Daniela Fadda, Carole Salis, Matteo Tuveri, Carlo Maria Carbonaro, Giuliano Vivanet
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(https://doi.org/10.55612/s-5002-063-003)
Abstract
Keywords: STEM education, remote laboratory, physics, learning, interest, motivation, satisfaction, high school.
References
1. Gonzalez H.B., Kuenzi J.J.: Science, technology, engineering, and mathematics (STEM) education: A primer, Washington, DC: Congressional Research Service, Library of Congress, (2012)
2. National Academies of Sciences, Engineering, and Medicine: Indicators for monitoring undergraduate STEM education. Washington, DC, USA: The National Academies Press, (2018) https://doi.org/10.17226/24943.
3. OECD: PISA 2022 Results (vol. I): The State of Learning and Equity in Education, PISA, OECD Publishing, Paris, (2023) https://doi.org/10.1787/53f23881-en
4. Higgins K, Huscroft-D’Angelo J., Crawford L.: Effects of Technology in Mathematics on Achievement, Motivation, and Attitude: A Meta-Analysis. Journal of Educational Computing Research 57, 283—319 (2019) https://doi.org/10.1177/07356331177484
5. Chauhan S.: A meta-analysis of the impact of technology on learning effectiveness of elementary students, Computers & Education, 105, 14–30 (2017) https://doi.org/10.1016/j.compedu.2016.11.005
6. Broadbent J., Poon W.L.: Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review, Internet and Higher Education, (2015) DOI: 10.1016/j.iheduc.2015.04.007
7. Hill M., Sharma, M.D., Johnston H.: How online learning modules can improve the representational fluency and conceptual understanding of university physics students, European Journal of Physics, 36, 045019 (2015) DOI: 10.1088/0143-0807/36/4/045019
8. Luksic P., Horvat B., Bauer A., Pisanski T.: Practical E-Learning for the Faculty of Mathematics and Physics at the University of Ljubljana, Interdisciplinary Journal of E-Skills and Lifelong Learning, 3, 73–83 (2007) DOI: 10.28945/387
9. Demirci, N.: Web-based vs. paper-based homework to evaluate students’ performance in Introductory physics courses and students’ perceptions: Two years experience, International Journal on E-Learning, 9 (4). (2010) https://doi.org/10.12973/ejmste/75371
10. Sulaiman F.: The effectiveness of PBL online on physics students’ creativity and critical thinking: A case study at University Malaysia Sabah, International Journal of Education and Research, 1 (3) (2013) https://hdl.handle.net/10289/4963
11. Vo H.M., Zhu C., Diep N.A.: The effect of blended learning on student performance at course-level in higher education: A meta-analysis, Studies in Educational Evaluation, 53, 17–28 (2017) DOI: 10.1016/j.stueduc.2017.01.002
12. Higgins S., Xiao Z., Katsipataki M. The impact of digital technology on learning: A summary for the Education Endowment Foundation, EEF – Education Endowment Foundation, (2012)
13. Education Endowment Foundation Teaching & Learning Toolkit: Digital technology, https://educationendowmentfoundation.org.uk/educationevidence/teaching-learning-toolkit (2019).
14. Gagné R., Briggs L.J.: Principles of instructional design, New York: Holton, Rinehart & Winston, (1974)
15. Merrill M.D.: First principles of instruction, Educational Technology, Research and Development, 50, 43-59 (2002) https://doi.org/10.1007/BF02505024
16. Rosenshine B.: Principles of instruction, Educational Practices Series 21, International Academy of Education – International Bureau of Education, (2010)
17. Reigeluth C.M.: Instructional-design theories and models: A new paradigm of instructional theory (vol. 2), London: Routledge, (2013)
18. Davies P.: What is evidence‐based education? British journal of educational studies, 47, 108–121 (1999) https://doi.org/10.1111/1467-8527.00106
19. Bell M.: The fundamentals of teaching: A five-step model to put the research evidence into practice, London – New York: Routledge, (2020)
20. Howard-Jones P.A.: Introducing neuroeducational research: Neuroscience, education and the brain from contexts to practice, Oxford-New York: Routledge, (2009)
21. Calvani A., Marzano A.: Evidence based education and effective teaching: how to integrate methodological and technological knowledge into teacher training, Journal of Educational, Cultural and Psychological Studies, 22, 125–141 (2020) https://dx.doi.org/10.7358/ecps-2020-022-maca
22. Hofstein A., Mamlok-Naaman R.: The laboratory in science education: The state of the art, Chemistry education research and practice, 8, 105–107 (2007) DOI: 10.1039/B7RP90003A
23. NRC – National Research Council: America’s lab report: Investigations in high school science, Washington, DC, USA: The National Academy Press, (2006) https://doi.org/10.17226/11311.
24. Dewey J.: The School and Society, Chicago, The University of Chicago Press, (1949)
25. America’s Lab Report: Investigations in High School Science, National Academies Press, (2006) https://doi.org/10.17226/11311.
26. Hernández-de-Menéndez M., Guevara A.V., Morales-Menendez R.: Virtual reality laboratories: A review of experiences, International Journal on Interactive Design and Manufacturing, 13, 947–966 (2019) DOI:10.1007/s12008-019-00558-7
27. Feldman A., Herman B.C.: Teacher contextual knowledge, Teaching and Learning Faculty Publications, 428, (2015) DOI: 10.1007/978-94-007-6165-0_208-4
28. Heradio R., de la Torre L., Galan D., Cabrerizo F.J., Herrera-Viedma E., Dormido S.: Virtual and remote labs in education: A bibliometric analysis, Computers & Education, 98, 14–38 (2016) DOI: 10.1016/j.arcontrol.2016.08.001
29. Zapata L., Larrondo M.: Models of collaborative remote laboratories and integration with learning environments, International Journal of Impact Engineering, 12, 14–21 (2016) https://doi.org/10.3991/ijoe.v12i09.6129
30. Fadda D., Salis C., Vivanet, G.: About the efficacy of virtual and remote laboratories in STEM education in secondary schools: A second-order systematic review, Journal of Educational, Cultural and Psychological Studies, 26, 49–70 (2022) https://dx.doi.org/10.7358/ecps-2022-026-fadd
31. Grout, I.: Remote laboratories as a means to widen participation in STEM education, Education Sciences, 7, 85 (2017) https://doi.org/10.3390/educsci7040085
32. Sypsas A., Kalles D.: Virtual laboratories in biology, biotechnology and chemistry education: A literature review. In: Proceeding of the 22nd Pan-Hellenic Conference on Informatics, Athens, Greece (2018) DOI: 10.1145/3291533.3291560
33. Poo M.C.P., Lau Y., Chen, Q.: Are virtual laboratories and remote laboratories enhancing the quality of sustainability education? Education Sciences, 13(11), 1110 (2023) https://doi.org/10.3390/educsci13111110
34. Hofstein, A., Lunetta, V.N.: The laboratory in science education: Foundations for the twenty-first century, Science Education, 88, 28–54 (2003) DOI: 10.1002/sce.10106
35. Tho S.W., Yeung Y.Y., Wei R., Chan K.W., So W.W.: A systematic review of remote laboratory work in science education with the support of visualizing its structure through the HistCite and CiteSpace software, International Journal of Science and Mathematics Education, 15, 1217–1236 (2017) DOI: 10.1007/s10763-016-9740-z
36. Rubim J.P., Mota V.P., Garcia L.G., Brito G.L.R., Santos G.F.: The use of remote experimentation as a teaching tool: A literature review, International Journal of Information and Education Technology, 11, 826–830 (2019) DOI: 10.18178/ijiet.2019.9.11.1312
37. Udin W.N., Ramli M., Muzzazinah: Virtual laboratory for enhancing students’ understanding on abstract biology concepts and laboratory skills: A systematic review, Journal of Physics: Conference Series, 1521, 1–5 (2020) DOI 10.1088/1742-6596/1521/4/042025
38. García-Zubia J.: Remote laboratories: Empowering STEM education with technology, World Scientific Publishing, (2021)
39. Feldman A., Herman B.C.: Teacher contextual knowledge, Teaching and Learning Faculty Publications, 428 (2015) https://doi.org/10.1007/978-94-007-2150-0_208
40. Roy P., Hasni A.: Les modèles et la modélisation vus par des enseignants de sciences et technologies du secondaire au Québec, McGill Journal of Education, 49, 349–371 (2015) https://mje.mcgill.ca/article/view/9081
41. Jameau A.: Les connaissances professionnelles des enseignants et leur évolution à travers une analyse de l’activité. Une étude de cas en physique au collège , Éducation et didactique, (2015) https://doi.org/10.4000/educationdidactique.2140
42. Martinand J.L.: Missions de l’éducation scientifique et technique, Revue internationale de l’éducation de Sèvres, 25, 9–12 (2000) https://doi.org/10.4000/ries.2550
43. Justi R.S., Gilbert J.K.: Science teachers’ knowledge about and attitudes towards the use of models and modelling in learning science, International Journal of Science Education, 24, 1273–1292 (2002) DOI: 10.1080/09500690210163198
44. Potvin P.: Proposition for improving the classical models of conceptual change based on neuroeducation evidence: conceptual prevalence, Neuroeducation, 2, 16–43 (2013) https://doi.org/10.24046/neuroed.20130201.16
45. Gagné R., Briggs L., Wager W.: Principles of Instructional Design (4th Ed.), Fort Worth, TX: HBJ College Publishers (1992)
46. Tuveri M., Zurru A., Fanti V., Fadda D., Vivanet G., Carbonaro C.M.: Online learning of physics during a pandemic: A report from an academic experience in Italy, Il Nuovo Cimento, 45, 232 (2022) DOI: 10.1393/ncc/i2022-22232-3
47. The European Committee of the Regions (2019/C 404/06), https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52018IR6435&from=IT
48. Wigfield A., Eccles J.S.: Expectancy-value theory of achievement motivation, Contemporary Educational Psychology, 25, 68–81 (2000) DOI:10.1006/ceps.1999.1015
49. OECD: PISA 2015 Results (vol. I): Excellence and equity in education, PISA, OECD Publishing, Paris, (2016) https://doi.org/10.1787/9789264266490-en
50. Ma J., Nickerson J.V.: Hands-on, simulated and remote laboratories: A comparative literature review, ACM Computing Surveys, 38, 1–24 (2006) https://doi.org/10.1145/1132960.1132961