{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T01:52:59Z","timestamp":1778291579176,"version":"3.51.4"},"reference-count":33,"publisher":"IGI Global","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,1,1]]},"abstract":"<p>Cognitive measures are directed to assess the load of working memory while performing different tasks. Excessive load on working memory hinders learning or performance of individuals. Lexile measure is the current tool used in assessing the difficulty levels of text reading in English language. Studies on correlating the cognitive load with EEG for classifying tasks based on Lexile measures have been performed for native English speakers. In this work, an attempt has been made to analyze the scope of Lexile measure for assessing the cognitive load of normal subjects. The protocol included reading and recall of texts with different Lexile complexities followed by resting phases. For increasing Lexile level complexities, a considerable increase in cognitive processing was noticed during task phase. Further, an increase in beta power was noticed at the central region indicating active information processing and decision making. Relative theta power (R?=0.11) was significant (p=0.022) in low Lexile level material and gradually decreased as the difficulty level of the tasks increased. Relative theta power was found to be decreasing as the complexity level of the text material increased and was found to dominate in both mid frontal and mid parietal regions during the recall phase. During test phase an increase in alpha power was observed at parietal region reflecting active information processing. This was evident from the highly significant (p=0.022), relative alpha power (Ra =0.036) for recall of high complexity Lexile material compared to medium (Ra=0.005) and low (Ra=0.005) level materials. Thus, it is seen that this study could be more effective in analyzing the cognitive load of subjects with different working memory efficiency. Also, while performing analysis on instructional material design based on cognitive load of different subjects, such procedures seem to be more significant.<\/p>","DOI":"10.4018\/ijcini.2014010102","type":"journal-article","created":{"date-parts":[[2014,9,10]],"date-time":"2014-09-10T14:12:55Z","timestamp":1410358375000},"page":"18-35","source":"Crossref","is-referenced-by-count":4,"title":["Analysis Of Cognitive Load For Bilingual Subjects"],"prefix":"10.4018","volume":"8","author":[{"given":"Pravin Kumar","family":"Subbaraj","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, SSN College of Engineering, Tamilnadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kavitha","family":"Anandan","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, SSN College of Engineering, Tamilnadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Geethanjali","family":"Balasubramanian","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, SSN College of Engineering, Tamilnadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mahesh","family":"Veezhinathan","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, SSN College of Engineering, Tamilnadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2432","reference":[{"key":"ijcini.2014010102-0","author":"F. 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