The Experts below are selected from a list of 4104 Experts worldwide ranked by ideXlab platform
Hsueh Hua Chuang - One of the best experts on this subject based on the ideXlab platform.
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Using Eye-Tracking Technology to Investigate the Impact of Different Types of Advance Organizers on Viewers’ Reading of Web-Based Content: A Pilot Study
Advances in Intelligent and Soft Computing, 2020Co-Authors: Chao-jung Chen, Hsueh Hua Chuang, Chi-jen HuangAbstract:This study utilized Eye-Tracking Technology to investigate how question and summary forms of advance organizers affected 9 college students’ information processing of web-based reading content. The results showed that students’ eyes fixated more on the question form than on the summary form organizer. However, viewers were found to spend more time reading the main reading content when summary form organizer was utilized. Trying to answer advance questions might have reinforced student memory of the to-be-learned content and further achieve effective retrieval of information from the web-based reading content. Further studies with large sample size and measures on achievement and cognitive load are needed to realize in-depth how the type of advance organizer affects viewers’ information processing.
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using eye tracking Technology to investigate the redundant effect of multimedia web pages on viewers cognitive processes
Computers in Human Behavior, 2011Co-Authors: Hsueh Hua ChuangAbstract:This study utilized Eye-Tracking Technology to determine the impact of redundant onscreen text information on viewers' cognitive processes with respect to multimedia information. Sixteen college students participated in the study and their eye-movement data and self-reported cognitive load ratings were collected as they viewed three web pages into which different forms of verbal explanations of thunderstorm systems were integrated. A repeated measure design was utilized to support the research purposes. The Eye-Tracking data showed that viewers relied on text information as the main information resource for determining meaning. Students' cognitive load reports reflected a redundant effect from the on screen text on their cognitive load level when both onscreen and narrative verbal messages were presented. However, eye-movement data revealed that viewers spent less time on the onscreen text when there was a narrative message presenting the same information. When the pictorial information was accompanied by both onscreen and narrative formats of verbal information, viewers seemed to be able to filter out redundant information. Additionally, replacing onscreen text with a voice-over seemed to globally orient viewers' eye fixations toward the illustration. Discussions on results and suggestions for future studies are provided in this paper.
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Using Eye-Tracking Technology to investigate the redundant effect of multimedia web pages on viewers' cognitive processes
Computers in Human Behavior, 2011Co-Authors: Han Chin Liu, Meng Lung Lai, Hsueh Hua ChuangAbstract:This study utilized Eye-Tracking Technology to determine the impact of redundant onscreen text information on viewers' cognitive processes with respect to multimedia information. Sixteen college students participated in the study and their eye-movement data and self-reported cognitive load ratings were collected as they viewed three web pages into which different forms of verbal explanations of thunderstorm systems were integrated. A repeated measure design was utilized to support the research purposes. The Eye-Tracking data showed that viewers relied on text information as the main information resource for determining meaning. Students' cognitive load reports reflected a redundant effect from the on screen text on their cognitive load level when both onscreen and narrative verbal messages were presented. However, eye-movement data revealed that viewers spent less time on the onscreen text when there was a narrative message presenting the same information. When the pictorial information was accompanied by both onscreen and narrative formats of verbal information, viewers seemed to be able to filter out redundant information. Additionally, replacing onscreen text with a voice-over seemed to globally orient viewers' eye fixations toward the illustration. Discussions on results and suggestions for future studies are provided in this paper. © 2011 Elsevier Ltd. All rights reserved.
Han Chin Liu - One of the best experts on this subject based on the ideXlab platform.
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Using Eye-Tracking Technology to investigate the redundant effect of multimedia web pages on viewers' cognitive processes
Computers in Human Behavior, 2011Co-Authors: Han Chin Liu, Meng Lung Lai, Hsueh Hua ChuangAbstract:This study utilized Eye-Tracking Technology to determine the impact of redundant onscreen text information on viewers' cognitive processes with respect to multimedia information. Sixteen college students participated in the study and their eye-movement data and self-reported cognitive load ratings were collected as they viewed three web pages into which different forms of verbal explanations of thunderstorm systems were integrated. A repeated measure design was utilized to support the research purposes. The Eye-Tracking data showed that viewers relied on text information as the main information resource for determining meaning. Students' cognitive load reports reflected a redundant effect from the on screen text on their cognitive load level when both onscreen and narrative verbal messages were presented. However, eye-movement data revealed that viewers spent less time on the onscreen text when there was a narrative message presenting the same information. When the pictorial information was accompanied by both onscreen and narrative formats of verbal information, viewers seemed to be able to filter out redundant information. Additionally, replacing onscreen text with a voice-over seemed to globally orient viewers' eye fixations toward the illustration. Discussions on results and suggestions for future studies are provided in this paper. © 2011 Elsevier Ltd. All rights reserved.
Ian Pitt - One of the best experts on this subject based on the ideXlab platform.
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Using eye tracking Technology to identify visual and verbal learners
2011 IEEE International Conference on Multimedia and Expo, 2011Co-Authors: Tracey J. Mehigan, Mary Barry, Aidan Kehoe, Ian PittAbstract:Learner style data is increasingly being incorporated into adaptive eLearning (electronic learning) systems for the development of personalized user models. This practice currently relies heavily on the prior completion of questionnaires by system users. Whilst potentially improving learning outcomes, the completion of questionnaires can be time consuming for users. Recent research indicates that it is possible to detect a user's preference on the Global / Sequential dimension of the FSLSM (Felder-Silverman Learner Style Model) through a user's mouse movement pattern, and other biometric Technology including eye tracking and accelerometer Technology. In this paper we discuss the potential of eye tracking Technology for inference of Visual / Verbal learners. The paper will discuss the results of a study conducted to detect individual user style data based on the Visual / Verbal dimension of the FSLSM.
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ICME - Using eye tracking Technology to identify visual and verbal learners
2011 IEEE International Conference on Multimedia and Expo, 2011Co-Authors: Tracey J. Mehigan, Mary Barry, Aidan Kehoe, Ian PittAbstract:Learner style data is increasingly being incorporated into adaptive eLearning (electronic learning) systems for the development of personalized user models. This practice currently relies heavily on the prior completion of questionnaires by system users. Whilst potentially improving learning outcomes, the completion of questionnaires can be time consuming for users. Recent research indicates that it is possible to detect a user's preference on the Global / Sequential dimension of the FSLSM (Felder-Silverman Learner Style Model) through a user's mouse movement pattern, and other biometric Technology including eye tracking and accelerometer Technology. In this paper we discuss the potential of eye tracking Technology for inference of Visual / Verbal learners. The paper will discuss the results of a study conducted to detect individual user style data based on the Visual / Verbal dimension of the FSLSM.
Meng Lung Lai - One of the best experts on this subject based on the ideXlab platform.
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Using Eye-Tracking Technology to investigate the redundant effect of multimedia web pages on viewers' cognitive processes
Computers in Human Behavior, 2011Co-Authors: Han Chin Liu, Meng Lung Lai, Hsueh Hua ChuangAbstract:This study utilized Eye-Tracking Technology to determine the impact of redundant onscreen text information on viewers' cognitive processes with respect to multimedia information. Sixteen college students participated in the study and their eye-movement data and self-reported cognitive load ratings were collected as they viewed three web pages into which different forms of verbal explanations of thunderstorm systems were integrated. A repeated measure design was utilized to support the research purposes. The Eye-Tracking data showed that viewers relied on text information as the main information resource for determining meaning. Students' cognitive load reports reflected a redundant effect from the on screen text on their cognitive load level when both onscreen and narrative verbal messages were presented. However, eye-movement data revealed that viewers spent less time on the onscreen text when there was a narrative message presenting the same information. When the pictorial information was accompanied by both onscreen and narrative formats of verbal information, viewers seemed to be able to filter out redundant information. Additionally, replacing onscreen text with a voice-over seemed to globally orient viewers' eye fixations toward the illustration. Discussions on results and suggestions for future studies are provided in this paper. © 2011 Elsevier Ltd. All rights reserved.
Tracey J. Mehigan - One of the best experts on this subject based on the ideXlab platform.
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Using eye tracking Technology to identify visual and verbal learners
2011 IEEE International Conference on Multimedia and Expo, 2011Co-Authors: Tracey J. Mehigan, Mary Barry, Aidan Kehoe, Ian PittAbstract:Learner style data is increasingly being incorporated into adaptive eLearning (electronic learning) systems for the development of personalized user models. This practice currently relies heavily on the prior completion of questionnaires by system users. Whilst potentially improving learning outcomes, the completion of questionnaires can be time consuming for users. Recent research indicates that it is possible to detect a user's preference on the Global / Sequential dimension of the FSLSM (Felder-Silverman Learner Style Model) through a user's mouse movement pattern, and other biometric Technology including eye tracking and accelerometer Technology. In this paper we discuss the potential of eye tracking Technology for inference of Visual / Verbal learners. The paper will discuss the results of a study conducted to detect individual user style data based on the Visual / Verbal dimension of the FSLSM.
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ICME - Using eye tracking Technology to identify visual and verbal learners
2011 IEEE International Conference on Multimedia and Expo, 2011Co-Authors: Tracey J. Mehigan, Mary Barry, Aidan Kehoe, Ian PittAbstract:Learner style data is increasingly being incorporated into adaptive eLearning (electronic learning) systems for the development of personalized user models. This practice currently relies heavily on the prior completion of questionnaires by system users. Whilst potentially improving learning outcomes, the completion of questionnaires can be time consuming for users. Recent research indicates that it is possible to detect a user's preference on the Global / Sequential dimension of the FSLSM (Felder-Silverman Learner Style Model) through a user's mouse movement pattern, and other biometric Technology including eye tracking and accelerometer Technology. In this paper we discuss the potential of eye tracking Technology for inference of Visual / Verbal learners. The paper will discuss the results of a study conducted to detect individual user style data based on the Visual / Verbal dimension of the FSLSM.
