Measuring cognitive load and cognition: metrics for technology-enhanced learning

被引:47
作者
Martin, Stewart [1 ]
机构
[1] Univ Hull, Fac Educ, Kingston Upon Hull, N Humberside, England
关键词
cognitive load; working memory; measurement; multimedia; technology; learning; learning analytics;
D O I
10.1080/13803611.2014.997140
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
This critical and reflective literature review examines international research published over the last decade to summarise the different kinds of measures that have been used to explore cognitive load and critiques the strengths and limitations of those focussed on the development of direct empirical approaches. Over the last 40 years, cognitive load theory has become established as one of the most successful and influential theoretical explanations of cognitive processing during learning. Despite this success, attempts to obtain direct objective measures of the theory's central theoretical construct - cognitive load - have proved elusive. This obstacle represents the most significant outstanding challenge for successfully embedding the theoretical and experimental work on cognitive load in empirical data from authentic learning situations. Progress to date on the theoretical and practical approaches to cognitive load are discussed along with the influences of individual differences on cognitive load in order to assess the prospects for the development and application of direct empirical measures of cognitive load especially in technology-rich contexts.
引用
收藏
页码:592 / 621
页数:30
相关论文
共 176 条
[1]   Dynamic Difficulty Using Brain Metrics of Workload [J].
Afergan, Daniel ;
Peck, Evan M. ;
Solovey, Erin T. ;
Jenkins, Andrew ;
Hincks, Samuel W. ;
Brown, Eli T. ;
Chang, Remco ;
Jacob, Robert J. K. .
32ND ANNUAL ACM CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI 2014), 2014, :3797-3806
[2]   A User Study of Visualization Effectiveness Using EEG and Cognitive Load [J].
Anderson, E. W. ;
Potter, K. C. ;
Matzen, L. E. ;
Shepherd, J. F. ;
Preston, G. A. ;
Silva, C. T. .
COMPUTER GRAPHICS FORUM, 2011, 30 (03) :791-800
[3]  
Anderson J. R, 1983, ARCHITECTURE COGNITI, DOI DOI 10.4324/9781315799438
[4]  
[Anonymous], 2013, P C HUMAN FACTORS CO, DOI [DOI 10.1145/2470654.2470723, 10. 1145/2470654. 2470723]
[5]   The influence of leads on cognitive load and learning in a hypertext environment [J].
Antonenko, Pavlo D. ;
Niederhauser, Dale S. .
COMPUTERS IN HUMAN BEHAVIOR, 2010, 26 (02) :140-150
[6]   THEORIES OF ACTION THAT INHIBIT INDIVIDUAL LEARNING [J].
ARGYRIS, C .
AMERICAN PSYCHOLOGIST, 1976, 31 (09) :638-654
[7]  
Ayaz H, 2012, AEROSP CONF PROC
[8]   Optical brain monitoring for operator training and mental workload assessment [J].
Ayaz, Hasan ;
Shewokis, Patricia A. ;
Bunce, Scott ;
Izzetoglu, Kurtulus ;
Willems, Ben ;
Onaral, Banu .
NEUROIMAGE, 2012, 59 (01) :36-47
[9]   Using subjective measures to detect variations of intrinsic cognitive load within problems [J].
Ayres, Paul .
LEARNING AND INSTRUCTION, 2006, 16 (05) :389-400
[10]   Cognitive Load Theory: New Directions and Challenges [J].
Ayres, Paul ;
Paas, Fred .
APPLIED COGNITIVE PSYCHOLOGY, 2012, 26 (06) :827-832