@article { , title = {Measuring cognitive load and cognition: metrics for technology-enhanced learning}, abstract = {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.}, doi = {10.1080/13803611.2014.997140}, eissn = {1744-4187}, issn = {1380-3611}, issue = {7-8}, journal = {Educational research and evaluation}, pages = {592-621}, publicationstatus = {Published}, publisher = {Routledge}, url = {https://hull-repository.worktribe.com/output/444413}, volume = {20}, keyword = {Education and Pedagogy, Cognitive load, Working memory, Measurement, Multimedia, Technology, Learning, Learning analytics}, year = {2014}, author = {Martin, Stewart} }