Resea ch Pape
Recommended ci a ion: Linnéusson, G., Smi h, C., Nizamis, K., & U enda Mo is,
M. (2025). Explo ing The U ili y o Causal Loop Diag ams o Analysing he
Con inuing Enginee ing Educa ion Ecosys em. In Kangaslampi, R., Langie, G.,
Jä inen, H.-M., & Nagy, B. (Eds.), SEFI 53 d Annual Con e ence. Eu opean
Socie y o Enginee ing Educa ion (SEFI), Tampe e, Finland. DOI:
10.5281/zenodo.17631581.
This Con e ence Pape is b ough o you o open access by he 53 d Annual Con e ence
o he Eu opean Socie y o Enginee ing Educa ion (SEFI) a Tampe e Uni e si y in
Tampe e, Finland. This wo k is licensed unde a C ea i e Commons
A ibu ion-NonComme cial-Sha e Alike 4.0 In e na ional License.
EXPLORING THE UTILITY OF CAUSAL LOOP DIAGRAMS FOR
ANALYSING THE CONTINUING ENGINEERING EDUCATION
ECOSYSTEM
G. Linnéussona,1, C.J.M. Smi hb, K. Nizamisc, M. U enda Mo isd
a Uni e si y o Skö de, Skö de ,Sweden
h ps://o cid.o g/0000-0001-8188-7288
Glasgow Caledonian Uni e si y, Glasgow, Sco land
h ps://o cid.o g/0000-0001-5708-6341
c Uni e si y o Twen e, Enschede, The Ne he lands
h ps://o cid.o g/0000-0002-6965-0242
d Uppsala Uni e si y, Uppsala, Sweden
h ps://o cid.o g/0000-0001-5100-4077
Con e ence Key A eas: Con inuing educa ion and li e-long lea ning in enginee ing;
Dialogue be ween enginee ing and socie y – e ec s on educa ion (Please selec wo
Con e ence Key A eas)
Keywo ds: Con inuing Enginee ing Educa ion; causal loop diag ams; sys ems
hinking; educa ion ecosys em
ABSTRACT
Con inuing Enginee ing Educa ion (CEE) plays a i al ole in equipping p o essionals
wi h he skills needed o na iga e echnological ad ancemen s and sus ainabili y
ansi ions. Howe e , he CEE ecosys em is complex, wi h mul iple s akeholde s,
in e dependen ac o s, and dynamic ade-o s ha challenge e ec i e decision-
making. This s udy explo es whe he sys ems hinking, speci ically causal loop
diag ams (CLDs), can p o ide a s uc u ed app oach o analysing hese dynamics
and in o ming policy and ins i u ional s a egies.
Using an induc i e, quali a i e app oach, we de eloped a CLD o map he Swedish
CEE ecosys em in he con ex o he G een T ansi ion. The model highligh s key
ein o cing and balancing eedback loops ha shape he sys em, including he
in e play be ween compe ence de elopmen , indus ial needs, labou ma ke
1 Co esponding Au ho
G. Linnéusson
ga y.linneus[email p o ec ed]e
dynamics, and educa ional adap a ion. I e eals how upskilling can d i e inno a ion
and economic g ow h while simul aneously in oducing ensions such as wo k o ce
u no e , ec ui men challenges, and ins i u ional ine ia. The indings unde sco e
ha e ec i e CEE policy equi es sys em-wide coo dina ion a he han isola ed
in e en ions.
This s udy demons a es he u ili y o CLDs as a ool o isualising ade-o s,
iden i ying le e age poin s, and os e ing mul i-s akeholde dialogue. While he model
is explo a o y, i se es as a ounda ion o u u e pa icipa o y alida ion and
e inemen . By applying sys ems hinking, his esea ch con ibu es o a mo e
in eg a ed unde s anding o CEE and o e s a me hodological basis o s a egic
decision-making in educa ion and wo k o ce de elopmen .
1 INTRODUCTION
Con inuing Enginee ing Educa ion (CEE) is becoming inc easingly i al as i aims o
eskill and upskill p o essional enginee s o na iga e a apidly changing wo ld
(Cede op, 2023; IET, 2025). Fo uni e si ies, i se es as a pa hway o socie al
impac (Knudsen e al., 2021; Soei o, 2006), while o indus ies, i enhances agili y
and esilience, empowe ing employees o adop new echnologies e ec i ely (WEF,
2024). CEE is also essen ial o sma socie ies and he digi al ans o ma ion, d i ing
economic p og ess, social inclusion and equal access o digi al ools. Ul ima ely, i
enables indi iduals and socie ies o h i e, inno a e, and ac i ely pa icipa e in he
digi al e a, making i a co ne s one o sma , sus ainable socie ies.
Sus ainable socie ies can u he bene i om he ansi ion o g een echnologies,
which a e ans o ming indus ies by minimizing en i onmen al ha m, imp o ing
e iciency, and p omo ing sus ainabili y. Inno a ions such as enewable ene gy,
elec ic ehicles, sus ainable ag icul u e, and g een buildings help comba clima e
change, educe pollu ion, and p ese e na u al esou ces, all while also os e ing
economic g ow h, job c ea ion, and imp o ed public heal h. This ans o ma ion
demands new compe encies om p o essionals, and CEE mus be p epa ed o mee
he challenge.
Since he 1980s, SEFI and he In e na ional Associa ion o Con inuing Enginee ing
Educa ion (IACEE) ha e add essed and pu on he map se e al endu ing challenges
CEE s ill aces oday ha call o inno a i e solu ions. Among o he s, cu iculum
e isions a e necessa y o keep up wi h echnological ad ancemen s (Azo ei a e al.,
2024). The indus y aces di icul ies in combining wo k and he need o de elop
employees because o he expenses associa ed wi h highe educa ion (Mi a &
Raskin, 2023), and he isk o no being able o e ain hem (Vää äjä e al., 2024).
Exis ing p og ams o e ed and he skills needed in he indus y a e no always
aligned (Ca a ozzolo e al., 2024). In using incen i e and engagemen is e y c ucial,
especially because he e is no pe cei ed immedia e use o he new skills gained
(Vää äjä e al., 2024). The eme gence o many ce i ica ions makes i di icul o o e
c eden ials and iden i y whe e he e is a need o emb ace di e en lea ning s yles
and eaching app oaches. Tackling hese issues calls o all s akeholde s o wo k
oge he and co-c ea e ac oss sys em bounda ies.
Many o hese challenges pe se e e due o he complexi y and dynamic na u e o
he CEE landscape. CEE cons i u es a sys em o ecosys ems wi h many
in e connec ed a iables ha e o s o analyse and unde s and hem sepa a ely lead
o pa ial agmen ed solu ions. CEE challenges should be add essed by na iga ing
delica e ade-o s be ween he di e en s akeholde s a he han op imizing one
aspec o ano he . Recen e o s ha e been ocused on c ea ing a common
language o cha ac e ize comp ehensi ely CEE and o e ing a ounda ion o u he
discussions (Ca a ozzolo e al., 2024). Howe e , in his wo k, he ocus is on
unde s anding he dynamics o such a complex sys em, as no s udies in ex an
li e a u e ha e been iden i ied seeking o de elop a sys ems-le el pe spec i e o
Con inuing Enginee ing Educa ion.
Sys ems hinking can p o ide us wi h powe ul ools o be e analyse and
unde s and dynamic complexi y in mul i ac o ial sys ems whose componen s a e
en angled and in e connec ed. To iden i y hese dynamic pa e ns o complex social
sys em beha iou and dynamic in e ac ions be ween sys em componen s, CLDs
(Fig1.) ha e been p oposed and used since 1981 (Ki kwood, 1998; Richa dson &
Pugh III, 1997)in a ious applica ion a eas, including heal hca e, and public policy
(C abolu e al., 2023; Linnéusson e al., 2022). Thus, by applying CLD o he domain
o CEE, ou s udy does no claim o in oduce a no el me hodological ool pe se, bu
a he o explo e i s alue and ele ance in a p e iously unde -explo ed a ea.
Fig. 1. Example o a ein o cing and a balancing causal loop. The le loop is ein o cing
(e en o ze o numbe o “-”), meaning a change in one di ec ion ampli ies i sel (e.g., money
in a sa ings accoun ea ns in e es , inc easing he balance and gene a ing mo e in e es ).
The igh loop is balancing (odd numbe o “-”), meaning a change in one di ec ion igge s
an opposing e ec (e.g., hunge leads o ea ing, which educes hunge ). The igu e was
c ea ed using Vensim.
Gi en he lack o exis ing s udies applying CLDs o educa ional sys ems and CEE,
his s udy explo es he esea ch ques ion: “How clea ly can sys ems hinking p o ide
a me hod o aid decision-making o impac ul co-c ea ion o alue in CEE?”
Speci ically, how can CLDs help explain key dynamics and isualise ade-o s,
enable s and ba ie s wi hin a CEE sys em?
2 METHODOLOGY
The lack o p io s udies has esul ed in a p agma ic explo a o y, mul i-me hod
quali a i e, induc i e app oach being u ilised; an app oach consis en wi h gaining
p ac ical insigh s o suppo and in o m u u e p ac ice and encompasses concep s
and p ac ices (Saunde s, Lewis and Tho nhill, 2023, p147). Mo eo e , as he
esea ch ques ion is in essence a me hodological ques ion, namely how clea ly can
CLDs be used o map he CEE ecosys em, hen he ocus o he pape ’s
me hodology was o limi he scope o de e mine whe he he CLD me hod had u ili y
in his con ex , in pa icula G een T ansi ion in Sweden, as p esen ed in Fig. 2.
Open discussions ook place be ween Au ho s 1 and 4 abou he CEE landscape in
Sweden, wi h a pa icula ocus on G een Technologies and he G een T ansi ion.
These discussions cen ed on Au ho 4’s unde s anding o he sys em, being an
owne -o -ques ion a a la ge Uni e si y o de eloping hei CEE ecosys em.
Subsequen ly, Au ho 1 induc i ely coded he ansc ip s and no es o iden i y key
ac o s and hei in e ac ions. Th ough mul iple i e a ions, his p ocess esul ed in a
e sion o a CLD ha e lec ed he ini ial unde s anding. Key ac o s we e also
de i ed om an ea lie s udy p oposing a axonomy o CEE p ac ices (Ca a ozzolo
e al., 2024). The CLD was hen p esen ed and e ined h ough se e al online
discussions wi h all au ho s. Once all au ho s ag eed ha he CLD had su icien
cla i y, i s u ili y was e alua ed. This app oach aligns wi h es ablished me hods o
de eloping CLDs (Baugh Li lejohns e al., 2021).
The u ili y o he model was add essed in wo ways, i s ly an in e nal e i ica ion by
au ho 4 (who d o e he ini ial c ea ion p ocess), and hen a alida ion by au ho 3
who was no in ol ed as much in he ea ly de elopmen .
Fig. 2. A g aphical ep esen a ion o he me hodology he au ho s ollowed o c ea ing (Da a
Collec ion), e ining, e i ying, and alida ing he p oposed CLD, in ha o de .
The e i ica ion p ocess was conduc ed by Au ho s 1 and 4 o ensu e ha he model
accu a ely e lec ed he expe iences, pe cei ed eali y, and biases o he ini ial
desc ip ion, as well as o alida e he eedback loops. The p ocess ollowed his
app oach: each loop was desc ibed and analysed by Au ho 4. Special a en ion was
gi en o causal loops ha modelled c i ical, con as ing goals and hose whe e he
pe cei ed ou pu led o unexpec ed esul s. Addi ionally, names and ou pu s we e
e i ied and u he discussed. The ou come o his p ocess was an ex ended model
desc ip ion, which se ed as he basis o he explana ion p esen ed in Sec ion 3.
A e he model e i ica ion, Au ho 3 pe o med a single-pe son alida ion. This
p ocess included he iden i ica ion o all causal ela ionships and a check on he
assump ions ha dic a ed each causali y. The pu pose was o check i hose a e
gene alizable o speci ic, i he model can be simpli ied wi hou loss o in o ma ion,
and i he loops iden i ied a e consis en wi h eali y. Addi ionally, i iden i ies hidden
loops and assesses he pola i y o he causal ela ionships. Addi ionally, he checked
i he diag am su icien ly ep esen s wha happens in p ac ice.
3 FINDINGS
3.1 The Cu en CLD o he Swedish CEE Ecosys em o G een T ansi ion
The CLD illus a es how p essu es ela ed o he g een ansi ion d i e complex
in e ac ions be ween companies, educa ion sys ems, and mac o-le el policy
en i onmen s. Compe ence de elopmen and upskilling suppo p oduc i i y gains
and echnological p og ess, bu also inc ease demands on he labou ma ke and
educa ional capaci y. Technological ansi ions and economic g ow h c ea e new
oppo uni ies while simul aneously in oducing sys emic ensions, such as
ec ui men challenges, u no e , and ins i u ional ine ia. The educa ion ecosys em
eme ges as a cen al ac o , balancing esponsi eness wi h in e nal limi a ions.
Fig. 3. CLD o he Swedish CEE ecosys em o G een T ansi ion, using Vensim.
need o g een
ansi ion
echnologies
in use
+
echnological
shi s
ap edu CEE
edu o e ings
in use
quali y o
edu o e ings
p oduc i i y
compe ence in
companies
wo kload
-
+
-
+need o
compe ence
domains in use
+
+
-
+
employee
u no e
+
+
in es men s
job ma ke
possibili ies
+
a ailable ap
employees o hi e
-
+
go e nmen al
undings
-
+
+
g een ech
de elopmen s
-
ac i e indus ial
businesses
+
p essu e o
de elop g een
ansi ion
compe ence
+
+
B1
Socie al need
Sho - e m
Edu esponse
B7
Compe ence
ein es men
R2
B3
R3
T ansi ion in
compe ence
T ansi ion in
wo kload
R4
T ansi ion in
Indus ial
job ma ke
+
+
+
+
+
-
esou ce cons ain s
in edu sys ems
+
-
ap edu
p og ams
+
-
+
+
+
a ac i eness o
edu p og ams
inancial s a us o
edu ecosys em
-
+
Compe ence loss
+
ime and
compe ence o
conside
ele ance o
socie y
-
+
S imula ion o Indus ial
ecosys em
S imula ion o Edu
ecosys em
Compe ence a ailabili y
Long- e m Edu esponse
-
+
+
R7
R5
Ex e nal a ac i eness
Edu
R11
In e nal
a ac i eness Edu
T ansi ion in
Edu need
Economic g ow h h ough echnological shi s
R9
R6
B10 R10
+
B2
Indus ial
esponse
R1
B5
R14
R13
B9
B8
T ansi ion in
echnologies
Go e nmen policies
Legend o colou s:
Mac o En i onmen
Indus ial Ecosys em
G een T ansi ion Need
Educa ional Ecosys em
Re inemen o
Edu o e ings
New Edu o e ings
R12
Unin ended
consequences
Edu wo kload
mobili y o
compe ence
+
+
+
B4
T ansi ion in
he Mac o
job ma ke
Wo ke
mobili y
Regional
mobili y
magni ica ion
B6
R8
+
R
B
Rein o cing loop; a ow indica es di ec ionali y
Balancing loop; a ow indica es di ec ionali y
The cu en Swedish CEE ecosys em is isualised in Figu e 3 h ough a CLD. As
desc ibed in he legends, he model is s uc u ed a ound i e key subsys ems
acco ding o colou hemes: G een T ansi ion Need, Indus ial Ecosys em, Mac o
En i onmen , Go e nmen Policies, and Educa ional Ecosys em. Howe e , in he
desc ip ion below, we na a e he CLD using ou key hema ic a eas o explain he
eedback dynamics shaping he Swedish CEE sys em o g een ansi ion.
3.2 Desc ip ion o he CLD
We ecommend ha eade s closely ollow he CLD while eading he desc ip ion,
whe e each loop—balancing (B) o ein o cing (R)—is clea ly iden i ied o suppo
unde s anding.
1. Compe ence De elopmen as a Response o Socie al Need (B1, B2) – As he
demand o a g een ansi ion in ensi ies, socie al expec a ions g ow o companies
o de elop ele an compe encies (B1). In esponse, companies in es in upskilling,
aiming o inc ease p oduc i i y and suppo echnological ad ancemen s ha enable
g een solu ions o eplace ou da ed ones, he eby easing he u gency o
ans o ma ion (B2).
2. T ansi ions and Tensions in he Indus ial Ecosys em (R1-R7, B3-B5) – Imp o ed
p oduc i i y gains can educe wo kloads, enabling companies o ein es ime in o
employee compe ence de elopmen , ueling a i uous cycle o knowledge and
pe o mance (R1). Howe e , accele a ing he use o eme ging echnologies du ing
ansi ions can mul iply wo kloads and inc ease employee u no e , in oducing
ic ion in he sys em (B3, R2, R4). These ensions may in ensi y as job ma ke
oppo uni ies expand, d i en by in es men s in he mac o le el (R7, B4), eshaping
labo dynamics (B5). O e ime, hese ansi ions ende bo h exis ing compe encies
(R3) and echnologies (R5) obsole e, dissol ing ea lie p essu es. To d i e he
desi ed ansi ion, he indus ial ecosys em is syne gis ically co-dependen on he
adap i e capaci ies o he educa ional ecosys em (R6).
3. Mac o En i onmen D i e s o Technological T ansi ions (B6, R8-R11) – As a
s a egic esponse o s imula e he desi ed echnological ansi ion, go e nmen -
unded mac o-le el in es men s in egional de elopmen can help ebalance egional
mobili y (B6), imp o ing compe ence mobili y and easing he ec ui men o c i ical
compe ences (R8). In he sho e m, mac o-le el unding can accele a e
echnological p og ess (R9) and gene a e sys em-wide economic g ow h (R10).
Howe e , as shown by loops R4, B5, and R11, hese a ge ed in e en ions may also
unin en ionally in ensi y job ma ke p essu es, ampli ying employee u no e wi hin
he indus ial ecosys em, hinde ing ec ui men , and po en ially educing in e es in
educa ion among ce ain g oups.
4. Educa ion Ecosys ems Adap a ion o Socie al P essu es (B7-B10, R12-R14) – In
esponse o p essu es o g een ansi ion compe encies, educa ion ecosys ems
mus e ol e hei o e ings. Uni e si ies may in oduce agile CEE p og ams o mee
immedia e indus ial needs (B7) and de elop long- e m o e ings, hough o en
slowed by ins i u ional ine ia (B8). The abili y o gene a e ele an o e ings depends
on inancial s abili y and exis ing quali y ac oss he educa ion ecosys em (B9).
Howe e , apid expansion isks in oducing in e nal esou ce cons ain s and
o e loaded wo kloads, leading o unin ended quali y educ ions (R12). In e nal
a ac i eness o he educa ion sys em (R13) can ein o ce ei he i uous o icious
dynamics, depending on sys em condi ions and he capaci y o p io i ize socie al
ele ance (R14). The e o e, when esou ce cons ain s inc ease, o esigh capaci y
may e ode, leading o misalignmen be ween educa ion o e ings and long- e m
socie al needs (B1 and R14). These in e nal dynamics a e ein o ced by p essu es
om mac o-le el in e en ions (R7, R9, R11), highligh ing he impo ance o
in es ing in ins i u ional o esigh o e ine o e ings in line wi h socie al, no jus
ma ke , needs (R14). This highligh s how go e nmen al in e ac ions wi h he
educa ion ecosys em, h ough unding and incen i es, may in luence sys emic
balance, depending on how hey in e ac wi h exis ing ins i u ional dynamics (B10).
4 DISCUSSION AND CONCLUSIONS
This s udy se ou o explo e whe he sys ems hinking—and in pa icula , causal
loop diag ams (CLDs)—can suppo decision-making and insigh s in he con ex o
Con inuing Enginee ing Educa ion (CEE), especially amid he p essu es o a g een
ansi ion. As indica ed he ein, whe e CLDs ha e p o en aluable in o he con ex s,
he esul ing model in his s udy simila ly o e s a s uc u ed iew o he complex
in e play be ween sys em elemen s, he e compe ence de elopmen , socie al needs,
echnological ansi ions, labou ma ke dynamics, he educa ion sys em, and
go e nmen policy in e en ions.
4.1 Insigh s om he Model
The CLD e eals how ein o cing loops—such as hose be ween upskilling,
p oduc i i y, and echnological inno a ion—in e ac wi h balancing and cons aining
o ces, including wo kload p essu es, ins i u ional ine ia, and labou ma ke ola ili y.
Indus ial ans o ma ion is no solely a ma e o inc easing educa ional ou pu ;
a he , he model highligh s he c i ical ole o sys em alignmen and coo dina ed
adap a ion. The educa ional ecosys em eme ges as bo h an enable and a po en ial
bo leneck, depending on i s in e nal o esigh capaci ies, adap i eness, and quali y.
The analysis also shows ha mac o-le el in e en ions, while o en in ended o
s imula e g ow h and inno a ion, can inad e en ly ampli y in e nal ensions wi hin
indus ial and educa ional subsys ems. This sugges s ha policy design o CEE
should conside no only whe e o in e ene bu also how sys emically hose
in e en ions in e ac wi h exis ing dynamics.
4.2 The Value o CLDs in CEE Resea ch and P ac ice
This s udy demons a es he alue o applying CLDs in CEE by highligh ing hei
capaci y o enhance unde s anding o complex dynamics and suppo mo e open
and collabo a i e decision-making. F om a esea ch pe spec i e, he CLD p o ided a
way o su ace and isualise he dynamic in e dependencies shaping CEE
ecosys ems, making explici how compe ence de elopmen , echnological
ansi ions, labou ma ke dynamics, educa ion sys em adap a ion, and mac o-le el
policy in e en ions in e ac o e ime. This explici mapping suppo s esea che s in
iden i ying le e age poin s, eedback s uc u es, and ensions ha may no be
appa en when s udying isola ed sys em componen s.
Conside ing he alue o p ac ice, by i s isualisa ions, he CLD can be a gued o
help os e deepe unde s anding among s akeholde s by enabling hem i s o “see”
he sys em — iden i ying key a iables and hei ela ionships — and hen mo e
owa ds a mo e p o ound “unde s anding” o how di e en ac ions and in e en ions
migh shape ou comes. This p ocess o isualisa ion and e lec ion can suppo
s akeholde s in ans o ming hei men al models, a c i ical s ep owa ds de eloping
mo e holis ic, sys emic solu ions in CEE. By acili a ing he su acing o men al
models, making hem mo e explici and sha ed, he CLD becomes a ool o
dialogue, co-c ea ion, and s a egic hinking, c ea ing he g ound o mo e open
decision-making ha aligns wi h he complexi y o he CEE landscape.
Thus, using CLDs in CEE esea ch and p ac ice con ibu es o bo h imp o ed sys em
awa eness and a sha ed ounda ion o collabo a i e, s a egic co-ac ions.
4.3 Me hodological Re lec ions and Limi a ions
One challenge encoun e ed in de eloping he CLD was balancing ‘accu acy’ (co ec
cause-e ec s uc u e, g ounded assump ions) wi h ‘use ulness’ (s imula ing
discussion, p omo ing unde s anding, guiding s a egic hinking). While his model
aimed o s uc u al alidi y, i p io i izes insigh o e p ecision. The model was
de eloped om a single, expe ienced sou ce wi h mul i-s akeholde insigh and
alida ed in e nally. I is no ye empi ically gene alized bu p o ides a s ong
concep ual basis o s akeholde engagemen and u u e esea ch.
4.4 Fu u e Wo k and Con ibu ion
The nex s ep is o use he CLD in pa icipa o y wo kshops wi h mul iple s akeholde s
o es and explo e he model, conside ing i s use ulness as a bounda y objec
ac oss posi ions in he CEE ecosys em o gene a e ac ionable insigh s. This p ocess
will no only enhance he model’s alidi y bu may also es ablish i as a co-c ea ion
ool o policy and cu iculum design. Beyond his nex s ep, u u e wo k will explo e
he CLD’s scalabili y p ope ies wi hin o he CEE con ex s in o he Eu opean
coun ies and explo e possibili ies o u he combine his app oach wi h sys em
dynamics simula ion o o he sys em me hods o quan i a i ely suppo explo a ion o
ade-o s be ween sho - e m and long- e m impac s o a ious in e en ions.
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