서지주요정보
Investigating the effect of cognitive effort on procrastination and its mechanism = 인지적 노력이 미루기 행동에 미치는 영향과 그 메커니즘 연구
서명 / 저자 Investigating the effect of cognitive effort on procrastination and its mechanism = 인지적 노력이 미루기 행동에 미치는 영향과 그 메커니즘 연구 / Sunghwa Ryu.
발행사항 [대전 : 한국과학기술원, 2024].
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8043215

소장위치/청구기호

학술문화관(도서관)2층 학위논문

MBIS 24016

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This thesis studied the impact of cognitive effort on procrastination through the development of a novel mental arithmetic task. The task was explicitly designed to examine procrastination behavior in immediate situations that demand putting in varying cognitive effort. The findings revealed that higher levels of cognitive effort corresponded with increased procrastination behaviors. Conversely, when the cognitive effort required for the same trial level was reduced, the rate of procrastination also decreased. Additionally, the cognitive effort was modeled as an exponential function within a procrastination model, and its influence on the computational model of procrastination was analyzed.

이 논문에서는 인지적 노력이 미루기 행동에 미치는 영향을 탐구하였다. 이를 위해 인지적 노력이 필요한 온라인 미루기 행동 관찰 실험을 설계하고 실행하였으며, 참가자들은 다양한 수준의 인지적 노력을 요구하는 암산 과제를 수행하였다. 그 결과, 인지적 노력이 많이 들어가는 암산 문제일수록 참가자들이 해당 문제를 미루는 경향이 높아졌으며, 같은 난이도의 문제여도 요구되는 인지적 노력이 줄어들면 미루는 경향이 감소하였다. 또한, 미루기 행동 모델에서 인지적 노력을 중요한 변수로 모델링하여 그 특성을 정량적으로 분석하였다. 본 연구는 인지적 노력이 과제 수행과 관련된 행동에 미치는 영향을 이해하는 데 기여를 하였다.

서지기타정보

서지기타정보
청구기호 {MBIS 24016
형태사항 iv, 28 p. : 삽도 ; 30 cm
언어 영어
일반주기 저자명의 한글표기 : 류성화
지도교수의 영문표기 : Sang Wan Lee
지도교수의 한글표기 : 이상완
Including appendix
학위논문 학위논문(석사) - 한국과학기술원 : 바이오및뇌공학과,
서지주기 References : p. 25-26
주제 Procrastination
Cognitive effort
Behavior experiment
Online experiment
Procrastination model
미루기 행동
인지적 노력
행동 실험
온라인 실험
미루기 행동 모델
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이 주제의 인기대출도서

(a) Experimental components ofthe online behavioral experiment. The experiment 1 ceeded in the given order of the components. (b) A diagram of a session in the mental arithm task.

The process of a delayed trial with the intervention condition applied. The intervention condition guides the participant in solvingthe arithmetic problem in astep-by-step manner, thus reducing the cognitive effort of the trial. The reward and penalties are the same as the trials in the original condition.

Conditions and Examples of Trial Difficulties

Questions of Irrational Procrastination Scale

Questions of Pure Procrastination Scale

(a) An error bar plot with a regression line of reaction times across trial difficulties. (b) An error bar plot with a regression line ofprocrastination ratio across trial difficulties. (c) An error bar plot with a regression line of accuracy across trial difficulties.

(a) A boxplot comparing accuracy between two participant groups of different procrasti- nation ratios. (w = 94.0, p= 0.1139) (b) A boxplot comparing the total score between two participant groups ofdifferent procrastination ratios. (w = 38.0,p< 0.001) PR: Procrastination Ratio

A boxplot comparing reaction time between participants of high and low procrastination ratio. The p-values were computed with the Mann-Whitney U test. PR: Procrastination Ratio

(a) Aboxplotcomparing accuracy between two trial conditions ofdelayed trials. (w = 190.0 p <0.05) (b) Aboxplot comparing the procrastination ratio between two trial conditions ofdelayed trials (w = 73.0,p< 0.001)

A boxplot comparing procrastination ratios between trial conditions of delayed trials in groups of procrastination severity. (Low_PR: w = 29.0,p<0.01, High_PR: w = 26.0,p < 0.001, PR: Procrastination Ratio)

Sensitivity curves of the model probability depending on parameter b for different values of trial difficulty denoted as R.

The figure shows the correlation matrices from global sensitivity analysis of model pa- rameters for trial difficulties 1, 3, 6, and 10. The correlation coefficient of the parameter b and the procrastination probability of the model increases from 0.19, 0.46, 0.73, to 0.82, respectively.

The figures (a) to (e) show the results of correlation analysis between each fitted model parameter and procrastination ratio from the behavior experiment.

A bar graph for comparing three models in an ablation studyofparameter a and b. Model#1 fixed both parameters a and b. Model#2 fixed only parameter a. Model#3 fitted both parameters a and b. (p < 0.05)