Effects of kind and amount of cognitive load and duration on prospective time estimation

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2015
Bıyık Sarı, Fatma
The estimation of temporal intervals is influenced by characteristics of a secondary task carried out during those intervals. Different kinds of cognitive load (e.g., memory load, attentional demand) and different amounts of load (low, high) of the secondary tasks modulate time estimation. Increase in the amount of cognitive load decreases time estimation. According to the Attentional Gate Model this is because the more attention is allocated to the secondary task, the less attention is left for the primary task – time estimation. Furthermore, amount of load may interact with length of the estimated interval such that people underestimate longer durations more than shorter durations under conditions of high but not low load. This may be due to the non-linear nature of the time scale underlying subjective time estimation. The present study aims to explore the effects of different kinds of cognitive load (memory load, executive load) and different amounts of load (low load, high load) for various time durations (short, medium, long) by using the prospective paradigm. It is expected that time estimation varies according to kind of load, amount of load, and duration. Furthermore, it was predicted that time estimation ratios (between objective durations and subjective, reproduced durations) get smaller with longer durations for high memory and executive loads. Two experiments were carried out and three duration lengths (12, 24 and 36 sec) were used in those experiments. Simon Task was used as a secondary executive task in the first experiment. In the second experiment, Memory Search Task was executed as a secondary task. The effects of duration and different amount of load were found. However, time estimation ratios changed across duration and different amount of load depending on types of cognitive load.

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Citation Formats
F. Bıyık Sarı, “Effects of kind and amount of cognitive load and duration on prospective time estimation,” M.S. - Master of Science, Middle East Technical University, 2015.