Διδακτική Φυσικών Επιστημών και Ψηφιακές Τεχνολογίες: Όψεις και Μετασχηματισμοί


Δημήτρης Ψύλλος
Abstract

Στην παρούσα εργασία, υποστηρίζουμε ότι η παιδαγωγική αξιοποίηση και ένταξη των ψηφιακών τεχνολογιών μπορεί να συντελέσει, σε κατάλληλες συνθήκες, στη βελτίωση ακόμα και στον δραστικό μετασχηματισμό της εκπαίδευσης στις Φυσικές Επιστήμες. Για τον σκοπό αυτό, εξετάζουμε τις παροχές και την αξιοποίηση των ψηφιακών τεχνολογιών, σε συνάρτηση με τις σύγχρονες έρευνες, τις διδακτικές προσεγγίσεις και τις θεωρίες στην περιοχή της Διδακτικής των Φυσικών Επιστημών. Αναλύεται και συζητείται η δημιουργική χρήση τους στη διδασκαλία και μάθηση των επιστημονικών εννοιών, των μεθόδων και της φύσης της επιστήμης. Η ένταξη των ψηφιακών τεχνολογιών έχει τη δυνατότητα υποστήριξης διδακτικών μετασχηματισμών του γνωστικού αντικειμένου, εργαστηριακής εργασίας και στρατηγικών μοντελοποίησης. Οι Διδακτικές Μαθησιακές Ακολουθίες είναι ένα κατάλληλο πλαίσιο έρευνας και ανάπτυξης, για την αξιοποίηση των ψηφιακών τεχνολογιών συνδυασμό με τη Διδακτική των Φυσικών Επιστημών.

Article Details
  • Section
  • Research Article
Downloads
Download data is not yet available.
Author Biography
Δημήτρης Ψύλλος, Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης

αφ. Καθηγητής

 

References
ΙΕΠ (2014). Πρόγραμμα Σπουδών Φυσικών Επιστημών Δημοτικού για το «Νέο Σχολείο»
Κουκιόγλου, Σ., Ψύλλος, Δ. (2019 ). Ενισχύοντας τις επιστημολογικές αντιλήψεις μαθητών γυμνασίου για τα επιστημονικά μοντέλα. 11ο Πανελλήνιο Συνέδριο- ΕΝΕΦΕΤ- Φλώρινα
Ταραμόπουλος, Α. & Ψύλλος, Δ. (2013). Σύγκριση πραγματικού και εικονικού εργαστηρίου ως προς την ικανότητα κατασκευής πραγματικών ηλεκτρικών κυκλωμάτων για μαθητές Γυμνασίου 8o Πανελλήνιο Συνέδριο Διδακτικής των Φυσικών Επιστημών και Νέων Τεχνολογιών στην Εκπαίδευση (ΕΝΕΦΕΤ), Πρακτικά σελ. 280-287, Βόλος.
Ταραμόπουλος, Α. & Ψύλλος, Δ. (2016). Αποτελεσματικότητα των εικονικών εργαστηριακών περιβαλλόντων στη διδασκαλία των ηλεκτρικών κυκλωμάτων στην Ελληνική Δευτεροβάθμια Εκπαίδευση. Πρακτικά 10ου Πανελλήνιου και Διεθνούς Συνεδρίου "Οι ΤΠΕ στην Εκπαίδευση", Επιμέλεια: Α. Μικρόπουλος, Ν. Παπαχρήστος, Α. Τσιάρα, Π. Χαλκή, 23-25 Σεπτεμβρίου 2016, Ιωάννινα, σελ. 447-453.
Χατζηκρανιώτης Ε., Μολοχίδης Α. (2017). Εισάγοντας μαθητές Γυμνασίου σε πειραματικές διερευνητικές δραστηριότητες. Στο Σταύρου Δ., Μιχαηλίδη Α. & Κοκολάκη Α. (2017). Πρακτικά 10ου Πανελληνίου Συνεδρίου Διδακτικής των Φυσικών Επιστημών και Νέων Τεχνολογιών στην Εκπαίδευση – Γεφυρώνοντας το Χάσμα μεταξύ Φυσικών Επιστημών, Κοινωνίας και Εκπαιδευτικής Πράξης, 7-9 Απριλίου 2017 (σσ. 689-697). Ρέθυμνο: Εκδόσεις GUTENBERG. ISBN: 978-960-86978-3-6
Ψύλλος, Δ., Μολοχίδης Α. (2017). Μελέτη επαναληπτικά εξελισσόμενης διδακτικής ακολουθίας για τη θερμική αγωγιμότητα των υλικών. Στο Σταύρου Δ., Μιχαηλίδη Α. & Κοκολάκη Α. (2017). Πρακτικά 10ου Πανελληνίου Συνεδρίου Διδακτικής των Φυσικών Επιστημών και Νέων Τεχνολογιών στην Εκπαίδευση – Γεφυρώνοντας το Χάσμα μεταξύ Φυσικών Επιστημών, Κοινωνίας και Εκπαιδευτικής Πράξης, 7-9 Απριλίου 2017 (σσ. 1213-1216). Ρέθυμνο: Εκδόσεις GUTENBERG. ISBN: 978-960-86978-3-6.
Ainsworth, S., Bibby, P. & Wood, D. (2002). Examining the Effects of Different Multiple Representational Systems in Learning Primary Mathematics, Journal of the Learning Sciences, 11(1): 25-61, doi: 10.1207/S15327809JLS1101_2.
Anastasiades, P. & Zaranis, N. (2016) (Eds). Research on e-Learning and ICT in Education Technological, Pedagogical and Instructional Perspectives. Springer.
Andersson, B. & Bach, F. (2005). On designing and evaluating teaching sequences taking geometrical optics as an example. Sci. Ed., 89: 196-218. doi:10.1002/sce.20044.
Bryce, C. M., Baliga, V. B., Nesnera, K. L. D., Fiack, D., Goetz, K., Tarjan, L. M. & Ash, D. (2016). Exploring models in the biology classroom. The American Biology Teacher, 78(1), 35-42.
Bumbacher, E., Salehi, S., Wieman, C. & Blikstein, P. (2017). Tools for Science Inquiry Learning: Tool Affordances, Experimentation Strategies, and Conceptual Understanding. Journal of Science Education and Technology.
Campbell, T., Seok, Oh P., Maughn, M., Kiriazis, N. & Zuwallack, R. (2015). A Review of Modeling Pedagogies: Pedagogical Functions, Discursive Acts, and Technology in Modeling Instruction Eurasia Journal of Mathematics, Science & Technology Education 11(1), 159-176.
Capobianco, B.M. (2007). A Self-Study of the Role of Technology in Promoting Reflection and Inquiry-Based Science Teaching. J Sci Teacher Educ 18, 271–295. https://doi.org/10.1007/s10972-007-9041-z
Cheng, M. F., Lin, J. L., Chang, Y. C., Li, H. W., Wu, T. Y. & Lin, D. M. (2014). Developing explanatory models of magnetic phenomena through model-based inquiry. Journal of Baltic Science Education, 13(3), 351-360.
Crawford, B. (2014). From inquiry to scientific practices in the science classroom. In N. G. Lederman & S. K. Abell (Eds.), Handbook of research on science education, Vol. II (pp. 515–541). New York, NY: Routledge.
Design-Based Research Collective. (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32, 5-8. doi:10.3102/0013189X 032001005.
Duit, R. & Treagust, D. (1998). Learning in science: From behaviourism towards social constructivism and beyond. In B. Fraser & K. Tobin, Eds. International Handbook of Science Education (pp. 3-25). Dordrecht, The Netherlands: Kluwer.
Duit, R., Gropengieίer, H. & Kattmann, U. (2005). Towards science education research that is relevant for improving practice: The model of educational reconstruction. In H. E. Fischer (Ed.), Developing standards in research on science education (pp. 1–9). London: Taylor & Francis.
Duschl, R. & Grandy,R. (2008).Teaching Scientific Inquiry: Recommendations for Research and Implementation.,Sense Publishers,Rotterdam, Netherlands.
Finkelstein, N.D., Adams, W.K., Keller, C.J., Kohl, P.B., Perkins, K.K., Podolefsky, N.S., & Reid, S. (2005) When learning about the real world is better done virtually: A study of substituting computer simulations for laboratory equipment, Physical Review Special Topics - Physics Education Research, 1, p. 1-8.
Fuhrmann, T., Schneider, B., Blikstein, P. (2018). Should students design or interact with models? Using the Bifocal Modelling Framework to investigate model construction in high school science. International Journal of Science Education 40(8):867-893.
Jaakkola, T. & Veermans, K. (2015). Effects of abstract and concrete simulation elements on science learning. Journal of Computer Assisted Learning 31:300-313.
Johnson, A. M, Reisslein, J. & Reisslein, M. (2013). Representation sequencing in computer-based engineering education. Computers & Education 72:249-261.
Kalyuga, S. (2007). Expertise reversal effect and its implications for learner-tailored instruction. Educational Psychology Review, 19, 509-539.
Karagianni, C. & Psillos, D. (2015). Learning with an about non-linear nature of inquiry. Proceeding ESERA Conference, Helsinki, 31 August- 4 September.
Kelly, A., Baek, J., Lesh, R. & Bannan-Ritland, B. (2008). Enabling innovations in education and systematizing their impact. In: Kelly, A. E., Lesh, R. &Baek. J. (Eds.). (2008a). Handbook of design research methods in education: Innovations in science, technology, mathematics and engineering learning and teaching (pp. 3–16) New York: Routledge.
Klahr, D., Triona, L.M. & Williams, C. (2007). Hands on what? the relative effectiveness of physical versus virtual materials in an engineering design project by middle school children. Journal of Research in Science Teaching, vol. 44, no. 1, p. 183-203.
Lefkos, I., Psillos, D. & Hatzikraniotis, E. (2011) Designing experiments on thermal interactions by secondary students in a simulated laboratory environment. Research in Science & Technological Education 29(2):189-204.
Lijnse, P. (2010). Didactical structures as an outcome of research on teaching-learning sequences. In K. Kortland & K. Klaassen (Eds.), Designing theory-based teaching – Learning sequences.
Louca, L. T. & Zacharia, Z. C. (2012). Modeling-based learning in science education: Cognitive, metacognitive, social, material and epistemological contributions. Educational Review, 64(4), 471–492. https://doi.org/10.1080/00131911.2011.628748.
Méheut, M. & Psillos, D. (2004). Teaching-Learning Sequences: aims and tools for science education research. International Journal of Science Education, 26(5), 515-535. doi:10.1080/09500690310001614762.
Moore, E. B., Chamberlain, J. M., Parson, R. & Perkins, K. K. (2014). PhET interactive simulations: Transformative tools for teaching chemistry. Journal of Chemical Education, 91(8), 1191-1197.
Moreno, R., Ozogul, G. & Reisslein, M. (2011). Teaching with concrete and abstract visual representations: Effects on studentsˈ problem solving, problem representations, and learning perceptions. Journal of Educational Psychology 103(1): 32-47.
Olympiou, G., Zacharias, Z. & deJong, T. (2013). Making the invisible visible: Enhancing students’ conceptual understanding by introducing representations of abstract objects in a simulation. Instructional Science, 41(3), 575–596. https://doi.org/10.1007/s11251-012-9245-2
Osborne, J. & Dillon, J. (2008). Science education in Europe: Critical reflections (Vol. 13). London: The Nuffield Foundation.
Psillos, D. & Kariotoglou, P., (2016). Theoretical Issues Related to Designing and Developing Teaching-Learning Sequences. In Dimitris Psillos & P. Kariotoglou (Eds.), Iterative Design of Teaching-Learning Sequences (pp. 11–34). https://doi.org/10.1007/978-94-007-7808-5_2
Riesen, S., Gijlers, H., Anjewierden A., de Jong, T., (2018). Supporting learners’ experiment designEducation Tech Research Dev https://doi.org/10.1007/s11423-017-9568-4
Rocard, M. (2007). Science education now: a renewed pedagogy for the future of Europe. EU report on science education_en.pdf. Retrieved 31 January 2011.
Ruten, N, van Joolingen, W. R. & van der Veen, J. T. (2012). The learning effects of computer simulations in science education. Computers & Education 58:136-153.
Ruthven Κ, Colette Laborde, John Leach, and Andrée Tiberghien (2009). Design Tools in Didactical Research: Instrumenting the Epistemological and Cognitive Aspects of the Design of Teaching Sequences Educational Researcher, Vol. 38, No. 5, pp. 329–342 DOI: 10.3102/0013189X09338513
Sadeh, I. & Zion, M. (2009). The development of dynamic inquiry performances within an open inquiry setting: A comparison to guided inquiry setting. Journal of Research in Science Teaching 46:1137–1160.
Schwarz, C. V. & White, B. Y. (2005). Metamodeling knowledge: Developing students’ understanding of scientific modeling. Cognition & Instruction, 23(2), 165–205. doi:10.1207/s1532690xci2302_1
Seel, N. M. (2017). Model-based learning: A synthesis of theory and research. Educational Technology Research and Development, 65(4), 931-966.
Sins, P.H.M., Savelsbergh, E.R., van Joolingen, W.R. & van Hout‐Wolters, B.H.A.M (2009) The Relation between Students’ Epistemological Understanding of Computer Models and their Cognitive Processing on a Modelling Task, International Journal of Science Education, 31:9, 1205-1229, DOI: 10.1080/09500690802192181.
Smetana, L. & Bell, R. (2012). Computer Simulations to Support Science Instruction and Learning: A critical review of the literature, International Journal of Science Education, 34:9, 1337-1370, DOI: 10.1080/09500693.2011.605182.
Soulios, I. & Psillos, D. (2016). Enhancing student teachers’ epistemological beliefs about models and conceptual understanding through a model-based inquiry process. International Journal of Science Education, 38(7):1212-1233.
Stavrou, D., Michailidi, E. & Sgouros, G. (2018). Development and dissemination of a teaching learning sequence on nanoscience and nanotechnology in a context of communities of learners. Chemistry Education Research and Practice, 19(4), 1065–1080.
Strippel, C & Sommer, S. (2015). Teaching Nature of Scientific Inquiry in Chemistry: How do German chemistry teachers use labwork to teach NOSI?, International Journal of Science Education, 37(18): 2965-2986, DOI: 10.1080/09500693.2015.1119330.
Taramopoulos, A. & Psillos, D. (2019). Promoting Representational Fluency through Dynamically Linked Concrete and Abstract Representations in Electric Circuits. Journal of Science Education and Technology 28(6):638-650.
Taramopoulos, A. & Psillos, D. (2017). Complex phenomena understanding in electricity through dynamically linked concrete and abstract representations. Journal of Computer Assisted Learning 33(2): 151-163.
Tarantino, G., Fazio, C. & Guastella, I. (2005). Designing and Validating a Teaching/ Learning Sequence about Elastic Wave Propagation: The Role of Pedagogical Tools. In Pinto, R. & Couso, D. (eds.), Proceedings of the fifth international conference of ESERA (Barcelona, Spain).
Testa, Italo, Lombardi, S., Monroy, G. & Sassi, E. (2016). Integrating Science and Technology in School Practice Through the Educational Reconstruction of Contents. In D. Psillos & P. Kariotoglou (Eds.), Iterative Design of Teaching-Learning Sequences (pp. 101–125). https://doi.org/10.1007/978-94-007-7808-5_6
Vorholzer, A., Von Aufschnaiter, C. & Boone, W.J. (2020). Fostering Upper Secondary Students’ Ability to Engage in Practices of Scientific Investigation: a Comparative Analysis of an Explicit and an Implicit Instructional Approach. Res Sci Educ 50, 333-359 doi.org/10.1007/s11165-018-9691-1.
Wang, T.L. & Tseng, Y.K. (2018). The comparative effectiveness of physical, virtual, and virtual-physical manipulatives on third-grade students’ science achievement and conceptual understanding of evaporation and condensation. International Journal of Science and Mathematics Education, 16(2), 203-219. doi:10.1007/s10763-016-9774-2.
Windschitl, M., Thompson, J. & Braaten, M. (2008). Beyond the scientific method: Model-based inquiry as a new paradigm of preference for school science investigations. Science Education, 92(5), 941-967. doi:10.1002/sce.20259.
Wiser, M. & Amin, T. G. (2001). Is heat hot? Inducing conceptual change by integrating everyday and scientific perspectives on thermal phenomena. Learning and Instruction 11:331-335.
Zacharias, Z. C. & Olympiou, G. (2011). Physical versus virtual manipulatives: Rethinking physics experimentation. Learning and Instruction, 21, 317-331.
Zhang, Z.H. & Linn, M.C. (2011). Can generating representations enhance learning with dynamic visualizations?. J. Res. Sci. Teach., 48: 1177-1198. doi:10.1002/tea.20443.
Zoupidis A., Spyrtou A., Malandrakis, G. & Kariotoglou, P. (2016). A Teaching Learning Sequence for introducing inquiry aspects and density as materials' property, in floating / sinking phenomena: the process of the sequence refinement. In Iterative design of teaching-learning sequences: introducing the science of materials in European schools, Springer Dordrecht Heidelberg New York London, ISBN-13:978-94-007-7807-8, p.167-199, DOI:10.1007/978-94-007-7808-5.