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Students’ metacognitive judgments in online search: a calibration study

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Abstract

Metacognitive judgment of one’s online search process (calibration) is an important element of searching efficiency. This study investigated Chinese university students’ calibration during online information search. Fourteen students s were asked to search answers for three assigned tasks. Immediately after the search, all participants attended individual interviews about their search behavior. Based on eye-tracking data of the actual search process, three profiles of searchers were identified: surface explorers, deep explorers, and smooth searchers. Eye-tracking and retrospective interview data were analyzed to examine the participants’ level of calibration. Results showed that the participants were not able to calibrate well on their searching process, with a mean score of 3.64 out of 10.0 (SD = 1.91), suggesting a mediocre level of calibration capacity. A moderate level of positive relationship (r = .42, p > .05) was also found between calibration scores and search performance scores, implying a general pattern wherein the high calibration group tended to perform better than the low calibration group. The findings called for integrating metacognitive judgment as a component of improving computer information literacy which, accordingly, could be used to enhance students’ ability to think critically about seeking and evaluating information.

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References

  • Abdekhoda, M., Dehnad, A., & Yousefi, M. (2016). Effectiveness of training intervention to improve medical student’s information literacy skills. Korean Journal of Medical Education, 28(4), 391–395. https://doi.org/10.3946/kjme.2016.44

    Article  Google Scholar 

  • Abuhamdieh, A. H., & Harder, J. T. (2015). Systematizing web search through a Meta-Cognitive, Systems-Based, Information Structuring Model (McSIS). Contemporary Issues in Education Research, 8(1), 33–44

    Google Scholar 

  • Alexander, P. A. (2013). Calibration: What is it and why it matters? An introduction to the special issue on calibrating calibration. Learning and Instruction, 24, 1–3. https://doi.org/10.1016/j.learninstruc.2012.10.003

    Article  Google Scholar 

  • Avargil, S., Lavi, R., & Dori, Y. J. (2018). Students’ metacognition and metacognitive strategies in science education. In Y. J. Dori, Z. R. Mevarech & D. R. Baker (Eds.), Cognition, metacognition, and culture in STEM education (pp. 33–64). Springer. https://doi.org/10.1007/978-3-319-66659-4

  • Azevedo, R., Moos, D. C., Johnson, A. M., & Chauncey, A. D. (2010). Measuring cognitive and metacognitive regulatory processes during hypermedia learning: Issues and challenges. Educational Psychologist, 45(4), 210–223. https://doi.org/10.1080/00461520.2010.515934

    Article  Google Scholar 

  • Azzopardi, L., Thomas, P., & Craswell, N. (2018, June). Measuring the utility of search engine result pages: An information foraging based measure. In Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (pp. 605–614). ACM. https://doi.org/10.1145/3209978.3210027

  • Binali, T., Tsai, C. C., & Chang, H. Y. (2021). University students’ profiles of online learning and their relation to online metacognitive regulation and internet-specific epistemic justification. Computers & Education, 175, 104315. https://doi.org/10.1016/j.compedu.2021.104315

    Article  Google Scholar 

  • Birjandi, P., Mirhassani, A., & Abbasian, G. (2006). Setting-based metacognitive strategy use. Journal of Faculty of Letters and Humanities, 49(198), 39–87

    Google Scholar 

  • Bowler, L. (2007). Methods for revealing the metacognitive knowledge of adolescent information seekers during the information search process. In Proceedings of the 36th Annual Conference of the Canadian Association for Information Science (CAIS), McGill University, Montreal, Quebec. https://doi.org/10.29173/cais206

  • Bowler, L. (2010). A taxonomy of adolescent metacognitive knowledge during the information search process. Library & Information Science Research, 32(1), 27–42. https://doi.org/10.1016/j.lisr.2009.09.005

    Article  Google Scholar 

  • Catrysse, L., Gijbels, D., Donche, V., De Maeyer, S., Lesterhuis, M., & Van den Bossche, P. (2018). How are learning strategies reflected in the eyes? Combining results from self-reports and eye-tracking. British Journal of Educational Psychology, 88(1), 118–137. https://doi.org/10.1111/bjep.12181

    Article  Google Scholar 

  • Chen, P., & Rossi, P. D. (2013). Utilising calibration accuracy information with adolescents to improve academic learning and performance. In H. Bembenutty, T. J. Cleary, & A. Kitsantas (Eds.), Applications of self-regulated learning across diverse disciplines (pp. 263–298). Information Age Publishing

  • Cho, B. Y., Afflerbach, P., & Han, H. (2018). Strategic processing in accessing, comprehending, and using multiple sources online. In J. L. G. Braasch, I. Bråten, & M. T. McCrudden (Eds.), Handbook of multiple source use (pp. 133–150). Routledge

  • Civilcharran, S., Hughes, M., & Maharaj, M. S. (2015). Uncovering Web search tactics in South African higher education. South African Journal of Information Management, 17(1), 1–8. https://doi.org/10.4102/sajim.v17i1.644

    Article  Google Scholar 

  • Connor, C. M., Day, S. L., Zargar, E., Wood, T. S., Taylor, K. S., Jones, M. R., & Hwang, J. K. (2019). Building word knowledge, learning strategies, and metacognition with the Word-Knowledge e-Book. Computers & Education, 128, 284–311. https://doi.org/10.1016/j.compedu.2018.09.016

    Article  Google Scholar 

  • Crescenzi, A. (2016). Metacognitive knowledge and metacognitive regulation in time-constrained in information search. In Proceedings of ACM SIGIR Conference (pp. 1–5), Pisa, Italy

  • Dahlen, S. P., Haeger, H., Hanson, K., & Montellano, M. (2020). Almost in the wild: Student search behaviors when librarians aren’t looking. The Journal of Academic Librarianship, 46, 102096. https://doi.org/10.1016/j.acalib.2019.102096

    Article  Google Scholar 

  • Davis, D., Chen, G., Jivet, I., Hauff, C., & Houben, G. J. (2016). Encouraging metacognition & self-regulation in MOOCs through increased learner feedback. In Proceedings of LAL@ LAK (pp. 17–22). Edinburgh, Scotland

  • Dever, D. A., & Azevedo, R. (2019, June). Examining gaze behaviors and metacognitive judgments of informational text within game-based learning environments. In Proceedings of International Conference on Artificial Intelligence in Education (pp. 121–132). Springer

  • DiGiacomo, G., & Chen, P. P. (2016). Enhancing self-regulatory skills through an intervention embedded in a middle school mathematics curriculum. Psychology in the Schools, 53(6), 601–616. https://doi.org/10.1002/pits.21929

    Article  Google Scholar 

  • Dinsmore, D. L., & Parkinson, M. M. (2013). What are confidence judgments made of? Students’ explanations for their confidence ratings and what that means for calibration. Learning and Instruction, 24, 4–14. https://doi.org/10.1016/j.learninstruc.2012.06.001

    Article  Google Scholar 

  • Dunlosky, J., & Thiede, K. W. (2013). Four cornerstones of calibration research: Why understanding students’ judgments can improve their achievement. Learning and Instruction, 24, 58–61. https://doi.org/10.1016/j.learninstruc.2012.05.002

    Article  Google Scholar 

  • Durodolu, O. O., & Ngoaketsi, J. M. (2019). Multilateral relationship between information literacy, self-concept and metacognitive ability. In N. Feza (Ed.), Metacognition in Learning (pp. 107–122). IntechOpen. https://doi.org/10.5772/intechopen.78892

  • Emory, B., & Luo, T. (2022). Metacognitive training and online community college students’ learning calibration and performance. Community College Journal of Research and Practice, 46(4), 240–256. https://doi.org/10.1080/10668926.2020.1841042

    Article  Google Scholar 

  • Evans, G. J. (2018). Windmills of your mind: Metacognition and lifelong learning. In Proceedings of the Canadian Engineering Education Association (CEEA) (pp. 1–5). Vancouver, Canada. https://doi.org/10.24908/pceea.v0i0.12985

  • Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906–911. https://doi.org/10.1037/0003-066X.34.10.906

    Article  Google Scholar 

  • Follmer, D. J., Patchan, M., & Spitznogle, R. (2022). Supporting college learners’ study time calibration: Relations to course achievement and self-regulated learning skills. Journal of College Reading and Learning. https://doi.org/10.1080/10790195.2022.2033646. Ahead-of-print

    Article  Google Scholar 

  • Forzani, E. (2018). How well can students evaluate online science information? Contributions of prior knowledge, gender, socioeconomic status, and offline reading ability. Reading Research Quarterly, 53(4), 385–390. https://doi.org/10.1002/rrq.218

    Article  Google Scholar 

  • Greene, J. A., Copeland, D. Z., Deekens, V. M., & Yu, S. B. (2018). Beyond knowledge: Examining digital literacy’s role in the acquisition of understanding in science. Computers and Education, 117, 141–159. https://doi.org/10.1016/j.compedu.2017.10.003

    Article  Google Scholar 

  • Hacker, D. J. (1998). Definitions and empirical foundations. In D. J. Hacker, J. Dunlosky & A. C. Grasser (Eds.), Metacognition in educational theory and practice (pp. 1–23). Lawrence Erlbaum Associates. https://doi.org/10.4324/9781410602350

  • Hahnel, C., Goldhammer, F., Kröhne, U., & Naumann, J. (2018). The role of reading skills in the evaluation of online information gathered from search engine environments. Computers in Human Behavior, 78, 223–234. https://doi.org/10.1016/j.chb.2017.10.004

    Article  Google Scholar 

  • Händel, M., de Bruin, A. B., & Dresel, M. (2020). Individual differences in local and global metacognitive judgments. Metacognition and Learning, 15(1), 51–75. https://doi.org/10.1007/s11409-020-09220-0

    Article  Google Scholar 

  • Händel, M., & Dresel, M. (2018). Confidence in performance judgment accuracy: The unskilled and unaware effect revisited. Metacognition and Learning, 13(3), 265–285. https://doi.org/10.1007/s11409-018-9185-6

    Article  Google Scholar 

  • Hautala, J., Kiili, C., Kammerer, Y., Loberg, O., Hokkanen, S., & Leppänen, P. H. (2018). Sixth graders’ evaluation strategies when reading Internet search results: An eye-tracking study. Behaviour & Information Technology, 37(8), 761–773. https://doi.org/10.1080/0144929X.2018.1477992

    Article  Google Scholar 

  • Huang, K., Law, V., & Lee, S. J. (2019). The role of learners’ epistemic beliefs in an online community of inquiry. British Journal of Educational Technology, 50(4), 1882–1895. https://doi.org/10.1111/bjet.12684

    Article  Google Scholar 

  • Ibieta, A., Hinostroza, J. E., & Labbé, C. (2019). Improving students’ information problem-solving skills on the Web through explicit instruction and the use of customized search software. Journal of Research on Technology in Education, 51(3), 217–238. https://doi.org/10.1080/15391523.2019.1576559

    Article  Google Scholar 

  • Karatas, K., & Arpaci, I. (2021). The role of self-directed learning, metacognition, and 21st century skills predicting the readiness for online learning. Contemporary Educational Technology, 13(3), ep300. https://doi.org/10.30935/cedtech/10786

    Article  Google Scholar 

  • Koriat, A. (2007). Metacognition and consciousness. In P. Zelazo, M. Moscovitch, & E. Thompson (Eds.), The Cambridge handbook of consciousness (pp. 289–325). Cambridge University Press. https://doi.org/10.1017/CBO9780511816789

  • Kuhn, D., & Dean, D. (2004). Metacognition: A bridge between cognitive psychology and educational practice. Theory into Practice, 43(4), 268–273. https://doi.org/10.1207/s15430421tip4304_4

    Article  Google Scholar 

  • Lazonder, A. W. (2003). Principles for designing web searching instruction. Education and Information Technologies, 8(2), 179–193. https://doi.org/10.1023/A:1024510531605

    Article  Google Scholar 

  • Lingel, K., Lenhart, J., & Schneider, W. (2019). Metacognition in mathematics: Do different metacognitive monitoring measures make a difference? Zdm Mathematics Education, 51(4), 587–600. https://doi.org/10.1007/s11858-019-01062-8

    Article  Google Scholar 

  • Macias, W., Lee, M., & Cunningham, N. (2018). Inside the mind of the online health information searcher using think-aloud protocol. Health Communication, 33(12), 1482–1493. https://doi.org/10.1080/10410236.2017.1372040

    Article  Google Scholar 

  • Martinez, M. E. (2006). What is metacognition? Phi Delta Kappan, 87(9), 696–699. https://doi.org/10.1177/003172170608700916

    Article  Google Scholar 

  • Mason, L., Boldrin, A., & Ariasi, N. (2010). Searching the Web to learn about a controversial topic: Are students epistemically active? Instructional Science, 38(6), 607–633. https://doi.org/10.1007/s11251-008-9089-y

    Article  Google Scholar 

  • Matsuda, T., Ushigome, R., Sonoda, M., Eto, M., Satoh, H., Hanada, T. … Katoh, D. (2019). Web search skill evaluation from eye and mouse momentum. In Proceedings of International Conference on Intelligent Human Systems Integration (pp. 884–888). Springer, Cham. https://doi.org/10.1007/978-3-030-11051-2_135

  • Miles, M. B., Huberman, A. M., & Saldaña, J. (2018). Qualitative data analysis: A methods sourcebook. Sage

  • Molina, A. I., Navarro, Ó., Ortega, M., & Lacruz, M. (2018). Evaluating multimedia learning materials in primary education using eye tracking. Computer Standards & Interfaces, 59, 45–60. https://doi.org/10.1016/j.csi.2018.02.004

    Article  Google Scholar 

  • Mudrick, N. V., Azevedo, R., & Taub, M. (2019). Integrating metacognitive judgments and eye movements using sequential pattern mining to understand processes underlying multimedia learning. Computers in Human Behavior, 96, 223–234. https://doi.org/10.1016/j.chb.2018.06.028

    Article  Google Scholar 

  • Pesout, O., & Nietfeld, J. L. (2021). How creative am I?: Examining judgments and predictors of creative performance. Thinking Skills and Creativity, 40, Article 100836. https://doi.org/10.1016/j.tsc.2021.100836

  • Reisoğlu, İ., Çebi, A., & Bahçekapılı, T. (2019). Online information searching behaviours: Examining the impact of task complexity, information searching experience, and cognitive style. Interactive Learning Environments. Ahead-of-print. https://doi.org/10.1080/10494820.2019.1662456

  • Reynders, G., Lantz, J., Ruder, S. M., Stanford, C. L., & Cole, R. S. (2020). Rubrics to assess critical thinking and information processing in undergraduate STEM courses. International Journal of STEM Education, 7(1), 1–15. https://doi.org/10.1186/s40594-020-00208-5

    Article  Google Scholar 

  • Riemer, M., Kubik, V., & Wolbers, T. (2019). The effect of feedback on temporal error monitoring and timing behavior. Behavioural Brain Research, 369, 111929. https://doi.org/10.1016/j.bbr.2019.111929

    Article  Google Scholar 

  • Roetzel, P. G. (2019). Information overload in the information age: A review of the literature from business administration, business psychology, and related disciplines with a bibliometric approach and framework development. Business Research, 12(2), 479–522. https://doi.org/10.1007/s40685-018-0069-z

    Article  Google Scholar 

  • Satori, M. (2022). Effects of field independence, metacognitive knowledge, and vocabulary knowledge on second language listening comprehension. International Journal of Listening, 1–14. https://doi.org/10.1080/10904018.2022.2056037

  • Sbaffi, L., & Rowley, J. (2017). Trust and credibility in web-based health information: A review and agenda for future research. Journal of Medical Internet Research, 19(6), 1–17. https://doi.org/10.2196/jmir.7579

    Article  Google Scholar 

  • Schindler, M., & Lilienthal, A. J. (2019). Students’ creative process in mathematics: Insights from eye-tracking-stimulated recall interview on students’ work on multiple solution tasks. International Journal of Science and Mathematics Education, 18, 1565–1586. https://doi.org/10.1007/s10763-019-10033-0

    Article  Google Scholar 

  • Schraw, G., Crippen, K. J., & Hartley, K. (2006). Promoting self-regulation in science education: metacognition as part of a broader perspective on learning. Research in Science Education, 36(1–2), 111–139. https://doi.org/10.1007/s11165-005-3917-8

    Article  Google Scholar 

  • Soto, C., de Blume, A. P. G., Jacovina, M., McNamara, D., Benson, N., & Riffo, B. (2019). Reading comprehension and metacognition: The importance of inferential skills. Cogent Education, 6(1), 1565067. https://doi.org/10.1080/2331186X.2019.1565067

    Article  Google Scholar 

  • Ståhl, T. (2019). Epistemic beliefs and Googling. Frontline Learning Research, 7(3), 27–63. https://doi.org/10.14786/flr.v7i3.417

    Article  Google Scholar 

  • Stolp, S., & Zabrucky, K. M. (2017). Contributions of metacognitive and self-regulated learning theories to investigations of calibration of comprehension. International Electronic Journal of Environmental Education, 2, 7–31

    Google Scholar 

  • Stoten, D. W. (2019). Metacognition, calibration, and self-regulated learning: An exploratory study of undergraduates in a business school. Learning: Research and Practice, 5(1), 24–47

    Google Scholar 

  • Tabachuk, N. P., Ledovskikh, I. A., Shulika, N. A., Karpova, I. V., Kazinets, V. A., & Polichka, A. E. (2018). Information competency and creative initiative of personality and their manifestation in activity. Journal of Social Studies Education Research, 9(1), 168–186

    Google Scholar 

  • Taub, M., & Azevedo, R. (2019). How does prior knowledge influence eye fixations and sequences of cognitive and metacognitive SRL processes during learning with an intelligent tutoring system? International Journal of Artificial Intelligence in Education, 29(1), 1–28. https://doi.org/10.1007/s40593-018-0165-4

    Article  Google Scholar 

  • Thiede, K., Wright, K. L., Hagenah, S., & Wenner, J. (2019). Drawings as diagnostic cues for metacomprehension judgment. In N. N. Feza (Ed.), Metacognition in learning (pp.65–79). IntechOpen. https://doi.org/10.5772/intechopen.78892

  • Țîru, C. M. (2021). Using students’ reflection in the university educational process–a qualitative approach. Educatia 21 Journal, 21, 49–61. https://doi.org/10.24193/ed21.2021.21.05

    Article  Google Scholar 

  • Tsai, M. J. (2009). Online information searching strategy inventory (OISSI): A quick version and a complete version. Computers & Education, 53(2), 473–483. https://doi.org/10.1016/j.compedu.2009.03.006

    Article  Google Scholar 

  • Tsai, M. J., Liang, J. C., Hou, H. T., & Tsai, C. C. (2012). University students’ online information searching strategies in different search contexts. Australasian Journal of Educational Technology, 28(5), 881–895. https://doi.org/10.14742/ajet.822

    Article  Google Scholar 

  • Tsai, Y. H., Lin, C. H., Hong, J. C., & Tai, K. H. (2018). The effects of metacognition on online learning interest and continuance to learn with MOOCs. Computers & Education, 121, 18–29. https://doi.org/10.1016/j.compedu.2018.02.011

    Article  Google Scholar 

  • Tsai, M. J., & Tsai, C. C. (2003). Information searching strategies in web-based science learning: The role of Internet self-efficacy. Innovations in Education and Teaching International, 40, 43–50. https://doi.org/10.1080/1355800032000038822

    Article  Google Scholar 

  • 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. https://doi.org/10.1016/j.compedu.2007.11.003

    Article  Google Scholar 

  • Tuluk, G., & Kepceoglu, I. (2019). Pre-service teachers’ web pedagogical content knowledge and online information searching strategies. International Journal of Evaluation and Research in Education, 8(2), 229–236. https://doi.org/10.11591/ijere.v8i2.18771

    Article  Google Scholar 

  • von Hoyer, J. F., Kimmerle, J., & Holtz, P. (2022). Acquisition of false certainty: Learners increase their confidence in the correctness of incorrect answers after online information search. Journal of Computer Assisted Learning. Ahead-of-print. https://doi.org/10.1111/jcal.12657

  • van Loon, M. H., de Bruin, A. B., van Gog, T., & van Merriënboer, J. J. (2013). Activation of inaccurate prior knowledge affects primary-school students’ metacognitive judgments and calibration. Learning and Instruction, 24, 15–25. https://doi.org/10.1016/j.learninstruc.2012.08.005

    Article  Google Scholar 

  • Veenman, M. V., Van Hout-Wolters, B. H., & Afflerbach, P. (2006). Metacognition and learning: Conceptual and methodological considerations. Metacognition and Learning, 1(1), 3–14. https://doi.org/10.1007/s11409-006-6893-0

    Article  Google Scholar 

  • Weber, H., Becker, D., & Hillmert, S. (2019). Information-seeking behaviour and academic success in higher education: Which search strategies matter for grade differences among university students and how does this relevance differ by field of study? Higher Education, 77(4), 657–678. https://doi.org/10.1007/s10734-018-0296-4

    Article  Google Scholar 

  • Weber, H., Hillmert, S., & Rott, K. J. (2018). Can digital information literacy among undergraduates be improved? Evidence from an experimental study. Teaching in Higher Education, 23(8), 909–926. https://doi.org/10.1080/13562517.2018.1449740

    Article  Google Scholar 

  • Whitebread, D., Coltman, P., Pasternak, D. P., Sangster, C., Grau, V., Bingham, S. … Demetriou, D. (2009). The development of two observational tools for assessing metacognition and self-regulated learning in young children. Metacognition and Learning, 4(1), 63–85. https://doi.org/10.1007/s11409-008-9033-1

    Article  Google Scholar 

  • Winne, P. H., & Jamieson-Noel, D. (2002). Exploring students’ calibration of self reports about study tactics and achievement. Contemporary Educational Psychology, 27(4), 551–572. https://doi.org/10.1016/S0361-476X(02)00006-1

    Article  Google Scholar 

  • Wu, J. Y., & Peng, Y. C. (2017). The modality effect on reading literacy: Perspectives from students’ online reading habits, cognitive and metacognitive strategies, and web navigation skills across regions. Interactive Learning Environments, 25(7), 859–876. https://doi.org/10.1080/10494820.2016.1224251

    Article  Google Scholar 

  • Zhai, X., Chu, X., Meng, N., Wang, M., Spector, M., Tsai, C. C., & Liu, H. (2022). The Effect of multi-mode stimuli of feedforward and eye tracking on metacognition—An Exploratory study using digital dictionaries. Educational Technology & Society, 25(1), 213–227

    Google Scholar 

  • Zhou, M., & Winne, P. H. (2012). Modeling academic achievement by self-reported versus traced goal orientation. Learning and Instruction, 22(6), 413-419.https://doi.org/10.1016/j.learninstruc.2012.03.004

  • Zhou, M. (2017). Do online search processes vary by task complexity? An eye-tracking study. International Journal of Social Science and Humanity, 7(11), 698-701. https://doi.org/10.18178/ijssh.2017.7.11.910

  • Zhou, M., & Lam, K. K. L. (2019). Metacognitive scaffolding for online information search in K-12 and higher education settings: A systematic review. Educational Technology Research and Development, 67(6), 1353-1384. https://doi.org/10.1007/s11423-019-09646-7

  • Zion, M., Adler, I., & Mevarech, Z. (2015). The effect of individual and social metacognitive support on students’ metacognitive performances in an online discussion. Journal of Educational Computing Research, 52(1), 50–87. https://doi.org/10.1177/0735633114568855

    Article  Google Scholar 

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This research was funded by the Multi-Year Research Grant in University of Macau (Ref.: MYRG2018-00084-FED).

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    Mingming Zhou

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Zhou, M. Students’ metacognitive judgments in online search: a calibration study. Educ Inf Technol 28, 2619–2638 (2023). https://doi.org/10.1007/s10639-022-11217-y

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