Career Development Learning and Employability Skills of Students

DOI: 10.7763/IPEDR. 2014. V70. 21
Career Development Learning and Employability Skills of Students in
Information and Communication Technology
Roberto T. Diamante
John Paul II College of Davao
Abstract. The study was carried out to determine the influence of career development learning on the
employability skills of ICT students utilizing non-experimental quantitative research design employing
descriptive-correlational method. The data were collected through universal sampling from 115 students
taking computer studies in John Paul II College of Davao using adapted close-ended questionnaire with fivepoint Likert’s scale. The statistics used to find the significance of the relationship between independent and
dependent variables is Pearson Product-Moment Correlation. Multiple Regressions was employed to identify
which among the domains of the independent variable best predicts the dependent variable. The findings
disclosed that the extents of career development learning of students as well as the level of their
employability skills were moderate and significant relationship of these variables existed. Further, there is
confirmation that career development learning is predictor of employability skills. This means that by
providing students with extensive support on career development learning, the higher is their chance of
attaining employable skills as a measure of global employment.
Keywords: Career Development Learning, Employability Skills, ICT Students, Likert’s Scale, Davao City.
1. Introduction
Career development learning and raising employability skills have emerged as an area for attention to
improve the transition from full-time education into employment [1]. In contrast, Bivand [2] averred that
education system does not supply enough people who are equipped with the skills that they need on job entry.
The commissioned research study of Purdon [3] provided evidences that demand for new skills is not
matched by supply, leading to an emerging skills deficit and insufficient employability skills. In the
Philippines, even though the country imposes the use of English as the medium of instruction and provides
job-enrichment programs, its graduates still lack communication and other employability skills [4]. In Davao
City, Cempron, et al. [5] found that there is a mismatch between the level of the human resources and the
extent of need of the call center and IT outsourcing sectors, in terms of employability (soft) skills and nontechnical attributes. These problematic situations prompted the researcher to investigate the plausible causes
or factors that would predict the employability skills of students in Information and Communication
Technology. Thus, making this institutional research as a welcome feat to students and a good fit to higher
education environment. The formulated research objectives are as follows:
To describe the extent of career development learning and the level of employability skills of ICT
students.

To determine the degree of association of career development learning on the employability skills of
ICT students.

To determine the degree of influence of the domain of career development learning on the domains
of employability skills of ICT students.
The research objectives are converted into null hypotheses and they are tested @ .05 Level of
Significance.



Ho1 There is no significant relationship between career developments learning on the employability
skills of ICT students.
Corresponding author. Tel.: + (082) 297-5586.
E-mail address: diamz_rtd888@yahoo.com.
110

Ho2 There is no domain of career development learning significantly influence on the domains of
employability skills of ICT students.
2. Methodology
The study employed non-experimental quantitative research design utilizing descriptive-correlational
technique. Quantitative methods attempt to maximize objectivity, replicability, and generalizibility of
findings, and are typically interested in prediction [6]. The respondents were 115 3rd year and 4th year
students, adopting universal sampling. The researcher adopted the research instrument from two sources. For
career development learning, the source was Association of Careers Advisory Services [7]. For
employability skills, the researcher adopted it from the framework of the Department of Education, Victoria,
Australia [8]. A five-point Likert’s scale was sued in determining the descriptive level of the variables. The
mean, standard deviation, Pearson (r) and regression were the statistical used for data treatment and analysis.
3. Results
3.1. Extent of career development learning
Table1: Extent of Career Development Learning of ICT Students
Domain
Mean
Descriptive Level
Self Awareness
3.24
Moderately Extensive
Opportunity Awareness
3.33
Moderately Extensive
Decision Making
3.37
Moderately Extensive
Transition Learning
3.20
Moderately Extensive
Overall
3.28
Moderately Extensive
As reflected in Table 1, the career development learning of students is moderately extensive. It could be
noted that the computed mean ratings fall between 2.50-3.49 with descriptive equivalent of moderately
extensive. This means that the ICT students are still in the developing stage of understanding the significant
bearing of Self- Awareness, Opportunity Awareness, Decision Making, and Transition Learning to their
future career. The moderate result is supplemented by the remarks of the Millennial Branding Company [9]
which stated that students are not aggressively preparing for their post-college careers. This is the reason
why students are struggling to find jobs because they fail to develop their careers while in college. Parrallel
to the idea of Daggette [10] who indicated that in reality, too few students are prepared for college or a career,
and even fewer are prepared for both. Students need the appropriate skills and knowledge for higher
education. They also need to know how to apply relevant skills and knowledge in an increasingly
sophisticated workforce.
3.2. Level of employability skills
As shown in Table 2, the result indicated moderate level for the employability skills of ICT students. All
domains are within the range of 2.50-3.49 or qualitatively described as moderate. This connotes that ICT
students are lacking of sufficient degree of proficiency in applying knowledge and understanding of
transferable skills as requirement for their future job entry. The moderate result is allied to the viewpoint of
Kantrowitz [11] who stressed out that insufficient preparation gives students a sense of not belonging and a
deficit in their own perspectives as academic beings when it comes to the skills most needed by employers.
He observed that students are lacking most in written and oral communication skills, adaptability and
managing multiple priorities, and making decisions and problem solving. Also, Robinson [12] denoted that
students are being ill-prepared to apply the transferable skills to their work is the fact that students often fail
to realize the importance of possessing transferable skills.
111
Table 2: Level of Employability Skills of ICT Students
Domain
Mean
Descriptive Level
Communication
3.20
Moderate
Teamwork
3.16
Moderate
Problem Solving
2.94
Moderate
Initiative and Enterprise
2.95
Moderate
Planning and Organizing
2.99
Moderate
Self-Management
3.35
Moderate
Learning
3.36
Moderate
Technology
3.46
Moderate
Overall
3.18
Moderate
3.3. Correlation between variables
Table 3: Correlation between Career Development Learning and Employability Skills
Employability
Skills
Career Development Learning
SA
OA
DM
TL
Overall
Communication
.480*
(.000)
.508*
(.000)
.558*
(.000)
.682*
(.000)
.637*
(.000)
Teamwork
.022
(.854)
.135
(.252)
.038
(.749)
.165
(.160)
.106
(.369)
Problem Solving
.532*
(.000)
.482*
(.000)
.638*
(.000)
.598*
(.000)
.641*
(.000)
Initiative and Enterprise
.473*
(.000)
.518*
(.000)
.567*
(.000)
.648*
(.000)
.631*
(.000)
Planning and Organizing
.402*
(.000)
.460*
(.000)
.601*
(.000)
.527*
(.000)
.527*
(.000)
Self-Management
.502*
(.000)
.583*
(.000)
.644*
(.000)
.700*
(.000)
.696*
(.000)
Learning
.587*
(.000)
.627*
(.000)
.668*
(.000)
.649*
(.000)
.722*
(.000)
Technology
.629*
(.000)
.682*
(.000)
.662*
(.000)
.755*
(.000)
.778*
(.000)
Overall
.619*
(.000)
.682*
(.000)
.747*
(.000)
.811*
(.000)
.818*
(.000)
Legend: SA – Self Awareness; OA – Opportunity Awareness; DM – Decision Making;
TL – Transition Learning
*Significant at p<.05
112
From Table 3, the correlation between career development learning and employability skills bear
significant relationship because the probability value of .000 (p<.05) lower than .05. This implies that career
development learning is a function of employability skills. This connotes further that the higher career
development learning of students will apparently increases their employability skills. Evidently, the result
that there is significant relationship between career development learning and employability skills supports
the theory of Gottfredson [13] which states that career development is a process requiring a high level of
cognitive proficiency. He viewed career development as a self-creation process in which individuals looked
for avenues or niches to express their employability proclivities within the boundaries of their own cultural
environment.
3.4. Influence of career development learning and employability skills
Table 4: Regression Analysis on Career Development Learning and Employability
Predictor
Variable
Self Awareness
Opportunity Awareness
Career Development
Learning
Decision Making
Transition Learning
R2= .719
F= 44. 205
ß
Coefficient
.088
-.020
.322
.540
tvalue
.945
-.178
3.121
5.216
p
value
.348
.859
.003*
.000*
p-value = .000
The regression in Table 4 shows the computed R-value of .848 and R2 value of .719 with adjusted R2
of .703 and standard error of the estimate equivalent to .26317. The adjusted R2 value of .703 is evident that
career development learning influences the employability skills by 70.3%. The difference of 29.7% is
accredited to other factors not covered in the current study. However, the ANOVA model shows the
computed F-value of 44.205 with the corresponding probability value of .000 lower than .05 level of
significance, then the null hypothesis that there is no domain of career development learning best predict the
employability skills is rejected in favor to the alternative hypothesis that there is domain of career
development learning best predict the employability skills.
To elaborate further the details of the results based on the coefficients table, the indicator Self-Awareness
is not predictor of employability skills with  coefficient of .088, t-value of .945 and probability value
of .348. In the same manner, the indicator Opportunity Awareness is likewise not a predictor of
employability skills with  coefficient of -.020, t-value of -.178 and probability value of .859. Nevertheless,
the indicators Decision-Making and Transition Learning are considered as best predictors of employability
skills. Decision-Making has  coefficient of .322, t-value of 3.121 and probability value of .003. While
Transition Learning has  coefficient of .540, t-value of 5.216 and probability value of .000. Thus, the higher
the  coefficient values have in Decision-Making and Transition Learning the greater their impact on the
employability skills of students in ICT.
4. Discussion and Conclusion
The results of this study show moderate career development learning and employability skills. This
purports that the underlying concepts, observations and principles of some authors presented earlier in this
paper are legitimate. Hence, this study affords concrete stand for higher echelon in this institution to find
reasonable initiatives for the development of ICT platforms by consulting higher education stakeholders
including renowned colleges and universities for Center of Excellence in ICT Education, business and
industry to review and identify best practices for integrating, developing, teaching, assessing and reporting
career development learning as a function and influential factor of employability skills. In this good
judgment, it is fitting that academic leaders initiate by engaging business sectors and industries in crafting of
113
a best practice framework of new curricular activities and programs in computer studies. The articulation of
curriculum mapping in computer studies enable the curriculum implementers to attune teaching approaches
for digital learners and to refine teaching philosophy which contribute to the overall goals of providing
quality education to students package with attributes on employable skills, technical knowledge, and
student’s lifelong capacity to act as a professional, responsible citizen and research-oriented learner.
5. Acknowledgment
This research study was funded by John Paul II College of Davao, Davao City, Philippines.
6. References
[1] R. Simmons. Entry to employment: discourses of inclusion and employability in work-based learning for young in
Journal of Education and Work, 2009. 22(2): 137 – 151.
[2] P. Bivand. The Impact of Devolution: Employment and Employability. Report for the Joseph Rowntree
Foundation, Joseph Rowntree Foundation, York, 2010. Retrieved May 18, 2013
http://www.jrf.org.uk/sites/files/jrf/impact-of-devolution-employment.pdf
[3] C. Purdon. Activity Agreement Pilots: Quantitative evaluation. London, Department for Children, Schools and
Families. Employability: rapid review Blades, Fauth and Gibb www.ncb.org.uk page 39 © National Children’s
Bureau, 2009.
[4] Seameo Innotech. Employability of Philippine IT graduates. Research Updates. Diliman, Quezon City, 2013.
[5] M. D. Cempron, H. E. Gementeza, J. A. Gorro, S. M. C. Navales, A. G. Reyes, and R. I. Talaboc. ICT SkillsIndustry Matching in Davao City. Undergraduate Thesis, University of Southeastern Philippines, Davao City.
Philippines, 2008.
[6] J. W. Creswell. Educational research (3rd ed.). Thousand Oaks, CA: Sage, 2007.
[7] Association of Graduate Careers Advisory Service. Career education learning outcomes. AGCAS, Sheffield,
England , 2005.
[8] Victoria Department of Education. Handbook for employability skills. Australia, 2006.
[9] Millennial Branding Company. Few have internships, are marketing themselves on LinkedIn and are engaging in
professional development activities. Boston, M A., 2012.
[10] W. Daggett. Preparing students for their technological future. 2010. Retrieved September 16, 2013 from
http://www.leadered.com.
[11] J. Kantrowitz. Many college students lack needed tech skills. Educational research report. 2010. Retrieved August
18, 2013 from http://educationresearchreport.blogspot.com.
[12] S. Robinson. Ethics and employability. Higher Education Academy. York , 2005. Retrieved May 19, 2013 at
www.heacademy.ac.uk.
[13] L. S. Gottfredson. Applying Gottfredson’s theory of circumscription and compromise in career guidance and
counseling. Career development and counseling: putting theory and research to work, 71–100. Hoboken, NJ:
Wiley, 2005.
114