A pattern to predict the occurrence of moment of information overload during online information searching / Nur Amirah Mustapar
Scholars have identified that individuals are confronted with information overload during searching for the information in the virtual library. They sometimes do not realize they are overloaded until the symptoms appear and this will lead to many bad effects such as stress and decreased efficiency i...
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my.uitm.ir.891302024-04-17T01:13:50Z https://ir.uitm.edu.my/id/eprint/89130/ A pattern to predict the occurrence of moment of information overload during online information searching / Nur Amirah Mustapar Mustapar, Nur Amirah Electronic information resource searching Scholars have identified that individuals are confronted with information overload during searching for the information in the virtual library. They sometimes do not realize they are overloaded until the symptoms appear and this will lead to many bad effects such as stress and decreased efficiency in decision making. Moreover, previous literature claims that information overload also will lead to the changes in physiological signal of an individual which later result in decreased efficiency of information processing. Several scholars have analysed this phenomenon and investigated its causes, symptoms, effects and countermeasures of information overload but there are lacking empirical data to detect moment of information overload as moment can be represented as a point along the chronological continuum at which occur a certain effects. The purpose of having those empirical data is that it can eliminate the bad effects of information overload. Therefore, the primary purpose of this research is to detect the existence and the occurrence of moment of information overload among individuals during searching in virtual library, which focusing on the pattern reflected in the physiological data that can potentially be used as indicator of moment of information overload. In order to detect the pattern of moment of information overload, this study adopted user testing methods and adopted methods from psychophysiology for elucidating relations between the mind and the body. Collected empirical data were analysed using quantitative analysis and were presented using graphs and tables. Moment is detected as changes of reading of indicator. Study findings revealed that heart rate measurement is the best measure compared to other physiological measurement and the underlying pattern of moment of information overload is presented in a form of matrix. From the study findings, the recommendation of the future work was made which is the detected pattern can be used to design an application which monitor the information load among the individuals. 2017 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/89130/1/89130.pdf A pattern to predict the occurrence of moment of information overload during online information searching / Nur Amirah Mustapar. (2017) Masters thesis, thesis, Universiti Teknologi MARA (UiTM). |
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Scholars have identified that individuals are confronted with information overload during searching for the information in the virtual library. They sometimes do not realize they are overloaded until the symptoms appear and this will lead to many bad effects such as stress and decreased efficiency in decision making. Moreover, previous literature claims that information overload also will lead to the changes in physiological signal of an individual which later result in decreased efficiency of information processing. Several scholars have analysed this phenomenon and investigated its causes, symptoms, effects and countermeasures of information overload but there are lacking empirical data to detect moment of information overload as moment can be represented as a point along the chronological continuum at which occur a certain effects. The purpose of having those empirical data is that it can eliminate the bad effects of information overload. Therefore, the primary purpose of this research is to detect the existence and the occurrence of moment of information overload among individuals during searching in virtual library, which focusing on the pattern reflected in the physiological data that can potentially be used as indicator of moment of information overload. In order to detect the pattern of moment of information overload, this study adopted user testing methods and adopted methods from psychophysiology for elucidating relations between the mind and the body. Collected empirical data were analysed using quantitative analysis and were presented using graphs and tables. Moment is detected as changes of reading of indicator. Study findings revealed that heart rate measurement is the best measure compared to other physiological measurement and the underlying pattern of moment of information overload is presented in a form of matrix. From the study findings, the recommendation of the future work was made which is the detected pattern can be used to design an application which monitor the information load among the individuals. |
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Thesis |
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Mustapar, Nur Amirah |
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Mustapar, Nur Amirah |
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Mustapar, Nur Amirah |
title |
A pattern to predict the occurrence of moment of information overload during online information searching / Nur Amirah Mustapar |
title_short |
A pattern to predict the occurrence of moment of information overload during online information searching / Nur Amirah Mustapar |
title_full |
A pattern to predict the occurrence of moment of information overload during online information searching / Nur Amirah Mustapar |
title_fullStr |
A pattern to predict the occurrence of moment of information overload during online information searching / Nur Amirah Mustapar |
title_full_unstemmed |
A pattern to predict the occurrence of moment of information overload during online information searching / Nur Amirah Mustapar |
title_sort |
pattern to predict the occurrence of moment of information overload during online information searching / nur amirah mustapar |
publishDate |
2017 |
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https://ir.uitm.edu.my/id/eprint/89130/1/89130.pdf https://ir.uitm.edu.my/id/eprint/89130/ |
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1797924807438761984 |
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13.18916 |