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How Students Prompt ChatGPT for Creative Problem-Solving: Process Mining of Hybrid
Human-AI Regulation
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April 9th, 2025.
This is a preprint of an article.
Contents may change prior to publication.
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Human-AI Regulation
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How Students Prompt ChatGPT for Creative Problem-Solving: Process Mining of Hybrid
Human-AI Regulation
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Human-AI Regulation
Introduction
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Measures
Creative problem-solving performance. )%%%%,1 $-)(*%)($ 4-3)*,1.
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Procedure
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3)*1 ))#11.J- *1D%%11)-))()3)#/9;;;# $% 1'%1#/1% $ 1 4
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1%D%,)*-(1/ % 4()-1D 1. D)D%#% 4D3)*D 1.%,)/
13).17=?F(#%H=(1.)#4.-1 , -1%D(()D/1)#%1.D)D%1),,%%
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:
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L ./1 1 (= :;<H= )% %11 D 1. -$ )#% -),%%* 4 %1#/ % F% =4=
4(*P1:;:L1*1(=:;::H1.1.%.)(/3N#,'D%%11)=;L
(41.)())-% 1.%.)(/ 1) =@;L (41.1D)())-% 1.%.)(/ 1) =@;L / (1 $1)%1
1.%.)(/1)=;?=. / 4#(D%%11)=;L,)/ 1 )(/-/, %F).E%^H1)=?;L
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%1-%,)% / 4.)D)313)(()D%/3)(()D%= 4./-/,' / ,1%1.1
,)% %11('3)(()D%/$3)(()D%FR I1%1(=:;;>H=)D$. 4./-/,'
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7
b b H % 3#/*1( 1.)1 ,( %%#*-1 )3) %#,,%%3#( -)(* %)(#1 ) F%
#*3)/1(=@@:;@H=
Results
.%#(1%%,1 )3 %1 /1 3 %1. / $ /#(-)*-1%#%/ ,)$%1 )%D 1..1
FYH=J1 1$(#1%1.#%3#(%%)3,.-)*-1'J* 4 1%%%), 1 )D 1.)$((
,1 $-)(*%)($ 4-3)*,FY:H= (('-),%%* 4 %*-()'/1)J*
1./ 33,% )$((-)*-1 4 %114 %1D. 4./()D-3)* 4 / $ /#(%
FY7H=
Prompts: Useful, Not-So-Useful, and Counterproductive for Creative Problem-Solving
(,)1 %( %1)31. -)*-11'-%1.1-1 , -1%#%/1) %1#,1.1 1.
1%%)(#1 )=(('FH-1 , -1%-)*-1/.11)41D /%F-)*-1
%6HF:H1.'#%/.1% 3)*1 )%)#,F?H/F7H 1.1.'%/
.11)-)$ /3/,)1.'-)$ //3/,)1. /%41/F%>@H=
6
Table 1
Descriptive statistics and intercorrelations between prompts and creative problem-solving performance, qualitative description and
examples of individual prompts.
ID Variable Min Max M SD
Correlation
with CPS Description Example
)*-1,)#1 9 7=6; :=>> =6; #*)3-)*-1% ),)$%1 )= cd
R)/,)#1 7 :6 6;=?> 7<=>@ =7@ $((D)/,)#1)3-)*-1%#%/ )
,)$%1 )=
cd
List of prompts
Idea generation
F%/)1%
%1#,1 )H
; ;=<? ;=67 =;@ . 1 (-)*-1-.% 4 3)*1 )
3)*1% %1#,1 )=
Z/1),)*#-D 1.1. /%1) *-)$)/ '
-(#%. 11)'=\
: Idea generation
F%-, 3 ,(('3)
,1 $ 1'H
; ? ;=7@ ;=97 =79 -, 3 , %1#,1 )3) /41 )
1)41.D 1.%-, 3 ,$(#1 ), 1
F) 4 ( 1'/8)#%3#(%%H=
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,#//( 4,#1%%1,=1'1),)*#-D 1.%)*1. 41.1
11(D (()#1-3)*4)D 1.%)*1. 4# N#=\
7 Idea generation
F%/)-$ )#%
%DH
; 7 ;=9 ;=>> =9 1 , -1%%(,1/) /3)*-$ )#%
%D%/%/.11)41*)
/%%/)1. %(,1 )=
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6 )$ / 4// 1 )(
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/I#%1*1%%.)#(/%#,.1.1 1D)#(/%1 ((* #'=\
? 3)*1 )41. 4 ; ? ;=6@ =; =:? e % 4.1% 3)*1 )%)#,
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> FeedbackF4(H ; > ;=6; ;=@9 =: /,D 1.)#1'%-, 3 ,/1 (%= Z/)E1( 1=\
< FeedbackF *-)$
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⟳
Note. -%1%1.* *($(#)1 /' / $ /#(-1 , -1=J-%1%1.*J *($(#)1 /' / $ /#(-1 , -1=M-%1%1.*$(#
)1 /' / $ /#(-1 , -1%=%)]%r,)33 , 1 %-)1/3)%%), 1 )1D-)*-1,)#1/D)/,)#1/L-*]%.) %-)1/3)%%), 1 )1D
/ $ /#(-)*-1%/=-%1%*,1 $-)(*%)($ 4-3)*,3),.-1 , -1=
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1.-)*-11'-%= %11.*)%13 , (-)*-13)41 4 /%D%-)$ / 41%
%1#,1 )%1)41.D 1.$(#1 ) , 1 F:L r% M =79 p `=;;H=%%.)D (
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1. ,)$%1 )%=
Differences between High- and Low-Performing Individuals
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,)$%1 )%D 1..1tF<?HM7=?>p`=;;dM;=9:,)*-/1)1. ()D-3)* 4
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( ('1)*-()' /41 )%-, 3 ,((' * 43),1 $)#1,)*%F:Ha:F<<HM:;=@@
p `=;;V M=?:-)$ / 4// 1 )(,)1J1F6Ha:F<<HM:;=@@ p `=;; V M=?:/
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-3)* 44)#-#%/.1*))31% 3)*1 )%)#,F?Ha:F<<HM?=<p M
=;:7V M=:>=
Table 2
Comparison of prompts used in high- and low-performing groups.
ID Variable Low CPS (N = 45) High CPS (N = 32) Comparison
M (SD) M (SD) ).E%d
)*-1,)#1 :=?>F=@H 6=?@F7=H ;=9:
R)/,)#1 :9=?>F:?=6H ?<=66F6?=>6H ;=9:
,,#,FUH ,,#,FUH *E%V
Idea generationF%/)1% %1#,1 )H <=U 9=7U =:
: Idea generationF%-, 3 ,(('3),1 $ 1'H >=<U ?7=U =?:
7 Idea generationF%/)-$ )#%%DH 6=6U :=?U =?
6 )$ / 4// 1 )(,)1J1 >=<U ?7=U =?:
? 3)*1 )41. 4 7?=>U :=?U =:> e
> FeedbackF4(H <=9U 7=7U =>
< FeedbackF *-)$,1 $ 1'H 6=6U 6;=>U =6?
9 % 43)feedback <=9U :=@U =;?
@ 41 ?=>U 9=9U =;6
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Figure 1
Visualization of the creative problem-solving process of a) high- and b) low-performing
individuals.
9
Note. . / ,1('3)(()D% 4-.% $ %#(('-%1 1. %N#1 (3()D)3 -)*-1% D 1.
-),%%%.)D 41.J,1#*)3 %1,% ,.,1 $ 1'/ ,1('3)(()D 4)1.%/
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pM=;;6=
Table 3
Fitness of process models in low- and high-performing groups of participants.
@
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),%%*)/(F 4.H 69U <:U
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Discussion
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