What does germane load mean? An empirical contribution to the cognitive load theory

While over the last decades, much attention has been paid to the mental workload in the field of human computer interactions, there is still a lack of consensus concerning the factors that generate it as well as the measurement methods that could reflect workload variations. Based on the multifactorial Cognitive Load Theory (CLT), our study aims to provide some food for thought about the subjective and objective measurement that can be used to disentangle the intrinsic, extraneous, and germane load. The purpose is to provide insight into the way cognitive load can explain how users' cognitive resources are allocated in the use of hypermedia, such as an online newspaper. A two-phase experiment has been conducted on the information retention from online news stories. Phase 1 (92 participants) examined the influence of multimedia content on performance as well as the relationships between cognitive loads and cognitive absorption. In Phase 2 (36 participants), eye-tracking data were collected in order to provide reliable and objective measures. Results confirmed that performance in information retention was impacted by the presence of multimedia content such as animations and pictures. The higher number of fixations on these animations suggests that users' attention could have been attracted by them. Results showed the expected opposite relationships between germane and extraneous load, a positive association between germane load and cognitive absorption and a non-linear association between intrinsic and germane load. The trends based on eye-tracking data analysis provide some interesting findings about the relationship between longer fixations, shorter saccades and cognitive load. Some issues are raised about the respective contribution of mean pupil diameter and Index of Cognitive Activity.

[1]  Werner Severin,et al.  Another look at cue summation , 1967 .

[2]  Alan D. Baddeley,et al.  Verbal Reasoning and Working Memory , 1976 .

[3]  Michelene T. H. Chi,et al.  Expertise in Problem Solving. , 1981 .

[4]  L. Mulder,et al.  Information processing and cardiovascular control. , 1981, Psychophysiology.

[5]  G. Salomon Television is "easy" and print is "tough": The differential investment of mental effort in learning as a function of perceptions and attributions. , 1984 .

[6]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .

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

[8]  M. Csíkszentmihályi Flow: The Psychology of Optimal Experience , 1990 .

[9]  L. Walrath,et al.  Eye movement and pupillary response indices of mental workload during visual search of symbolic displays. , 1992, Applied ergonomics.

[10]  F. Paas Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. , 1992 .

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

[12]  R W Backs Going beyond heart rate: autonomic space and cardiovascular assessment of mental workload. , 1995, The International journal of aviation psychology.

[13]  K. Rayner Eye movements in reading and information processing: 20 years of research. , 1998, Psychological bulletin.

[14]  F. Paas,et al.  Cognitive Architecture and Instructional Design , 1998 .

[15]  S. Sundar,et al.  Multimedia Effects on Processing and Perception of Online News: A Study of Picture, Audio, and Video Downloads , 2000 .

[16]  Elena Karahanna,et al.  Time Flies When You're Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage , 2000, MIS Q..

[17]  Ping Zhang,et al.  The Effects of Animation on Information Seeking Performance on the World Wide Web: Securing Attention or Interfering with Primary Tasks? , 2000, J. Assoc. Inf. Syst..

[18]  Y. Maor,et al.  A comparison of three measures: the time trade-off technique, global health-related quality of life and the SF-36 in dialysis patients. , 2001, Journal of clinical epidemiology.

[19]  R. Mayer,et al.  Cognitive constraints on multimedia learning: When presenting more material results in less understanding. , 2001 .

[20]  Michelle E. Bayles,et al.  Designing online banner advertisements: should we animate? , 2002, CHI.

[21]  S. P. Marshall,et al.  The Index of Cognitive Activity: measuring cognitive workload , 2002, Proceedings of the IEEE 7th Conference on Human Factors and Power Plants.

[22]  F. Paas,et al.  Cognitive Load Measurement as a Means to Advance Cognitive Load Theory , 2003 .

[23]  D. Leutner,et al.  Direct Measurement of Cognitive Load in Multimedia Learning , 2003 .

[24]  Anthony J. Hornof,et al.  Banner ads hinder visual search and are forgotten , 2004, CHI EA '04.

[25]  Yongxia Skadberg,et al.  Visitors' flow experience while browsing a Web site: its measurement, contributing factors and consequences , 2004, Comput. Hum. Behav..

[26]  Richard Catrambone,et al.  Designing Instructional Examples to Reduce Intrinsic Cognitive Load: Molar versus Modular Presentation of Solution Procedures , 2004 .

[27]  F. Paas,et al.  Memory load and the cognitive pupillary response in aging. , 2004, Psychophysiology.

[28]  K. Scherer,et al.  How Seductive Details Do Their Damage : A Theory of Cognitive Interest in Science Learning , 2004 .

[29]  Lee Ann Potter Making the Abstract Concrete. , 2005 .

[30]  Yu-Chen Chen,et al.  Extrinsic versus intrinsic motivations for consumers to shop on-line , 2005, Inf. Manag..

[31]  Paul Ayres Using subjective measures to detect variations of intrinsic cognitive load within problems , 2006 .

[32]  André Tricot,et al.  Utilisation d'un hypermédia et apprentissage : deux activités concurrentes ou complémentaires ? , 2006 .

[33]  Richard Catrambone,et al.  Making the abstract concrete: Visualizing mathematical solution procedures , 2006, Comput. Hum. Behav..

[34]  Aline Chevalier,et al.  Web designers and web users: Influence of the ergonomic quality of the web site on the information search , 2006, Int. J. Hum. Comput. Stud..

[35]  Sandra P Marshall,et al.  Identifying cognitive state from eye metrics. , 2007, Aviation, space, and environmental medicine.

[36]  W. Schnotz,et al.  A Reconsideration of Cognitive Load Theory , 2007 .

[37]  R. Mayer,et al.  Interactive Multimodal Learning Environments , 2007 .

[38]  Robert R. Whelan Neuroimaging of cognitive load in instructional multimedia , 2007 .

[39]  Arthur M. Jacobs,et al.  OGAMA (Open Gaze and Mouse Analyzer): Open-source software designed to analyze eye and mouse movements in slideshow study designs , 2008, Behavior research methods.

[40]  Krista E. DeLeeuw,et al.  A Comparison of Three Measures of Cognitive Load: Evidence for Separable Measures of Intrinsic, Extraneous, and Germane Load , 2008 .

[41]  Sean Bechhofer,et al.  Visual complexity and aesthetic perception of web pages , 2008, SIGDOC '08.

[42]  Paul A. Cairns,et al.  Measuring and defining the experience of immersion in games , 2008, Int. J. Hum. Comput. Stud..

[43]  Aline Chevalier,et al.  The use of Tholos software for combining measures of mental workload: Toward theoretical and methodological improvements , 2008, Behavior research methods.

[44]  Tjerk de Greef,et al.  Eye Movement as Indicators of Mental Workload to Trigger Adaptive Automation , 2009, HCI.

[45]  K. Scheiter,et al.  The Scientific Value of Cognitive Load Theory: A Research Agenda Based on the Structuralist View of Theories , 2009 .

[46]  Donald Voet,et al.  Time flies when you're having fun , 2009, Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology.

[47]  Katharina Scheiter,et al.  Explaining the split-attention effect: Is the reduction of extraneous cognitive load accompanied by an increase in germane cognitive load? , 2009, Comput. Hum. Behav..

[48]  T. Gog,et al.  Effects of prior knowledge and concept-map structure on disorientation, cognitive load, and learning , 2009 .

[49]  J. Dusek,et al.  Impact of Incremental Increases in Cognitive Workload on Physiological Arousal and Performance in Young Adult Drivers , 2009 .

[50]  Fred Paas,et al.  Uncovering cognitive processes: Different techniques that can contribute to cognitive load research and instruction , 2009, Comput. Hum. Behav..

[51]  Cristian Hofmann,et al.  Integrating cognitive load theory and concepts of human-computer interaction , 2010, Comput. Hum. Behav..

[52]  T. Baccino,et al.  Analyzing the pupil response due to increased cognitive demand: an independent component analysis study. , 2010, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[53]  T. Jong Cognitive load theory, educational research, and instructional design: some food for thought , 2010 .

[54]  Jukka Hyönä,et al.  The Use of Eye Movements in the Study of Multimedia Learning. , 2010 .

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

[56]  Han-Chin Liu,et al.  Using eye-tracking technology to investigate the redundant effect of multimedia web pages on viewers' cognitive processes , 2011, Comput. Hum. Behav..

[57]  José J. Cañas,et al.  A neuroergonomic approach to evaluating mental workload in hypermedia interactions , 2011 .

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

[59]  Paul Chandler,et al.  Contemporary cognitive load theory research: The good, the bad and the ugly , 2011, Comput. Hum. Behav..

[60]  Siyuan Chen,et al.  Eye activity as a measure of human mental effort in HCI , 2011, IUI '11.

[61]  Michael J. Albers Tapping as a measure of cognitive load and website usability , 2011, SIGDOC '11.

[62]  Hasan Ayaz,et al.  Optical brain monitoring for operator training and mental workload assessment , 2012, NeuroImage.

[63]  Sandra P. Marshall,et al.  Measuring cognitive workload across different eye tracking hardware platforms , 2012, ETRA.

[64]  Abdallah Namoune,et al.  Predicting user attention in complex web pages , 2012, Behav. Inf. Technol..

[65]  C. Mélan,et al.  What is the relationship between mental workload factors and cognitive load types? , 2012, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[66]  T. Gog,et al.  Development of an instrument for measuring different types of cognitive load , 2013, Behavior Research Methods.

[67]  C. V. D. Leemput,et al.  Acceptabilité des sites web et ergonomie de l'interface : Etude de l'influence de l'utilisabilité objective et de la charge cognitive , 2013 .

[68]  Siyuan Chen,et al.  Automatic classification of eye activity for cognitive load measurement with emotion interference , 2013, Comput. Methods Programs Biomed..

[69]  Ricardo Buettner,et al.  Cognitive Workload of Humans Using Artificial Intelligence Systems: Towards Objective Measurement Applying Eye-Tracking Technology , 2013, KI.

[70]  Naomi S. Altman,et al.  Points of significance: Nonparametric tests , 2014, Nature Methods.

[71]  Benjamin Naumann,et al.  Mental Representations A Dual Coding Approach , 2016 .

[72]  Alan Kennedy,et al.  Book Review: Eye Tracking: A Comprehensive Guide to Methods and Measures , 2016, Quarterly journal of experimental psychology.