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Listening instead of reading: using network drawing task as a re-constructed method and measure of knowledge in mind

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Abstract

The trend of podcast and audiobook listening is on the rise, thus paving the way for a new, popular learning environment. It is crucial to deliberate on the influence of multiple-text listening comprehension. This research aimed to explore the impact of conceptual network processing on multiple-text comprehension performance from the perspective of long-term working memory (LT-WM). Additionally, it examined the sensitivity of a concept network analysis measure in facilitating the construction of conceptual structures during text listening. To this end, 128 participants were randomly assigned to four different treatment groups. These groups varied in terms of text order (theoretical text followed by applied text or vice versa) and post-listening network drawing tasks. Participants either drew concept maps using key terms specific to each text or irrelevant terms as a control group. After completing both texts, all participants were required to complete a final multi-document network drawing task. Finally, a multiple-choice delayed test was administered three days later. The findings suggest that conceptual networks in LT-WM significantly influence multiple-text comprehension performance. Furthermore, the network drawing task appears to be an effective method for reconstructing knowledge structures in LT-WM, serving as a complementary measure to the MCT in assessing listening comprehension.

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References

  • Anmarkrud, Ø., McCrudden, M. T., Bråten, I., & Strømsø, H. I. (2013). Task-oriented reading of multiple documents: Online comprehension processes and offline products. Instructional Science, 41(5), 873–894. https://doi.org/10.1007/s11251-013-9263-8.

    Article  Google Scholar 

  • Arehalli, S., & Wittenberg, E. (2021). Experimental filler design influences error correction rates in a word restoration paradigm. Linguistics Vanguard, 7(1), 20200052. https://doi.org/10.1515/lingvan-2020-0052.

    Article  Google Scholar 

  • Baddeley, A. D., & Hitch, G. (1974). Working memory. Psychology of Learning and Motivation, 8, 47–89. https://doi.org/10.1016/S0079-7421(08)60452-1.

    Article  Google Scholar 

  • Bohn-Gettler, C. M., & Kendeou, P. (2014). The interplay of reader goals, working memory, and text structure during reading. Contemporary Educational Psychology, 39(3), 206–219. https://doi.org/10.1016/j.cedpsych.2014.05.003.

    Article  Google Scholar 

  • Bransford, J. D., & Johnson, M. K. (1972). Contextual prerequisites for understanding: Some investigations of comprehension and recall. Journal of Verbal Learning and Verbal Behavior, 11(6), 717–726. https://doi.org/10.1016/S0022-5371(72)80006-9.

    Article  Google Scholar 

  • Brown, A. L., Armbruster, B. B., & Baker, L. (1986). The role of metacognition in reading and studying. In J. Orasanu (Ed.), Reading comprehension: From research to practice (pp. 49–75). Hillsdale, NJ: Erlbaum.

  • Cerdán, R., Candel, C., & Leppink, J. (2018). Cognitive load and learning in the study of multiple documents. Frontiers in Education, 3. https://doi.org/10.3389/feduc.2018.00059.

  • Cerdán, R., Máñez, I., & Serrano-Mendizábal, M. (2021). Reading from multiple documents: The role of text availability and question type. Reading Research Quarterly, 56(1), 209–220. https://doi.org/10.1002/rrq.380.

    Article  Google Scholar 

  • Chen, X., Wei, Z., Li, Z., & Clariana, R. B. (2022). The influence of the conceptual structure of external representations when relearning history content. Educational Technology Research and Development, 71(2), 415–439. https://doi.org/10.1007/s11423-022-10176-y.

    Article  Google Scholar 

  • Clariana, R. B. (2010a). Deriving individual and group knowledge structure from network diagrams and from essays. In D. Ifenthaler, P. Pirnay-Dummer, & N. Seel (Eds.), Computer-based Diagnostics and systematic analysis of knowledge (pp. 117–130). Springer.

  • Clariana, R. B. (2010b). Multi-decision approaches for eliciting knowledge structure. In D. Ifenthaler, P. Pirnay-Dummer, & N. M. Seel (Eds.), Computer-based Diagnostics and systematic analysis of knowledge (pp. 41–59). Springer.

  • Clariana, R. B., & Koul, R. (2004). A computer-based approach for translating text into concept map-like referentations. In A. J. Cañas, J. D. Novak, & F. M. González (Eds.), Proceedings First International Conference on Concept Mapping (CMC’04) (Vol. 1, pp. 125–133). Pamplona, Spain.

  • Clariana, R. B., & Wallace, P. E. (2007). A comparison of pair-wise, list-wise, and clustering approaches for eliciting structural knowledge in information systems courses. International Journal of Instructional Media, 36(3), 287–302.

    Google Scholar 

  • Clariana, R. B., Koul, R., & Salehi, R. (2006). The criterion-related validity of a computer-based approach for scoring concept maps. International Journal of Instructional Media, 33(3), 317–325.

    Google Scholar 

  • Clariana, R. B., Engelmann, T., & Yu, W. (2013). Using centrality of concept maps as a measure of problem space states in computer-supported collaborative problem solving. Educational Technology Research and Development, 61(3), 423–442.

    Article  Google Scholar 

  • Clariana, R. B., Rysavy, M. D., & Taricani, E. (2015). Text signals influence team artifacts. Educational Technology Research and Development, 63, 35–52.

    Article  Google Scholar 

  • Clariana, R. B., Tang, H., & Chen, X. (2022). Corroborating a sorting task measure of individual and of local collective knowledge structure. Educational Technology Research and Development. https://doi.org/10.1007/s11423-022-10123-x.

    Article  Google Scholar 

  • Da, R. (2020). I am a bee (in Chinese). Duzhe, 9, 28–29.

    Google Scholar 

  • Dai, J. (2007). Input modality, input frequency, and text comprehension (in Chinese). Foreign Language Teaching and Research, 39(4), 285–293.

    Google Scholar 

  • Denning, A., Pewonka, B., Grunspan, D., & Marin, A. J. (2018). Digital textbooks: The effects of input modality and distraction on student learning at a hispanic-serving Institution. Scholarship of Teaching and Learning in Psychology, 4(3), 127–139. https://www.researchgate.net/publication/327637737.

    Article  Google Scholar 

  • Diao, Y., & Sweller, J. (2007). Redundancy in foreign language reading comprehension instruction: Concurrent written and spoken presentations. Learning and Instruction, 17, 78–88.

    Article  Google Scholar 

  • Elleman, A. M., & Oslund, E. L. (2019). Reading Comprehension Research: Implications for practice and policy. Policy Insights from the Behavioral and Brain Sciences, 6(1), 3–11. https://doi.org/10.1177/2372732218816339.

    Article  Google Scholar 

  • Engelmann, T., & Hesse, F. W. (2010). How digital concept maps about the collaborators’ knowledge and information influence computer supported collaborative problem solving. International Journal of Computer-Supported Collaborative Learning, 5(3), 299–319.

    Article  Google Scholar 

  • Ericsson, K. A., & Delaney, P. F. (1999). Long-term working memory as an alternative to capacity models of working memory in everyday skilled performance. In A. Miyake, & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 257–297). Cambridge University Press.

  • Ericsson, K. A., & Kintsch, W. (1995). Long-term working memory. Psychological Review, 102(2), 211–245.

    Article  Google Scholar 

  • Fischetti, M. (2020). Inside the coronavirus (in Chinese). Huan Qiu Ke Xue, 7, 24–29.

    Google Scholar 

  • Follmer, D. J., Fang, S. Y., Clariana, R. B., Meyer, B. J. F., & Li, P. (2018). What predicts adult readers’ understanding of STEM texts? Reading and Writing, 31, 185–214.

    Article  Google Scholar 

  • Garner, R. (1987). Metacognition and reading comprehension. Ablex.

  • Gernsbacher, M. A., Varner, K. R., & Faust, M. E. (1990). Investigating differences in general comprehension skill. Journal of Experimental Psychology: Learning Memory and Cognition, 16(3), 430–445. https://doi.org/10.1037/0278-7393.16.3.430.

    Article  Google Scholar 

  • Gu, Q., & Yin, N. (2014). The influence of modality on cognitive load in L2 discourse comprehension (in Chinese). Overseas English(07), 7–8.

  • Gu, Q., & Yin, N. (2017). Cognitive load in Chinese EFL learners’ comprehension process—A listening/reading comparative study (in Chinese). Foreign Language Teaching and Research, 49(5), 754–766.

    Google Scholar 

  • Guo, X., & Wang, D. (2018). The evolution and differentiation of the broadcasting paradigm of news broadcasting in China (in Chinese). Journal of Chinese Radio and Television(11), 83–85.

  • Hübner, S., Nückles, M., & Renkl, A. (2010). Writing learning journals: Instructional support to overcome learning-strategy deficits. Learning and Instruction, 20(1), 18–29.

    Article  Google Scholar 

  • Hahnel, C., Kroehne, U., Goldhammer, F., Schoor, C., Mahlow, N., & Artelt, C. (2019). Validating process variables of sourcing in an assessment of multiple document comprehension. British Journal of Educational Psychology, 89(3), 524–537. https://doi.org/10.1111/bjep.12278.

  • Ifenthaler, D. (2014). Toward automated computer-based visualization and assessment of team-based performance. Journal of Educational Psychology, 106(3), 651–665. https://doi.org/10.1037/a0035505.

    Article  Google Scholar 

  • Jonassen, D. H., Beisner, K., & Yacci, M. (1993). Structural knowledge: Techniques for representing, conveying and acquiring structural knowledge. LEA.

  • Karsli, M. B., Demirel, T., & Kursun, E. (2020). Examination of different reading strategies with eye tracking measures in paragraph questions. Hacettepe University Journal of Education, 35(1), 92–106. https://doi.org/10.16986/HUJE.2019051160.

    Article  Google Scholar 

  • Kim, M. K. (2012). Cross-validation study of methods and technologies to assess mental models in a complex problem solving situation. Computers in Human Behavior, 28, 703–717.

    Article  Google Scholar 

  • Kim, K., & Clariana, R. B. (2015). Knowledge structure measures of reader’s situation models across languages: Translation engenders richer structure. Technology Knowledge and Learning, 20, 249–268. https://doi.org/10.1007/s10758-015-9246-8.

    Article  Google Scholar 

  • Kintsch, W. (1988). The role of knowledge in discourse comprehension: A construction-integration model. Psychological Review, 95(2), 163–182. https://doi.org/10.1037/0033-295X.95.2.163.

    Article  Google Scholar 

  • Kintsch, W., & van Dijk, T. A. (1978). Toward a model of text comprehension and production. Psychological Review, 85(5), 363–394. https://doi.org/10.1037/0033-295X.85.5.363.

    Article  Google Scholar 

  • Koul, R., Clariana, R. B., & Salehi, R. (2005). Comparing sveral human and computer-based methods for scoring concept maps and essays. Journal of Educational Computing Research, 32(3), 227–239.

    Article  Google Scholar 

  • Leahy, W., & Sweller, J. (2011). Cognitive load theory, modality of presentation and the transient information effect. Applied Cognitive Psychology, 25(6), 943–951. https://doi.org/10.1002/acp.1787.

    Article  Google Scholar 

  • Leahy, W., & Sweller, J. (2016). Cognitive load theory and the effects of transient information on the modality effect. Instructional Science, 44(1), 107–123. https://doi.org/10.1007/s11251-015-9362-9.

    Article  Google Scholar 

  • Lehmann, T., Pirnay-Dummer, P., & Schmidt-Borcherding, F. (2020). Fostering integrated mental models of different professional knowledge domains: Instructional approaches and model-based analyses. Educational Technology Research and Development, 68, 905–927. https://doi.org/10.1007/s11423-019-09704-0.

    Article  Google Scholar 

  • Li, P., & Clariana, R. B. (2019). Reading comprehension in L1 and L2: An integrative approach. Journal of Neurolinguistics, 50, 94–105.

    Article  Google Scholar 

  • Madrid, I. R., van Oostendorp, H., & Puerta Melguizo, M. C. (2009). The effects of the number of links and navigation support on cognitive load and learning with hypertext: The mediating role of reading order. Computers in Human Behavior, 25(1), 66–75.

    Article  Google Scholar 

  • Mayer, R. (2004). Cognitive theory of multimedia learning. In R. Mayer (Ed.), The cambridge handbook of multimedia learning (pp. 43–72). (2nd ed.) New York, NY, USA.

  • McCrudden, M. T., Kulikowich, J. M., Lyu, B., & Huynh, L. (2022). Promoting integration and learning from multiple complementary texts. Journal of Educational Psychology, 114(8), 1832–1843. https://doi.org/10.1037/edu0000746.

    Article  Google Scholar 

  • NPR, & Edison-Research (2023). The spoken word audio report. Retrieved from https://www.nationalpublicmedia.com/insights/reports/the-spoken-word-audio-report/.

  • Oakhill, J., Hartt, J., & Samols, D. (2005). Levels of comprehension monitoring and working memory in good and poor comprehenders. Reading and Writing, 18, 657–686. https://doi.org/10.1007/s11145-005-3355-z.

    Article  Google Scholar 

  • Perfetti, C. A. (1989). There are generalized abilities and one of them is reading. In L. Resnick (Ed.), Knowing and learning: Essays in honor of Robert Glaser (pp. 307–335). Hillsdale, NJ: Lawrence.

  • Perfetti, C. A., & Stafura, J. (2014). Word knowledge in a theory of reading comprehension. Scientific Studies of Reading, 18(1), 22–37. https://doi.org/10.1080/10888438.2013.827687.

    Article  Google Scholar 

  • Primor, L., Yeari, M., & Katzir, T. (2021). Choosing the right question: The effect of different question types on multiple text integration. Reading and Writing, 36, 1539–1567. https://doi.org/10.1007/s11145-021-10127-8.

    Article  Google Scholar 

  • Qu, K., & Zhang, Q. (2014). Double-content example learning and its significant enlightenment (in Chinese). Journal of Psychological Science, 37(2), 373–376.

    Google Scholar 

  • Ray, M. N., & Meyer, B. J. F. (2011). Individual differences in children’s knowledge of expository text structures: A review of the literature. International Electronic Journal of Environmental Education, 4(1), 67–82.

    Google Scholar 

  • Rouet, J. F., Saux, G., Ros, C., Stadtler, M., Vibert, N., & Britt, M. A. (2020). Inside document models: Role of source attributes in readers’ integration of multiple text contents. Discourse Processes, 1–20. https://doi.org/10.1080/0163853X.2020.1750246.

  • Salmerón, L., Kintsch, W., & Cañas, J. J. (2006). Reading strategies and prior knowledge in learning from hypertext. Memory and Cognition, 34(5), 1157–1171.

    Article  Google Scholar 

  • Schleicher, A. T., Claudia (2000). Assessing reading literacy in PISA. Measuring Student Knowledge and skills: The PISA 2000 Assessment of Reading, Mathematical and scientific literacy. Education and skills (pp. 24–29). Organisation for Economic Cooperation and Development.

  • Schnotz, W. (2023). Comprehension of text. In W. Schnotz (Ed.), Multimedia Comprehension (pp. 63–86). Cambridge University Press.

  • St. Hilaire, K. J. (2017). The pretesting effect: How question-type and structure building ability impact learning (Master). Wake Forest University, ProQuest Dissertations & Theses Globa. (Pablication No. 1954045888).

  • Tang, H., & Clariana, R. B. (2017). Leveraging a sorting task as a measure of knowledge structure in bilingual settings. Technology Knowledge and Learning, 22(1), 23–35. https://doi.org/10.1007/s10758-016-9290-z.

    Article  Google Scholar 

  • Triplett, R. L., Jaworski, J. M., & Neville, K. J. (2014). An examination of long-term working memory capacity. Journal of Aviation Technology and Engineering, 3(2), 20–27.

    Article  Google Scholar 

  • Urakami, J., & Krems, J. F. (2012). How hypertext reading sequences affect understanding of causal and temporal relations in story comprehension. Instructional Science, 40(2), 277–295. https://doi.org/10.1007/s11251-011-9178-1.

    Article  Google Scholar 

  • Vidal-Abarca, E., Martinez, T., Salmerón, L., Cerdán, R., Gilabert, R., Gil, L., & Ferris, R. (2011). Recording online processes in task-oriented reading with read&answer. Behavior Research Methods, 43(1), 179–192. https://doi.org/10.3758/s13428-010-0032-1.

    Article  Google Scholar 

  • Waldholz, M. (2020). Fast-track drugs (in Chinese). Huan Qiu Ke Xue, 7, 30–33.

    Google Scholar 

  • Wei, Z., Chen, X., & Clariana, R. B. (2022). Measures of knowledge structure in reading comprehension (in Chinese). Psychological Science, 45(2), 306–315. https://doi.org/10.16719/j.cnki.1671-6981.20220206.

    Article  Google Scholar 

  • Wei, Z., Zhang, Y., Clariana, R. B., & Chen, X. (2023). The effect of reading prompt and post-reading task on multiple document integration: Evidence from concept network analysis. Educational Technology Research and Development. https://doi.org/10.1007/s11423-023-10326-w.

    Article  Google Scholar 

  • Wolf, M. C., Muijselaar, M. M. L., Boonstra, A. M., & de Bree, E. H. (2019). The relationship between reading and listening comprehension: Shared and modality-specific components. Reading and Writing, 32, 1747–1767. https://doi.org/10.1007/s11145-018-9924-8.

    Article  Google Scholar 

  • Yan, G., Xiong, J., Zang, C., Yu, L., Cui, L., & Bai, X. (2013). Review of eye-movement measures in reading research (in Chinese). Advances in Psychological Science, 21(4), 589–605. https://doi.org/10.3724/SP.J.1042.2013.00589.

    Article  Google Scholar 

  • Yang, F., Sui, X., & Yi, Y. (2020). An eye movement study for the guidance mechanism of long-distance regressions in Chinese reading (in Chinese). Acta Psychologica Sinica, 52(8), 921–932. https://doi.org/10.3724/SP.J.1041.2020.00921.

    Article  Google Scholar 

  • Zhang, Z., & Yuan, K. H. (2018). Practical statistical power analysis using Webpower and R. ISDSA.

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National Natural Science Foundation of China, Grant/Award Numbers: 31970983.

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Chen, X., Zhang, Y. & Dai, Q. Listening instead of reading: using network drawing task as a re-constructed method and measure of knowledge in mind. Read Writ (2024). https://doi.org/10.1007/s11145-024-10554-3

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