Abstract
When expensive, complex, or challenging experimental set-ups are unavailable or impracticable, virtual and remote labs can serve as an alternative that promotes practical experimental skill development and discovery-based learning. Virtual and remote labs enable students to take responsibility for demonstration experiments in an active and yet harmless way. The analysis of spectra is fundamental to our modern understanding of wave optics and colour perception. For this reason, every student should have the opportunity to conduct their own optical emission experiments. Since spectrometers are expensive and accurate calibration is necessary to achieve high quality spectra of energy distribution, we developed a remotely controlled laboratory on optical spectrometry (http://myrcl.net links to multilingual version). Additionally, a virtual lab version is available for off-line use (http://virtualremotelab.net). With this tools, many different objectives can be realized by students. Banchi and Bell (2008) describe four levels of inquiry in activities with decreasing predefined structure: confirmation inquiry, structured inquiry, guided inquiry and open inquiry. Based on this classification, we developed different learning scenarios that allow students to introduce themselves to atomic physics, to compare and to rate customary light sources and finally to choose light sources for distinct lighting situations. Since these topics are new to the students, they need additional information (e.g., on the experimental set-up). This leads to the question of which domain specific knowledge should be offered to the students at what time? Moreover, how should the information be presented? Students clearly need additional information on the set-up of the proposed experiment and control. The literature review has suggested presenting the information during the learning phase. When this is not possible, the learners should be forced to read the additional information in advance. Perceived reading attentiveness differed for information types (structural-attributive, functional-cybernetic, pragmatic). Effects on performance and knowledge acquisition is subject to future studies.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alexander, P. A., Judy, J. E.: The Interaction of Domain-Specific and Strategic Knowledge in Academic Performance. Review of Educational Research 58(4), 375–404 (1988). https://doi.org/10.3102/00346543058004375
Ayres, P.: Using subjective measures to detect variations of intrinsic cognitive load within problems. Learning and Instruction 16(5), 389–400 (2006). https://doi.org/10.1016/j.learninstruc.2006.09.001
Bamberger, R., Rabin, A. T.: New Approaches to Readability: Austrian Research. The Reading Teacher 37(6), 512–519 (1984)
Banchi, H., Bell, R. L.: The Many Levels of Inquiry. Science and Children 46, 26–29 (2008)
Bandura, A.: Self-efficacy: The exercise of control. Freeman, New York, NY (1997).
Baumert, J., Köller, O.: Unterrichtsgestaltung, verständnisvolles Lernen und multiple Zielerreichung im Mathematik- und Physikunterricht der gymnasialen Oberstufe. In J. Baumert, W. Bos, R. Lehmann (eds.), TIMSS/III: Bd. 2. Mathematische und physikalische Kompetenzen am Ende der gymnasialen Oberstufe. Leske + Budrich, Opladen (2000).
Bereiter, C., Scardamalia, M.: Intentional Learning as a Goal of Instruction. In L. B. Resnick (ed.), Knowing, learning, and instruction. Essays in honor of Robert Glase, pp. 361–392. Hillsdale, NJ: Erlbaum (1989)
Bransford, J. D., Brown, A. L., Anderson, J. R., Gelman, R., Glaser, R., Greenough, W. T., Phillips, M. J.: How People Learn: Brain, Mind, Experience, and School: Expanded Edition. National Academy Press, Washington, D.C. (2000)
Bratfisch, O., Borg, G., Dornič, S.: Perceived Item-Difficulty in Three Tests of Intellectual Performance Capacity. In Reports from the Institute of Applied Psychology (No. 29). Stockholm (1972)
Brown, A. L., DeLoache, J. S.: Skills, plans, and self-regulation. In R. S. Siegler (ed.), Children’s Thinking: What Develops?, pp. 3–36. Erlbau, Hillsdale, NJ (1978)
Brünken, R., Plass, J. L., Leutner, D.: Direct Measurement of Cognitive Load in Multimedia Learning. Educational Psychologist 38(1), 53–61 (2003). https://doi.org/10.1207/S15326985EP3801_7
Butler, D. L., Winne, P. H.: Feedback and Self-Regulated Learning: A Theoretical Synthesis. Review of Educational Research 65(3), 245–281 (1995). https://doi.org/10.3102/00346543065003245
Crouch, C. H., Mazur, E.: Peer Instruction: Ten Years of Experience and Results. American Journal of Physics 69, 970–977 (2001). https://doi.org/10.1119/1.1374249
de Jong, T., van Joolingen, W. R.: Scientific Discovery Learning With Computer Simulations of Conceptual Domains. Review of Educational Research, 68(2) 179–201 (1998). https://doi.org/10.3102/00346543068002179
Deci, E. L., Ryan, R. M.: Die Selbstbestimmungstheorie der Motivation. Zeitschrift für Pädagogik, 39(2), 223–238 (1993)
Duit, R., Tesch, M.: On the role of the experiment in science teaching and learning – Visions and the reality of instructional practice. In M. Kalogiannakis, D. Stavrou, P. G. Michaelides (eds.) HSci 2010. 7th International Conference Hands-on Science “Bridging the Science and Society gap”, July 25-31, 2010, Greece. Rethymno: The University of Crete (2010)
Flesch, R.: A new readability yardstick. Journal of Applied Psychology 32(3), 221–233 (1948). https://doi.org/10.1037/h0057532
Flückiger, F. Beiträge zur Entwicklung eines vereinheitlichten Informations-Begriffs (Dissertation). Universität Bern, Bern (1995).
Flückiger, F.: Towards a unified concept of information: Presentation of a new approach. World Futures: Journal of General Evolution 49(3-4), 309–320 (1997). https://doi.org/10.1080/02604027.1997.9972637
Gopher, D., Braune, R.: On the Psychophysics of Workload: Why Bother with Subjective Measures? Human Factors: The Journal of the Human Factors and Ergonomics Society 26(5), 519–532 (1984). https://doi.org/10.1177/001872088402600504
Harlen, W.: Effective teaching of science: A review of research. SCRE publication Using research series: vol. 21. Scottish Council for Research in Education, Glasgow (1999)
Hmelo, C. E., Nagarajan, A., Day, R. S.: Effects of High and Low Prior Knowledge on Construction of a Joint Problem Space. The Journal of Experimental Education 69(1), 36–56 (2000). https://doi.org/10.1080/00220970009600648
Hofstein, A., Lunetta, V. N.: The Role of the Laboratory in Science Teaching: Neglected Aspects of Research. Review of Educational Research 52(2), 201–217 (1982). https://doi.org/10.3102/00346543052002201
Hofstein, A., Lunetta, V. N.: The laboratory in science education: Foundations for the twenty-first century. Science Education 88(1), 28–54 (2004). https://doi.org/10.1002/sce.10106
Hulshof, C. D., de Jong, T.: Using just-in-time information to support scientific discovery learning in a computer-based simulation. Interactive Learning Environments 14(1), 79–94 (2006). https://doi.org/10.1080/10494820600769171
King, A.: From sage on the stage to guide on the side. College Teaching 41(1), 30 (1993). https://doi.org/10.1080/87567555.1993.9926781
Krapp, A.: Interest, motivation and learning: An educational-psychological perspective. European Journal of Psychology of Education 14(1), 23–40 (1999). https://doi.org/10.1007/BF03173109
Krapp, A.: Basic needs and the development of interest and intrinsic motivational orientations. Feelings and Emotions in the Learning Process Feelings and Emotions in the Learning Process 15(5), 381–395 (2005). https://doi.org/10.1016/j.learninstruc.2005.07.007
Langer, I., Schulz von Thun, F., Tausch, R.: Sich verständlich ausdrücken (9., neu gest. Aufl). Reinhardt, München (2011)
Lavoie, D. R., Good, R.: The nature and use of prediction skills in a biological computer simulation. Journal of Research in Science Teaching 25(5), 335–360 (1988). https://doi.org/10.1002/tea.3660250503
Lazonder, A. W., Wilhelm, P., van Lieburg, E.: Unraveling the influence of domain knowledge during simulation-based inquiry learning. Instructional Science 37(5), 437–451 (2009). https://doi.org/10.1007/s11251-008-9055-8
Leutner, D.: Guided discovery learning with computer-based simulation games: Effects of adaptive and non-adaptive instructional support. Learning and Instruction 3(2), 113–132 (1993). https://doi.org/10.1016/0959-4752(93)90011-N
Marcus, N., Cooper, M., Sweller, J.: Understanding Instructions. Journal of Educational Psychology 88(1), 49–63 (1996)
Mazur, E.: Peer instruction: A user’s manual. Prentice Hall series in educational innovation. Pearson/Prentice Hall, Upper Saddle River, NJ. (1997)
Morris, C. W.: Foundations of the theory of signs. International Encyclopedia of Unified Science. University of Chicago Press, Chicago (1938).
Paas, F. G.: Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of Educational Psychology 84(4), 429–434 (1992).
Paas, F. G. W. C., van Merriënboer, J. J. G.: The Efficiency of Instructional Conditions: An Approach to Combine Mental Effort and Performance Measures. Human Factors 35(4), 737–743 (1993). https://doi.org/10.1177/001872089303500412
Paas, F. G. W. C., Merriënboer, J. J. G., van Adam, J. J.: Measurement of Cognitive Load in Instructional Research. Perceptual and Motor Skills 79(1), 419–430 (1994). https://doi.org/10.2466/pms.1994.79.1.419
Schauble, L., Glaser, R., Raghavan, K., Reiner, M.: Causal models and experimentation strategies in scientific reasoning. The Journal of the Learning Sciences 1(2), 201–238 (1991). https://doi.org/10.1207/s15327809jls0102_3
Schraw, G.: Promoting general metacognitive awareness. Instructional Science 26(1-2), 113–125 (1998). https://doi.org/10.1023/A:1003044231033
Seidel, T., Prenzel, M., Duit, R., Euler, M., Geiser, H., Hoffmann, L., Rimmele, R.: “Jetzt bitte alle nach vorn schauen!” - Lehr-Lernskripts im Physikunterricht und damit verbundenen Bedingungen für individuelle Lernprozesse. Unterrichtswissenschaft, 30(1), 52–77 (2002)
Tesch, M., Duit, R.: Experimentieren im Physikunterricht – Ergebnisse einer Videostudie. Zeitschrift für Didaktik der Naturwissenschaften, 10, 51–69 (2004)
Thoms, L.-J., Girwidz, R. Training and assessment of experimental competencies from a distance: Optical spectrometry via the Internet. Il Nuovo Cimento C 38(3), 1–10. (2015)
van Gog, T., Paas, F.: Instructional Efficiency: Revisiting the Original Construct in Educational Research. Educational Psychologist 43(1), 16–26 (2008). https://doi.org/10.1080/00461520701756248
von Weizsäcker, C. F.: Die Einheit der Natur: Studien von Carl Friedrich von Weizsäcker. Hanser, München (1971)
von Weizsäcker, E. U. (ed.): SpringerBriefs on pioneers in science and practice: Vol. 28. Ernst Ulrich von Weizsäcker: A pioneer on environmental, climate and energy policies. Springer, Cham (2014)
von Weizsäcker, E., von Weizsäcker, C.: Wiederaufnahme der begrifflichen Frage: Was ist Information. Nova Acta Leopoldina, 37(206), 535–555 (1972)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Thoms, LJ., Girwidz, R. (2018). The Role of Information in Inquiry-Based Learning in a Remote Lab on Optical Spectrometry. In: Sokołowska, D., Michelini, M. (eds) The Role of Laboratory Work in Improving Physics Teaching and Learning. Springer, Cham. https://doi.org/10.1007/978-3-319-96184-2_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-96184-2_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-96183-5
Online ISBN: 978-3-319-96184-2
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)