Education Research and Practice, 11(4), 253–261.

    Article  Google Scholar 

  10. Gregorius, R. M., Santos, R., Dano, J. B., & Gutierrez, J. J. (2010). Can animations effectively substitute for traditional teaching methods? Part II: Potential for differentiated learning. Chemistry Education Research and Practice, 11(4), 262–266.

    Article  Google Scholar 

  11. Kontogeorgiou, Α. Μ., Bellou, J., & Mikropoulos, T. A. (2008). Being inside the Quantum Atom. PsychNology Journal, 6(1), 83–98, http://www.psychnology.org/328.php.

    Google Scholar 

  12. Rizman Herga, N., Čagran, B., & Dinevski, D. (2016). Virtual laboratory in the role of dynamic visualisation for better understanding of chemistry in primary school. Eurasia Journal of Mathematics, Science and Technology Education, 12, 593–608. https://doi.org/10.12973/eurasia.2016.1224a

    Google Scholar 

  13. Aksela, M., & Lundell, J. (2008). Computer-based molecular modeling: Finnish school teachers’ experiences and views. Chemistry Education Research and Practice, 9(4), 301–308.

    Article  Google Scholar 

  14. Lavonen, J., Juuti, K., & Meisalo, V. (2003). Designing a user-friendly microcomputer-based laboratory package through the factor analysis of teacher evaluations. International Journal of Science Education, 25(12), 1471–1487.

    Article  Google Scholar 

  15. Savec, V. F., Vrtačnik, M., Gilbert, J. K., & Peklaj, C. (2006). In-service and pre-service teachers’ opinion on the use of models in teaching chemistry. Acta Chimica Slovenica, 53(3), 381–390.

    Google Scholar 

  16. Ardac, D., & Akaygun, S. (2004). Effectiveness of multimedia-based instruction that emphasizes molecular representations on students’ understanding of chemical change. Journal of Research in Science Teaching, 41(4), 317–337.

    Article  Google Scholar 

  17. Ardac, D., & Akaygun, S. (2005). Using static and dynamic visuals to represent chemical change at molecular level. International Journal of Science Education, 27(11), 1269–1298.

    Article  Google Scholar 

  18. Adadan, E., Irving, K. E., & Trundle, K. C. (2009). Impacts of multi-representational instruction on high school students’ conceptual understandings of the particulate nature of matter. International Journal of Science Education, 31(13), 1743–1775.

    Article  Google Scholar 

  19. Urhahne, D., Nick, S., & Schanze, S. (2009). The effect of three-dimensional simulations on the understanding of chemical structures and their properties. Research in Science Education, 39(4), 495–513.

    Article  Google Scholar 

  20. Lewis, M. S., Zhao, J., & Montclare, J. K. (2012). Development and implementation of high school chemistry modules using touch-screen technologies. Journal of Chemical Education, 89, 1012–1018.

    Article  Google Scholar 

  21. Dori, Y., & Kaberman, Z. (2012). Assessing high school chemistry students’ modeling sub-skills in a computerized molecular modeling learning environment. Instructional Science, 40(1), 69–91.

    Article  Google Scholar 

  22. Stieff, M. (2011). Improving representational competence using molecular simulations embedded in inquiry activities. Journal of Research in Science Teaching, 48(10), 1137–1158.

    Article  Google Scholar 

  23. Akaygun, S. (2016). Is the oxygen atom static or dynamic? The effect of generating animations on students’ mental models of atomic structure. Chemistry Education Research and Practice, 17(4), 788–807.

    Article  Google Scholar 

  24. Chee, Y. S., & Tan, C. D. (2012). Becoming chemists through game-based inquiry learning: The case of legends of Alkhimia. Electronic Journal of e-Learning, 10(2), 185–198.

    Google Scholar 

  25. Tatli, Z., & Ayas, A. (2012). Virtual chemistry laboratory: Effect of constructivist learning environment. Turkish Online Journal of Distance Education, 13(1), 183–199.

    Google Scholar 

  26. Dori, Y. J., & Sasson, I. (2008). Chemical understanding and graphing skills in an honors case-based computerized chemistry laboratory environment: The value of bidirectional visual and textual representations. Journal of Research in Science Teaching, 45(2), 219–250.

    Article  Google Scholar 

  27. Ashton, H. S., Beevers, C. E., Korabinski, A. A., & Youngson, M. A. (2005). Investigating the medium effect in computer-aided assessment of school Chemistry and college Computing national examinations. British Journal of Educational Technology, 36(5), 771–787.

    Article  Google Scholar 

  28. Jagodziński, P., & Wolski, R. (2015). Assessment of application technology of natural user interfaces in the creation of a virtual chemical laboratory. Journal of Science Education and Technology, 24(1), 16–28.

    Article  Google Scholar 

  29. Liu, X. (2006). Effects of combined hands-on laboratory and computer modeling on student learning of gas laws: A Quasi-Experimental Study. Journal of Science Education and Technology, 15(1), 89–100.

    Article  Google Scholar 

  30. Abdullah, S., & Shariff, A. (2008). The effects of inquiry-based computer simulation with cooperative learning on scientific thinking and conceptual understanding of gas laws. Eurasia Journal of Mathematics, Science & Technology, 4(4), 387–398.

    Article  Google Scholar 

  31. Levy, S., & Wilensky, U. (2009). Students’ Learning with the Connected Chemistry (CC1) Curriculum: Navigating the complexities of the particulate world. Journal of Science Education and Technology, 18(3), 243–254.

    Article  Google Scholar 

  32. Plass, J. L., Milne, C., Homer, B. D., Schwartz, R. N., Hayward, E. O., Jordan, T., … Barrientos, J. (2012). Investigating the effectiveness of computer simulations for chemistry learning. Journal of Research in Science Teaching, 49(3), 394–419.

    Article  Google Scholar 

  33. Trey, L., & Khan, S. (2008). How science students can learn about unobservable phenomena using computer-based analogies. Computers & Education, 51(2), 519–529.

    Article  Google Scholar 

  34. Paiva, J. C., & Da Costa, L. A. (2010). Exploration guides as a strategy to improve the effectiveness of educational software in chemistry. Journal of Chemical Education, 87(6), 589–591.

    Article  Google Scholar 

  35. Scherer, R., & Tiemann, R. (2012). Factors of problem-solving competency in a virtual chemistry environment: The role of metacognitive knowledge about strategies. Computers & Education, 59(4), 1199–1214.

    Article  Google Scholar 

  36. Korakakis, G., Pavlatou, E. A., Palyvos, J. A., & Spyrellis, N. (2009). 3D visualization types in multimedia applications for science learning: A case study for 8th grade students in Greece. Computers & Education, 52(2), 390–401.

    Article  Google Scholar 

  37. Avramiotis, S., & Tsaparlis, G. (2013). Using computer simulations in chemistry problem solving. Chemistry Education Research and Practice, 14(3), 297–311.

    Article  Google Scholar 

  38. Özmen, H. (2008). The influence of computer-assisted instruction on students’ conceptual understanding of chemical bonding and attitude toward chemistry: A case for Turkey. Computers & Education, 51(1), 423–438.

    Article  Google Scholar 

  39. Özmen, H., Demircioğlu, H., & Demircioğlu, G. (2009). The effects of conceptual change texts accompanied with animations on overcoming 11th grade students’ alternative conceptions of chemical bonding. Computers & Education, 52(3), 681–695.

    Article  Google Scholar 

  40. Özmen, H. (2011). Effect of animation enhanced conceptual change texts on 6th grade students’ understanding of the particulate nature of matter and transformation during phase changes. Computers & Education, 57(1), 1114–1126.

    Article  Google Scholar 

  41. Lamb, R. L., & Annetta, L. (2013). The use of online modules and the effect on student outcomes in a high school chemistry class. Journal of Science Education and Technology, 22(5), 603–613.

    Article  Google Scholar 

  42. Eichler, M. L., Del Pino, J. C., & da Cruz Fagundes, L. (2004). Development of cognitive conducts during a computer simulated environmental analysis. Chemistry Education Research and Practice, 5(2), 157–174.

    Article  Google Scholar 

  43. Rodrigues, S. (2007). Factors that influence pupil engagement with science simulations: The role of distraction, vividness, logic, instruction and prior knowledge. Chemistry Education Research and Practice, 8(1), 1–12.

    Article  Google Scholar 

  44. Ambrogi, P., Caselli, M., Montalti, M., & Venturi, M. (2008). Make sense of nanochemistry and nanotechnology. Chemistry Education Research and Practice, 9(1), 5–10.

    Article  Google Scholar 

  45. Barak, M., & Hussein-Farraj, R. (2013). Integrating model-based learning and animations for enhancing students’ understanding of proteins structure and function. Research in Science Education, 43(2), 619–636.

    Article  Google Scholar 

  46. Osman, K., & Lee, T. T. (2014). Impact of interactive multimedia module with pedagogical agents on students’ understanding and motivation in the learning of electrochemistry. International Journal of Science and Mathematics Education, 12(2), 395–421.

    Article  Google Scholar 

  47. Ullah, S., Ali, N., & Rahman, S. U. (2016). The effect of procedural guidance on students’ skill enhancement in a virtual chemistry laboratory. Journal of Chemical Education, 93(12), 2018–2025.

    Article  Google Scholar 

  48. Vital, F. (2012). Creating a positive learning environment with the use of clickers in a high school chemistry classroom. Journal of Chemical Education, 89, 470–473.

    Article  Google Scholar 

  49. Kaberman, Z., & Dori, Y. (2009). Metacognition in chemical education: Question posing in the case-based computerized learning environment. Instructional Science, 37(5), 403–436.

    Article  Google Scholar 

  50. Rodrigues, S. (2009). Using chemistry simulations: Attention capture, selective amnesia and inattentional blindness. Chemistry Education Research and Practice, 12(1), 40–46.

    Article  Google Scholar 

  51. Paivio, A. (1990). Mental representations: A dual coding approach. New York: Oxford University Press.

    Book  Google Scholar 

  52. Mayer, R. E. (2002). Cognitive theory and the design of multimedia instruction: An example of the two-way street between cognition and instruction. New Directions for Teaching and Learning, 89, 55–71.

    Article  Google Scholar 

  53. Tsaparlis, G., & Sevian, H. (2013). Introduction: Concepts of matter—Complex to teach and difficult to learn. In G. Tsaparlis & H. Sevian (Eds.), Concepts of matter in science education, innovations in science education and technology (pp. 1–8). Dordrecht: Springer.

    Chapter  Google Scholar 

  54. Feynman, R. (1995). Six easy pieces. Reading: Addison-Wesley.

    Google Scholar 

  55. Bouwma-Gearhart, J., Stewart, J., & Brown, K. (2009). Student misapplication of a gas-like model to explain particle movement in heated solids: Implications for curriculum and instruction towards students’ creation and revision of accurate explanatory models. International Journal of Science Education, 31(9), 1157–1174.

    Article  Google Scholar 

  56. Kalkanis, G. (2013). From the scientific to the educational: Using monte Carlo simulations of the microkosmos for science education by inquiry. In G. Tsaparlis & H. Sevian (Eds.), Concepts of matter in science education, innovations in science education and technology (pp. 301–315). Dordrecht: Springer.

    Chapter  Google Scholar 

  57. Johnstone, A. H. (1997). Chemical education, science or alchemy? Journal of Chemical Education, 74(3), 262–268.

    Article  Google Scholar 

  58. Urhahne, D., Nick, S., Poepping, A. C., & Schulz, S. J. (2013). The effects of study tasks in a computer-based chemistry learning environment. Journal of Science Education and Technology, 22(6), 993–1003.

    Article  Google Scholar 

  59. Johnstone, A. H. (1993). The development of chemistry teaching. Journal of Chemical Education, 70(9), 701–704.

    Article  Google Scholar 

  60. Mahaffy, P. (2004). The future shape of Chemistry education. Chemistry Education Research and Practice, 5(3), 229–245.

    Article  Google Scholar 

  61. Wu, H., & Shah, P. (2004). Exploring visuospatial thinking in chemistry learning. Science Education, 88(3), 465–492.

    Article  Google Scholar 

  62. Wofford, J. (2009). K-16 Computationally rich science education: A Ten-Year review of the journal of science education and technology (1998–2008). Journal of Science Education and Technology, 18(1), 29–36.

    Google Scholar 

  63. Mishra, P., & Koehler, M.J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.

    Google Scholar 

  64. Agapova, O., Jones, L., Ushakov, A., Ratcliffe, A. & Varanka Martin, M. A. (2002). Encouraging independent chemistry learning through multimedia design experiences. Chemical Education International, 3(1). Retrieved May 2, 2014 from http://www.iupac.org/publications/cei/vol3/0301x0an8.html.

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Author information

Authors and Affiliations

  1. Directorate for Secondary Education, Ioannina, GR, Greece

    Ioanna Bellou

  2. University of Ioannina, Educational Approaches to Virtual Reality Lab, GR, Ioannina, Greece

    Nikiforos M. Papachristos & Tassos A. Mikropoulos

Authors
  1. Ioanna Bellou
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  2. Nikiforos M. Papachristos
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  3. Tassos A. Mikropoulos
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Correspondence to Tassos A. Mikropoulos .

Editor information

Editors and Affiliations

  1. Department of Digital Systems, University of Piraeus, Piraeus, Greece

    Demetrios Sampson

  2. Learning, Design and Technology, University of Mannheim, Mannheim, Baden-WĂĽrttemberg, Germany

    Dirk Ifenthaler

  3. Department of Learning Technologies, University of North Texas, Denton, Texas, USA

    J. Michael Spector

  4. Institute for Teaching & Learning Innovation (ITaLI), The University of Queensland, St. Lucia, Queensland, Australia

    Pedro IsaĂ­as

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Bellou, I., Papachristos, N.M., Mikropoulos, T.A. (2018). Digital Learning Technologies in Chemistry Education: A Review. In: Sampson, D., Ifenthaler, D., Spector, J., IsaĂ­as, P. (eds) Digital Technologies: Sustainable Innovations for Improving Teaching and Learning. Springer, Cham. https://doi.org/10.1007/978-3-319-73417-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-73417-0_4

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-73417-0

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