© 2023 The Au ho (s) Dis ibu ed as a Hog e e OpenMind a icle Zei sch i ü Pädagogische Psychologie (2024), 38 (1–2), 3–13
unde he license CC BY 4.0 (h ps://c ea i ecommons.o g/licenses/by/4.0) h ps://doi.o g/10.1024/1010-0652/a000364
O iginal A icle
Ca ego iza ion o simula ed
diagnos ic si ua ions and he salience
o diagnos ic in o ma ion
Concep ual amewo k
Nils Mach s1 , Olga Che niko a2, Tho ben Jansen3 , Ma c Weidenbusch4 , F ank Fische 2,
and Jens Mölle 1
1
Ins i u e o Psychology o Lea ning and Ins uc ion (IPL), Kiel Uni e si y, Ge many
2
Chai o Educa ion and Educa ional Psychology, Uni e si y o Munich (LMU), Ge many
3
Leibniz Ins i u e o Science and Ma hema ics Educa ion (IPN), Kiel Uni e si y, Ge many
4
Uni e si y Hospi al, Uni e si y o Munich (LMU), Ge many
Abs ac : Simula ed diagnos ic si ua ions unc ion as lea ning en i onmen s and esea ch ools o deepen he unde s anding o diagnos ic
p ocesses. In his concep ual pape , we p esen a amewo k ha ul ils wo pu poses. Fi s , we ca ego ize simula ions o diagnos ic si ua ions
using six desc ip i e componen s: physical en i onmen , social embeddedness, diagnos ic asks, ac i i ies, in o ma ion, and decisions. Second,
we disc imina e he salience o diagnos ic in o ma ion in o ou ace s: access, p ominence, simplici y, and cla i y. These ace s de e mine he
likelihood ha pa icipan s in a simula ion will pe cei e and p ocess ele an diagnos ic in o ma ion owa d co ec o accu a e diagnos ic de-
cisions. We use one simula ion o explain hese componen s and ace s in mo e de ail. Wi h his sys ema ic concep ualiza ion, we in end o
deepen he unde s anding o how and why simula ions wo k in c ea ing au hen ic diagnos ic si ua ions, measu ing diagnos ic compe encies,
and p o iding lea ning en i onmen s o he acili a ion o hese compe encies in highe educa ion.
Keywo ds: diagnos ic compe encies, simula ions, lea ning en i onmen s
Ka ego isie ung on Simula ionen diagnos ische Si ua ionen und die Bedeu ung diagnos ische In o ma ionen: Konzep ionelle Rahmen
Zusammen assung: Simula ionen diagnos ische Si ua ionen dienen sowohl als Le numgebung als auch als Fo schungsins umen e zu Ve -
ie ung des Ve s ändnisses on diagnos ischen P ozessen. In diesem konzep ionellen Papie s ellen wi einen Rahmen o , de zwei Zwecke
e üll . E s ens ka ego isie en wi Simula ionen diagnos ische Si ua ionen anhand on sechs desk ip i en Komponen en: physische Umge-
bung, soziale Einbe ung, diagnos ische Au gaben, Ak i i ä en, In o ma ionen und En scheidungen. Zwei ens un e scheiden wi die Salienz de
diagnos ischen In o ma ionen in ie Face en: Zugänglichkei , Au älligkei , Ein achhei und Kla hei . Diese Face en bes immen die Wah -
scheinlichkei , dass die Teilnehme _innen an eine Simula ion ele an e diagnos ische In o ma ionen wah nehmen und e a bei en, um ko -
ek e ode genaue diagnos ische En scheidungen e en zu können. Wi e wenden eine Beispielsimula ion, um die Komponen en und Face -
en nähe zu e läu e n. Mi diese sys ema ischen Konzep ualisie ung wollen wi das Ve s ändnis da ü e ie en, wie und wa um Simula ionen
bei de Scha ung au hen ische diagnos ische Si ua ionen, de Messung diagnos ische Kompe enzen und de Be ei s ellung on Le numge-
bungen ü die Fö de ung diese Kompe enzen in de Hochschulbildung unk ionie en.
Schlüsselwö e : Diagnos ische Kompe enzen, Simula ionen, Le numgebungen
In oduc ion
Making p o essional decisions based on knowledge o o h-
e people's cha ac e is ics is a c ucial ac i i y in many
p o essional domains, such as diagnosing pa ien s in medi-
cine, de e mining clien s' needs in counseling, o iden i y-
ing lea ne s' misconcep ions in eaching. These ac i i ies
equi e a ange o skills ela ed o collec ing, e alua ing,
and u ilizing diagnos ic in o ma ion. T aining people in
hese skills is one o he essen ial asks o highe educa ion
(e. g., Che niko a, Hei zmann, Fink, e al., 2020). One
me hod o acili a ing hei u he de elopmen is he im-
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4 N. Mach s e al., Ca ego iza ion o simula ed diagnos ic si ua ions
Zei sch i ü Pädagogische Psychologie (2024), 38 (1–2), 3–13 © 2023 The Au ho (s) Dis ibu ed as a Hog e e OpenMind a icle
unde he license CC BY 4.0 (h ps://c ea i ecommons.o g/licenses/by/4.0)
plemen a ion o simula ion-based lea ning (e. g., Cook,
2014; Che niko a, Hei zmann, S adle , e al., 2020; Ga -
meie e al., 2015). Simula ed diagnos ic si ua ions a e
equen ly used o in es iga e diagnos ic p ocesses in di -
e en domains (Cod eanu e al., 2020; Kaise e al., 2013;
Südkamp e al., 2008) and o e alua e he e ec i eness o
lea ning and eaching s a egies (e. g., Che niko a, Hei z-
mann, S adle , e al., 2020). Howe e , he e is no ame-
wo k ha allows o c oss-domain compa isons o simula-
ion ea u es, he gene alizabili y o he ob ained esul s,
and he ans e o good p ac ices be ween domains.
The e o e, we aim o de elop such a amewo k.
In doing so, we ely on (1) he simila i ies in scien i ic
easoning and a gumen a ion ha unde lie he diagnos ic
p ocesses in medical and eache educa ion (see Fische
e al., 2014) and (2) he e ec s o p oblem-sol ing on he
de elopmen o diagnos ic compe ences ac oss domains
(Che niko a, Hei zmann, Fink, e al., 2020). In spi e o all
he possible di e ences be ween he con ex s o eal-li e
diagnos ic si ua ions, simula ed diagnos ic si ua ions
sha e se e al ea u es ac oss domains. A co e ea u e ha
makes simula ions e ec i e ools o esea ch and educa-
ion is ha hey o e a high le el o design con ol in e ms
o he asks gi en o pa icipan s, he a ailable diagnos ic
ac i i ies, and he diagnos ic in o ma ion ha pa icipan s
ecei e. This con ol allows o esea ching and acili a ing
diagnos ic compe encies in pa icula diagnos ic si ua-
ions, such as si ua ions wi h a lo o unce ain y, a ely
occu ing si ua ions, o si ua ions ocusing on indi idual
diagnos ic ac i i ies. Howe e , gains in he in e nal alidi-
y o such con olled condi ions can also inc ease hei
a i iciali y, posing a h ea o aspec s o ex e nal alidi y
(e. g., pe cei ed u ili y alue and au hen ici y) ha play
a signi ican ole in he e ec i eness o simula ions
(Che niko a e al., 2024). This makes i a delica e bu c u-
cial ask o he designe s o simula ions o ind a balance
be ween expe imen al con ol and he au hen ic ep esen-
a ion o ac ual si ua ions.
S udies ha u ilize simula ed diagnos ic si ua ions em-
ploy di e en measu es o diagnos ic compe encies, such
as judgmen accu acy (e. g., Kaise e al., 2017), o he sco -
ing me hods o diagnos ic success (e. g., Klug e al., 2013;
K on e al., 2021), and epo a ious measu es o he
aining e ec s (Che niko a, Hei zmann, S adle , e al.,
2020). A close look a speci ic applica ions o simula ions
also e eals di e ences in how designe s ealize con ol
o e elemen s o he simula ion. Fo example, he au ho s
may decide o elie e pa icipan s om a diagnos ic ac i -
i y, such as he e alua ion o diagnos ic in o ma ion, by
labeling ele an pieces o in o ma ion, hus making i
easie o a i e a co ec diagnos ic decisions. Al e na i e-
ly, hey migh o e load pa icipan s wi h dis ac ing i el-
e an in o ma ion, equi ing pa icipan s o ac i ely selec
ele an in o ma ion. Ul ima ely, simula ions can be
adap ed o a ious pu poses, bu simila e ec sizes can
yield di e en meanings depending on he simula ion de-
sign.
Exis ing concep ual amewo ks desc ibe he na u e o
diagnos ic ac i i ies, indi idual p e equisi es, ins uc ion,
and con ex (Che niko a e al., 2022; Hei zmann e al.,
2019; Loibl e al., 2020); howe e , hey do no p o ide a
sys ema ic b eakdown o di e ences be ween how a ious
diagnos ic si ua ions a e applied o simula ions, especially
in e ms o he p esen a ion o diagnos ic in o ma ion and
he ways o p ocessing hem. Consequen ly, we hope o
es ablish a concep ual amewo k o accoun o hese di -
e ences so ha we can sys ema ically ca ego ize simula -
ed diagnos ic si ua ions, explain a iances in hei esul s,
and ul ima ely p o ide a common language o he design
p inciples o simula ed diagnos ic si ua ions used o meas-
u e and acili a e diagnos ic compe encies.
Ou app oach en ails wo s eps. Fi s , we es ablish an
ou e amewo k o he s uc u al componen s o simula -
ed diagnos ic si ua ions. Exis ing modeling app oaches
p o ide insigh s in o he s uc u al elemen s o diagnos ic
si ua ions in eal-li e con ex s (Fiske & Neube g, 1990;
Ka s e al., 2017; Loibl e al., 2020). Ou amewo k builds
on hese exis ing concep s; howe e , is clea ly o ien ed o-
wa d wha Loibl e al. (2020) call he ex e nal aspec s o
he diagnos ic si ua ion, as hese aspec s a e modi iable
h ough simula ion design p inciples. Second, we es ablish
a ocus on diagnos ic in o ma ion, elabo a ing on why i
ep esen s he co e componen o a diagnos ic si ua ion as
he basis o each diagnos ic decision. In doing so, we u i-
lize he psychological e m salience – he p ope y o s imu-
li o s and ou and be likely o d aw a pe cei e s' selec i e
a en ion (Higgins, 1996) – o classi y he p esen a ion o
ele an diagnos ic in o ma ion in a simula ion. Gene ally,
ou app oach implies ha a highe salience o ele an in-
o ma ion inc eases he likelihood o pa icipan s making
co ec o accu a e diagnos ic decisions (Che niko a e al.,
2024). Then, wi h ou concep es ablished, we p esen an
example o how he amewo k can be applied o he e-
sea ch design o an exis ing simula ed diagnos ic si ua-
ion. Finally, we discuss ou concep using a esea ch agen-
da ou line deduced om i s applica ion possibili ies,
including he in e play be ween con ol o e he salience
o in o ma ion and he pe cei ed au hen ici y o a simula-
ion.
Simula ed diagnos ic si ua ions
Fo his amewo k, we de ine diagnos ic si ua ions om a
minimalis pe spec i e. In o he wo ds, we aim o iden i y
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N. Mach s e al., Ca ego iza ion o simula ed diagnos ic si ua ions 5
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he necessa y and su icien componen s o diagnos ic
si ua ions ac oss domains, as well as he addi ional com-
ponen s ha con ibu e o he a iabili y o such si ua-
ions. We also build ou amewo k on he p emise o be-
ing able o ec ea e a diagnos ic si ua ion accu a ely in a
simula ion. Acco dingly, in e e ence o he ecen ly in o-
duced DiaCoM model o diagnos ic si ua ions (Loibl e al.,
2020), indi idual diagnos icians' cha ac e is ics a e o
second na u e o he p oposed gene al s uc u e o a diag-
nos ic si ua ion. O he wise, ou app oach sha es s uc u al
simila i ies, whe eby we shi he ocus owa d inding
amilies o echnical componen s ha simula ion design-
e s exe cise con ol o e .
We p opose ha he gene al s uc u e o diagnos ic si u-
a ions mus necessa ily include – in he b oades sense –
diagnos icians who (a) iden i y diagnos ic in o ma ion on
diagnos ic a ge s and (b) apply his in o ma ion o ensu-
ing diagnos ic decisions. In addi ion o hese necessa y el-
emen s, mos diagnos ic si ua ions include objec i es o
pe o ming diagnos ics and a diagnos ic p ocess ha in-
cludes a ious diagnos ic ac i i ies o accomplish hese
objec i es. Finally, diagnos ic si ua ions un old unde spe-
ci ic physical condi ions and a e embedded in some o m
o social in e ac ion o social ele ance.
In simula ions o diagnos ic si ua ions, designe s c ea e
ep esen a ions o such si ua ions using a ying se s o
ools and deg ees o p oximi y o examples om eal li e
(G ossmann e al., 2009). Two impo an esea ch ields
o simula ed diagnos ic si ua ions in highe educa ion
a emedicine and educa ion, which – despi e ob ious dis-
pa i ies – sha e he gene al s uc u e o diagnos ic si ua-
ions (Hei zmann e al., 2019). A main di e ence among
simula ion designs conce ns whe he pa icipan s in e ac
wi h simula ed pe sons and de i e in o ma ion a leas
pa ly om his in e ac ion, o whe he hey acqui e ac-
cess h ough documen ed in o ma ion (Hei zmann e al.,
2019). Bo h he medical and educa ional ields o e ep e-
sen a ions o hese wo gene al design app oaches. Fo ex-
ample, in he educa ional ield, Kaise e al. (2017) used
simula ed s uden s in a simula ed class oom. Pa icipan s
in he ole o a eache applied a ques ion-answe schema
as a o m o simpli ied ins uc ion o ga he ing in o ma-
ion on hei s uden s' lesson pe o mance by in e ac ing
wi h hem. In he medical ield, Liaw and Huang (2013)
used a pa ien simula o ha p esen ed espi a o y and
ca dio ascula dis ess symp oms, and pa icipan s pe -
o med acu e ca e managemen based on hei in e ac-
ions wi h he pa ien simula o . Al e na i ely, in ano he
example om he educa ional ield, Jansen e al.'s (2021)
pa icipan s had access o mul iple s uden ex s and had
o make a ious judgmen s on he quali y o hese ex s by
p ocessing he documen ed in o ma ion a di e en ana-
ly ical le els. In a simila example om he medical ield,
Chambe land e al. (2015) p esen ed pa icipan s wi h
clinical cases o jaundice ha included he pa ien 's chie
complain ; backg ound in o ma ion; and indings om his-
o y- aking, a physical examina ion, and labo a o y es s.
The pa icipan s hen had o p ocess he documen s o
make diagnos ic decisions abou he unde lying diseases.
In bo h basic simula ion design p inciples, he close
ela ionship be ween con en and lea ning scena ios in
highe educa ion ins i u ions and eal-wo ld p o essional
si ua ions helps suppo u u e p o essionals in acqui ing
p ac ice-o ien ed p o essional knowledge, skills, and com-
pe ences (Blömeke e al., 2015). Al hough sys ema ic e-
sea ch has e ealed he la ge posi i e e ec s o simula ion-
based lea ning in di e en domains o highe educa ion
(Cook e al., 2013; Theelen e al., 2019), analyses ha e also
e ealed la ge he e ogenei y in he e ec s, indica ing ha
simula ion-based lea ning en i onmen s and he included
ins uc ional suppo measu es di e in hei e ec i eness
(Che niko a, Hei zmann, S adle , e al., 2020). A emp s
o explo e di e en ea u es o simula ion-based en i on-
men s – such as he use o echnology, ins uc ional sup-
po , and lea ne s' p e equisi es (Che niko a, Hei zmann,
S adle , e al., 2020) – s ill lea e much o his a iance un-
explained.
I is impo an o conside he ex en o which simula-
ions ep esen ac ual p ac ice in e ms o he lea ne 's de-
mands, he na u e o he simula ed si ua ion and he en i-
onmen , and he pa icipan s in ol ed (Allen e al., 1991).
Hams a e al. (2014) also emphasized he impo ance o
dis inguishing be ween he physical esemblance and
unc ional co espondence o a ask o scena io. Howe e ,
simula ed en i onmen s also o e he oppo uni y o se-
lec and modi y ep esen a ions o eali y (G ossman e al.,
2009). As such, simula ions allow o ocusing on speci ic
aspec s o ac ual asks and p ocesses, hus enabling he
in es iga ion o speci ic e ec s unde expe imen al con-
ol and he inclusion o a ge ed aining in e en ions.
Es ablishing a clea concep ualiza ion o such modi ica-
ions should hus allow o he pinpoin ing o he wo king
mechanisms o simula ions and he iden i ica ion o which
modi ica ions a e necessa y and which may h ea en a
simula ion's pe cei ed u ili y alue and au hen ici y.
In wha ollows, we expand on Loibl e al.'s (2020) and
Hei zmann e al.'s (2019) amewo ks and p opose he sys-
ema ic ca ego iza ion o simula ed diagnos ic si ua ions
ac oss six componen s, emphasizing he componen o di-
agnos ic in o ma ion. We u he es ablish a concep o
salience o diagnos ic in o ma ion and ca ego ize ou ac-
e s. This concep ualiza ion e eals ha di e en simula-
ions p o ide di e en oppo uni ies o in es iga e and
acili a e he alidi y o diagnos ic decisions in e ms o
pa icipan s gaining access o ele an in o ma ion, ocus-
ing on ele an in o ma ion, managing complex decision
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6 N. Mach s e al., Ca ego iza ion o simula ed diagnos ic si ua ions
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s uc u es, and dealing wi h ambiguous in o ma ion. Wi h
ou example, we show ha ou p oposed componen s can
be smoo hly applied o diagnos ic si ua ions and ha he
p esen ed diagnos ic in o ma ion can be classi ied com-
p ehensi ely using he ace s o salience.
Wi h his concep ual amewo k, we lay he g oundwo k
o a be e heo e ical unde s anding o he he e ogenei y
o he e ec s o di e en ly simula ed diagnos ic si ua ions
(see Che niko a, Hei zmann, S adle , e al., 2020). The
amewo k can also se e as a common e e ence and lan-
guage o desc ibe simula ed diagnos ic si ua ions and,
hus, sys ema ize esea ch. A be e unde s anding o and
mo e sys ema ic esea ch on simula ions can ul ima ely
help de i e design p inciples o simula ions o di e en
p o essional diagnos ic si ua ions and o pa icipan s wi h
di e en p e equisi es.
Concep ual amewo k
Componen s o simula ed diagnos ic
si ua ions
Al hough simula ed diagnos ic si ua ions ha e undamen-
al di e ences in e ms o hei basic design p inciples,
hey also ha e clea pa allels ac oss di e en domains and
applica ions (Che niko a, Hei zmann, Fink, e al., 2020).
In his chap e , we ou line six componen s ha enable he
sys ema ic desc ip ion and di e en ia ion o simula ed di-
agnos ic si ua ions (see Figu e1). Beyond he ca ego iza-
1 Fo example, in a co e diagnos ic si ua ion, a eache may ecei e a s uden answe and he simula ion may ask o an es ima ion ega ding
whe he he s uden unde s ood he opic. Nei he he diagnos ic ask no ac i i y a e equi ed o his co e si ua ion.
ion o di e en simula ions, hese componen s should
also p o ide a clea isualiza ion o whe e in a simula ion
designe s ha e he oppo uni y o c ea e a ia ions and
implemen in e en ions o in es iga e and inc ease lea n-
ing gains in measu es o diagnos ic success h ough he
ins uc ional applica ion o such simula ions. I is impo -
an o no e ha by ocusing on he design choices in simu-
la ions, we exclude indi idual pa icipan s' cha ac e is ics
and s a es om he componen s o he simula ed diagnos-
ic si ua ion. This leads o a clea dis inc ion be ween his
amewo k o diagnos ic si ua ions and he DiaCoM mod-
el (Loibl e al., 2020).
The gene al idea is as ollows: A simula ion o a diagnos-
ic si ua ion has a physical en i onmen and is socially em-
bedded bo h wi hin and ou side i sel . The inne pa ep-
esen s he ac ual simula ion and mus always include he
co e componen s o diagnos ic si ua ions: diagnos ic in-
o ma ion and diagnos ic decisions.1 Addi ionally, i usu-
ally includes diagnos ic asks and ac i i ies. The logical
p ocess o a simula ion en ails se ing he ask, s a ing he
ac i i ies, ending wi h a pool o in o ma ion, and conclud-
ing wi h a diagnos ic decision. Ne e heless, i is easy o
imagine a diagnos ic p ocess ha includes e ined asks a
la e s ages o he simula ion and p elimina y diagnos ic
decisions in he cou se o diagnos ic ac i i ies. Conse-
quen ly, he ou componen s wi hin he simula ion o e -
lap while main aining hei logical o de .
In he ollowing sec ions, we desc ibe he six compo-
nen s in mo e de ail o es ablish he ou e amewo k o
ou ocal concep o he salience o he p esen ed diagnos-
ic in o ma ion.
Social Embeddedness
Physical En i onmen
Diagnos ic
Tasks
Simula ion Timeline
Diagnos ic
In o ma ion
•Access
•P ominence
•Simplici y
•Cla i y
Diagnos ic
Ac i i ies
Diagnos ic
Decisions
Co e Componen s
Figu e 1. Componen s o simula ions o diagnos ic si ua ions
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N. Mach s e al., Ca ego iza ion o simula ed diagnos ic si ua ions 7
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Physical en i onmen
The physical en i onmen o simula ions conce ns he
physical and echnical condi ions wi hin he simula ion i -
sel and he ex e nal se up o he simula ion. I in ol es
he design app oach (e. g., documen analysis o in e ac-
ion wi h simula ed pe sons o g oups), he simula ion o -
ma (e. g., compu e simula ion, ole-play, o ideo i-
gne es), and he ex e nal applica ion o he simula ion
(e. g., in a class oom o labo a o y se ing). In summa y, i
e e s o how in o ma ion is p esen ed o he pa icipan s
and how hey a e enabled o in e ac wi h pa s o he sim-
ula ion.
Social embeddedness
The social embeddedness o simula ions conce ns he so-
cial, emo ional, and mo i a ional condi ions bo h wi hin
he simula ion i sel and wi hin i s ex e nal se up. I in-
ol es ele an pe sons (e. g., employe s, ins uc o s, s u-
den s, o collabo a i e pa ne s), a ewa d s uc u e (e. g.,
pa icipa ion allowances o gami ica ion elemen s), eed-
back mechanisms (e. g., eedback abou co ec diagnoses
a e comple ion o he assigned asks), o pe sonal ele-
ance (e. g., pa icipa ing in he simula ion o acqui e a
ce i ica e) and e e s o why and wi h whom one should
pa icipa e. I is impo an o s ess ha he echnical com-
ponen o social embeddedness conce ns he condi ions
ou lined in he design and applica ion o he simula ion.
Ac ual measu es o emo ional and mo i a ional s a es a e
dependen a iables o hese condi ions. Howe e , such
measu es can alida e wha he simula ion design wan s o
achie e.
Diagnos ic asks
Diagnos ic asks conce n he ins uc ion pa icipan s e-
cei e in he ini ial o ansi ional phases o a simula ion.
These asks can include he ini ial in o ma ion om which
diagnos ic decisions ollow and he p omp ing o ecom-
menda ion o ele an diagnos ic ac i i ies. Diagnos ic
asks mus ini ia e diagnos ic ac i i ies; hus, we do no
conside he di ec eques o make diagnos ic decisions
a e acqui ing diagnos ic in o ma ion o be a diagnos ic
ask. Ob iously, diagnos ic asks p esen an excellen op-
po uni y o in e en ional expe imen al-con olled de-
signs in simula ions by gi ing g oups o pa icipan s di e -
en ins uc ions conce ning hei ac i i ies du ing he
simula ion (e. g., ins uc ions may ad ise an expe imen al
g oup o sys ema ically collec in o ma ion on mul iple
a ge cha ac e is ics, whe eas a con ol g oup may ecei e
no such ins uc ion).
Diagnos ic ac i i ies
Diagnos ic ac i i ies a e wha he pa icipan s do du ing
he simula ion and include bo h ac ions as well as cogni-
i e p ocesses. In acco dance wi h ou minimalis ic de ini-
ion o diagnos ic si ua ions, diagnos ic ac i i ies mus
en ail iden i ying diagnos ic in o ma ion o suppo subse-
quen diagnos ic decisions. In addi ion, many simula ions
equi e pa icipan s o gene a e diagnos ic in o ma ion
h ough a ious a ailable ac ions. Fu he diagnos ic ac-
i i ies can include es ablishing diagnos ic objec i es o
u u e ac ions, gene a ing hypo heses ha may in luence
u he engagemen wi h diagnos ic asks, and e alua ing
collec ed diagnos ic in o ma ion. Simula ions can exe cise
con ol o e a ange o hese cogni i e ac i i ies (e. g., by
modi ying he p esen ed in o ma ion, o by p omp ing
speci ic ac i i ies). Simula ions can also explica e o he -
wise unobse able cogni i e ac i i ies (e. g., by allowing o
equi ing pa icipan s o documen hei ac i i ies o hei
acqui ed diagnos ic in o ma ion), hus making hese
ac i i ies a ailable as dependen a iables. Conside ing
ha we excluded pa icipan s' emo ional and psychologi-
cal s a es as a componen o he amewo k bu included
diagnos ic ac i i ies, we may appea o be walking a hin
line, as bo h a e o some ex en dependen a iables. How-
e e , he ange o possible ac ions associa ed wi h diag-
nos ic ac i i ies is na u ally cons ained by he design o
each simula ion; his makes hese ac i i ies a genuine am-
ily o con olled elemen s despi e he possibili y ha ac u-
ally pe o med diagnos ic ac i i ies could be es ablished
as mode a o s and media o s o measu es o diagnos ic
success.
Diagnos ic in o ma ion
Diagnos ic in o ma ion conce ns s imuli ha a e pe cei -
able by he pa icipan s du ing he simula ion and ha
pe ain in any way o a diagnos ic a ge (e. g., a s uden 's
answe on a es o a pa ien 's e bal desc ip ion o a symp-
om). Diagnos ic in o ma ion is also an essen ial compo-
nen o diagnos ic si ua ions, as i cons i u es he ounda-
ion o he ensuing diagnos ic decisions. Thus, i is he
ocal poin o his amewo k, and he di e en ace s o i s
salience a e u he elabo a ed upon in he sec ion a e
he nex . Na u ally, complex s imuli o en con ain smalle
pieces o in o ma ion, which simula ion designe s can
modi y sepa a ely (e. g., ea u es o long s uden essays o
eco ded con e sa ions). To p o ide a comp ehensi e de i-
ni ion o in o ma ion p esen ed in a simula ion, we di e -
en ia e be ween diagnos ically ele an and i ele an in-
o ma ion: ele an pieces o in o ma ion suppo accu a e
diagnos ic decisions o in e es in some way, while i ele-
an in o ma ion does no . Especially when a simula ion
equi es mul iple diagnos ic decisions pe a ge , pieces o
in o ma ion can be ele an o one decision and i ele an
o ano he . We limi his amewo k o he concep ualiza-
ion o ele an in o ma ion; howe e , i should also be
ex endable o i ele an in o ma ion, en ailing a mo e
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8 N. Mach s e al., Ca ego iza ion o simula ed diagnos ic si ua ions
Zei sch i ü Pädagogische Psychologie (2024), 38 (1–2), 3–13 © 2023 The Au ho (s) Dis ibu ed as a Hog e e OpenMind a icle
unde he license CC BY 4.0 (h ps://c ea i ecommons.o g/licenses/by/4.0)
complex in es iga ion o he in e play o ele an and i -
ele an in o ma ion ha exceeds he scope o his pape .
Diagnos ic decisions
Diagnos ic decisions conce n he pa icipan s' indi idual
diagnos ic p oduc s. They can include diagnoses (e. g.,
naming a medical illness o deciding on a s uden miscon-
cep ion), judgmen s (e. g., es ima ing a s uden 's compe-
ence), p edic ions (e. g., p edic ing he cou se o an illness
o es ima ing u u e pe o mance), and ollow-up ac ions
(e. g., choosing a he apy o p o iding s uden counseling).
Following ou de ini ion, a diagnos ic si ua ion mus al-
ways include a leas one explici decision om ei he ca -
ego y; howe e , i does no necessa ily include mul iple
explica ions (e. g., choosing explici ollow-up ac ions
wi hou p eceding explici judgmen s). I mo e han one
explica ion is included, he logical o de will be o a i e a
an assessmen and hen o make a p edic ion o choose a
ollow-up ac ion acco dingly. In simula ions, pa icipan s
usually epo diagnos ic decisions in an open o closed
ques ionnai e o ma ; howe e , e bal epo s o ac ual
pe o mances o ollow-up ac ions a e also possible in spe-
ci ic simula ions (e. g., ole play). In e ms o measu ing
diagnos ic compe encies beyond knowledge es ing, diag-
nos ic decisions ep esen dependen a iables and lead o
he calcula ion o sco es h ough compa ison o success
c i e ia.
Salience o diagnos ic in o ma ion
Salience is he p ope y ha makes s imuli s and ou and
be likely o d aw he pe cei e s' selec i e a en ion (Hig-
gins, 1996). Visual examples o en include mul iple s imu-
li, whe eby salien s imuli s and ou om o he s. Ea ly
esea ch e ealed ha pe cei e s ecall mo e in o ma ion
abou salien s imuli (McA hu & Ginsbe g, 1981) and
ha hese s imuli ecei e disp opo iona e weigh ing in
subsequen judgmen s (Taylo & Fiske, 1978).
Howe e , while esea che s ha e ound ha people gen-
e ally ag ee on which pa s o a pic u e o scene a e salien
(T eisman & Gelade, 1980; Wol e, 1997), indi iduals' a -
en ion can be di ec ed h ough many di e en means.
Thus, an impo an dis inc ion is whe he salience pe -
ains only o he quali ies o he s imulus o whe he sali-
ence is a hypo he ical cons uc o an indi idual's cogni-
i e p ocesses when pe cei ing s imuli. While Taylo and
Fiske (1978) emphasized he impo ance o he indi idual
poin o iew in hei de ini ion o salience, Higgins (1996)
ied o di e en ia e be ween he gene alizable a ibu es
o s imuli and indi idual cogni i e p ocesses. In a simula-
ion, he gene alizable p ope ies o s imuli, he guiding o
cogni i e p ocesses h ough ins uc ional design, and he
pa icipan s' indi idual di e ences in pe cei ing he simu-
la ion come oge he . Consequen ly, we need a concep u-
aliza ion o salience ha allows o he gene alizable ca e-
go iza ion o he simula ion design while main aining he
possibili y o including pa icipan s' indi idual di e ences
as mode a o s.
To achie e his, we chose o es ablish a e y b oad con-
cep o salience ha includes mul iple ace s, a ge ing
cogni i e p ocessing in diagnos ic si ua ions h ough he
p esen a ion o di e en kinds o in o ma ion du ing a
simula ion. Ou lis o he ou ace s o salience includes
he o he wise dis inc concep s o access, p ominence,
simplici y, and cla i y, whe e p ominence ep esen s sali-
ence in a na owe sense. Because we wan o concep ual-
ize how pa icipan s' a en ion is di ec ed in simula ions
h ough he p esen a ion o in o ma ion, we coalesce
hese o he wise dis inc e ms o exhaus he a ge ed cog-
ni i e p ocesses. These aspec s a e simila o Funde 's
(1995) ealis ic accu acy model, which p oposes ou ac-
e s o diagnos ic in o ma ion ha lead o an accu a e judg-
men : ele ance, a ailabili y, de ec ion, and u iliza ion.
Funde 's aspec s o a ailabili y and de ec ion sha e ea-
u es wi h ou aspec s o access and p ominence. Howe
e ,
we ea ele ance as a p econdi ion o conside ing a
piece o in o ma ion o be diagnos ic in ou amewo k,
keeping i in mind o a possible ex ension ha includes a
model o he in e play o ele an and i ele an in o ma-
ion. Finally, we conside he u iliza ion o diagnos ic in-
o ma ion as an ou come o i s salience and, hus, a de-
penden a iable in ou app oach.
Access
Simila o Funde 's (1995) concep o a ailabili y, access
de e mines whe he ele an in o ma ion becomes physi-
cally a ailable o pa icipan s du ing a simula ion. Fo a
single piece o in o ma ion, access is dicho omous: i is
ei he o e ly ep esen ed a one poin in he simula ion, o
i emains hidden. Each diagnos ic c i e ion – ep esen ing
co ec o accu a e diagnos ic decisions – can ha e a popu-
la ion o ele an in o ma ion, bu a simula ion design may
o may no p o ide access o his in o ma ion. High access
en ails ha pa icipan s a e likely o iden i y he mos ele-
an in o ma ion du ing he simula ion, whe eas low ac-
cess en ails ha a subs an ial amoun o ele an in o ma-
ion is likely o be wi hheld om o no e ie ed by he
pa icipan s. As we conside access in a physical sense and
no in a cogni i e sense, in o ma ion can be physically ac-
cessible bu likely o be missed. Cogni i e accessibili y
mo e so ac o s in o he o he ace s o salience.
P ominence
P ominence de e mines whe he ele an in o ma ion
s ands ou and is likely o d aw pa icipan s' a en ion du -
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N. Mach s e al., Ca ego iza ion o simula ed diagnos ic si ua ions 9
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ing a simula ion. In Funde 's (1995) e minology, p omi-
nence is he d i ing ac o behind in o ma ion de ec ion. I
can be igge ed by audio isual ma ke s o he pieces o in-
o ma ion and hei con ex ual p esen a ion; empo al po-
si ioning o du a ion o p esen a ion; and simula ion plo
sequencing. Addi ionally, diagnos ic asks, such as p o id-
ing p omp s on how o p oceed wi h diagnos ic in o ma-
ion, can enhance i s p ominence. In con as , he densi y
o possibly i ele an in o ma ion can dec ease p omi-
nence du ing a simula ion. Fo a single piece o in o ma-
ion, p ominence is nei he ca ego ical no de ini e. To de-
e mine he p ominence o ele an in o ma ion, we need
o es ima e i ei he heo e ically (e. g., by asking simula ion
expe s) o empi ically (e. g., by asking he pa icipan s).
Consequen ly, in e -indi idual di e ences conce ning he
p ominence o pieces o in o ma ion can be a h ea o he
eliabili y o i s es ima ion. The lowe he ag eemen on
whe he a piece o in o ma ion in a simula ion is p omi-
nen , he less eliable he poin es ima e o i s p ominence
is. Ne e heless, indi idual di e ences in he pe cep ion o
salience can lead o in e es ing esea ch ques ions. One
pe son may ind a piece o in o ma ion e y ala ming,
whe eas ano he pe son may ba ely no ice i . Thus – in ad-
di ion o i s manipula ion ia simula ion design – explica -
ing pa icipan 's pe cep ions o he salience o s imuli
makes p ominence a dependen a iable ha can be used
in media ion and mode a ion analyses. O e all, a high
p ominence o ele an in o ma ion means ha ele an
pieces o in o ma ion will s and ou and pa icipan s will
likely ac i ely pe cei e i , whe eas low p ominence en ails
ha ele an in o ma ion will be p esen ed in a way ha
makes i mo e likely o pa icipan s no o ac i ely engage
he in o ma ion and possibly o e look o o ge i .
Simplici y
Simplici y desc ibes he amoun and complexi y o ele-
an in o ma ion in combina ion wi h he numbe o diag-
nos ic decisions. The amoun and complexi y esul om
he numbe o decodable pieces o in o ma ion (e. g., a
long s uden essay can be decoded in o a e y high numbe
o single pieces, whe eas a single es sco e is a e y simple
piece o in o ma ion). The numbe o diagnos ic decisions
esul s om he numbe o a ge s (e. g., he numbe o
s uden s in a class oom o he numbe o pa ien s ha
mus be diagnosed in a ound) and he numbe o deci-
sions pe a ge (e. g., he numbe o compe encies o es i-
ma e pe s uden o he equi ed numbe o di e en ial
diagnoses pe pa ien ). High simplici y en ails a ew sim-
ple pieces o ele an in o ma ion combined wi h ew a -
ge s and ew decisions pe a ge . Low simplici y en ails a
hea y load o complex pieces o in o ma ion ha pa ici-
pan s mus a ibu e o mul iple diagnos ic decisions, pos-
sibly anging ac oss mul iple a ge s.
Cla i y
Cla i y de e mines whe he ele an in o ma ion in he
simula ion objec i ely leads o p ecise and unambiguous
diagnos ic decisions. As such, i conce ns he eliabili y o
mapping ele an in o ma ion in he simula ion on o he
espec i e decisions. In line wi h es heo y, single pieces
o in o ma ion ha e ela i ely low eliabili y; howe e , his
does no imply ha a la ge pool o in o ma ion necessa i-
ly leads o unambiguous esul s. In o ma ion pa e ns may
e en seem o en ail clea diagnos ic decisions o pa ici-
pan s bu may be objec i ely ambiguous. Fo example, a
diagnos ic si ua ion could include highly simila diagnos-
ic in o ma ion o wo a ge s ha equi e undamen ally
di e en diagnos ic decisions. Like p ominence, cla i y is
nei he ca ego ical no de ini e; hus, i mus be es ima ed.
This es ima ion could include using he ag eemen o ex-
pe s on diagnos ic alloca ions o decisions based on spe-
ci ic in o ma ion. High cla i y en ails ha ele an in o -
ma ion will p oduce clea , unambiguous esul s when
p ocessed co ec ly, whe eas low cla i y en ails he oppo-
si e.
Example: The simula ed class oom
in Kaise e al. (2013)
In his sec ion, we in oduce one published example o a
simula ed diagnos ic si ua ion – Kaise e al.'s (2013) simu-
la ed class oom – and ca ego ize i using he in oduced
concep ual amewo k. In his s udy, he au ho s in es i-
ga ed he in e play o s uden s' lesson pe o mance and
lesson engagemen in pa icipan s' judgmen s in a simu-
la ed class oom en i onmen o a sample o (n = 40)
eache candida es. A u he desc ip ion o he simula ed
diagnos ic si ua ion is embedded in he ca ego ies o ou
amewo k. Ou ocus is on explo ing he salience o diag-
nos ic in o ma ion unde he ou sepa a e headings be-
low. I is impo an o no e ha wi hin his ocus, we apply
heu is ic wo ding ca ego ies o he ou salience ace s; we
hope ha his will p o ide an ini ial app oach o de i ing
sys ema ic scales in he u u e.
The physical en i onmen o his simula ed class oom
was an in e ac i e compu e applica ion ha led pa ici-
pan s h ough a simula ion using onsc een ins uc ions.
S a ic pic u es and names ep esen simula ed s uden s.
The pa icipan s in e ac ed wi h hese s uden s using a
ques ion-answe schema. They clicked on ques ions in a
gi en pool, and he s uden s eac ed by signaling ha hey
wan o p o ide an answe . Pa icipan s hen clicked on
any one s uden , and an answe appea ed on he sc een.
A e he simula ed lesson was o e , he pa icipan s made
diagnos ic decisions o each s uden by u ilizing judg-
men scales. In e ms o he ex e nal se up in he epo ed
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10 N. Mach s e al., Ca ego iza ion o simula ed diagnos ic si ua ions
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sample, he esea che s in i ed pa icipan s o a labo a o y
o pe o m he simula ion on local compu e s in a s and-
a dized se ing.
The social embeddedness o his simula ed class oom is
explained in wha ollows. The pa icipan s in e ac ed wi h
he simula ed s uden s in a simpli ied manne . The simu-
la ed s uden s we e no pe sonally in oduced, and social
in o ma ion was gained only om pic u es, names, and
answe s. The e was no ewa d s uc u e o eedback
mechanism wi hin he simula ion. The ex e nal se up in-
cluded s anda dized ins uc ion om an expe imen e ,
and he ex e nal ewa d s uc u e in ol ed paymen o
pa icipa ion. Unsys ema ic eedback indica ed ha he
pa icipan s el he simula ion was a mode a ely ele an
ep esen a ion o hei la e p ac ice.
The diagnos ic asks assigned a he ou se o his simula-
ion we e o comple e a lesson wi h a simula ed class by
selec ing on- opic ques ions, add essing hese ques ions o
he class, calling upon s uden s, and making judgmen s
abou he s uden s a he end o he lesson. The asks we e
no epea ed o elabo a ed upon un il diagnos ic decisions
we e eques ed a e he lesson.
The diagnos ic ac i i ies in his simula ion included he
iden i ica ion and gene a ion o diagnos ic in o ma ion,
along wi h he a ailable ac ions o choosing ques ions and
selec ing s uden s o answe hese ques ions. On a cogni-
i e le el, i was ad an ageous o pa icipan s o memo-
ize s uden s' answe s and signaling equency o make
accu a e judgmen s a e he lesson; he ac i e documen-
a ion o diagnos ic in o ma ion was p ohibi ed. Pa ici-
pan s we e asked nei he o gene a e addi ional diagnos ic
objec i es no o o mula e hypo heses abou he s uden s
du ing he simula ion p ocess. As s uden s' answe s we e
al eady ma ked in e ms o whe he hey we e co ec o
inco ec , he diagnos ic ac i i y o e alua ing he in o -
ma ion was no equi ed.
The salience o diagnos ic in o ma ion is a he co e o
ou examina ion. Thus, we p esen de ails conce ning he
ou ace s o salience – access, p ominence, simplici y,
and cla i y – in subsec ions ollowing he nex pa ag aph.
Gene ally speaking, he ele an diagnos ic in o ma ion in
his simula ion was he s uden s' signals a e he pa ici-
pan s di ec ed ques ions o he class and he co ec ness o
he s uden s' answe s when hey we e called upon. Addi-
ional i ele an in o ma ion likely a ose om he s u-
den s' names and pic u es.
The diagnos ic decisions in his simula ion in ol ed judg-
men s o he s uden s' lesson pe o mance and engage-
men . Using a pe cen age scale, he pa icipan s we e
asked o epo o each s uden he ela i e equency o
co ec esponses in compa ison o inco ec esponses
and he ela i e equency o signals in compa ison o he
numbe o ques ions asked du ing he lesson, espec i ely.
Access
Access o ele an diagnos ic in o ma ion was high in his
simula ion, al hough his was due o he speci ic na u e o
he judgmen s. As desc ibed abo e, lesson pe o mance
was ope a ionalized as he ela i e equency o he co -
ec answe s o each s uden . Lesson engagemen was op-
e a ionalized as he ela i e equency o he signals o
each s uden . Pa icipan s called upon he s uden s hem-
sel es and we e shown whe he he s uden 's esponses o
each ques ion we e co ec . They we e also shown each
s uden 's signal. Thus, pa icipan s had access o e e y
piece o in o ma ion ha cons i u ed he diagnos ic c i e-
ia, as he c i e ia we e based on he diagnos ic in o ma-
ion he pa icipan s gene a ed. Ne e heless, one can eas-
ily imagine how he simula ed class oom could be used
di e en ly. Fo example, judgmen s could be eques ed
ega ding s uden s' unde lying compe encies o abili ies,
while he limi ed numbe o calls on he s uden s would
es ic access o ele an in o ma ion on he judgmen c i-
e ia (i. e., ewe calls would en ail less access o ele an
in o ma ion).
P ominence
As desc ibed abo e, he p ominence o he ele an diag-
nos ic in o ma ion mus be es ima ed. In his case, we es i-
ma e he p ominence o diagnos ic in o ma ion in he
simula ion o be mode a e. The s uden s' signals and an-
swe s we e cen al o he main diagnos ic ac i i y o gene -
a ing diagnos ic in o ma ion wi hou in e e ing wi h he
in o ma ion. Addi ionally, s uden s' signals we e isually
highligh ed on he compu e sc een using colo ed ames,
and s uden s' answe s ecei ed addi ional colo ed high-
ligh ing based on whe he hey we e co ec o inco ec .
Howe e , he pa icipan s had o agg ega e s uden an-
swe s in o hei pos -lesson summa i e judgmen wi hou
documen a ion and based only on memo y. Thus, he
p ominence o each answe and i s co ec ness likely di-
minished h ough he agg ega ion p ocess un il he end o
he lesson.
Simplici y
The simplici y o he ele an diagnos ic in o ma ion in
his simula ion was mode a e. Al hough he s uden s' sig-
nals and he co ec ness o he s uden s' answe s had a
simple and o e dicho omous na u e, he pa icipan s di-
ec ed a ious ques ions o he class du ing one lesson, e-
sul ing in a espec i e amoun o answe in o ma ion. Ad-
di ionally, he pa icipan s ecei ed signaling in o ma ion
o each ques ion and o each simula ed s uden , esul ing
in a mul i ude o pieces o signaling in o ma ion. This
amoun o in o ma ion was combined wi h wo dis inc
judgmen s made on each o nine s uden s. Consequen ly,
a high amoun o e y simple in o ma ion had o be a ib-
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N. Mach s e al., Ca ego iza ion o simula ed diagnos ic si ua ions 11
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u ed o a mode a ely high numbe o o e all 18 diagnos ic
decisions, which we conside o be mode a ely simple.
Cla i y
The cla i y o he ele an diagnos ic in o ma ion in his
simula ion was e y high due o he na u e o i s design.
The asks used o he ques ion-answe schema had solu-
ions ha we e clea ly co ec o inco ec , and s uden
answe s we e lagged acco dingly in he simula ion. This
in o ma ion was used o he agg ega ed diagnos ic c i e-
ion o lesson pe o mance. Fu he mo e, he s uden s
immedia ely signaled a e a ques ion was di ec ed a he
class. This signaling in o ma ion was used o he agg e-
ga ed diagnos ic c i e ion o lesson engagemen . Addi-
ionally, he e was no sou ce o objec i e un eliabili y o
ambigui y in mapping he diagnos ic in o ma ion o he
diagnos ic c i e ia. I p ocessed co ec ly, he diagnos ic
in o ma ion would lead o an exac diagnos ic decision.
Discussion
In he p e ious sec ions, we ou lined ou concep ual
amewo k o ca ego izing simula ed diagnos ic si ua-
ions, ocusing on he salience o he diagnos ic in o ma-
ion in such simula ions. We elabo a ed on six concep ual
componen s – physical en i onmen , social embedded-
ness, diagnos ic asks, diagnos ic ac i i ies, diagnos ic in-
o ma ion, and diagnos ic decisions – and p oposed ha
he e a e ou ace s o he salience o he diagnos ic in o -
ma ion p esen ed in simula ions: access, p ominence, sim-
plici y, and cla i y. We u he used one in-dep h example
o demons a e how o desc ibe and ca ego ize he design
o a simula ed diagnos ic si ua ion on a concep ual le el
and in e ms o he salience o i s diagnos ic in o ma ion.
The applica ion o simula ions o diagnos ic si ua ions
includes esea ch on he s uc u e and measu emen o
diagnos ic compe encies and on how hei design as lea n-
ing en i onmen s a ec s he ad ancemen o such compe-
encies. Fo bo h pu poses, he exis ing s udies and con-
cep ual amewo ks ha e me ely ouched upon simula ion
design p inciples conce ning he p esen a ion o diagnos-
ic in o ma ion (Che niko a e al., 2022; Hei zmann e al.,
2019), while also epo ing he e ogenei y be ween he co-
e icien s o diagnos ic compe encies and he e ec sizes
o simula ions used as lea ning en i onmen s. Cu en
me a-analy ical esea ch (Che niko a e al., 2024) indi-
ca es ha he salience o diagnos ic in o ma ion can go
beyond he exis ing indings ela ed o o he mode a o s in
explaining he a iance o lea ning gains in measu es o
diagnos ic success. The p esen ed concep ual amewo k
enables a clea desc ip ion and ca ego iza ion o simula-
ions o diagnos ic si ua ions and opens up possibili ies o
iden i y p ecisely how hese simula ions p esen diagnos-
ic in o ma ion o pa icipan s. The amewo k should p o-
ide oppo uni ies o he sys ema ic manipula ion o he
salience o ele an in o ma ion in simula ions and o a -
ge ing he diagnos ic ac i i ies in ol ed in dealing wi h
mo e o less salien in o ma ion h ough in e en ions.
Fo example, in e en ions could aim (1) o guide pa ici-
pan s o gain be e access o ele an in o ma ion, (2) o
make impo an in o ma ion mo e p ominen , o (3) o e-
ie e diagnos ic in o ma ion ha p oduces objec i ely
clea e diagnos ic esul s.
A possible agenda o u u e esea ch includes he ol-
lowing:
a. he ca ego iza ion o exis ing simula ed diagnos ic si u-
a ions o conclusi e summa ies in a me a-analysis;
b. he applica ion o his amewo k o he design o new
simula ions o communica e on common g ound con-
ce ning he applica ion o simula ions o diagnos ic si u-
a ions;
c. he ealiza ion o sys ema ic salience a ia ions in exis -
ing and new simula ions o diagnos ic si ua ions o in-
es iga e on an expe imen al le el which aspec s o in-
o ma ion salience a e esponsible o di e ences in
measu es o diagnos ic compe encies; and
d. he alida ion o in e en ions a ge ing in o ma ion sa-
lience o de i e ecommenda ions o he acili a ion o
diagnos ic compe encies.
O e all, we conside simula ed diagnos ic si ua ions o
be e ec i e ools o esea ch on he s uc u e and meas-
u emen o diagnos ic compe encies and on he e ec s o
he design o lea ning en i onmen s on he ad ancemen
o such compe encies. Howe e , he espec i e e ec s o
simula ions exhibi la ge a ia ions ha exis ing me a-
analyses and amewo ks canno ully add ess. In his
pape , we p esen an app oach o d i e he esea ch on
simula ed diagnos ic si ua ions o wa d by enabling he
sys ema ic ca ego iza ion o design p inciples, ocusing on
he salience o diagnos ic in o ma ion – a opic ha has no
ye ecei ed any sys ema ic a en ion. Wi h ou ame-
wo k, we o e o he au ho s a e e ence o hei simula-
ion designs and sugges ha ailing o conside he sali-
ence o diagnos ic in o ma ion in speci ic s udies o
lea ning en i onmen s can lead o se ious misin e p e a-
ions o he epo ed coe icien s.
Re e ences
Allen, J., Bu a di, L., & Hays, R. (1991). The ela ionship o simula-
o ideli y o ask and pe o mance a iables.
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