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Effects of a career education classroom course
on high school students’career management
competencies and career orientation in Hungary
LAJOS PÁLVÖLGYIp
Institute of Education, ELTE Eötvös Loránd University, Budapest, Hungary
RESEARCH ARTICLE
Received: January 6, 2024 •Accepted: February 13, 2024
© 2024 The Author(s)
ABSTRACT
Several researchers have highlighted the need to strengthen school-based career education in Hungary.
After reviewing the international literature on similar programs, this study reports on the impact of an
innovative, multi-method career education course. It aimed to support Hungarian high school (ISCED 344)
students in grades 10–11 in making decisions on further education and career choices, and in dealing
with related uncertainties and difficulties, mainly through developing career management competence.
Using a quasi-experimental design, the intervention group of 92 students showed significantly better
results on half of the 20 career orientation variables assessed six months after the end of the intervention
of 12 three-quarter-hour sessions, with low effect sizes compared to the pre-intervention assessment,
and the 96-student control group. In addition to a self-developed questionnaire, the CDDQ Career
Decision-Making Difficulties Questionnaire; and the CFI Career Factors Inventory were used. The
effectiveness of the intervention was independent of factors such as gender, age, academic performance,
and parental education. The study concludes with the suggestion that an enhanced version of the course
could be an officially recommended supplementary career education program in Hungarian high schools.
KEYWORDS
career guidance, lifelong guidance, career education, career intervention, program effectiveness, high schools,
career management skills, career choice
pCorresponding author. E-mail: lajos@projecon.hu
Hungarian Educational Research Journal
DOI: 10.1556/063.2024.00287
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INTRODUCTION
The difficult task of deciding on the further education and career choices of high school students
must be prepared by thorough information, exploration, and careful reflection. Making a well-
informed and considered decision is important not only for the individual but also for society.
Such a decision requires the career choice maturity of the individual, which can be achieved
through a long process of career orientation activities. In our time, an individual’s career is
determined by a series of decisions that become relevant at different points in his or her life.
Accelerating changes in the world of work will increasingly require career adjustment in the
adult lives of today’s young people, making it less and less adaptive to link an individual to a
single occupation (Sultana, 2012). The aim is to achieve and maintain career choice maturity
as far as possible and, if necessary, to re-establish it in new life situations in line with new
requirements and opportunities. This ability is needed throughout one’s life in our rapidly
changing world and is called career adaptability. The term refers to the ability of individuals
to cope with transitions, adapt smoothly to change, and maintain a balance in their career roles
(Chen et al., 2020;Super & Knasel, 1981). The lifelong guidance (LLG) (EU, 2004) approach,
associated with the paradigm of lifelong learning (LLL), is, therefore, the appropriate response
to the challenges of our time (Barnes, Bimrose, Brown, Kettunen, & Vuorinen, 2020;
Borbély-Pecze, 2010;Borbély-Pecze, Gyöngyösi, & Juhász, 2013;Jackson, 2014).
There are several complementary theoretical approaches to career guidance, of which
Savickas’(2005) theory of career building is particularly noteworthy in today’s fast-changing
times. Lifelong career development requires the management of a series of transitions, and
therefore the concept of career management skills and the need to develop these skills becomes
essential (Sultana, 2012). The need for life-career construction enhances the importance of
career decision self-efficacy, which is the individual’s belief in his or her ability to successfully
perform the decision-related activities of self-evaluation and career awareness, goal selection,
planning, and problem-solving during career development (Taylor & Betz, 1983; cited in Török,
2016, p. 20). This belief is attitudinal in nature but may be underpinned by the necessary
competence system.
According to the ELGPN Glossary career management skills (CMS) include “a range of
competencies which provide structured ways for individuals (and groups) to gather, analyze,
synthesize and organize self, educational and occupational information, as well as the skills to
make and implement decisions and transitions.”(Jackson, 2014, p. 16) Career education aims
to develop the CMS by applying targeted “programs and activities of learning to help people to
develop the skills necessary to manage their career and life pathway. These include accessing and
making effective use of career information and guidance.”(Jackson, 2014, p. 15)
In this study, instead of CMS, we use the broader concept of career management competence
(CMC). The term “competence”implies more than mere skill or knowledge, but involves values
and attitudes as well (Sultana, 2009). The Hungarian Qualification Framework defines it as a set
of components of knowledge, skills, attitudes, autonomy, and responsibility. It is based on the
European Qualifications Framework, but slightly expands its descriptors (Lukács & Derényi,
2017). In our view, CMC should be defined with these dimensions in mind. In general, CMC is
the set of all traits, characteristics, qualities, attributes, and constructs in an individual that
enable them to develop and manage their career effectively throughout their life.
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Several models are known for what the development of CMC should be aimed at. These
frameworks can therefore be seen as structural models reflecting the content of CMC. The four-
element DOTS model (Law & Watts, 1977) is widely known and accepted, the components of
which are: the development of decision-making skills; opportunity awareness; transition
learning (such as job-search skills); and self-awareness. The four components of this basic model
can be considered as minimum requirements for all other approaches. The new version of
DOTS extends this concept by defining a “career-learning space”(Law, 1999). King (2004)
developed a framework based on positioning, influence, and boundary management behaviors.
According to his view, the development of these competencies ensures that individuals have
the connections, preparation, and experience necessary for their chosen career. Another
example is the model of Hawkins and Winter (1995), which highlights the following
components: self-awareness, self-promotion, access to opportunities, action planning,
networking, decision-making, negotiation, political awareness, coping with uncertainty, devel-
opment focus, and transfer skills. Driesel-Lange, Kracke, Hany, and Kunz (2020) build their
matrix-structure CMC model on four phases of career choice: turning in, exploring, deciding,
and attaining; while each phase is associated with three identical areas of competence: knowl-
edge, motivation, and action. Looking at the 12 cells resulting from this matrix structure, further
details can be broken down.
Several Hungarian authors pointed out that the effectiveness of career guidance and career
education in schools needs to be improved in the everyday practice of public education; that
more attention needs to be paid to it in teacher education; and that the operational conditions
for career guidance services in Hungary need to be improved (Borbély-Pecze et al., 2013;
Borbély-Pecze & Suhajda, 2017;Fazakas, 2009;Hegyi-Halmos, 2016;Kenderfi, 2019;Olteanu,
2022;Pogátsnik, 2018). This area often receives insufficient attention in the everyday practice of
public education in Hungary. In this situation, the question of whether (and how) career edu-
cation programs can be designed to develop certain CMC elements of students is of increased
importance. Regardless of the current situation of career guidance for school-age learners in
other countries, this question is of concern to many authors around the world. Several inter-
national studies confirm the effectiveness of career education interventions in schools.
Folsom (2005) reviewed 50 studies on the effectiveness of career courses offered in US higher
education, 90% of which showed positive effects in career planning, career decision-making,
career ability, professional identity, internal locus of control, and professional/career develop-
ment maturity.
A review of a larger number and variety of publications from our research shows the purpose
of experimental career training courses accompanied by impact measurement. The following
typical examples can be mentioned at the level of secondary and higher education without
claiming to be exhaustive. We limit ourselves to relatively short courses of a few days, up to
a maximum of one semester (and do not look at comprehensive and complex solutions imple-
mented across education systems in different countries). The majority of researchers are satisfied
with finding a significant improvement without examining the effect size. Where effect sizes are
identified, they tend to be small, which is not surprising for such limited interventions. A more
detailed overview of the cited literature sources can be found in Appendix.
Enhancement of career decision-making skills (Lam & Santos, 2018;Miles & Naidoo, 2017;
Reese & Miller, 2006;Wei, 2021);
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Positive impact on school-to-work transition (Jackson & Wilton, 2016;Koen, Klehe, & Van
Vianen, 2012;Sávoly & Dost, 2020);
Enhanced self-efficacy and confidence (Falco & Summers, 2019;Glessner, Rockinson-Szap-
kiw, & Lopez, 2017;Shea, Ma, Yeh, Lee, & Pituc, 2009;Török, 2016);
Career development competencies enhancement (Jackson & Wilton, 2016;Kim & Lee, 2023;
Scott & Ciani, 2008;Wei, 2021);
Emotional intelligence and well-being improvement (Di Fabio & Kenny, 2010;Freeman,
Lenz, & Reardon, 2017;Glessner et al., 2017;Sullivan & Mahalik, 2000);
Reduction in career indecision and anxiety (Olteanu, 2022;Shea et al., 2009;Sullivan &
Mahalik, 2000;Thrift, Ulloa-Heath, Reardon, & Peterson, 2012);
Improved career decision states and commitment (Babarovic, Devic, & Blazev, 2020;Miller,
Osborn, Sampson, Peterson, & Reardon, 2018;Peng, 2001);
Enhanced life satisfaction and adaptability (Ferrari, Nota, & Soresi, 2012;Gulsen, Secim, &
Savickas, 2021;Sávoly & Dost, 2020).
RESEARCH QUESTIONS
The present research is part of a larger project, which aims to answer the following three
research questions:
RQ-1: What are the relationships between students’background characteristics and the career
orientation variables used, in particular students’career decision state, their level of career
management competence, and their career choice uncertainty and difficulties in the sample
studied?
RQ-2: Can the available data identify students who need more intensive career guidance support?
RQ-3: Can the career orientation characteristics of students be improved by a 12-session career
education program, and what differences and patterns emerge?
The results related to the first two research questions above have been reported in a previous
publication. In that paper, we identified several specific difficulties faced by high school students and
identified groups that need more intensive career guidance support (Pálvölgyi, 2022). The present
study focuses exclusively on the third research question. Based on previous observations, experience,
and the goal-oriented design of the intervention used, the hypotheses related to RQ-3 are:
H-3-1: There will be a significant improvement in the student’s assessed career orientation
characteristics compared to baseline, and control group, even six months after the
intervention.
H-3-2: There are no significant differences in the impact of the intervention according to the
demographic variables examined and the level of students’academic achievement.
METHODS
This section describes the sample, the questionnaires and variables used, and the career educa-
tion program whose impact was studied.
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Sample
Using a quasi-experimental design, measurements were taken in a pre-test in February 2022 and
a post-test in December 2022, six months after the intervention, which was completed in June
2022. Participants were 10th and 11th-grade Hungarian high school (ISCED 344) students who
had already reached 11th and 12th grade at the time of the post-test.
As we could not oblige any institution to participate in the research, we worked with high
schools that showed a willingness to cooperate (volunteer sampling). The pilot (experimental)
group and the control group were organized in two different but otherwise very similar schools.
Both schools were medium-sized four-grade high schools in various outlying residential districts
of the capital on the Pest side, with very similar average scores on the National Assessment of
Basic Competencies (NABC) having very similar average family background indicators. Only a
very small difference is detected for the latter two values, and this is in favor of the control
group. On this basis, both schools can be considered approximately average Hungarian high
schools in a large city. The sample characteristics are summarized in Table 1.
Variables and tools
The unit of analysis is the student in this study. The pre-test and post-test data were collected
using online questionnaires. Below is a brief description of the independent and dependent
variables.
The independent (background) variables are gender, age, and grade of the student; academic
performance average of the previous year; father’s and mother’s educational attainment (highest
level of education with five response options).
In the first part of the survey, a self-developed career orientation questionnaire was used to
collect data on several dependent variables, including certain CMC components. In contrast
to other similar questionnaires, the assessment of the level of competence is not based on
subjective self-assessment, but on knowledge assessment and task solving, i.e. it is not aimed
at estimating the perceived competence, but the actual possessed CMC concerning the compe-
tence elements under examination. The questionnaire was piloted in December 2021, when
27 students at a high school in Budapest not participating in the study completed it (with
discussion of questions in some cases).
Table 1. Sample characteristics
Characteristics Pilot group Control group
Headcount pre-test 100 106
Headcount post-test 92 96
Female (%) 64% 54%
Age group (year) 15–19 16–21
Age M/SD (year) 17.44/0.93 17.61/0.93
Upper cohort (grade 11/12) (%) 50% 48%
Academic performance (1–5) M/SD 3.97/0.56 3.99/0.51
National Assessment of Basic Competencies
(NBAC) school mean aggregated scorep
1,666 1,695
Family background index school mean value p0.53 0.55
pSource: National Assessment of Basic Competencies (NABC) 2021 10th grade site database.
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All dependent variables used in the study are collectively referred to as career orientation
variables and are listed below:
Career orientation activity. Based on a one-item question: “Have you gathered information/
experience through the following activities?”The respondent could tick any of the 12 activities
listed and could also tick any other activity. The value of the variable is the number of activities.
Career decision state (process progress). Six questions were asked about the further education
and career path envisaged, and a composite indicator was formed based on all the answers,
considering how confident the respondent was in his/her answers (five-point Likert scale).
A higher value indicates a more precise and confident vision.
Career choice awareness. This variable tries to describe the soundness of the link between
preferred career direction and self-awareness (applied self-awareness, based on 4 items).
Example: the previous question asked what the respondent thinks his/her occupation will be
at the age of 30. This question takes this further: “If you have indicated an occupation here,
could you explain why this is?”(Open question)
Career decision self-efficacy (confidence). Based on a one-item question: “When I think about
the fact that I will have to decide in grade 12 how my life will develop after finishing high school
(further education, career choice), I am confident that I will be able to make a good decision.”
Answer on a 9-point Likert scale (1 5not at all true for me; 9 5absolutely true for me).
CMC components. Nine items deal with different elements of CMC, using a variety of
questioning techniques. This composite indicator is based on the answers and solutions, with
a higher score value indicating a higher level of competence. Example: “Your classmate asked
you, which are the best places on the Internet to find useful information on career opportunities,
further education, and/or self-awareness. Which websites would you recommend?”
The next part of the questionnaire consisted of the Hungarian version of the CFI Career
Factors Inventory (Chartrand et al., 1990), adapted by Lukács (2012). The following dependent
variables were derived from the subscales of the questionnaire:
Career choice anxiety (5 items, five-degree semantic differential scale)
Generalized indecisiveness (3 items, five-degree semantic differential scale)
Need for career information (5 items, five-point Likert scale indicating the level of agreement)
Need for self-knowledge (4 items, five-point Likert scale indicating the level of agreement)
The last part of the questionnaire was made up of the Hungarian version of the CDDQ
Career Decision-Making Difficulties Questionnaire (Gati, Krausz, & Osipow, 1996) adapted by
Olteanu (2022). Each question is answered using a nine-point Likert scale (1 5not at all
characteristic of me; 9 5well characteristic of me). A higher value of the variable in each case
indicates a higher level of difficulty. Some of the variables below overlap to some extent with one
or other of the variables in the CFI questionnaire. This could not be avoided in this case, but it
helps to assess the validity of the data collection. The following dependent variables were derived
from the ten subscales of the questionnaire:
Readiness
◦Lack of motivation (3 items)
◦General indecisiveness (3 items)
◦Dysfunctional beliefs (4 items)
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Lack of Information about
◦The decision process stages (3 items)
◦Self (4 items)
◦Occupations (3 items)
◦Ways of obtaining additional information (2 items)
Difficulties related to Inconsistent Information
◦Unreliable information (3 items)
◦Internal conflicts (5 items)
◦External conflicts (2 items)
In addition to the above, an extra variable is the response to the CDDQ’sfinal summative
one-item question on how difficult the respondent finally feels in making a career choice
(9-point Likert scale).
Intervention
The career education program aimed to develop certain elements of the CMC and, in connec-
tion with this, to support current career orientation activities, to help students explore the
further education path, and to increase their self-awareness. It was designed with a lifelong
guidance approach, following active learning (Bonwell & Eison, 1991) based understanding of
learning and teaching. The content was based on the concept of CMC expressed in the DOTS
model (Law & Watts, 1977). The sessions covered topics such as self-awareness, career aware-
ness, further learning opportunities, exploration methods, and steps and difficulties of career
decision-making. We have tried to design the targeted outcomes to fit the cognitive items of the
measurement tools used. The design aimed to be consistent with the career construction theory
(Savickas, 2005); and Lent, Brown, and Hackett’s (1994) social cognitive career theory.
The classroom course consisted of 12 sessions and ran from February to June 2022.
The 45-min sessions took place during selected class teacher lessons for the whole participating
class and were conducted by the program developer researcher, partly with the assistance of two
graduate students in education (teaching team). A mixed method approach was applied, using
short teacher and student presentations, discussions, Kahoot quizzes, individual and pair work,
games and exercises, online exploration, watching and discussing videos, etc. The class work was
mainly based on small groups formed permanently according to the student’s interests, to allow
the group members to get to know each other better and to give feedback to each other at the
end of the program.
The work was completely paperless, using only digital media. The learning aids and multi-
media content for each session were available in a Google Classroom system. All 100 students
from the two cohorts and four classes were registered in the same Classroom. Group works were
also uploaded to the common Classroom interface, alongside regular news and communication
on the message board. In addition, the individual classes and the groups within them used
exclusively their own Google Drive platforms and documents for their work. Pupils used school
tablets and their smartphones via the school Wifi network.
In the final part of the program, each group carried out a mini-project, in which they
completed self-awareness tests available on the Internet, and used the knowledge gained in
the sessions to identify the further education and career paths that suited their interests.
In the final session, they gave short presentations on their ideas for further education and
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careers at the start of the program, what they have done since then, what their current (not yet
final) ideas are, and what they plan to do in the next period.
The project work was supported by a detailed individual digital workbook, which can be used
as a guide for self-awareness and individual career exploration work, with several practical
instructions and fillable templates. Here, pupils could record their notes and results on an
ongoing basis, exclusively for themselves, using information, tools, and opportunities available
on the Internet. Students were given many tips to help them with their career guidance, various
additional experiential activities were suggested during the sessions, and individual counseling
was offered. However, there was little demand (8%) for the latter.
In particular, several difficulties were encountered during the first sessions. Logistical diffi-
culties have arisen, partly due to increased demand for digital equipment. The external teaching
team had no local knowledge and did not know the students. It was unrealistic to expect to learn
the names of many pupils in relatively few sessions. The course would have benefited from a
90-min double-hour schedule, which was not feasible. Based on initial feedback and suggestions
from class teachers and students, the methods used were modified to increase the proportion of
practical sessions, further increasing interactivity and group work.
Ethical permission
The Research Ethics Committee of ELTE Faculty of Education and Psychology permitted the
research under No. 2021/480-2.
RESULTS
Statistical analyses were performed using IBM SPSS Statistics Version 28. The first step was to
examine the distribution of the dependent variables. The Kolmogorov-Smirnov test did not
confirm the normal distribution of any variable. For the CFI Career Factors Inventory and
the CDDQ Career Decision-Making Difficulties Questionnaire tests, we also estimated the
McDonald’s Omega values, in addition to the usually estimated Cronbach’s alpha values, there-
fore. The two reliability measures showed very similar values, ranging between 0.691 and 0.943,
i.e. they can be judged as acceptable. The only exception is the CDDQ Dysfunctional Beliefs
subscale with an Omega value of 0.587. Although this value cannot be judged as critical, since
there are only four items in the scale, we argue here that a high value cannot be expected when
judging different beliefs, since one is less dependent on the other, and so a lower value does not
indicate poor reliability. (For two subscales of the CDDQ questionnaire, Mcdonald’s Omega
value could not be estimated, because the number of items is less than three.)
The pre-test measured the baseline condition at the beginning of the intervention. The two
groups also appeared quite similar in terms of the dependent variables. Using the Mann-Whitney U
Test for independent samples, only three of the 20 dependent variables tested were significantly
different. Two of those were to the detriment of the pilot group. As shown in Table 2, these were the
Career orientation activity and the CMC components variables. The third variable showed a slight
difference in favor of the experimental group, but this is not considered relevant as no significant
change was subsequently observed for this variable in either group between pre- and post-test.
Table 3 gives an overview of all pre-test and post-test results for the pilot group. 13 variables
show significant change compared with the baseline. Higher mean values are better for the first
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five variables, while lower mean values are considered more favorable for the CFI and CDDQ
variables. The direction of change is favorable in all cases except for the CDDQ external conflicts
variable. Based on Cohen’sdvalues, the changes with the largest effect sizes are in decreasing
order for Career orientation activity, CMC components, Career decision self-efficacy, and
CDDQ dysfunctional beliefs.
As seen in Table 4, significant changes also occurred in the control group in the 11 months
between the two tests in terms of Career decision state and CFI career information need. Both
Table 2. Significant pre-test differences
Variables
Pre-test
Pilot group Control group Mann-Whitney
M SD M SD U dp
Career orientation activity 2.80 1.77 3.49 1.59 3,845 0.421 0.003
CMC components 3.30 1.90 3.92 2.15 4,162 0.307 0.031
CDDQ gen. indecisiveness 5.24 2.01 5.93 1.98 3,394 0.104 0.026
Legend: M5mean, SD 5standard deviation, U 5Mann-Whitney U value, d5Cohen’sdeffect size,
p5level of significance. (N5206).
Table 3. Pre-test versus post-test results of all variables for the pilot group
Variables
Pilot group
Pre Post Mann-Whitney
M SD M SD U dp
Career orientation activity 2.80 1.77 3.68 1.88 5,721 0.432 0.003
Career decision state 2.61 1.65 3.14 1.54 5,408 0.332 0.023
Career choice awareness 1.39 1.36 1.85 1.37 5,966 0.301 0.030
Career decision self-efficacy 5.79 2.44 6.73 2.10 5,942 0.399 0.005
CMC components 3.30 1.90 4.45 2.66 5,847 0.408 0.005
CFI career choice anxiety 2.73 1.06 2.42 1.12 3,656 0.301 0.041
CFI gen. indecisiveness 2.92 0.92 2.92 1.04
CFI career information need 3.59 0.69 3.32 0.80 3,485 0.369 0.013
CFI need for self-knowledge 3.57 1.15 3.22 1.29
CDDQ lack of motivation 3.48 1.75 3.14 1.43
CDDQ gen. indecisiveness 5.24 2.01 5.12 1.86
CDDQ dysfunctional beliefs 4.69 1.36 4.11 1.39 2,661 0.398 0.012
CDDQ lack of inf. dec. process 4.41 2.26 3.73 1.85 2,813 0.319 0.042
CDDQ lack of inf. on self 4.16 2.23 3.90 1.99
CDDQ lack of inf. occupations 4.57 2.10 3.89 1.87 2,752 0.350 0.026
CDDQ lack of add. information 3.84 2.06 3.19 1.69 2,818 0.316 0.043
CDDQ unreliable information 3.54 1.84 3.86 1.88
CDDQ internal conflicts 3.88 1.82 3.98 1.71
CDDQ external conflicts 3.17 1.90 3.87 1.95 4,156 0.365 0.019
CDDQ summary of difficulties 5.85 2.18 5.19 2.10 2,810 0.320 0.040
Legend: see Table 2.(N592).
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variables changed here in a favorable direction. Finally, Table 5 shows the significant differences
between the two groups at the time of the post-test measurement. In the first five cases, the
values of the pilot group are more favorable, while in the last case, the control group’s value is
better (CDDQ external conflicts).
Spearman’s correlation test revealed no significant relationship between the independent
variables listed above and the changes in the 20 dependent variables for the pilot group. Some
exceptions are the following weak correlations. Students with lower academic achievement
showed some greater reduction in difficulty with unreliable information (rho 50.205;
p50.044). For the lower educational attainment of the father. difficulty with general indeci-
siveness (rho 50.279; p50.007) and difficulty with lack of information about occupations
(rho 50.220; p50.035) were more reduced; while lower mother’s education was associated
with some greater reduction in CFI generalized indecisiveness (rho 50.228; p50.034). These
small differences may also be related to the fact that there is more room for improvement for
variables with a less favorable initial value.
DISCUSSION
The effectiveness of the intervention is supported by the fact that a dozen of the 20 dependent
variables changed positively in the case of the experimental group, while only two significant
Table 4. Significant differences between pre-test and post-test results for the control group
Variables
Control group
Pre Post Mann-Whitney
M SD M SD U dp
Career decision state 2.54 1.48 2.99 1.33 5,315 0.316 0.031
CFI career information need 3.55 0.68 3.30 0.77 3,161 0.366 0.016
No significant differences were found for other variables not shown here.
Legend: see Table 2.(N596).
Table 5. Significant post-test differences
Variables
Post test
Pilot group Control group Mann-Whitney
M SD M SD U dp
Career choice awareness 1.85 1.37 1.40 1.28 5,206 0.313 0.031
Career decision self-efficacy 6.73 2.10 5.39 2.49 5,694 0.515 0.000
CMC components 4.45 2.66 3.47 1.92 5,175 0.345 0.020
CFI career choice anxiety 2.42 1.12 2.98 1.14 2,793 0.494 0.001
CDDQ gen. indecisiveness 5.12 1.86 5.83 2.00 3,600 0.295 0.025
CDDQ external conflicts 3.87 1.95 3.05 2.24 3,837 0.434 0.007
No significant differences were found for other variables not shown here.
Legend: see Table 2.(N5188).
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positive changes were observed in the control group between the two tests. However, all the
effect sizes for the significant changes in Table 3 are small, based on the usual interpretation of
Cohen’sdvalues. This magnitude is in line with what the Whiston, Yue Li, Mitts, and Wright
(2017) meta-analytic study considers to be the usual average for this type of intervention. The
small effect size is not surprising half a year after the end of the intervention, which consisted of
only 12 sessions. The change had the largest effect sizes in the case of the two variables in which
the pilot group was significantly at a disadvantage during the pre-test.
What do the variables that have not changed significantly tell us? Due to the nature of the
CFI indecisiveness and CDDQ generalized indecisiveness variables, no such change can be
expected in these cases. The other two similar variables, the CFI need for self-knowledge and
the CDDQ lack of information on self, decreased in value but not significantly. It seems that
such a short intervention is not sufficient to achieve lasting significant results in the area of
self-awareness. The situation is similar for the CDDQ lack of motivation variable. The latter is
unfortunate because the initial focus of the educational intervention could logically be on
increasing career orientation activity and related motivation. The former was better achieved.
Since there has been a change, the results are interpreted as suggesting that a longer, well-
distributed, and well-implemented program using active learning and experiential pedagogical
methods would significantly improve motivation for a similar group of learners.
The CDDQ external conflict variable shows a different behavior from the above, as its value
significantly worsened for the pilot group. In our opinion, external and internal conflicts typi-
cally occur in the decision-making process when this process has already progressed, and
therefore we consider this change as a possible sign of progress, i.e. in our interpretation it does
not necessarily contradict the overall picture painted by the other results. Consistent with what
has been said, the values of the CDDQ internal conflicts and the CDDQ unreliable information
variables, which are of the same nature, did increase, but not significantly.
Between the two tests, the control group had no major career guidance programs or activities
organized at the school or class level. As seen in Table 4, the following two control group
variables changed positively: the progress of the career decision state, and the need for career
information measured by CFI. (CDDQ also has a similar subscale reflecting a lack of informa-
tion about occupations, and its value has also decreased, but not significantly.) Both significant
control group variable changes point to a slow progression in the decision-making process,
based on some exploration of further education and career choices. By the time of the post-test,
the upper cohort had generated this trend as they approached the important decision point of
submitting their applications for further education in February 2023. They show significant
differences between the pre-test, and post-test, while the lower cohort does not, as shown by
independent-samples Mann-Whitney U test results (control group upper cohort career decision
state: Cohen’sd50.533; U 51,482; p50.011; and CFI need for career information: Cohen’s
d50.566; U 5580; p50.013).
The significant differences found in the post-to-post comparison (Table 5) support the
overall picture. Taking into account the results of the control group, it cannot be concluded
that the changes in the two above discussed variables were caused by the intervention. For the
remaining ten variables, however, it can be claimed. Our first hypothesis was therefore partially
fulfilled.
The results of the Spearman correlation test suggest that the effectiveness of the pilot course
is essentially independent of factors such as gender, age, academic performance, and the father’s
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and mother’s education, which is an important beneficial feature of the intervention. Our second
hypothesis is therefore fulfilled.
CONCLUSION
Our previous study has shown that many high school students have poor career management
competence (CMC) and many need increased differentiated support based on unfavorable
scores on examined career orientation variables (Pálvölgyi, 2022). The present study has shown
that a relatively short intervention in a realistic school setting may already be capable of
achieving demonstrable lasting improvement on a range of important career orientation
variables. In particular, significant and lasting improvements were achieved in certain CMC
knowledge and skills-related variables, while career choice anxiety decreased. The mixed method
classroom intervention was embedded as a kind of supplementary mini-curriculum in the
school timetable for 10th and 11th grade high school students, which was perceived differently
by individuals, but mostly positively according to the different feedback.
Only a few similar studies are using Hungarian samples (see Appendix). What makes this
study unique is the wide range of variables used and the fact that it is not based solely on
self-assessment, but also includes knowledge and skills tests for some CMC items. Another
distinctive feature is that the impact of the intervention was examined over a six-month time
horizon. The lasting, albeit small, effect on the ten variables can be considered an important
result, which could pave the way for the dissemination of similar programs in Hungarian high
schools.
We suggest that this program should not be implemented on a campaign basis, as was done
in the research, but spread over several years, thus ensuring the necessary continuity of career
orientation. A class teacher who knows the students well and schedules the different sessions at
the right times can be much more successful than the current teacher team of this pilot program.
Career guidance should become a permanent focus of class teachers’educational work, to which
subject teachers can also make important contributions, e.g. by using active learning methods
(such as project-based learning). School psychologists, career guidance services, professional
civil society organizations, parents, and companies can provide additional valuable support. It
would be advantageous if the heads of institutions were given more room for maneuver to
sometimes use competent external service providers for certain activities and programs. Sup-
porting career guidance and career education could be an important evaluation aspect in the
internal performance evaluation system for teachers to be introduced in the near future in
Hungary.
The limitation of our research is that it is not based on a nationally representative sample.
Nevertheless, the schools included can be considered fairly average in terms of their main
parameters. The intervention was based on a combination of several methods, but we did not
test the effectiveness of each of the components separately. We also did not investigate whether
there might be other methodological approaches or combinations of methods that could lead to
better results. The study could be extended in this direction, although it is worth noting that
Mackay, Morris, Hooley, and Neary (2015) highlighted in their meta-analysis that combining
several intervention methods is generally more effective than using only one. It would be
worthwhile to further develop the program based on the experiences, feedback, and suggestions
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of teachers and students, and to test its effectiveness with other age groups, and in more schools.
The enhanced version could become a supplementary career education program officially rec-
ommended for Hungarian high schools. The final step could be to increase the number of such
sessions and activities in their compulsory curricula, after proper preparation.
ACKNOWLEDGEMENT
I would like to thank Mr. Tibor Bors Borbély-Pecze Ph.D. (Institute of Research on Adult
Education and Knowledge Management, ELTE Eötvös Loránd University, Budapest, Hungary)
for his guidance in researching the theoretical aspects of lifelong guidance.
ABOUT THE AUTHOR
Lajos Pálvölgyi is external member of the Research Group on Higher Education and Innovation
at the Institute of Education, ELTE Eötvös Loránd University, and managing director of PRO-
JECON Project Consulting Ltd. His research interests are related to educational innovation,
project-based learning and career education.
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Appendix
Typical examples of career education courses accompanied by impact measurement
References Target group Intervention Results
Babarovic et al.
(2020)
Eighth-grade
middle-school
students (Croatia)
School program (interests,
skills, work values,
learning about the labor
market and secondary
schools, career planning,
decision making) (eight
45-min group workshops)
Career readiness and career
decision-making
independence improved
along with the shortage
of career information.
Di Fabio and Kenny
(2010)
High school students
(Italy)
Training program to improve
learners’emotional
intelligence using an
ability-based model (four
weekly 2.5-h sessions)
Emotional intelligence
increased and perceived
indecisiveness and career
decision difficulties
decreased
Falco and Summers
(2019)
Girls attending a
medium-sized
public high school
(Arizona)
Nine 50-min group sessions
designed to improve
career decision
self-efficacy and STEM
self-efficacy
Positive impact on
participants’career
decision self-efficacy and
STEM self-efficacy (with
moderate to large effect
sizes)
Ferrari et al. (2012) Italian adolescents
are selected
according to their
level of career
indecision and
poor future
orientation
Structured 10-didactic unit
intervention to promote
learners’orientation
towards the future, learn
about the current world
of work, elevate career
determination (ten
weekly 2 h)
Increased time perspective,
continuity, hope, and
career decidedness as
compared to controls
Fouad, Cotter, and
Kantamneni
(2009)
Students at a large
Midwestern urban
university, mainly
freshmen (U.S.)
A semester-long career
exploration course entitled
“Foundations of Academic
Success: Planning Your
Majorand/orCareer"
Students’career decision-
making difficulties
decreased, career
self-efficacy increased,
and perceptions of
barriers did not change
Freeman et al. (2017) Undergraduate
college students
(Florida)
A theory-based,
comprehensive career
development course
during a 16-week semester.
Significant positive effect on
career decision and
affective states
Glessner et al. (2017) Middle school
students (Florida)
Workshop of the Florida
Choices program including
virtual career exploration
activities and a local college
campus tour (4 days)
Higher levels of college and
career self-efficacy than
controls
(continued)
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Continued
References Target group Intervention Results
Gulsen et al. (2021) Ninth-grade high
school students
(Northern
Cyprus)
Psychoeducational
course(career construction
processes, self-exploration,
career adaptability, future
orientation, narrative
identity and life
satisfaction) (five
60–75-min sessions)
Significant increases in
scores on all measures
(Design my future scale,
Career adaptabilities
scale, Satisfaction with
life scale)
Jackson and Wilton
(2016)
Business
undergraduates
(UK and
Australian
universities)
Work-integrated learning
program (with part-time
or full-time work in
industry)
Positive impact on career
management
competencies,
development of
self-awareness,
opportunity awareness,
decision-making
learning, transition
learning
Kim and Lee (2023) High school students
in Korea
The goal of the study is to
estimate the effectiveness
of career education
programs offered by high
schools
Career clubs and career
experience programs
were identified as
effective in enhancing
students’career
development
competencies
Koen et al. (2012) Graduates about to
transition from
school to work
One-day intensive training
for career adaptability
(in groups of 15 people
with two instructors)
Improved school-to-work
transition, increase in
concern, control, and
curiosity in the long run
Lam and Santos
(2018)
First-year Malaysian
college students
College career educational
course (4 sessions, 2 h
each)
Greater career decision-
making self-efficacy and
certainty; lower career
decision-making
difficulties
Miles and Naidoo
(2017)
South African Grade
11 learners with
diverse socio-
economic
backgrounds
Career intervention
program derived from
social cognitive career
theory designed for the
South African context
(six 1.5-h sessions)
Increased career maturity
expressed in enhanced
career decision-making
self-efficacy (medium
effect)
Miller et al. (2018) Undergraduate
university
students
(Southeastern
United States)
Comprehensive 3-credit
career course influenced
by cognitive information
processing theory
Progress in career decision
states; more certainty
about occupational
choice, and confidence
about the process of
decision making.
(continued)
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Continued
References Target group Intervention Results
Olteanu (2022) Hungarian 10–12.
grade high school
students
Decision-making training
for choosing a career and
further education
(decision-making
process, self-knowledge,
self-reflection) (twelve
45-min lessons)
Positive effect on general
indecisiveness, career
anxiety, need for
self-knowledge, and lack
of information on the
decision process
Osborn, Howard,
and Leierer (2011)
Racially and
ethnically diverse
college freshmen
(Florida)
1-credit-hour career
development course with
lectures, interactive
group activities, reflective
homework exercises,
reading assignments
(6 weeks)
Freshmen with the highest
level of dysfunctional
career thinking indicated
the most dramatic
decrease (reductions
occurred irrespective of
students’gender or race/
ethnicity)
Peng (2001) College freshmen
(Taiwan)
Two different career
education courses
(cognitive restructuring
intervention and career
decision skills training)
Improved career decidedness
compared to the control
group (without significant
differences between both
experimental groups).
Reese and Miller
(2006)
University students
(Texas)
Career development course
designed to help
undecided students with
career decision-making
Increased career decision-
making self-efficacy
(obtaining occupational
information, setting
career goals, career
planning); lower
perceived career decision
difficulties.
Sávoly and Dost
(2020)
Senior-year
university
students in Turkey
Career educational course
adopting a school-to-
work transition skills
program developed in
the USA
(12 sessions, 90 min
each)
Positive impact on school-
to-work transition,
higher career
adaptability, and career
optimism
Scott and Ciani
(2008)
Undergraduate
students attending
a large
Midwestern
University (U.S.)
A semester-long one-credit-
hour voluntary career
explorations course
(occupational interests,
decision making)
Increased adaptive
self-efficacy beliefs and,
a stronger sense of
vocational identity.
Especially effective for
increasing women’s
judgments of efficacy for
career planning and
problem-solving.
(continued)
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Continued
References Target group Intervention Results
Shea et al. (2009) Low-income, urban
Chinese
immigrant youth
School-based, culturally
responsive career
exploration and
assessment group
intervention for
increasing career
self-efficacy
Decrease in career
indecision; increases in
academic, career, college
help-seeking, and career
decision-making
self-efficacy; increase in
career decision-making
making, collective
self-esteem.
Sullivan and Mahalik
(2000)
Women enrolled in
three universities
in New England
Career group intervention
designed to increase
career-related self-
efficacy for women
(6 weeks)
Increased career decision-
making self-efficacy,
vocational exploration, and
commitment for women
(and maintained those
gains at 6-week follow-up)
Talib, Salleh, Amat,
Ghavifekr, and
Ariff (2015)
Community college
students in
Malaysia
Career education course
(9 sessions, 2 h each)
Positive effect on career
development (career
planning abilities, self-
efficacy, and career
maturity)
Thrift et al. (2012) Pacific Island college
students
Classroom course focusing
on individuals’career
interests and
dysfunctional thoughts
using the Career
Thoughts Inventory
Workbook (4 sessions)
Lowercareerdysfunctional
thoughts, reframe negative
statements into positive
statements, positive effect
on decision-making
confusion and
commitment anxiety
Török (2016) Hungarian 10th and
11th grade high
school students
Three-hour group session
to increase self-efficacy
(reflection of own career
plans, commitment to
development) (groups of
12 people organized)
School self-efficacy and
career decision self-
efficacy increased
significantly, career
choice anxiety decreased
significantly
Wei (2021) Undergraduate
university
students (Taiwan)
College career course with
high-intensity and low-
intensity action-based
homework assignments
(18 weeks, 36 h)
High-intensity action-based
homework: better-
enhanced career
exploration (no difference
between the two groups in
terms of enhanced career
self-efficacy)
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