Skip to main content
Original Article

The role of cognitive load in university students' comprehension of multiple documents

Published Online:https://doi.org/10.1024/1010-0652/a000238

Abstract. The study investigates the cognitive load of students working on tasks that require the comprehension of multiple documents (Multiple Document Comprehension, MDC). In a sample of 310 students, perceived task difficulty (PD) and mental effort (ME) were examined in terms of task characteristics, individual characteristics, and students' processing behavior. Moreover, it was investigated if PD and ME can still contribute to MDC while controlling for these variables. The perceived difficulty of the task was shown to be related to the number of documents, text length, study level, and sourcing. Mental effort was predicted by text length, study level, and processing time. When including these variables as covariates, cognitive load was incrementally predictive of MDC. The results are discussed in terms of how working memory resources can shape the process of comprehending multiple documents.


Die Rolle kognitiver Belastung für das Verständnis multipler Dokumente von Studierenden

Zusammenfassung. Die Studie untersucht das Belastungserleben (Cognitive Load) von Studierenden beim Bearbeiten von Aufgaben, die das Verstehen multipler Dokumente erfordern (Multiple Document Comprehension, MDC). Es wurde geprüft, inwiefern die wahrgenommene Aufgabenschwierigkeit und die mentale Anstrengung von 310 Studierenden durch aufgabenspezifische Eigenschaften, individuelle Merkmale und ihr Bearbeitungsverhalten bestimmt werden und darüber hinaus MDC erklären. Für die Aufgabenschwierigkeit wurde gezeigt, dass sie mit der Dokumentenanzahl, der Textlänge, dem Studienniveau sowie der Berücksichtigung von Quellen in Zusammenhang steht. Die mentale Anstrengung wurde durch die Textlänge, das Studienniveau und Bearbeitungszeiten vorhergesagt. Unter Einschluss dieser Variablen als Kovariaten war das Belastungserleben inkrementell prädiktiv für MDC. Die Ergebnisse werden dahingehend diskutiert, wie Arbeitsgedächtnisressourcen den Prozess des Verstehens multipler Dokumente gestalten können.

References

  • Anmarkrud, Ø., Bråten, I., & Strømsø, H. I. (2014). Multiple-documents literacy: Strategic processing, source awareness, and argumentation when reading multiple conflicting documents. Learning and Individual Differences, 30, 64 – 76. https://doi.org/10.1016/j.lindif.2013.01.007 First citation in articleCrossrefGoogle Scholar

  • Ayres, P., & Sweller, J. (2005). The split-attention principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 135 – 146). New York: Cambridge University Press. First citation in articleCrossrefGoogle Scholar

  • Ayres, P. (2006). Using subjective measures to detect variations of intrinsic cognitive load within problems. Learning and Instruction, 16(5), 389 – 400. https://doi.org/10.1016/j.learninstruc.2006.09.001 First citation in articleCrossrefGoogle Scholar

  • Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1 – 48. https://doi.org/10.18637/jss.v067.i01 First citation in articleGoogle Scholar

  • Bråten, I., Stadtler, M., & Salmerón, L. (2018). The role of sourcing in discourse comprehension. In M. F. SchoberD. N. RappM. A. Britt (Eds.), Handbook of Discourse Processes. New York, NY: Taylor & Francis. First citation in articleGoogle Scholar

  • Britt, M. A., & Aglinskas, C. (2002). Improving students' ability to identify and use source information. Cognition and Instruction, 20(4), 485 – 522. First citation in articleCrossrefGoogle Scholar

  • Britt, M. A., & Rouet, J.-F. (2012). Learning with Multiple Documents: Component skills and their acquisition. In J. R. KirbyM. J. Lawson (Eds.), Enhancing the quality of learning: Dispositions, instruction, and learning processes (pp. 276 – 314). New York: Cambridge University Press. First citation in articleCrossrefGoogle Scholar

  • Britt, M. A., & Sommer, J. (2004). Facilitating textual integration with macro-structure focusing tasks. Reading Psychology, 25(4), 313 – 339. https://doi.org/10.1080/02702710490522658 First citation in articleCrossrefGoogle Scholar

  • Chen, O., Castro-Alonso, J. C., Paas, F., & Sweller, J. (2018). Extending Cognitive Load Theory to Incorporate Working Memory Resource Depletion: Evidence from the Spacing Effect. Educational Psychology Review, 30(2), 483 – 501. https://doi.org/10.1007/s10648-017-9426-2 First citation in articleCrossrefGoogle Scholar

  • Chen, O., Kalyuga, S., & Sweller, J. (2017). The Expertise Reversal Effect is a Variant of the More General Element Interactivity Effect. Educational Psychology Review, 29(2), 393 – 405. https://doi.org/10.1007/s10648-016-9359-1 First citation in articleCrossrefGoogle Scholar

  • Choi, H.-H., van Merriënboer, J. J. G., & Paas, F. (2014). Effects of the Physical Environment on Cognitive Load and Learning: Towards a New Model of Cognitive Load. Educational Psychology Review, 26(2), 225 – 244. https://doi.org/10.1007/s10648-014-9262-6 First citation in articleCrossrefGoogle Scholar

  • DeStefano, D., & LeFevre, J.-A. (2007). Cognitive load in hypertext reading: A review. Computers in Human Behavior, 23(3), 1616 – 1641. https://doi.org/10.1016/j.chb.2005.08.012 First citation in articleCrossrefGoogle Scholar

  • Goldhammer, F., Naumann, J., Stelter, A., Tóth, K., Rölke, H., & Klieme, E. (2014). The Time on Task Effect in Reading and Problem Solving Is Moderated by Task Difficulty and Skill: Insights From a Computer-Based Large-Scale Assessment. Journal of Educational Psychology, 106(3), 608 – 626. First citation in articleCrossrefGoogle Scholar

  • Hagen, Å. M., Braasch, J. L. G., & Bråten, I. (2014). Relationships between spontaneous note-taking, self-reported strategies and comprehension when reading multiple texts in different task conditions. Journal of Research in Reading, 37, 141 – 157. https://doi.org/10.1111/j.1467-9817.2012.01536.x First citation in articleCrossrefGoogle 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, bjep.12278. https://doi.org/10.1111/bjep.12278 First citation in articleCrossrefGoogle Scholar

  • Händel, M., Artelt, C., & Weinert, S. (2013). Assessing metacognitive knowledge: Development and evaluation of a test instrument. Journal of Educational Research Online, 5, 162 – 188. First citation in articleGoogle Scholar

  • Hutchins, E. (1995). How a Cockpit Remembers Its Speeds. Cognitive Science, 19(3), 265 – 288. First citation in articleCrossrefGoogle Scholar

  • Klepsch, M., Schmitz, F., & Seufert, T. (2017). Development and Validation of Two Instruments Measuring Intrinsic, Extraneous, and Germane Cognitive Load. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.01997 First citation in articleCrossrefGoogle Scholar

  • Kobayashi, K. (2009). The influence of topic knowledge, external strategy use, and college experience on students' comprehension of controversial texts. Learning and Individual Differences, 19(1), 130 – 134. https://doi.org/10.1016/j.lindif.2008.06.001 First citation in articleCrossrefGoogle Scholar

  • Korbach, A., Brünken, R., & Park, B. (2018). Differentiating Different Types of Cognitive Load: a Comparison of Different Measures. Educational Psychology Review, 30(2), 503 – 529. https://doi.org/10.1007/s10648-017-9404-8 First citation in articleCrossrefGoogle Scholar

  • Krell, M. (2015). Evaluating an instrument to measure mental load and mental effort using item response theory. Science Education Review Letters, Research Letters 2015, 1 – 6. First citation in articleGoogle Scholar

  • Kroehne, U., & Goldhammer, F. (2018). How to conceptualize, represent, and analyze log data from technology-based assessments? A generic framework and an application to questionnaire items. Behaviormetrika. https://doi.org/10.1007/s41237-018-0063-y First citation in articleCrossrefGoogle Scholar

  • Landis, J. R., & Koch, G. (1977). The measurement of observer agreement for categorial data. Biometrics, 33(1), 159 – 174. First citation in articleCrossrefGoogle Scholar

  • Le Bigot, L., & Rouet, J.-F. (2007). The impact of presentation format, task assignment, and prior knowledge on students' comprehension of multiple online documents. Journal of Literacy Research, 39(4), 445 – 470. First citation in articleCrossrefGoogle Scholar

  • Leppink, J., & van den Heuvel, A. (2015). The evolution of cognitive load theory and its application to medical education. Perspectives on Medical Education, 4(3), 119 – 127. https://doi.org/10.1007/s40037-015-0192-x First citation in articleCrossrefGoogle Scholar

  • Moos, D. C. (2009). Note-taking while learning hypermedia: Cognitive and motivational considerations. Computers in Human Behavior, 25(5), 1120 – 1128. https://doi.org/10.1016/j.chb.2009.05.004 First citation in articleCrossrefGoogle Scholar

  • Nelson, T. O., & Narens, L. (1990). Metamemory: A theoretical framework and new findings. The Psychology of Learning and Motivation, 26, 125 – 141. First citation in articleCrossrefGoogle Scholar

  • Paas, F. (1992). Training Strategies for Attaining Transfer of Problem-Solving Skill in Statistics: A Cognitive-Load Approach. Journal of Educational Psychology, 84(4), 429 – 434. First citation in articleCrossrefGoogle Scholar

  • Paas, F., & Sweller, J. (2012). An Evolutionary Upgrade of Cognitive Load Theory: Using the Human Motor System and Collaboration to Support the Learning of Complex Cognitive Tasks. Educational Psychology Review, 24(1), 27 – 45. https://doi.org/10.1007/s10648-011-9179-2 First citation in articleCrossrefGoogle Scholar

  • Paas, F., Tuovinen, J. E., Tabbers, H., & Van Gerven, P. W. M. (2003). Cognitive Load Measurement as a Means to Advance Cognitive Load Theory. Educational Psychologist, 38(1), 63 – 71. https://doi.org/10.1207/S15326985EP3801_8 First citation in articleCrossrefGoogle Scholar

  • Perfetti, C. (2007). Reading Ability: Lexical Quality to Comprehension. Scientific Studies of Reading, 11(4), 357 – 383. First citation in articleCrossrefGoogle Scholar

  • R Core Team. (2018). R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from http://www.R-project.org/ First citation in articleGoogle Scholar

  • Revelle, W. (2018). psych: Procedures for Psychological, Psychometric, and Personality Research. Evanston, Illinois: Northwestern University. Retrieved from https://CRAN.R-project.org/package=psych First citation in articleGoogle Scholar

  • Robitzsch, A., Kiefer, T., & Wu, M. (2017). TAM: Test analysis modules. Retrieved from https://CRAN.R-project.org/package=TAM First citation in articleGoogle Scholar

  • Rouet, J.-F., Ros, C., Goumi, A., Macedo-Rouet, M., & Dinet, J. (2011). The influence of surface and deep cues on primary and secondary school students assessment of relevance in Web menus. Learning and Instruction, 21(2), 205 – 219. https://doi.org/10.1016/j.learninstruc.2010.02.007 First citation in articleCrossrefGoogle Scholar

  • Scheiter, K., Gerjets, P., Vollmann, B., & Catrambone, R. (2009). The impact of learner characteristics on information utilization strategies, cognitive load experienced, and performance in hypermedia learning. Learning and Instruction, 19(5), 387 – 401. https://doi.org/10.1016/j.learninstruc.2009.02.004 First citation in articleCrossrefGoogle Scholar

  • Schoor, C., Hahnel, C., Artelt, C., Reimann, D., Kröhne, U., & Goldhammer, F. (in press). Entwicklung und Skalierung eines Tests zur Erfassung des Verständnisses multipler Dokumente von Studierenden [Developing and Scaling a Test of Multiple Document Comprehension in University Students]. Diagnostica. First citation in articleGoogle Scholar

  • Sweller, J. (2010). Element Interactivity and Intrinsic, Extraneous, and Germane Cognitive Load. Educational Psychology Review, 22(2), 123 – 138. https://doi.org/10.1007/s10648-010-9128-5 First citation in articleCrossrefGoogle Scholar

  • Sweller, J., Ayres, P. L., & Kalyuga, S. (2011). Cognitive load theory. New York: Springer. First citation in articleCrossrefGoogle Scholar

  • Therriault, D. J., & Rinck, M. (2007). Multidimensional Situation Models. In F. SchmalhoferC. A. Perfetti (Eds.), Higher level language processes in the brain: inference and comprehension processes (pp. 311 – 328). Mahwah, NJ: Erlbaum. First citation in articleGoogle Scholar

  • Trapmann, S., Hell, B., Weigand, S., & Schuler, H. (2007). Die Validität von Schulnoten zur Vorhersage des Studienerfolgs – eine Metaanalyse [The validity of school grades for predicting study success – a meta-analysis]. Zeitschrift für Pädagogische Psychologie, 21(1), 11 – 27. https://doi.org/10.1024/1010-0652.21.1.11 First citation in articleLinkGoogle Scholar

  • van Buuren, S. (2012). Flexible imputation of missing data. Boca Raton, FL: CRC Press. First citation in articleCrossrefGoogle Scholar

  • Weinstein, C. E., & Mayer, R. E. (1983). The teaching of learning strategies. Innovation Abstracts, 5(32). First citation in articleGoogle Scholar

  • Wiley, J., Goldman, S. R., Graesser, A. C., Sanchez, C. A., Ash, I. K., & Hemmerich, J. A. (2009). Source Evaluation, Comprehension, and Learning in Internet Science Inquiry Tasks. American Educational Research Journal, 46(4), 1060 – 1106. https://doi.org/10.3102/0002831209333183 First citation in articleCrossrefGoogle Scholar

  • Wineburg, S. (1991). Historical Problem Solving: A Study of the Cognitive Processes Used in the Evaluation of Documentary and Pictorial Evidence. Journal of Educational Psychology, 83(1), 73 – 87. First citation in articleCrossrefGoogle Scholar