Facilitating Concept Map Analysis: Generating and Evaluating Representative General Chemistry Concept Maps with a Novel Use of Image J, Gephi, JPathfinder, and R

Emily Z. Huie; Risa Uday Sathe; Anish Wadhwa; Efrain Vasquez Santos; Ozcan Gulacar

doi:10.29333/ejmste/11484

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Emily Z. Huie ¹ , Risa Uday Sathe ¹ , Anish Wadhwa ¹ , Efrain Vasquez Santos ¹ , Ozcan Gulacar ¹ ^*

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¹ Chemistry, University of California, USA^* Corresponding Author

Abstract

Concept maps are powerful tools used to reveal challenges in students’ learning. However, their use introduces complexities when a large group of students’ conceptualizations need to be examined. In this study, concept maps of 344 general chemistry students were analyzed after grouping them based on achievement in chemistry, math proficiency, and gender. The analysis was also expanded with the consideration of eccentricity values and the extended chemistry triplet. Although some similarities exist between the map of high-achieving students in chemistry and that of high-performing students in the Mathematics Placement Test (MPT), the calculated eccentricity values show interesting variations. On the other hand, the analysis of the map of the low-performing students in MPT and that of low-achieving students in chemistry revealed no clear patterns of symbolic, macroscopic, and submicroscopic terms. Practical suggestions were included to increase the use of representative maps in different assessment and teaching scenarios.

Keywords

chemistry education
assessment
constructivism
concept maps
chemistry triplet

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, Volume 18, Issue 1, January 2022, Article No: em2063

https://doi.org/10.29333/ejmste/11484

Publication date: 03 Jan 2022

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Declaration of Conflict of Interest: No conflict of interest is declared by author(s).

Data sharing statement: Data supporting the findings and conclusions are available upon request from the corresponding author(s).

References

Ambrose, S. A., Bridges, M., DiPietro, M., Lovett, M., & Norman, M. (2010). How learning works: Seven research-based principles for smart teaching. Jossey-Bass.
Andrews, M. H., & Andrews, L. (1979). First-year chemistry grades and SAT math scores. Journal of Chemical Education, 56(4), 231-232. https://doi.org/10.1021/ed056p231
Bada, S. O. (2015). Constructivism learning theory: A paradigm for teaching and learning. IOSR Journal of Research & Method in Education, 5(6), 66-70. https://doi.org/10.9790/7388-05616670
Becker, N., Stanford, C., Towns, M., & Cole, R. (2015). Translating across macroscopic, submicroscopic, and symbolic levels: the role of instructor facilitation in an inquiry-oriented physical chemistry class. Chemistry Education Research and Practice, 16(4), 769-785. https://doi.org/10.1039/c5rp00064E
Boujaoude, S., & Attieh, M. (2008). The effect of using concept maps as study tools on achievement in chemistry. EURASIA Journal of Mathematics, Science & Technology Education, 4(3), 233. https://doi.org/10.12973/ejmste/75345
Burrows, N. L., & Mooring, S. R. (2015). Using concept mapping to uncover students’ knowledge structures of chemical bonding concepts. Chemistry Education Research and Practice, 16(1), 53-66. https://doi.org/10.1039/c4rp00180j
Caine, G., & Caine, R. N. (2006). Meaningful learning and the executive functions of the brain. New Directions for Adult and Continuing Education, 2006(110), 53-61. https://doi.org/10.1002/ace.219
Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5(2), 121-152. https://doi.org/10.1207/s15516709cog0502_2
Chi, M. T. H., Glaser, R., & Farr, M. J. (1988). The nature of expertise. Lawrence Erlbaum. https://doi.org/10.1038/332441a0
Cohen, R., & Kelly, A. M. (2019). Community college chemistry coursetaking and STEM academic persistence. Journal of Chemical Education, 96(1), 3-11. https://doi.org/10.1021/acs.jchemed.8b00586
Coll, R., Ali, S., Bonato, J., & Rohindra, D. (2006). Investigating first-year chemistry learning difficulties in the South Pacific: A case study from Fiji. International Journal of Science and Mathematics Education, 4(3), 365-390. https://doi.org/10.1007/s10763-005-9007-6
Cotes, S., & Cotuá, J. (2014). Using audience response systems during interactive lectures to promote active learning and conceptual understanding of stoichiometry. Journal of Chemical Education, 91(5), 673. https://doi.org/10.1021/ed400111m
de Astudillo, L. R., & Niaz, M. (1996). Reasoning strategies used by students to solve stoichiometry problems and its relationship to alternative conceptions, prior knowledge, and cognitive variables. Journal of Science Education and Technology, 5(2), 131-140. https://doi.org/10.1007/bf01575153
diSessa, A. A. (1988). Knowledge in pieces. In G. Forman, P. B. Pufall, G. Forman, & P. B. Pufall (Eds.), Constructivism in the computer age. (pp. 49-70). Lawrence Erlbaum Associates, Inc.
Dori, Y. J., & Hameiri, M. (2003). Multidimensional analysis system for quantitative chemistry problems: Symbol, macro, micro, and process aspects. Journal of Research in Science Teaching, 40(3), 278-302. https://doi.org/10.1002/tea.10077
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. https://doi.org/10.1002/tea.20197
Earl, B. L. (2007). Concept maps for general chemistry. Journal of Chemical Education, 84(11), 1788-1789. https://doi.org/10.1021/ed084p1788
Ekmekci, A., Sahin, A., Gulacar, O., & Almus, K. (2018). High school students’ semantic networks of scientific method in an international science Olympiad context. Eurasia Journal of Mathematics, Science and Technology Education, 14(10), em1604. https://doi.org/10.29333/ejmste/93677
Ezeudu, F. O. (2015). A SWOT analysis of male and female students’ performance in chemistry: A comparative study. Journal of Education and Practice, 6(28), 53-60.
Gadner, J., & Ohnesorge, D. (2004). Conceptual knowledge organisation and the problem of understanding. In J. Gadner, R. Buber, & L. Richards (Eds.), Organising knowledge: Methods and case studies (pp. 60-74). Palgrave Macmillan UK. https://doi.org/10.1057/9780230523111_4
Gerstner, S., & Bogner, F. X. (2009). Concept map structure, gender and teaching methods: An investigation of students’ science learning. Educational Research, 51(4), 425-438. https://doi.org/10.1080/00131880903354758
Gulacar, O., Eilks, I., & Bowman, C. R. (2014). Differences in general cognitive abilities and domain-specific skills of higher- and lower-achieving students in stoichiometry. Journal of Chemical Education, 91(7), 961-968. https://doi.org/10.1021/ed400894b
Gulacar, O., Milkey, A., & Eilks, I. (2020). Exploring cluster changes in students’ knowledge structures throughout general chemistry. Eurasia Journal of Mathematics, Science and Technology Education, 16(6), em1850. https://doi.org/10.29333/ejmste/7860
Gulacar, O., Milkey, A., & McLane, S. (2019). Exploring the effect of prior knowledge and gender on undergraduate students’ knowledge structures in chemistry. Eurasia Journal of Mathematics, Science and Technology Education, 15(8), em1726. https://doi.org/10.29333/ejmste/106231
Gulacar, O., Sinan, O., Bowman, C., & Yildirim, Y. (2015). Exploring the changes in students’ understanding of the scientific method using word associations. Research in Science Education, 45(5), 717-726. https://doi.org/10.1007/s11165-014-9443-9
Heron, M., Kinchin, I. M., & Medland, E. (2018). Interview talk and the co-construction of concept maps. Educational Research, 60(4), 373-389. https://doi.org/10.1080/00131881.2018.1522963
Johnston, P. R., Watters, D. J., Brown, C. L., & Loughlin, W. A. (2016). An investigation into student perceptions towards mathematics and their performance in first year chemistry: Introduction of online maths skills support. Chemistry Education Research and Practice, 17(4), 1203-1214. https://doi.org/10.1039/C6RP00175K
Johnstone, A. H. (1991). Why is science difficult to learn? Things are seldom what they seem. Journal of Computer Assisted Learning, 7(2), 75-83. https://doi.org/10.1111/j.1365-2729.1991.tb00230.x
Kaya, O. (2008). A student-centred approach: Assessing the changes in pospective science teachers’ conceptual understanding by concept mapping in a general chemistry laboratory. Research in Science Education, 38(1), 91-110. https://doi.org/10.1007/s11165-007-9048-7
Kibar, Z. B., Yaman, F., & Ayas, A. (2013). Assessing prospective chemistry teachers’ understanding of gases through qualitative and quantitative analyses of their concept maps. Chemistry Education Research and Practice, 14(4), 542-554. https://doi.org/10.1039/C3RP00052D
Kodali, T. (2016). Hierarchical clustering in R. https://www.r-bloggers.com/hierarchical-clustering-in-r-2/
Kohn, K. P., Underwood, S. M., & Cooper, M. M. (2018). Energy connections and misconnections across chemistry and biology. CBE Life Sciences Education, 17(1), Article 3. https://doi.org/10.1187/cbe.17-08-0169
Krabbe, H. (2014). Digital concept mapping for formative assessment. In D. Ifenthaler, & R. Hanewald (Eds.), Digital knowledge maps in education: Technology-enhanced support for teachers and learners (pp. 275-297). Springer New York + Business Media. https://doi.org/10.1007/978-1-4614-3178-7_15
Kruskal, J. B., & Wish, M. (1978). Multidimensional scaling. Sage Publications. https://doi.org/10.4135/9781412985130
Luxford, C. J., & Bretz, S. L. (2014). Development of the bonding representations inventory to identify student misconceptions about covalent and ionic bonding representations. Journal of Chemical Education, 91(3), 312-320. https://doi.org/10.1021/ed400700q
Luxford, C. J., & Holme, T. A. (2015). What do conceptual holes in assessment say about the topics we teach in general chemistry? Journal of Chemical Education, 92(6), 993. https://doi.org/10.1021/ed500889j
Meijers, F. (1998). The development of a career identity. International Journal for the Advancement of Counselling, 20(3), 191-207. https://doi.org/10.1023/A:1005399417256
Murphy, K., Holme, T., Zenisky, A., Carithers, H., & Knaus, K. (2012). Building the ACS exams anchoring concept content map for undergraduate chemistry. Journal of Chemical Education, 89(6), 715-720. https://doi.org/10.1021/ed300049w
Neiles, K. Y. (2014). Measuring knowledge: Tools to measure students’ mental organization of chemistry information. ACS Symposium Series, 1166, 169-190. https://doi.org/10.1021/bk-2014-1166.ch010
Nicoll, G., Francisco, J., & Nakhleh, M. B. (2001). An investigation of the value of using concept maps in general chemistry. Journal of Chemical Education, 78(8), 1111. https://doi.org/10.1021/ED078P1111
Ørom, A. (2003). Knowledge organization in the domain of art studies – history, transition and conceptual changes. Knowledge Organization, 30(3), 128-143. https://doi.org/10.5771/0943-7444-2008-2-3-86
Paideya, V., & Sookrajh, R. (2010). Exploring the use of supplemental instruction: Supporting deep understanding and higher-order thinking in chemistry. South African Journal of Higher Education, 24(5), 758-770.
Pirnay-Dummer, P. (2014). Gainfully guided misconception. In D. Ifenthaler, & R. Hanewald (Eds.), Digital knowledge maps in education: Technology-enhanced support for teachers and learners (pp. 253-273). Springer New York. https://doi.org/10.1007/978-1-4614-3178-7_14
Pólya, G. (1945). How to solve it a new aspect of mathematical method. Princeton University Press. https://doi.org/10.1515/9781400828678
Preininger, A. (2017). Embedded mathematics in chemistry: A case study of students’ attitudes and mastery. Journal of Science Education and Technology, 26(1), 58-69. https://doi.org/10.1007/s10956-016-9651-3
Ralph, V. R., & Lewis, S. E. (2018). Chemistry topics posing incommensurate difficulty to students with low math aptitude scores. Chemistry Education Research and Practice, 19(3), 867-884. https://doi.org/10.1039/c8rp00115d
Schreiber, D. A., & Abbeg, G. L. (1991). Scoring student- generated concept maps in introductory college chemistry. Paper prepared for The National Association for Research in Science Teaching Annual Meeting, Lake Geneva, WI.
Sharara, H. (2011). How structural assessment of knowledge can be used for the identification of specific alternative conceptions and for assessing domain competence in physics [M.A. thesis, University of Ottawa].
Smith, G. A., & Bermea, S. B. (2012). Using students’ sketches to recognize alternative conceptions about plate tectonics persisting from prior instruction. Journal of Geoscience Education, 60(4), 350-359. https://doi.org/10.5408/11-251.1
Smith, J. P., diSessa, A. A., & Roschelle, J. (1994). Misconceptions reconceived: A constructivist analysis of knowledge in transition. The Journal of the Learning Sciences, 3(2), 115-163. https://doi.org/10.1207/s15327809jls0302_1
Taber, K. S. (2013). Revisiting the chemistry triplet: Drawing upon the nature of chemical knowledge and the psychology of learning to inform chemistry education. Chemistry Education Research and Practice, 14(2), 156-168. https://doi.org/10.1039/C3RP00012E
Tait, H., & Entwistle, N. (1996). Identifying students at risk through ineffective study strategies. Higher Education, 31(1), 97-116. https://doi.org/10.1007/BF00129109
Talanquer, V. (2011a). Macro, submicro, and symbolic: The many faces of the chemistry “triplet”. International Journal of Science Education, 33(2), 179-195. https://doi.org/10.1080/09500690903386435
Talbert, L. E., Bonner, J., Mortezaei, K., Guregyan, C., Henbest, G., & Eichler, J. F. (2020). Revisiting the use of concept maps in a large enrollment general chemistry course: implementation and assessment. Chemistry Education Research and Practice, 21(1), 37-50. https://doi.org/10.1039/c9rp00059C
Teichert, M. A., Schroeder, M. J., Lin, S., Dillner, D. K., Komperda, R., & Bunce, D. M. (2020). Problem-solving behaviors of different achievement groups on multiple-choice questions in general chemistry. Journal of Chemical Education, 97(1), 3-15. https://doi.org/10.1021/acs.jchemed.9b00774
Trumpower, D. L., Filiz, M., & Sarwar, G. S. (2014). Assessment for learning using digital knowledge maps. In D. Ifenthaler, & R. Hanewald (Eds.), Digital knowledge maps in education: Technology-enhanced support for teachers and learners (pp. 221-237). Springer New York. https://doi.org/10.1007/978-1-4614-3178-7_12
van Kesteren, M. T. R., Krabbendam, L., & Meeter, M. (2018). Integrating educational knowledge: reactivation of prior knowledge during educational learning enhances memory integration. NPJ Science of Learning, 3(11), 1-8. https://doi.org/10.1038/s41539-018-0027-8
Van Zele, E., Lenaerts, J., & Wieme, W. (2004). Improving the usefulness of concept maps as a research tool for science education. International Journal of Science Education, 26(9), 1043-1064. https://doi.org/10.1080/1468181032000158336
Von Der Heidt, T. (2015). Concept maps for assessing change in learning: a study of undergraduate business students in first-year marketing in China. Assessment & Evaluation in Higher Education, 40(2), 286-308. https://doi.org/10.1080/02602938.2014.910637
Vrabec, M., & Prokša, M. (2016). Identifying misconceptions related to chemical bonding concepts in the Slovak school system using the bonding representations inventory as a diagnostic tool. Journal of Chemical Education, 93(8), 1364-1370. https://doi.org/10.1021/acs.jchemed.5b00953
Williamson, V. M., Walker, D. R., Chuu, E., Broadway, S., Mamiya, B., Powell, C. B., Shelton, G. R., Weber, R., Dabney, A. R., & Mason, D. (2020). Impact of basic arithmetic skills on success in first-semester general chemistry. Chemistry Education Research and Practice, 21(1), 51-61. https://doi.org/10.1039/c9rp00077a
Wilson, J. (1996). Concept maps about chemical equilibrium and students’ achievement scores. Research in Science Education, 26(2), 169-185. https://doi.org/10.1007/BF02356430
Yaman, F., & Ayas, A. (2015). Assessing changes in high school students’ conceptual understanding through concept maps before and after the Computer-Based Predict-Observe-Explain (CB-POE) tasks on acid-base chemistry at the secondary level. Chemistry Education Research and Practice, 16(4), 843. https://doi.org/10.1039/C5RP00088B
Yeh, Y.-C. (2004). Seventh graders’ academic achievement, creativity, and ability to construct a cross-domain concept map-A brain function perspective. The Journal of Creative Behavior, 38(2), 125. https://doi.org/10.1002/j.2162-6057.2004.tb01236.x

How to cite this article

APA

Huie, E. Z., Sathe, R. U., Wadhwa, A., Santos, E. V., & Gulacar, O. (2022). Facilitating Concept Map Analysis: Generating and Evaluating Representative General Chemistry Concept Maps with a Novel Use of Image J, Gephi, JPathfinder, and R. Eurasia Journal of Mathematics, Science and Technology Education, 18(1), em2063. https://doi.org/10.29333/ejmste/11484

Vancouver

Huie EZ, Sathe RU, Wadhwa A, Santos EV, Gulacar O. Facilitating Concept Map Analysis: Generating and Evaluating Representative General Chemistry Concept Maps with a Novel Use of Image J, Gephi, JPathfinder, and R. EURASIA J Math Sci Tech Ed. 2022;18(1):em2063. https://doi.org/10.29333/ejmste/11484

AMA

Huie EZ, Sathe RU, Wadhwa A, Santos EV, Gulacar O. Facilitating Concept Map Analysis: Generating and Evaluating Representative General Chemistry Concept Maps with a Novel Use of Image J, Gephi, JPathfinder, and R. EURASIA J Math Sci Tech Ed. 2022;18(1), em2063. https://doi.org/10.29333/ejmste/11484

Chicago

Huie, Emily Z., Risa Uday Sathe, Anish Wadhwa, Efrain Vasquez Santos, and Ozcan Gulacar. "Facilitating Concept Map Analysis: Generating and Evaluating Representative General Chemistry Concept Maps with a Novel Use of Image J, Gephi, JPathfinder, and R". Eurasia Journal of Mathematics, Science and Technology Education 2022 18 no. 1 (2022): em2063. https://doi.org/10.29333/ejmste/11484

Harvard

Huie, E. Z., Sathe, R. U., Wadhwa, A., Santos, E. V., and Gulacar, O. (2022). Facilitating Concept Map Analysis: Generating and Evaluating Representative General Chemistry Concept Maps with a Novel Use of Image J, Gephi, JPathfinder, and R. Eurasia Journal of Mathematics, Science and Technology Education, 18(1), em2063. https://doi.org/10.29333/ejmste/11484

MLA

Huie, Emily Z. et al. "Facilitating Concept Map Analysis: Generating and Evaluating Representative General Chemistry Concept Maps with a Novel Use of Image J, Gephi, JPathfinder, and R". Eurasia Journal of Mathematics, Science and Technology Education, vol. 18, no. 1, 2022, em2063. https://doi.org/10.29333/ejmste/11484