Fostering learners’ metacognitive skills of keyword reformulation in image seeking by location-based hierarchical navigation

Research Article

Abstract

It is critical that students learn how to retrieve useful information in hypermedia environments, a task that is often especially difficult when it comes to image retrieval, as little text feedback is given that allows them to reformulate keywords they need to use. This situation may make students feel disorientated while attempting image searching. This study thus designed an image navigation tool, location-based hierarchical navigation support (LHINS), which can dynamically construct a compact WordNet-based hierarchy augmented by location. Using this tool, learners can assimilate new information based on their existing knowledge structure, thus avoiding cognitive overload so as to scaffold their metacognitive skills. Sixty-four high school students were invited to take part in an experiment to test the efficacy of the proposed tool compared to a normal keyword-based search (NKBS) system. The experiment evaluated not only the students’ task completion time in the NKBS and LHINS groups, but also their keyword reformulation process, in order to determine the differences in their metacognitive skills. The results revealed that the LHINS group tended to complete the tasks faster and develop better metacognitive skills related to keyword reformulation as compared to the NKBS group. This finding suggests that an image search engine, enhanced by a compact hierarchical navigation tool, can help learners develop better search strategies. When examining how learners with different cognitive styles used the tool, the results showed that learner performance depends on cognitive style, as well as the image retrieval system used, and thus a more detailed investigation of the interaction between the tool and cognitive styles was conducted. Based on these results, several suggestions are derived for designing a more powerful image navigation tool.

Keywords

Cognitive styles Hypermedia learning system Image seeking Information retrieval Navigation Semantic analysis 

References

  1. Adipat, B., Zhang, D. S., & Zhou, L. N. (2011). The effects of tree-view based presentation adaptation on mobile web browsing. MIS Quarterly, 35(1), 99–121.Google Scholar
  2. Arnone, M. P., Small, R. V., Chauncey, S. A., & McKenna, H. P. (2011). Curiosity, interest and engagement in technology-pervasive learning environments: A new research agenda. Educational Technology Research and Development, 59(2), 181–198.CrossRefGoogle Scholar
  3. Ausubel, D. P., Novak, J. D., & Hanesian, H. (1978). Educational psychology: A cognitive view (2nd ed.). New York: Jolt, Rinchart and Winston.Google Scholar
  4. Bannert, M., Hildebrand, M., & Mengelkamp, C. (2009). Effects of a metacognitive support device in learning environments. Computers in Human Behavior, 25(4), 829–835.CrossRefGoogle Scholar
  5. Bryan-Kinns, N., Blandford, A., & Thimbleby, H. (2000). Interaction modelling for digital libraries. Paper Presented at the Workshop on Evaluation of Information Management System, New Britain.Google Scholar
  6. Bulu, S. T., & Pedersen, S. (2010). Scaffolding middle school students’ content knowledge and ill-structured problem solving in a problem-based hypermedia learning environment. Educational Technology Research and Development, 58(5), 507–529.CrossRefGoogle Scholar
  7. Chen, J. -Y., Bouman, C. A., & Dalton, J. (1998). Similarity pyramids for browsing and organization of large image databases. Paper Presented at the Human Vision and Electronic Imaging III, San Jose, CA.Google Scholar
  8. Chen, S. Y., Fan, J. P., & Macredie, R. D. (2006). Navigation in hypermedia learning systems: Experts vs. novices. Computers in Human Behavior, 22(2), 251–266.CrossRefGoogle Scholar
  9. Chen, S. Y., & Liu, X. (2009). Mining students’ learning patterns and performance in Web-based instruction: A cognitive style approach. Interactive Learning Environments, 19(2), 179–192.CrossRefGoogle Scholar
  10. Clarebout, G., Horz, H., Schnotz, W., & Elen, J. (2010). The relation between self-regulation and the embedding of support in learning environments. Educational Technology Research and Development, 58(5), 573–587.CrossRefGoogle Scholar
  11. Cromley, J. G., & Azevedo, R. (2009). Locating information within extended hypermedia. Educational Technology Research and Development, 57(3), 287–313.CrossRefGoogle Scholar
  12. Daniels, H. L., & Moore, D. M. (2000). Interaction of cognitive style and learner control in a hypermedia environment. International Journal of Instructional Media, 27(4), 369–383.Google Scholar
  13. Datta, R., Joshi, D., Li, J., & Wang, J. Z. (2008). Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys, 40(2), 5:1–5:60.Google Scholar
  14. DeStefano, D., & LeFevre, J. A. (2007). Cognitive load in hypertext reading: A review. Computers in Human Behavior, 23(3), 1616–1641.CrossRefGoogle Scholar
  15. Dias, P., Gomes, M. J., & Correia, P. (1999). Disorientation in hypermedia environments: Mechanisms to support navigation. Journal of Educational Computing Research, 20(2), 93–117.CrossRefGoogle Scholar
  16. Farrell, I. H., & Moore, D. M. (2001). The effect of navigation tools on learners’ achievement and attitude in a hypermedia environment. Journal of Educational Technology Systems, 29(2), 169–181.CrossRefGoogle Scholar
  17. Fehrenbach, C. R. (1994). Cognitive style of gifted and average readers. Roeper Review, 16(4), 290–292.CrossRefGoogle Scholar
  18. Garcia, L., Nussbaum, M., & Preiss, D. D. (2011). Is the use of information and communication technology related to performance in working memory tasks? Evidence from seventh-grade students. Computers & Education, 57(3), 2068–2076.CrossRefGoogle Scholar
  19. Goker, A., & Myrhaug, H. (2008). Evaluation of a mobile information system in context. Information Processing and Management, 44(1), 39–65.CrossRefGoogle Scholar
  20. Gong, Z., Muyeba, M., & Guo, J. (2010). Business information query expansion through semantic network. Enterprise Information Systems, 4(1), 1–22.CrossRefGoogle Scholar
  21. Hay, D. B., Kehoe, C., Miquel, M. E., Hatzipanagos, S., Kinchin, I. M., Keevil, S. F., et al. (2008). Measuring the quality of e-learning. British Journal of Educational Technology, 39(6), 1037–1056.CrossRefGoogle Scholar
  22. Hearst, M. (2006). Clustering versus faceted categories for information exploration. Communications of the ACM, 49(4), 59–61.CrossRefGoogle Scholar
  23. Huang, Y. M., Chiu, P. S., Liu, T. C., & Chen, T. S. (2011a). The design and implementation of a meaningful learning-based evaluation method for ubiquitous learning. Computers & Education, 57(4), 2291–2302.CrossRefGoogle Scholar
  24. Huang, Y.-M., Huang, Y.-M., Liu, C.-H., & Tsai, C.-C. (2011b). Applying social tagging to manage cognitive load in a Web 2.0 self-learning environment. Interactive Learning Environments. doi:10.1080/10494820.2011.555839.
  25. Huang, Y. M., Huang, Y. M., Huang, S. H., & Lin, Y. T. (2012a). A ubiquitous English vocabulary learning system: Evidence of active/passive attitudes vs. usefulness/ease-of-use. Computers & Education, 58(1), 273–282.CrossRefGoogle Scholar
  26. Huang, Y. M., Liang, T. H., Su, Y. N., & Chen, N. S. (2012b). Empowering personalized learning with an interactive e-book learning system for elementary school students. Educational Technology Research and Development, 60(4), 703–722.Google Scholar
  27. Huang, Y. M., Lin, Y. T., & Cheng, S. C. (2010). Effectiveness of a mobile plant learning system in a science curriculum in Taiwanese elementary education. Computers & Education, 54(1), 47–58.Google Scholar
  28. Hwang, G. J., Chen, C. Y., Tsai, P. S., & Tsai, C. C. (2011). An expert system for improving web-based problem-solving ability of students. Expert Systems with Applications, 38(7), 8664–8672.CrossRefGoogle Scholar
  29. Khan, L., McLeod, D., & Hovy, E. (2004). Retrieval effectiveness of an ontology-based model for information selection. VLDB Journal, 13(1), 71–85.CrossRefGoogle Scholar
  30. Khine, M. S. (1996). The interaction of cognitive styles with varying levels of feedback in multimedia presentation. International Journal of Instructional Media, 23(3), 229–237.Google Scholar
  31. Krishnamachari, S., & Abdel-Mottaleb, M. (1999). Image browsing using hierarchical clustering. Paper Presented at the 4th IEEE Symposium on Computers and Communications, Red Sea, Egypt.Google Scholar
  32. Lee, H. L., & Olson, H. A. (2005). Hierarchical navigation: An exploration of Yahoo! directories. Knowledge Organization, 32(1), 10–24.Google Scholar
  33. Leonard, N. H., Scholl, R. W., & Kowalski, K. B. (1999). Information processing style and decision making. Journal of Organizational Behavior, 20(3), 407–420.CrossRefGoogle Scholar
  34. Lin, C. Y., & Hu, R. P. (2003). Students’ understanding of energy flow and matter cycling in the context of the food chain, photosynthesis, and respiration. International Journal of Science Education, 25(12), 1529–1544.CrossRefGoogle Scholar
  35. Liu, C. J., & Shen, M. H. (2011). The influence of different representations on solving concentration problems at elementary school. Journal of Science Education and Technology, 20(5), 621–629.Google Scholar
  36. Liu, M.-C., Wen, D., Kinshuk, & Huang, Y.-M. (2010). Learning animal concepts with semantic hierarchy-based location-aware image browsing and ecology task generator. Paper Presented at the 6th IEEE International Conference on Wireless, Mobile and Ubiquitous Technologies in Education, WMUTE 2010, Kaohsiung, Taiwan.Google Scholar
  37. Mills, R. J., Paper, D., Lawless, K. A., & Kulikowich, J. M. (2002). Hypertext navigation: An intrinsic component of the corporate intranet. Journal of Computer Information Systems, 42(3), 44–50.Google Scholar
  38. Morgan, H. (1997). Cognitive styles and classroom learning. Westport, CT: Praeger.Google Scholar
  39. Nilsson, R. M., & Mayer, R. E. (2002). The effects of graphic organizers giving cues to the structure of a hypertext document on users’ navigation strategies and performance. International Journal of Human Computer Studies, 57(1), 1–26.CrossRefGoogle Scholar
  40. Ogbu, J. U. (1992). Understanding cultural diversity and learning. Educational Researcher, 21(8), 5–14.Google Scholar
  41. Palmquist, R. A., & Kim, K. S. (2000). Cognitive style and on-line database search experience as predictors of Web search performance. Journal of the American Society for Information Science, 51(6), 558–566.CrossRefGoogle Scholar
  42. Quintana, C., Zhang, M. L., & Krajcik, J. (2005). A framework for supporting metacognitive aspects of online inquiry through software-based scaffolding. Educational Psychologist, 40(4), 235–244.CrossRefGoogle Scholar
  43. Ramirez, M., & Castaneda, A. (1974). Cultural democracy, bicognitive development, and education. New York, NY: Academic Press.Google Scholar
  44. Rittschof, K. A. (2010). Field dependence–independence as visuospatial and executive functioning in working memory: Implications for instructional systems design and research. Educational Technology Research and Development, 58(1), 99–114.CrossRefGoogle Scholar
  45. Salampasis, M., Tait, J., & Bloor, C. (1998). Evaluation of information-seeking performance in hypermedia digital libraries. Interacting with Computers, 10(3), 269–284.CrossRefGoogle Scholar
  46. Saracho, O. (1991). Cognitive style and social behavior in young Mexican American children. International Journal of Early Childhood, 23(2), 21–38.CrossRefGoogle Scholar
  47. Scheiter, K., & Gerjets, P. (2007). Learner control in hypermedia environments. Educational Psychology Review, 19(3), 285–307.CrossRefGoogle Scholar
  48. She, H. C., Cheng, M. T., Li, T. W., Wang, C. Y., Chiu, H. T., Lee, P. Z., et al. (2012). Web-based undergraduate chemistry problem-solving: The interplay of task performance, domain knowledge and web-searching strategies. Computers & Education, 59(2), 750–761.CrossRefGoogle Scholar
  49. Stanton, N., Correia, A. P., & Dias, P. (2000). Efficacy of a map on search, orientation and access behaviour in a hypermedia system. Computers & Education, 35(4), 263–279.CrossRefGoogle Scholar
  50. Tu, Y. W., Shih, M., & Tsai, C. C. (2008). Eighth graders’ web searching strategies and outcomes: The role of task types, web experiences and epistemological beliefs. Computers & Education, 51(3), 1142–1153.CrossRefGoogle Scholar
  51. Vega-Gorgojo, G., Bote-Lorenzo, M. L., Asensio-Perez, J. I., Gomez-Sanchez, E., Dimitriadis, Y. A., & Jorrin-Abellan, I. M. (2010). Semantic search of tools for collaborative learning with the Ontoolsearch system. Computers & Education, 54(4), 835–848.CrossRefGoogle Scholar
  52. Waniek, J., & Ewald, K. (2008). Cognitive costs of navigation aids in hypermedia learning. Journal of Educational Computing Research, 39(2), 185–204.CrossRefGoogle Scholar
  53. Witkin, H. A., Moore, C. A., Goodenough, D. R., & Cox, P. W. (1977). Field-dependent and field-independent cognitive styles and their educational implications. Review of Educational Research, 47(1), 1–64.Google Scholar
  54. Witkin, H. A., Oltman, P. K., Raskin, E., & Karp, S. A. (1971). A manual for the embedded figures tests. Palo Alto, CA, USA: Consulting Psychologists Press.Google Scholar
  55. Wu, Z., & Palmer, M. (1994). Verbs semantics and lexical selection. Paper Presented at the Proceedings of the 32nd Annual Meeting on Association for Computational Linguistics, Las Cruces, New Mexico, USA.Google Scholar
  56. Yang, W. S., Cheng, H. C., & Dia, J. B. (2008). A location-aware recommender system for mobile shopping environments. Expert Systems with Applications, 34(1), 437–445.CrossRefGoogle Scholar
  57. Yang, J., Wenyin, L., Zhang, H., & Zhuang, Y. (2001). Thesaurus-aided approach for image browsing and retrieval. Paper Presented at the 2001 IEEE International Conference on Multimedia and Expo, ICME 2001, Tokyo, Japan.Google Scholar

Copyright information

© Association for Educational Communications and Technology 2012

Authors and Affiliations

  • Ming-Chi Liu
    • 1
  • Yueh-Min Huang
    • 1
  • Kinshuk
    • 2
  • Dunwei Wen
    • 2
  1. 1.Department of Engineering ScienceNational Cheng Kung UniversityTainan CityTaiwan, ROC
  2. 2.School of Computing and Information SystemsAthabasca UniversityAthabascaCanada

Personalised recommendations