Investigating factors that influence on ICT usage in

Int Rev Public Nonprofit Mark DOI 10.1007/s12208-013-0095-7 O R I G I N A L A RT I C L E

Investigating factors that influence on ICT usage in higher education: a descriptive analysis M. Angeles Iniesta-Bonillo & Raquel Sánchez-Fernández & Walesska Schlesinger

Received: 14 March 2013 / Accepted: 2 May 2013 # Springer-Verlag Berlin Heidelberg 2013

Abstract Information and communication technologies (ICT) can represent a source of competitive advantage for an organization. In particular, the spreading of ICT knowledge and experience in higher education is a key component of the educational reform agenda. The objective of this paper is to characterize the ICT usage levels of the graduates, as well as the influence of variables such as gender, university of origin and area of knowledge on their level of ICT usage. Based on an empirical study on a representative sample of graduates from two Spanish universities, the results confirm that graduates’ experiences with some particular technologies in education are related to gender, area of expertise and university of origin. Keywords ICTusage . Higher education . Gender . University oforigin . Areas of expertise

1 Introduction Information and Communication Technologies (ICT) have been described as an important influence or change (Moensa et al. 2010). Many researchers argue that ICT infrastructure is essential to the rapid development of emerging economies (Blignaut et al. 2010; Hsu 2011; Ngwenyama and Morawczynski 2009; Peeraer and Van Petegem 2011; Sang et al. 2010) and has become increasingly important M. A. Iniesta-Bonillo (*) : R. Sánchez-Fernández Department of Economics and Business, University of Almeria Ctra Sacramento, s/n 04120 Cañada de San Urbano, Almeria, Spain e-mail: [email protected] R. Sánchez-Fernández e-mail: [email protected] W. Schlesinger Marketing and Market Research Department, University of Valencia Valencia, Spain e-mail: [email protected]

A. Iniesta-Bonillo et al.

to organizations throughout the world (Stuart et al. 2009). Learning of ICT is essential for organizational survival, since the adoption of ICT can improve efficiency of business process and provides new ways to achieve and maintain a competitive advantage (King and Teo 1996; Probst and Buchel 1997; Yau and Cheng 2010). Additionally, ICT have an important role in the customer-firm relationship, influencing variables such as customer satisfaction, commitment and loyalty (Bauer et al. 2002). Focusing on the educational environment, integration of ICT has been a key component of an educational reform agenda (Peeraer and Van Petegem 2011). Nowadays higher education is going through a period of transformations due to, among others, two reasons: the introduction of new information and communication technologies and the construction of common spaces for higher education. These facts have entailed a significant change in the educational activity: teachers are becoming learning facilitators and students are playing a more active role in the construction of their knowledge. For that reason, teachers must find mechanisms in order to facilitate this new learning perspective (López et al. 2005) In this sense, ICT have been considered as an indispensable tool to fully participate in the knowledge society, since it is assumed that ICT can bring revolutionary changes in teaching methodologies (Peeraer and Van Petegem 2011). Innovation does not lie per se in the introduction and use of ICT, but in its role as contributor of student-centered forms of teaching and learning. As early as 1998, the UNESCO World Education Report (UNESCO 1998), Teachers and teaching in a changing world, described the impact of ICT in the conventional teaching and learning methods, predicting the transformation of the teaching-learning process, as well as the way teachers and students would have access to knowledge and information. Nowadays, the European Higher Education System has been a favorable factor to the greater understanding of the importance of ICT in the educational context. In particular, several studies have pointed out that ICT have become an essential tool for higher education (Heemskerk et al. 2009; Jung 2009; López et al. 2005; Moensa et al. 2010; Peeraer and Van Petegem 2011). The introduction of ICT in the educational field can offer several opportunities for both learners and teachers (Barak 2007; Barak and Dori 2005; Haq 2012; Stuart et al. 2009). Peeraer and Van Petegem (2011) indicate that one key area of teachers’ attitudes towards ICT is their understanding of how they will benefit their work and their students’ learning. Factors such as accessibility provided by ICT, its pedagogical potential, the ease of usage for teachers and students, the growing social pressure for its adoption, the need to overcome time and space limits of on-site teaching and the new opportunities of the global university area, seem to be powerful reasons to this growing interest in the study of ICT (Bates 1993). The introduction of educational ICT has been accompanied by a proliferation of research on ICT (Vekiri 2010). A great amount of studies have analyzed which factors are influencing or constraining integration of ICT in education in general, and the use of ICT for teaching practice in particular (Justel et al. 2004; Peeraer and Van Petegem 2011). Groff and Mouza (2008) distinguish between critical factors, including legislative level factors, district and school level factors, factors associated with students and teachers, factors inherent to the technology itself, and factors associated with the technology-enhanced project. Mumtaz (2000) considers three interlocking factors in

Investigating factors that influence on ICT usage

the spread of use of ICT for teaching practice: institution, resources, and teachers. Authors such as Peeraer and Van Petegem (2011) and Drent and Meelissen (2008), categorize factors that influence on the integration of ICT in education into those which can be manipulated (for example, access to ICT, intensity of use, confidence, and skills) and those which cannot be manipulated (for example, gender, age and teaching subject). Particularly interesting has been the study of variables such as gender (Dlodlo 2009; Heemskerk et al. 2009; Ilomäki and Rantanen 2007; Jung 2009; Kennewell and Morgan 2006; Wymer 2011), age (Goodwin and McElwee 1999; Hakkarainen et al. 2000; Peeraer and Van Petegem 2011; Sang et al. 2010), institution location (Alfaro and Alfaro 2011; Blignaut et al. 2010), attitudes towards ICT (Hakkarainen et al. 2000; Peeraer and Van Petegem 2011; Sang et al. 2010; Zhou et al. 2010), and ICT skills (Hakkarainen et al. 2000; Peeraer and Van Petegem 2011), related to the ICT usage in the educational context. In this paper, we focus on one of the variables that have been analyzed in the most recent literature, that is, the influence of gender-related characteristics on educational ICT usage (Dlodlo 2009; Haq 2012; Heemskerk et al. 2009; Jung 2009). Some literature on educational computing is found with conflicting findings about the impact of gender (Teo 2008). Since the introduction and diffusion of computers, ICT related activities have been viewed as a ‘male domain’ (Sang et al. 2010). Significant differences between males and females have been observed for technical ICT capabilities (Markauskaite 2006). But given that technologies have become a normal part of the workplace setting, a number of researchers argue that computing should no longer be regarded as a male domain. This emphasizes the need to reconsider the current potential impact of gender in the context of educational ICT usage. Likewise, we analyze the influence of location (Alfaro and Alfaro 2011; Blignaut et al. 2010), in particular, the university or educational institution of origin. Moreover, we evaluate the role of a variable that has been ignored in the literature, that is, the area of expertise, in the ICT usage. In order to plan more effective learning opportunities for higher education, it is important to understand how these factors influence on ICT usage. In order to achieve these objectives, we have structured this paper as follows. First of all, we present a short theoretical overview on ICT and its relevance to educational research. We then describe the influence of gender, university and area of expertise on ICT usage in higher education. Based on the review of the literature, an evaluative framework is set out, followed by a description of the research methodology. Thereafter, the influence of the three factors is analyzed, based on an exploratory study in two Spanish universities with very different characteristics in terms of size and age. The paper concludes with a discussion of the findings and managerial implications for the educational institutions.

2 Theoretical background When approaching the use of ICT in education, three objectives are generally distinguished (Plomp et al. 1996): (i) the use of ICT as object of study (to learning about ICT, which enables students to use ICT in their daily life); (ii) the use of ICT as aspect of a discipline or profession (the development of ICT skills for professional or


vocational purposes); and (iii) the use of ICT as medium for teaching and learning (it focuses on the use of ICT for the enhancement of the learning process of students). This paper will focus on the third objective, analyzing some factors that influence on graduates ICT usage, such as gender, location and area of expertise. In the literature, there has been an increasing interest in the influence of student and/or graduated gender on the ICT usage (Dlodlo 2009; Hakkarainen et al. 2000; Ilomäki and Rantanen 2007; Peeraer and Van Petegem 2011). Thus, several articles show that student’s experiences with technology in education vary and, more specifically, may be related to gender (Heemskerk et al. 2009; Kennewell and Morgan 2006; Jung 2009; Vekiri 2010). Gender differences in students’ appreciation of the educational use of ICT parallels the research that continues to show gender differences in computer attitudes, although the gender gap in the use and knowledge about ICT has diminished (Cooper 2006). Several articles have been published regarding gender differences in the development of ICT capability. Authors such as like Busch (1995) or Kennewell and Morgan (2006) indicate that a number of gender differences may exist regarding attitudes towards computers, experiences gained with computers, performance on tasks set and perceived self-efficacy in the use of computers. In particular, some authors have focused on young people’s computer use (Heemskerk et al. 2009; Ilomäki and Rantanen 2007; Vekiri 2010), indicating that boys have better ICT skills, and considering different levels of ICT usage: boys make a higher use of ICT in their leisure time; their attitudes toward ICT are more positive than the attitudes of girls; they use ICT more for playing and recreational purposes; they are more interested in hardware; and they take on more independent challenges for learning ICT than girls do (Ilomäki and Rantanen 2007). In particular, girls’ attitudes are found to be less positive when confidence in working with technology and the role of ICT in students’ future plans are at stake (Volman et al. 2005). Girls tend to respond less positively than boys to items aimed at measuring computer attitude in general, whereas they report enthusiastically about applications for word processing and drawing (Volman and Van Eck 2001). Moreover, research on ICT learning shows that girls tend to have less positive beliefs about the value of ICT and their own ICT skills compared to boys, that are more likely than girls to have access to a personal computer at home, to use computers in the context of peer activities, and to attend computer clubs (Vekiri 2010; Volman and van Eck 2001). Additionally, Ilomäki and Rantanen (2007) have indicated that there is a small group of, mainly, boys with especially advanced skills and understanding of ICT. In many cases, these students form networks with others interested in ICT, they are ICT supporters in their schools, and they perform demanding ICT services in their neighborhood. The relatively advanced capability of young students can be seen as a kind of expertise, and it is often appreciated, even by adults, in their social environment. It has become clear over the past few years that we should differentiate between some types of ICT usage when making statements about gender differences in the use and appreciation of ICT (Heemskerk et al. 2009). Some authors argue that technology still has a special connection with male culture (Ilomäki and Rantanen 2007). The culture of technological know-how is a set of socially constituted practices, and these practices have encouraged boys and men, more than girls and women (Clegg 2001). Stepulevage (2001) noticed that the ICT competence was linked with the formation of gender identity. For a boy, it functioned as a construction of male-identity.


Regarding location, several studies have considered it and/or characteristics of the educational institution as factors, which stimulate or limit the innovative use of ICT. In this sense, some authors, such as Alfaro and Alfaro (2011), Blignaut et al. (2010), or Ngwenyama and Morawczynski (2009), have analyzed the influence of the introduction of ICT on economic growth and human development in different countries. Furthermore, Hadjithoma and Karagiorgi (2009) delved into a micro-level, exploring the role of different communities and their impact on the extent and quality of ICT implementation. Moreover, Drent and Meelissen (2008) considered the impact of some characteristics of the educational institutions on the implementation of ICT in education, and Peeraer and Van Petegem (2011) showed that province gives an indication of the additional influence of contextual factors at the level of the individual teacher education institution on ICT usage. Therefore, there is a significant body of evidence supporting the notion that gender plays an important role in actual ICT usage. However, this relationship has not been deeply analyzed among graduates in the higher educational context. Moreover, previous literature has ignored the impact of location (in particular, the university) and the area of expertise in the ICT usage. To illustrate the conditions under which successful ICT takes place, this paper focuses on the implementation of ICT through graduates in universities.

3 Method 3.1 Data collection and sample The empirical research designed to test our proposed hypotheses was conducted in the context of higher education in Spain. We considered a total of 1000 graduates in the last 3 and 2 years before the fieldwork in two Spanish universities: 500 from the University of Almería, that is a young and small university, and 500 from de University of Valencia, an old and comprehensive one. They were interviewed individually by personnel of an external market research institute using CATI (Computer Assisted Telephone Interview) from February to March 2009. Simple random sampling was used to select sample units from the graduate database for those years, in order to assure the best representation of the universe. We interviewed graduates from two academic years in order to avoid some potential biases derived from particular circumstances associated to a specific academic course. The sample resembles the universe of graduates in the two universities analysed for the period considered. Graduates from all areas of knowledge (humanities, social sciences, experimental sciences, health and technical studies) were interviewed, and the sample maintains the proportion of men/women of the database of graduates (Table 1). 3.2 Measures and pretest A questionnaire was used as a data collection tool. As a preliminary step, qualitative research was done by several in-depth interviews with some university members


Table 1 Demographics % (N=1000)

Gender Area of expertise

Female

67.2

Male

32.8

Arts and Humanities Sciences Health Sciences

15.7

Social and Legal Sciences

58.9

Engineering and Architecture University

6.6 10.7

8.1

University of Valencia

50.0

University of Almería

50.0

because, given their experience, job, or knowledge of the context, they could help in the adaptation of the ICT usage instrument to the study context. ICT usage was measured with a scale of 7 items, using an 11-point Likert scale from 0=“totally disagree” to 10=“totally agree”. Given the inexistence of scales for measuring this construct in the specific field of research, the proposed items cover the main ICT used by students during their learning process. Following the literature, ICT are classified in three types of tools: communication, author and administration tools, supporting the teaching; research; and administrative management processes of the educational service. Moreover, an expert panel checked these items and generated the final questionnaire. Table 2 shows the 7 items composing the intensity of educational ICT usage measurement instrument: the first 3 items support the administrative management process and help the communication among administrative personnel and teachers with students and graduates; the following 4 items mainly support the teaching and research process. Then, the main ICT at students’ disposal have been taken into account, which complements the service universities provide to their students. A pre-test study was carried out in order to increase the measurement reliability. Cronbach’s Alpha for the multi-item measure of ICT usage was .86, above the minimum of .70 accepted (Nunnally 1978). Some items were reworded trying to increase scale homogeneity. An exploratory factor analysis was developed in order to check the one-dimensionality of the scale proposed. Results are found in Table 3.

Table 2 ICT usage scale ICT1

Access to the website of the University to search for information

ICT2

Virtual secretary of the University (to check marks, registration fees, schedules, books)

ICT3

University e-mail

ICT4

Virtual classroom (to download documents, forums,activities, etc.)

ICT5

Electronic resources of the University (journals, databases, etc.)

ICT6

Usage of projectors for classroom presentations

ICT7

Usage of Internet for the learning process


Table 3 Exploratory factor analysis of the ICT usage scale

% Variance explained= 59.54 Cronbach’s Alpha =.868 Kaiser-Meyer-Olkin =.890; Barlett’s Sphericity: Chi-square=3916.056; Degrees of freedom = 21; SIG. =.000

ICT usage items

Factor loadings

Item-total correlation

ICT1

.892

.797

ICT2

.873

.770

ICT3

.828

.724

ICT4

.809

.713

ICT5

.657

.561

ICT6

.413

.331

ICT7

.817

.716

Table 4 provides the correlation matrix of the ICT usage items. As it can be observed, each pair of items show a high correlation, which indicates the proximity of the seven aspects included as part of the ICT usage. 3.3 Results In order to develop an exploratory analysis about the level of use of each ICT made by the graduates during their training at their university, we reduced the measurement scale to four levels –never, once in a while, often, very frequent– (Table 5). Findings show that most of the graduates used ICT on a regular basis. As it is observed, about 55.4 % of the graduates acceded very frequently to the website of the university to search for information and to the virtual secretary in order to check marks, registration fees, schedules, books, etc. Only 6 % of the graduates reported that they never used university e-mail during their studies. A similar rate, around 8.1 %, was also found for graduates’ usage of virtual classroom to download documents, for forums, etc. The use of projectors for classroom presentations, however, was even less frequent than the use of electronic resources (journals, databases, etc.) of the university. About 10.4 % reported that they had never used the electronic resources, and 24.5 % said that they had never used the projectors. Finally, about 51.1 % reported to have used very frequently Internet for learning process. Regression analysis was also performed to examine the influence of gender, type of university, and area of expertise of the graduates on the usage of each ICT item Table 4 Correlations among ICT usage items ICT items

Mean

ICT1

ICT1

7.190

1.000

ICT2

7.160

.838***

ICT3

6.930

.707***

.688***

6.440

***

.648***

.590***

***

***

.465***

.536***

***

***

.266***

.282***

***

***

.430***

ICT4 ICT5 ICT6 ICT7

5.880 4.320 7.100

ICT2

.635

.460

***

.265

***

.713

*P < .10; **P < .05; ***P < .01

ICT3

ICT4

ICT5

ICT6

ICT7

1.000

.443 .244

***

.652

1.000

.265 .609

1.000

.589

1.000 1.000 .293***

1.000


Table 5 Percentage of ICT usage

0–1=Never; 2–4=Once in a while; 5–7=often; 8–10=Very frequent

ICT items

Never

Once in a while

Often

Very frequent

Mean

SD

ICT1

2.7

9.8

32.8

54.7

3.4

.77

ICT2

3.9

8.3

32.4

55.4

3.3

.79

ICT3

6.0

10.5

30.4

53.1

3.3

.88

ICT4

8.1

13.3

34.2

44.4

3.1

.93

ICT5

10.4

14.6

42.6

32.4

2.9

.94

ICT6

24.5

21.9

38.9

14.7

2.4

1.01

ICT7

3.2

9.7

36.0

51.1

3.3

.78

(Table 6). Results show that only the regression conducted on the second item of ICT was not significant. Graduates’ gender, university and area of expertise do not determine the use of the virtual secretaries of the universities. For all educational ICT forms, the gender of graduates is the main variable in determining their level of usage. It significantly explains the majority of the ICT items, except the use of the virtual secretary and the projectors for classroom presentations. It is also remarkable that the area of expertise only influences the usage of two ICT variables: the virtual classroom and the usage, in general, of the Internet for the learning process. Similarly, the university where graduates made their training also influences on the usage of the virtual classroom and, additionally, on the electronic resources and projectors for presentations.

4 Discussion and conclusions Research about educational ICT integration has raised questions about ICT usage. The present study reports findings about which factors influence on this variable. Results confirm that graduates’ experiences with technology in education are related to gender, area of expertise and the type of university where they were studying. As expected, gender showed a significant influence on ICT usage, confirming the results of previous studies (Ilomäki and Rantanen 2007; Kennewell and Morgan 2006; Vekiri 2010; Volman et al. 2005). Cross tabulation of the ICT categorized items and gender, university and area of expertise, gave some ideas about the ICT users profile.1 Regarding gender, there are no differences between men and women in the usage of projectors for classroom presentations (ICT6) (p>.1). This result is certainly logic given that students use projects at class usually for making presentations, which are required to all students regardless of their gender. There are small differences between them in the frequency of access to the university website (ICT1), usage of the virtual secretary of the university (ICT2), and usage of the Internet for the learning process (ICT7) (p