Embedded interruptions and task complexity influence schema-related cognitive load progression in an abstract learning task.

Cognitive processes related to schema acquisition comprise an essential source of demands in learning situations. Since the related amount of cognitive load is supposed to change over time, plausible temporal models of load progression based on different theoretical backgrounds are inspected in this study. A total of 116 student participants completed a basal symbol sequence learning task, which provided insights into underlying cognitive dynamics. Two levels of task complexity were determined by the amount of elements within the symbol sequence. In addition, interruptions due to an embedded secondary task occurred at five predefined stages over the task. Within the resulting 2x5-factorial mixed between-within design, the continuous monitoring of efficiency in learning performance enabled assumptions on relevant resource investment. From the obtained results, a nonlinear change of learning efficiency over time seems most plausible in terms of cognitive load progression. Moreover, different effects of the induced interruptions show up in conditions of task complexity, which indicate the activation of distinct cognitive mechanisms related to structural aspects of the task. Findings are discussed in the light of evidence from research on memory and information processing.

[1]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[2]  Richard P. Heitz,et al.  Complex working memory span tasks and higher-order cognition: A latent-variable analysis of the relationship between processing and storage , 2009, Memory.

[3]  M. Lee,et al.  Bayesian Cognitive Modeling: A Practical Course , 2014 .

[4]  G. Schwarz.  Estimating the Dimension of a Model , 1978 .

[5]  John Sweller,et al.  Cognitive Load During Problem Solving: Effects on Learning , 1988, Cogn. Sci..

[6]  Peter Gerjets,et al.  The influence of a waiting intention on action performance : Efficiency impairment and volitional protection in tasks of varying difficulty , 1997 .

[7]  D. McNamara.  Reading both high-coherence and low-coherence texts: effects of text sequence and prior knowledge. , 2001, Canadian journal of experimental psychology = Revue canadienne de psychologie experimentale.

[8]  Richard C. Anderson.  Role of the Reader's Schema in Comprehension, Learning, and Memory , 2018, Theoretical Models and Processes of Literacy.

[9]  Katharina Scheiter,et al.  Distraction during learning with hypermedia: difficult tasks help to keep task goals on track , 2014, Front. Psychol..

[10]  J. Gregory Trafton,et al.  Preparing to resume an interrupted task: effects of prospective goal encoding and retrospective rehearsal , 2003, Int. J. Hum. Comput. Stud..

[11]  Günter Daniel Rey,et al.  The expertise reversal effect: cognitive load and motivational explanations. , 2011, Journal of experimental psychology. Applied.

[12]  Lana M Trick,et al.  More than superstition: Differential effects of featural heterogeneity and change on subitizing and counting , 2008, Perception & psychophysics.

[13]  Jens F. Beckmann,et al.  Taming a Beast of Burden--On Some Issues with the Conceptualisation and Operationalisation of Cognitive Load. , 2010 .

[14]  Gregory Schraw,et al.  Conceptions of Efficiency: Applications in Learning and Problem Solving , 2010 .

[15]  Karin Landerl,et al.  Subitizing and counting in typical and atypical development. , 2011, Developmental science.

[16]  Slava Kalyuga.  Cognitive Load Theory: How Many Types of Load Does It Really Need? , 2011 .

[17]  D. Broadbent,et al.  What makes interruptions disruptive? A study of length, similarity, and complexity , 1989 .

[18]  K. Barton.  MuMIn : multi-model inference, R package version 0.12.0 , 2009 .

[19]  Richard P. Heitz,et al.  An automated version of the operation span task , 2005, Behavior research methods.

[20]  J. Piaget,et al.  The Origins of Intelligence in Children , 1971 .

[21]  R. Yerkes,et al.  The relation of strength of stimulus to rapidity of habit‐formation , 1908 .

[22]  J. Trafton,et al.  The effect of interruption duration and demand on resuming suspended goals. , 2008, Journal of experimental psychology. Applied.

[23]  Clara E. Bussenius,et al.  Memory : A Contribution to Experimental Psychology , 2017 .

[24]  Christopher D. Wickens,et al.  Multiple resources and performance prediction , 2002 .

[25]  S. Greven,et al.  On the behaviour of marginal and conditional AIC in linear mixed models , 2010 .

[26]  Jiajie Zhang,et al.  A Concept Analysis of the Phenomenon Interruption , 2007, ANS. Advances in nursing science.

[27]  Zoltan Dienes,et al.  Using Bayes to get the most out of non-significant results , 2014, Front. Psychol..

[28]  E. Bjork,et al.  Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. , 2011 .

[29]  D. Dooling,et al.  Intrusion of a thematic idea in retention of prose. , 1974 .

[30]  Slava Kalyuga.  Expertise Reversal Effect and Its Implications for Learner-Tailored Instruction , 2007 .

[31]  F. Paas,et al.  Teaching complex rather than simple tasks: balancing intrinsic and germane load to enhance transfer of learning , 2006 .

[32]  Slava Kalyuga,et al.  When problem solving is superior to studying worked examples. , 2001 .

[33]  What enumeration studies can show us about spatial attention: evidence for limited capacity preattentive processing. , 1993 .

[34]  A. Beck,et al.  THINKING AND DEPRESSION. II. THEORY AND THERAPY. , 1964, Archives of general psychiatry.

[35]  J. Kuha.  AIC and BIC , 2004 .

[36]  N. Cowan,et al.  The Magical Mystery Four , 2010, Current directions in psychological science.

[37]  Nicole Fruehauf.  Flow The Psychology Of Optimal Experience , 2016 .

[38]  H. Akaike.  A new look at the statistical model identification , 1974 .

[39]  Z. Pylyshyn,et al.  Why are small and large numbers enumerated differently? A limited-capacity preattentive stage in vision. , 1994, Psychological review.

[40]  Steve Nebel,et al.  One for all?! Simultaneous examination of load-inducing factors for advancing media-related instructional research , 2016, Comput. Educ..

[41]  P. Dux,et al.  Transfer of training benefits requires rules we cannot see (or hear). , 2016, Journal of experimental psychology. Human perception and performance.

[42]  J. G. Schuurman,et al.  Redirecting learners' attention during training: Effects on cognitive load, transfer test performance and training efficiency. , 2002 .

[43]  P. Kirschner,et al.  External representation of argumentation in CSCL and the management of cognitive load , 2002 .

[44]  F. Paas,et al.  Instructional control of cognitive load in the training of complex cognitive tasks , 1994 .

[45]  David E. Rumelhart,et al.  The Representation of Knowledge in Memory 1 , 2017 .

[46]  Marcia K. Johnson,et al.  Contextual prerequisites for understanding: Some investigations of comprehension and recall , 1972 .

[47]  Moritz Krell,et al.  Evaluating an instrument to measure mental load and mental effort using Item Response Theory , 2015 .

[48]  P. Chandler,et al.  Assimilating complex information , 2002 .

[49]  John B. Black,et al.  Scripts in memory for text , 1979, Cognitive Psychology.

[50]  P. Brockhoff,et al.  Tests in Linear Mixed Effects Models , 2015 .

[51]  Jan Theeuwes,et al.  OpenSesame: An open-source, graphical experiment builder for the social sciences , 2011, Behavior Research Methods.

[52]  G. Mandler,et al.  Subitizing: an analysis of its component processes. , 1982, Journal of experimental psychology. General.

[53]  Z. Pylyshyn,et al.  What enumeration studies can show us about spatial attention: evidence for limited capacity preattentive processing. , 1993, Journal of experimental psychology. Human perception and performance.

[54]  W. Kintsch,et al.  Are Good Texts Always Better? Interactions of Text Coherence, Background Knowledge, and Levels of Understanding in Learning From Text , 1996 .

[55]  Walter Schneider,et al.  Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. , 1977 .

[56]  Rolf Schwonke,et al.  Metacognitive Load - Useful, or Extraneous Concept? Metacognitive and Self-Regulatory Demands in Computer-Based Learning , 2015, J. Educ. Technol. Soc..

[57]  Roger Azevedo,et al.  Advances in scaffolding learning with hypertext and hypermedia: a summary and critical analysis , 2008 .

[58]  J. G. Hollands,et al.  Engineering Psychology and Human Performance , 1984 .

[59]  J. Neuschatz,et al.  The effect of memory schemata on memory and the phenomenological experience of naturalistic situations , 2002 .

[60]  J. Sweller.  Element Interactivity and Intrinsic, Extraneous, and Germane Cognitive Load , 2010 .

[61]  Oliver Lindemann,et al.  Expyriment: A Python library for cognitive and neuroscientific experiments , 2014, Behavior research methods.

[62]  Jeffrey N. Rouder,et al.  Computation of Bayes Factors for Common Designs , 2015 .

[63]  Slava Kalyuga.  Cognitive Load Theory: Schema Acquisition and Sources of Cognitive Load , 2010 .

[64]  Jeffrey L. Foster,et al.  Shortened complex span tasks can reliably measure working memory capacity , 2015, Memory & cognition.

[65]  Jeroen J. G. van Merriënboer,et al.  The Beast of Aggregating Cognitive Load Measures in Technology-Based Learning , 2015, J. Educ. Technol. Soc..

[66]  R. Atkinson,et al.  Structuring the Transition From Example Study to Problem Solving in Cognitive Skill Acquisition: A Cognitive Load Perspective , 2003 .

[67]  Alexander Renkl,et al.  Toward an Instructionally Oriented Theory of Example-Based Learning , 2014, Cogn. Sci..

[68]  B. Zimmerman.  Self-Regulated Learning and Academic Achievement: An Overview , 1990 .

[69]  Yixin Fang,et al.  Asymptotic Equivalence between Cross-Validations and Akaike Information Criteria in Mixed-Effects Models , 2021 .

[70]  John Sweller,et al.  Cognitive Load Theory , 2020, Encyclopedia of Education and Information Technologies.

[71]  Michael F. Bunting,et al.  Working memory span tasks: A methodological review and user’s guide , 2005, Psychonomic bulletin & review.

[72]  P. Chandler,et al.  Why Some Material Is Difficult to Learn , 1994 .

[73]  D. Rumelhart.  Schemata: The Building Blocks of Cognition , 2017 .

[74]  Vanessa E. Ghosh,et al.  What is a memory schema? A historical perspective on current neuroscience literature , 2014, Neuropsychologia.

[75]  H. Jeffreys,et al.  Theory of probability , 1896 .

[76]  G. Holmes,et al.  Sensory disturbances from cerebral lesions , 1911 .

[77]  W. Brewer,et al.  Role of schemata in memory for places , 1981, Cognitive Psychology.

[78]  E. M. Jensen,et al.  The subitizing and counting of visually presented fields of dots. , 1950 .

[79]  David R. Anderson,et al.  Model selection and multimodel inference : a practical information-theoretic approach , 2003 .

[80]  Martin Valcke,et al.  Cognitive load: updating the theory? , 2002 .