Reconstruct creative destructionknowledge through creative disruption

Muhammad Nizam Zainuddin, Mohd Fairuz Abd Rahim and Mohd Rozaini Mohd Rejab

Abstract

Purpose – With internet technology, knowledge acquisition surpasses the confinement of the

university’s campus or syllabus. Concurrently, an entrepreneurship programme has recently been

offered to students, positioning universities as an experimental ground for the breeding of

entrepreneurs. Thus, this paper seeks to evaluate the effect of entrepreneurship education syllabi

empowered with current information communication technology (ICT) exposure towards students’

entrepreneurial self-efficacy together with social norms and their entrepreneurial intention; and whether

this latest development lives up to stakeholders’ expectations.

Design/methodology/approach – Data were collected through a census survey of entrepreneurship

students at four MSC-Status universities that offer entrepreneurship degree programmes. Quantitative

analyses such as regression were performed.

Findings – Specialised entrepreneurship education with ICT exposure significantly affects a student’s

entrepreneurial self-efficacy. However social norms were found to be a poor predictor towards

entrepreneurial intention, explaining the diminished level of influence lecturers had upon their students’

behaviour.

Research limitations/implications – This study focuses on a group of entrepreneurship students who

are exposed to ICTapplications at that stipulated time, and as such, the findings cannot be generalised

as technology evolves rapidly. The findings are also limited to only entrepreneurial intention and

demonstrate the outcome in Malaysia’s higher education industry.

Practical implications – The two direct stakeholders i.e. the university’s management and lecturers,

may need to reconstruct their respective initiatives by introducing ‘‘creative disruption’’ philosophies,

policies and pedagogies to facilitate the ‘‘creative destruction’’ mode of education into realising its full

potential.

Originality/value – This paper provides an insight into challenges that universities face in delivering

distinctive knowledge consisting of theories and practices. Together, they require constructive and

radical yet practical initiatives.

Keywords Entrepreneurialism, Education, Learning organizations, Social learning, Planned behaviours,Malaysia

Paper type Research paper

Introduction

Higher education institutes’ (HEIs) practices underwent tremendous transformation in recent

decades, globalisation (Deema et al., 2008), technological advancement (Georgina and

Olson, 2008) and a new breed of ‘‘information age mindset’’ students as their prime receivers

(Frand, 2000), were identified as elements behind this process; causing HEIs to rethink their

quality propositions to the public (Houston, 2008). This includes offering in-demand

programmes such as entrepreneurship (Kuratko, 2005) and thinking ahead, managing

disruptive technologies (Bower and Christensen, 1995) to stay in touch with industries.

The nexus between advancement and subsequently integration of Information and

Communication Technology (ICT) into HEIs’ landscapes are becoming more viable.

PAGE 34 j ON THE HORIZON j VOL. 20 NO. 1 2012, pp. 34-48, Q Emerald Group Publishing Limited, ISSN 1074-8121 DOI 10.1108/10748121211202053

Muhammad Nizam

Zainuddin,

Mohd Fairuz Abd Rahim and

Mohd Rozaini Mohd Rejab

are all Lecturers in the

Faculty of Management,

Multimedia University,

Cyberjaya, Malaysia.

Described by Friedman (2005) as power of ten world flatteners; combinations of netscape,

uploading, in-forming and ‘‘the steroids’’; the phenomenon rapidly changing the old norm of

physical classroom learning into new norm of virtual access of new knowledge chambers

with just the click of a mouse. This occurrence promoted many education management

research papers: particularly on how to improve educational equities post ICT-adoption

(Darling-Hammond, 2009) and how to deal with changes from the ‘‘Cartesan’’ view of

learning to the social view of learning resulting from the ICT integration into the classroom

(Brown and Adler, 2008).

Riding on the internet platform, open courseware and content regarded as enablers for

achieving universal right to education (Caswell et al., 2008), has opened up information

gateway to the widest possible audience (Downe, 2007). Meanwhile, through personal

message application found in Social Networking Sites (SNSs) like Facebook, Twitter and

LinkedIn, students may directly communicate with any public personality including

entrepreneurs, sportsmen, and artists. What makes more of a substantial, increasing trend

of university students were found to rely on SNSs for information compared to other

communication mediums (Ellison, 2007).

Nevertheless, Jedeskog and Nissen (2004) found that there were two ongoing trends

associated with the infusion of ICT in the classroom, a changing of students’ focus from

content to form, and a dissolution of boundaries in terms of room, time and activity. They

found that both variables have created a situation where ‘‘to perform’’ something with a

computer seems to be more important than to comprehend the content of a certain subject.

On possible impacts of SNSs, Peluchette and Karl (2008) suggested that SNSs may

positively increase adolescents’ self esteem and the well-being of students through the

positive feedback that they receive online but an adverse effect was possible if the feedback

was negative.

Concurrently, reacting to market demand; specialised entrepreneurship education (SEE)

programmes were observed in the recent decades (Kuratko, 2005) due to the growing

popularity of the entrepreneurship domain itself. SEE programmes were established mostly

at business schools at universities (Kirby, 2004) and the specific objective of SEE is to create

more entrepreneurial individuals who can act as independent entrepreneurs (Hytti and

O’Gorman, 2004).

Despite the proliferation of SEE, Pittaway and Cope (2007) found there was a lack of

consensus on what entrepreneurship or enterprise education actually ‘‘is’’ when

implemented in practice; this includes basic entrepreneurship typology subscribed by

the business schools (Gibb, 1987) that seem unsettled. There are two most subscribed

entrepreneurship definitions provided by Richard Cantillon (1755) and Joseph Schumpeter

(1934). The former defines entrepreneurship as ‘‘an act of undertaking business and

making profits after resale stage,’’ and the latter emphasised on ‘‘the way of creative

destruction that used a creative and innovative approach to exploit commercial

opportunity.’’ The question here, in business schools is, which definition is closer –

Cantillonian or Schumpeterian? Perhaps, discrepancies like this might influence the overall

delivery of SEE, where entrepreneurship educators are still undecided as to whether to

portray an entrepreneur as a ‘‘commercial business person’’ or ‘‘creative market

destructor,’’ because different syllabi, resources and approaches are needed in making

either references and the outcomes are likely be different. Due to this confusion, Hindle

(2007) believed that business schools were the wrong place to teach entrepreneurship

education because of their conventional approaches of teaching entrepreneurship in

normal business management templates.

Together, the combination of ICT and SEE programmes creates a ‘‘new form’’ of education

and led HEIs on experimental ground. This situation is assumed to directly affect the

universities’ stakeholders (i.e. universities’ management, lecturers/educators and students)

imposing a greater challenge ahead; with information that is widely accessible and social

learning that is no longer confined to a university’s environment. Two research questions

(RQs) arise:

VOL. 20 NO. 1 2012 jON THE HORIZONj PAGE 35

RQ1. Do entrepreneurship students perceive that the SEE syllabi empowered with

current ICT exposure increase their entrepreneurial self-efficacy (ESE)?

RQ2. Surrounded by widely available information (SNSs, open courseware & content),

do entrepreneurship students perceive that their educators’ social norms (SN)

have significant influence towards their intention to become self-employed?

Accordingly, this paper aims to empirically evaluate and confirm the current combined

phenomenon of SEE delivery and ICTexposure together with SEE educators’ SN influence in

the university; contribute ideas to reconstruct a new form of ideal SEE’s programme offering

through creative disruption by injecting ’’new norm’’ elements comprising of the three P’s

approach: philosophies, policies and pedagogies that will use ICT as a medium, thus

maintaining university relevancy and increase quality propositions to public.

The university: the ideal incubator for entrepreneurship antecedents

Many theories underlined antecedents of why an individual perceived opportunity and later

acted entrepreneurially (Meyer, 2004; Lee and Venkataraman, 2006; Reynolds et al., 2004;

Krueger et al., 2000; Shapero and Sokol, 1982). Yet scholars are also interested to find a

suitable candidate and place to cultivate these antecedents to develop future

entrepreneurs. Initially, Gibb (1987) discovered that young individuals were the ideal

candidates to be nurtured as future entrepreneurs. Subsequently, the university was chosen

as the best provider of entrepreneurship educational settings due to its fertile ground for

development of antecedents of entrepreneurial behaviour (Davidsson, 1995; Krueger and

Brazeal, 1994; Krueger and Carsrud, 1993). The selection was where the highest

entrepreneurship rates were achieved in universities that had invested the most in

entrepreneurship education for their students (Varela and Jimenez, 2001) and younger

individuals were found more likely to start a new firm compared to older ones once they

received the right educational support (Levesque and Minniti, 2006).

According to Savickas (2002), university students are at the ‘‘exploration’’ stage, whereby all

the interaction of personality traits are being explored rigorously and the student may start to

choose a career in the process of ‘‘circumscription stage’’ or reject unacceptable

alternatives (Gottfredson, 2002). This career decision-making period is in line with social

learning perspective (Bandura, 1977), and that choosing a particular career is influenced by

positive and consistent reinforcement from observing significant occupational role models

(e.g. family, close friends, idols, educators) and being exposed to images related to specific

careers (Krumboltz et al., 1976).

Effect of SEE delivery empowered by ICT towards students’ ESE

Previous studies have established direct positive association between SEE and ESE

(Davidsson, 1995, Krueger and Brazeal, 1994) through acquisition of management tools and

exposure to entrepreneurial situations (Krueger and Carsrud, 1993). SEE’s were found to be

enhancing variables that formed ESE like the need of achievements, locus of control

(Hansemark, 1998; Ehrlich et al., 2000; Wilson et al., 2007).

In contrast, Dilts and Fowler (1999) argued that only certain teaching methods

(i.e. traineeships and field learning) were more successful than others in preparing

students for an entrepreneurial career. Therefore, if entrepreneurship educators lack

pedagogical knowledge and skills, and even unsettled typology of what to teach, it might

affect the delivery of learning experiences to students. This concern proved to be

substantial. Bennett (2006) found that academicians’ definitions of entrepreneurship were

influenced by their backgrounds and by the number of years they had worked in the

business sector. Therefore, if educators lacked or had no experience in creative destruction,

they were unable to precisely illustrate the process – and worst still – they would provide the

wrong perception of entrepreneurship towards students. The level of ESE transferred to

students would be less substantial.

PAGE 36 jON THE HORIZONj VOL. 20 NO. 1 2012

With regards to exposure to ICT, Oliver and Burke (2008) found that almost 50 percent of

Engineering and Business students in Australia, Ethiopia and Malaysia owned laptops. With

high rates of ownership, students are assumed to be exposed to ICT hardware, software,

programme applications and have access to the internet.

There are three levels of implications resulting from ICT exposure:

1. An individual level, Passig and Levin’s (2000) found that students do not only study the

subject matter, but also learn how to deal with the synthetically programmed environment

– mimicking the real process of nature with or without the knowledge of consequences of

such action.

2. At duo-level perspective, Solomon et al.(2002) found that ICT allows lecturers to

communicate better with students by sharing resources and ideas effectively through

multiple sources of learning tools comprising of distance education and multi-media

lessons of both ‘‘real’’ and ‘‘virtual’’ courses, made possible by internet connectivity

(Alberti et al., 2004).

3. At group-level, technology improves the ability to learn and support the creation and

maintenance of a learning culture (Rahim et al., 2008; Watkins and Marsick, 1999).

Regardless, Watson et al. (2004) mentioned that the yardsticks of a successful education

programme with ICTexposure are that students understand the potential applications of ICT

(ESE) obtained through classroom experiences and later innovatively utilise them as

business tools. Lee and Bertera (2007), proved that graduate students who use online forum

demonstrate heightened self-efficacy and Kurbanoglu (2003) concludes that self-efficacy is

closely linked to information literacy.

The effects of SEE educators’ SN towards students’ EI

SN can be defined as unwritten rules of conduct (Elster, 1989) that are derived from beliefs

about the normative expectations of others and motivation to comply with these expectations

(Scholten et al., 2004).

March (1988) theorised that SN provides the guideline for desirable behaviour within a

culture. Assuming that the university acts as an incubator for EI perception, the norm set by

the university is that an entrepreneurship degree student seeks self-employment to exploit

perceived opportunity rather than employment in a large organisation, and then it is obvious

that starting a firm will be considered an appropriate action. This argument is supported by

Bryant and Bryant (1998) where social norms in a community (university) changes what is

more likely to be seen as an opportunity.

Empirical results of SN variables towards EI were generally mixed. SN was proven to be an

important variable towards EI (Kolvereid, 1996, Krueger, 1993, Grundsten, 2004) because

students’ lack of knowledge and experience and are often in the midst of investigating their

career choice preferences. Therefore, the opinions of parents, partners, friends, and

important others might be influential in this process (Gelderen et al., 2006).

In contrast, scholars also found SN to be unreliable predictor to EI. According to

Scholten et al. (2004), SN played a marginal role where only individuals who

experienced a positive view on entrepreneurship amongst their immediate contacts is

associated with the intention of entrepreneurship. Meanwhile, Krueger et al.(2000), held

that SN are less predictive for individuals who have a high internal locus of control. Basu

and Virick (2008) discovered there were no significant differences between the SN of

those who had prior exposure to entrepreneurship education and prior experience in

entrepreneurship, Fayolle et al. (2005) suggested that SN were not significantly affected

by entrepreneurship education. Finally, Linan et al. (2005) totally dismissed SN as

insignificant predictor to EI.

VOL. 20 NO. 1 2012 jON THE HORIZONj PAGE 37

Research methodology

(i) Method of sampling

A total 186 final and penultimate year entrepreneurship degree students from four (4) major

public and private universities with Multimedia Super Corridor (MSC) statuses in Malaysia

namely: Universiti Utara Malaysia (University I), Universiti Malaysia Sabah (University II),

Universiti Tenaga Nasional (University III) and Multimedia University (University IV), were

sampled via a census survey. MSC-status universities were chosen due to their affiliation

with multimedia technologies used to produce or enhance their teaching, research, and

overall process (MSC, 2010). Final and penultimate year students were chosen due to their

juncture in facing imminent career-making decisions(Krueger and Kickul, 2006; Krueger

et al., 2000).

(ii) Research operationalisation

The research questionnaire was constructed based on the modification of validated

previous studies. Both paper and digital versions were created. The questionnaire was

personally administered at the respective universities and those unreachable respondents

(due to their practicum semester) were contacted and received the same questionnaire via

their personal e-mail.

To measure the factors that influence the entrepreneurial intention, the paper employed the

variables used in previous studies (Kolvereid and Isaksen, 2006; Kolvereid, 1996). Using

existing scales is advantageous because these measures have been validated and proven

to have good psychometric properties. It allows cumulative knowledge development and

enables findings to be explained within the context of extant literature and empiricism

(Mavondo et al., 2005). All variables were measured using a four-point Likert scale.

There are four variables in this research consisting of two dependent variables (EI and ESE)

and two independent variables (SEEICT and SN). These variables are paired in two groups

according to arrangement of hypotheses testing.

1. Group I (H1):

B ESE – The dependent variable ESE was measured using 16 items that indicate the

respondent’s perception of his or her ability to behave entrepreneurially. The items

were developed based on the modification of past validated studies (Kolvereid, 1996;

Ajzen, 1991; Linan and Chen, 2006; Noble et al., 1999; Tkachev and Kolvereid, 1999;

Tretten, 2005).

B SEEICT – The independent variable SEEICT was measured using 12 items that

indicate the perception of SEE delivery and ICT exposure the respondent received in

the university. The items were developed based on the modification of past validated

studies (Kickul and Krueger, 2004; Shapero, 1982; Tretten, 2005; Ajzen, 1991;

Kolvereid, 1996).

2. Group II (H2):

B EI – The dependent variable EI indicates a respondent’s entrepreneurial intention of

whether to become self-employed or employed in an established organisation. There

were ten four-Likert-scale questions, developed based on modification from existing

studies (Kolvereid, 1996, Kolvereid and Isaksen, 2006, Krueger et al., 2000, Linan and

Chen, 2006, Tretten, 2005)

B SN – The independent variable of SN indicates the level of students’ compliance

towards SEE’s educator’s SN influence. The variable was measured using four items.

The items were developed based on the modification of past studies (Kolvereid, 1996,

Tretten, 2005).

3. Types of analyses. Four types of analysis were performed: collection of demographic

profiles analysis: data such as students’ years of study, university, age, gender and

pre-university academic status were collected; descriptive analysis; reliability analysis;

and hypotheses testing of simple linear and multiple regression analyses.

PAGE 38 jON THE HORIZONj VOL. 20 NO. 1 2012

4. Hypotheses formulation. Based on the discussions regarding relevant variables that

formed the basis of theoretical framework, the paper developed two hypotheses:

B H1. SEE syllabi with ICT exposure will positively contribute to students’ ESE.

B H2. Students’ SN towards their SEE educators is less likely to influence their EI.

Findings

1. Demographic profiles. Of the 186 respondents, as depicted in Table I, the majority of

respondents were final year students. A total 67 percent of them were from public

universities with the female outnumbering the male population. Almost 94 percent of the

population fell into the 21-25 years age bracket. Of them 66 percent were Malaysian

Higher School Certificate Holders, followed by Malaysian School Certificate Holders

(12 percent), Diploma holders (11 percent) and others.

2. Descriptive analysis. As depicted in Table II, the mean score of all variables were more

than or close to three out of the four-point scale. This indicates that respondents mostly

agreed with the statements. The highest mean score of 3.14 is contributed by SEEICTwith

SN reporting the lowest mean score of 2.64. The standard deviations were 0.45 and 0.60

Table II Results of descriptive analysis

Constructs Meana SD

SEEICT 3.14 0.45ESE 2.75 0.34SN 2.64 0.60EI 2.85 0.42

Notes: a1¼ strongly disagree, 2 ¼ disagree, 3 ¼ agree, 4 ¼ strongly agree

Table I Demographic profiles

Items Frequency Percentage

StudentsFinal 132 71Penultimate 54 29

UniversityUniversity I 55 30University II 69 37University III 37 20University IV 25 13

GenderMale 62 33Female 124 67

AgeUnder 20 9 4.821-25 174 93.526-30 1 0.5Above 31 2 1.1

Education levelSPM (Malaysian Certificate Examination) 22 12STPM (Malaysian Higher Certificate Examination) 122 66Diploma 21 11Matriculation 15 8Others 6 3Total 186 100

VOL. 20 NO. 1 2012 jON THE HORIZONj PAGE 39

respectively. The standard deviation scores for all the variables were below one,

indicating that the respondents have rated all elements consistently.

3. Reliability analysis. As shown in Table III, the reliability analysis found that all the variables

were highly reliable and can be used for further statistical analyses. The high alpha value

indicates high consistency in the respondents’ answers and therefore no items were

dropped.

4. Hypotheses testing.

B The Effect of SEEICT towards ESE. A simple linear regression was used to check for

the predictor value of SEEICT towards ESE. Referring to Table I (Item 3), the adjusted

R 2 result is 41.9 percent. Based on the result, the students’ SEEICT positively affects

their ESE. The result indicates that the current SEE delivery and ICT exposure that

students experience is perceived to increase their ESE. Both SEE syllabi and ample

ICT exposure enable them to build their confidence in becoming a successfully

self-employed person. The students perceived that when they receive new,

meaningful knowledge and sufficient ICT exposure provided by their universities,

the more confident they become in their entrepreneurial ability. Perhaps their

universities’ ‘‘new norm’’ practices were up to standard of the ‘‘information age

mindset.’’

The Effect of SN towards EI. A simple linear regression was used to check for the

predictor value of SN towards EI. As depicted in Table IV (Item 1), the adjusted R 2

result is 12.7 percent. Based on the result, SN of lecturers are significant but with low

explanatory power. There are various factors that may contribute to the results.

First, the students might have high locuses of control (Krueger et al., 2000), therefore

they care less about what people around them think (including SEE educators) of their

career-decision making.

Second, no educators within the students’ significant circle play a significant role in

asserting their influence towards the students’ career choice, thus the students do not

consider any ideas from them as significant; educators are either not qualified to

advise them about their future career path because of the lack of academic

credentials, expertise and entrepreneurial experience. Perhaps the confusion on the

entrepreneurship typology that were delivered by SEE educators portrayed the image

of self-employed entrepreneurs perceived by students; where students perceive

entrepreneurs as normal business persons (Cantillonian) rather than creative

destructors (Schumpeterian).

Table IV Results of regression analyses

Items R R 2 Adj. R 2 F Sig. level*

(1) Dependent variable – ESEIndependent variable – SEEICT 0.650 0.423 0.419 134.618 0.000(2) Dependent variable – EIIndependent variable – SN 0.363 0.131 0.127 27.842 0.000

Note: *Significant at 0.01 level

Table III Results of reliability analysis

Constructs No. of questions Cronbach qlpha

SEEICT 14 0.913ESE 16 0.802SN 4 0.748EI 10 0.817

PAGE 40 jON THE HORIZONj VOL. 20 NO. 1 2012

Third, this indicates diminishing influence of educators and maybe the growing

influence of information that students obtain online, breaking the traditional social

learning perception of only lecturers providing their students with knowledge. Regular

conversations with successful entrepreneurs through online applications like

Facebook and LinkedIn asking for business tips and advice may be more

appealing to students’ perceptions of entrepreneurship.

Discussions

In order to improve the overall delivery of SEE and ICT exposure together with the declining

influence of SEE educators, there are three approaches of ‘‘creative disruption’’ that require

a drastic reconstruction of entrepreneurship knowledge to be more Schumpeterian than

Cantillonian. The 3P’s SEE Module comprises of: philosophies, policies and pedagogies,

which integrates ICT as one of the medium of delivery.

(i) Entrepreneurial philosophies

A major challenge for universities to restore the influence upon the new generation of

students requires them to radically change the way of thinking and mode of knowledge

delivery.

Universities need to play the role of being a real incubator for students by gathering

resources to provide experienced SEE educators from both the industry and academia that

are capable to expose students with what they can expect from the world of

entrepreneurship. A radical approach is to separate entrepreneurship education initiatives

from business schools by creating a unique entrepreneurship centre parked under a

strategic division that oversees the entrepreneurship development activities at faculties,

including Engineering, IT, Humanity, Arts and others (Hindle, 2007).

It is vital to change the current intellectual learning philosophy in the university from

‘‘produce’’ and ‘‘perform,’’ to ‘‘pause’’ and ‘‘reflect’’ (Cherwitz and Sullivan, 2002).

Universities need to make space for students to contemplate their personal, professional

and intellectual identities based on the experience they acquire; the kind of reflection that

can yield sustained productivity and satisfaction in the long run. By doing so, universities

can simulate the real entrepreneur world of tacit knowledge and heuristics judgment. In

addition, universities need to introduce trajectory of ‘‘discovery-ownership-accountability’’

(Cherwitz and Hurtado, 2007; Shaver and Scott, 1991). From the outset, students are

encouraged to discover their personal, intellectual, and professional interests and to make

explicit and thoughtful connections among these goals. Perhaps the adult learning

philosophy (Hannon, 2005b) that provides the foundation for reflection and analysis of

current approaches against philosophical beliefs, through discussion about the potential

contrasts and conflicts, between underpinning foundations and purpose-in-action can be a

good blueprint.

(ii) University management policies

Adaptation to rapid changes such as SEE and ICT, requires continuous and frequent

adjustments to what people do and how people do it (Lusher and Lewis, 2008) and this

requires the university management to embrace the learning organisation (LO) practices

and policies.

First, there needs to be less emphasis on organisational structure and concurrently

emphasis on systems for facilitating and implementing change. By having a flexible,

organic structure and system, a university’s management will be more receptive to adopt

and manage new technologies, especially ICT, due to less cumbersome procedures and

rules that they have to adhere to (Gephart et al., 1996) and it is considered as the primary

condition influencing a university’s ability to acquire new knowledge (Kang and Snell,

2009).

Second, there is growing literature that emphasises on the effectiveness and the roles of

mentors and professional people that influence students (Turker and Selcuk, 2009), thus

VOL. 20 NO. 1 2012 jON THE HORIZONj PAGE 41

university management should practise flexible staffing and appointment policies (Gibb,

2005). This can be done by including professorships of practice, adjunct professors,

fellowship secondments for members of the stakeholder community, and visiting

entrepreneur teaching fellowships to increase the pool of experts. Students will become

more respectful and interested to acquire knowledge from well-known experts. Next,

educators should be allowed to take sabbatical leave and attend industrial attachment to

oversee the development of entrepreneurship practices in the industry and for the

educators (Omar and Mohamed, 2009) to adapt and upgrade themselves to become

specialist mentors. Besides, educators should be given time flexibility to serve three pillars

of academic enterprise of teaching, research and outreach, therefore they will become

mutually complementary with students’ expectations (Carayannis, 2009).

Third, there should be more research and development with small firms, larger corporations

and government agencies. These parties can contribute grants for entrepreneurship

practicum and students’ consulting project. At the same time, they can absorb successful

student entrepreneurs into their organisation as intrapreneurs.

(iii) SEE educators’ pedagogies

The biggest challenge to reconstruct entrepreneurship pedagogies is to produce a

combination of the creative talents of the artist, the skills and ability of the artisan, yet include

the applied knowledge of the technician with the know-what of the professional (Anderson

and Jack, 2008).

The best way to expose students is by providing experiential entrepreneurial training such

as entrepreneurship practicum in the university during final year (Zainuddin and Rejab,

2010) and students’ consulting project (Heriot et al., 2008) through social enterprise

chapters like Students in Free Enterprise (SIFE) www.sife.org. This approach will somehow

provide macro experiential learning (Wani et al., 2004) that not just affects their cognitive

learning but also affective learning too. According to Kolb and Kolb (2005), by engaging

students through experiential learning students can learn through feedback, conflict,

differences, and disagreements that draw out their beliefs and ideas about a topic through

holistic process that encompasses a person’s cognition, thinking, feeling, perceiving, and

behaving.

In addition, rapid innovation will eventually change the traditional academic roles from ‘‘the

sage on stage’’ to ‘‘a guide on the side,’’ (Hannon, 2005a). Anderson (2003) proposed deep

and meaningful formal learning, supporting one of the three forms of interaction (i.e.

student–teacher; student-student; student-content interactions) at a high level. The other

two may be offered at minimal levels, or even eliminated, without degrading the educational

experience. High levels of more than one of these three modes will likely provide a more

satisfying educational experience, though these experiences may not be as cost or timely

effective as less interactive learning sequences. The combination of specialised

entrepreneurship education and the ICT-based learning application contributes to

students’ entrepreneurial self-efficacy. One way is to insert ICT based-business

simulations based on interactive games (Hindle, 2002) that can integrate problem-based

learning similar to popular online games programme like Football Manager, SIM City and

others.

Entrepreneurship educators should quickly embrace the latest technology to stay in

students’ SN circle of influence. The latest way of using SNSs as a medium for students to

operate their business activities, like using Facebook to perform the marketing promotion,

can increase the influence of educators.

Conclusions

The study provides an important analysis of the state of Malaysian universities’ with regards

to SEE; ICT exposure; and SEE educators’ SN impacts on students with regards to their EI.

PAGE 42 jON THE HORIZONj VOL. 20 NO. 1 2012

Two research questions were answered, resulting in a combination that SEE and ICT

positively impacts students’ ESE and indicates a positive sign of universities managing

disruptive technologies in reaction to market demand. However, students do not wish to

comply with their respective SEE educators’ SN and this perhaps indicates growing

influence of online information (SNSs, open courseware and contents) that breaks the

traditional social learning perception.

This study has general and specific limitations that need to be taken into account. First,

the sample size was restricted to only four (4) Malaysian universities, omitting other

universities and Higher Education Institutions. The respondents were reached through

limited methods available to the researcher given the constraints in time and other

resources. The research specifically targeted students majoring in entrepreneurship,

omitting students from other majors who enrolled elective entrepreneurship subjects. The

results could have been different if the same studies were conducted on other universities

and HEIs. However, the sample size was large enough for the results to be considered as

valid (Sekaran, 2005).

Second, this research employed a cross-sectional design that focuses on specific issue at

one point at time. A longitudinal design may provide different results because the complex

and dynamic interrelationship between variables evolve over time. This would be more

suitable to capture the employment intention in detail due to its possibility to change over

time.

Third, the current study used a single item or limited-item in measuring key-constructs,

resulting in the lack of sophistication in assessing the employment intention decision making

in the context of the individual’s story, circumstances, contexts and complexities (Nabi et al.,

2006). It is difficult to measure the employment intention due to its reliance on subjective

perceptions, in which some are abstract in nature. This is acknowledged by previous

scholars who attempted to assess the entrepreneurial intention (Autio et al., 2000; Krueger

et al., 2000; Peterman and Kennedy, 2003).

Finally, the entrepreneurial intention model will remain as intention. The transition from

entrepreneurial intentions to actual start-ups is often assumed in literature, but is

under-researched when it comes to the career development and decision-making

processes. Graduate career choices are highly complex, contextualised, and diverse

processes that entail elements of various theoretical perspectives and are not too universally

accepted as a ‘‘general theory’’ (Nabi et al., 2006). The connection between training,

support, intent and actual career-choice to start-up businesses remain under-investigated.

Given the complexity of the career-decision processes a simple relationship cannot be

expected. The availability of are too many alternative intention models makes it difficult to

consistently define entrepreneurial intention and to generalise the findings. Thus, there is a

need to integrate and reduce the number of alternative intention models and to use a

consistent definition of entrepreneurial intent (Shook et al., 2003).

The results of this research have raised more questions and possibilities for future

studies. A larger sample size is needed to capture the higher generalisation impacts.

The reach and richness of the study can be increased by including other universities

and HEIs, which would provide better indicators in the future. Plus, the longitudinal

research design should be implemented to track the following batch of entrepreneurship

students to assess the impacts of entrepreneurship education over time. Future studies

can also conduct a comprehensive comparison study between entrepreneurship

education delivery in both private and public universities and determine which

entrepreneurship education course is more effective. From the findings, efforts can be

made to identity, synergise and blend the most effective methods. Lastly, future research

can also integrate various entrepreneurial intention models to capture some other

variables missing from the TPB model. The variables such as disposition factors, trigger

factors, push-pull factors, cognitive factors of entrepreneurship students and others

should be considered in a new research framework.

VOL. 20 NO. 1 2012 jON THE HORIZONj PAGE 43

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About the authors

Muhammad Nizam Zainuddin completed his MPhil degree from Multimedia University,Cyberjaya, Malaysia in 2009, and graduated from Universiti Tenaga Nasional with a BBA(Hons) in Entrepreneur Development in 2002. His areas of specialisation areentrepreneurship education, ICT, creativity and innovation, and behavioural science. He isan entrepreneurship lecturer/educator at the Faculty of Management, Multimedia University,Malaysia. Muhammad Nizam Zainuddin is the corresponding author and can be contactedat: muhammad.nizam@mmu.edu.my or nizam.zainuddin@gmail.com

Mohd Fairuz Abd Rahim is a Lecturer at the Faculty of Managemet, Multimedia University,Malaysia. He holds a MPhil degree from Multimedia University, Malaysia and is currentlypursuing his PhD in the area of learning organisation and human resource management.

Mohd Rozaini Mohd Rejab holds a master’s degree in Information Management from MARAUniversity of Technology, Malaysia. His areas of interests are strategy and managementhistory. He is currently lecturing at the Faculty of Management, Multimedia University,Malaysia.

PAGE 48 jON THE HORIZONj VOL. 20 NO. 1 2012

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