Computers & Education 63 (2013) 306–317

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Computers & Education

journal homepage: www.elsevier .com/locate/compedu

Perceived playfulness, gender differences and technology acceptancemodel in a blended learning scenario

Antonio Padilla-Meléndez*, Ana Rosa del Aguila-Obra, Aurora Garrido-MorenoUniversity of Malaga, Spain

a r t i c l e i n f o

Article history:Received 25 February 2012Received in revised form5 November 2012Accepted 18 December 2012

Keywords:Perceived playfulnessGenderTechnology acceptance modelBlended learning

* Corresponding author. Facultad de Estudios SocialE-mail address: apm@uma.es (A. Padilla-Melénde

0360-1315/$ – see front matter � 2012 Elsevier Ltd.http://dx.doi.org/10.1016/j.compedu.2012.12.014

a b s t r a c t

The importance of technology for education is increasing year-by-year at all educational levels andparticularly for Universities. This paper reexamines one important determinant of technology acceptanceand use, such as perceived playfulness in the context of a blended learning setting and reveals existinggender differences. After a literature review on the mentioned topics, some statistical analysis, such asdifference between means and structural equation modeling, were run with a sample of 484 students.The main contribution of this study is to provide evidence that there exist gender differences in the effectof playfulness in the student attitude toward a technology and the intention to use it. In females,playfulness has a direct influence on attitude toward using the system. In males, this influence ismediated by perceived usefulness. Some implications and conclusions are included.

� 2012 Elsevier Ltd. All rights reserved.

1. Introduction

The introduction of technology in University programs or degrees is vital at the present time. Students are already digital natives thathave grownwith the technology and expect to use it at the University. Besides, one of the most significant changes in the field of educationduring the information age is the paradigm shift from teacher-centered to learner-centered education (Byoung-Chan, Jeong-Ok, & In, 2009).

In today’s society, students spend much of their spare time playing multimedia, interactive and social online games and entertainmenttechnology in general. In fact, today’s students are mostly from the Net Generation, and they arrive at university having been consumers oftechnology in ways that previous generations barely understand (Junco & Mastrodicasa, 2007). They may associate technology more withplayfulness thanwith learning. Therefore, it is interesting to analyze the influence of the game and enjoy, including also gender differences,regarding the intended use and the use of technology to support teaching and learning processes.

The Technology Acceptance Model (TAM) (Davis, 1989) is the most frequently cited and influential model for understanding theacceptance of information technology and has received extensive empirical support (e.g., Venkatesh, Morris, Davis, & Davis, 2003). In thiscontext, some extrinsic and intrinsic motivators of technology acceptance have been considered. Extrinsic motivators, such as perceivedusefulness and ease of use (Lee, Cheung, & Chen, 2005) have being proved to be key determinants of the acceptance and use of e-learningsystems, however, little is known about students’ perceptions in a blended learning setting (Tselios, Daskalakis, & Papadopoulou, 2011).Different constructs such as playfulness, enjoyment and flow, have been proposed as intrinsic motivators. In particular, playfulness isdefined as an individual’s tendency to interact spontaneously, inventively and imaginatively with computers (Webster & Martocchio, 1992).It has beenwidely included in the TAMmodel as a facilitating condition, influencing directly the extrinsic motivators. However, there is nota clear understanding of its specific role and influence on both perceived usefulness and ease of use. Consequently, more research is neededto further explore the nature and specific influence of usage-context factors, such as perceived playfulness, on user’s acceptance of a specificsystem (Moon & Kim, 2001).

Additionally, some studies introduce the gender perspective when testing TAM and consider playfulness. The results so far seem to becontradictory. In some cases no gender differences have been found (Whitley, 1997). In others, evidence has suggested gender differencesbecause males use internet for entertainment and web page creation more than females do (Papastergiou & Solomonidou, 2005).

es y del Trabajo, Campus de Teatinos (Ampliación), Universidad de Málaga, 29071 Málaga, Spain. Tel.: þ34 951952084.z).

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Furthermore, gender differences exist also with regard to web acceptance and use, particularly in flow, ease of use and usefulness (Sánchez-Franco, 2006). Especially, it has been observed that men’s usage decisions were more significantly influenced by their perception of use-fulness (Kim, 2010; Ong & Lai, 2006). In addition, both genders have been found to use more a web-based system if it is playful and itscontent is clear and relative to the course, being men mostly motivated by perceived usefulness and women by ease of use (Terzis &Economides, 2011a).

Due to these contradictory results, it is necessary to analyze in detail what are the determinants of intention to use from a genderperspective and in particular considering playfulness. Thus, the objectives of this paper are twofold. Firstly, to test a TAM-based extendedmodel including perceived playfulness as intrinsic motivator for explaining the intention of use of blended learning systems. Secondly, toanalyze the differences in themodel related to gender, in the context of the TAM, andwith students users of a blended learning system (BLS).This paper contributes to the literature, firstly, providing evidence about the acceptance (including gender differences) of an underrepre-sented technology such as Moodle as blended learning system with longitudinal data from undergraduates enrolled in technical and non-technical degrees. Secondly, the influence of perceived playfulness on perceived ease of use and perceived usefulness is analyzed, froma gender perspective. This allows proposing some relevant implications to take into account when adopting blended learning systems.

The context inwhich the research is conducted is a University where Moodle is used as BLS. The particular innovative experience relatedto this paper has been developed longitudinally through a period of three years of teaching Management to 1290 students.

The paper continues with a literature review on TAM, perceived playfulness and gender and TAM. From this, a research model is pro-posed, and the methodology and main results are summarized and discussed. The conclusions and limitations close the paper.

2. Literature review

2.1. TAM

The TAMmodel is widely known (Ma & Liu, 2004; Venkatesh, 2000; Venkatesh & Davis, 2000; Venkatesh, Speier, & Morris, 2002) and ithas received strong theoretical and empirical support in the literature, being cited more than 700 times (Davis, 2007). The TAMmodel wasinitially developed by Davis (1989), based on the theoretical grounding of the Theory of Reasoned Action (Fishbein & Ajzen, 1975). TAMdescribes the issue of how users accept and use a specific technology, as a function of the causal relationships between systems designfeatures, perceived usefulness, perceived ease of use, attitude toward using, and use. The TAM assumes that user adoption and effective useare determined by the intention to use a system, which is in turn affected by perceived usefulness, ease of use and attitudes toward using thesystem. Consequently, perceived usefulness and perceived ease of use are the two primary predictors of effective acceptance and use. Theinitial model was subsequently improved, by adding other relevant variables. Accordingly, TAM2 incorporates additional theoretical con-structs, including social influence processes and cognitive instrumental processes (Venkatesh & Davis, 2000). Subsequently, TAM3 positsnew theoretical relationships such as the moderating effects of experience on key relationships, suggesting that experience will moderatethe relationships between perceived ease of use and perceived usefulness, computer anxiety and perceived ease of use and perceived ease ofuse and behavioral intention (Venkatesh & Bala, 2008).

In particular, there have been published several papers in the context of the application of TAM in an educational context (Dasgupta,Granger, & McGarry, 2002; Escobar-Rodriguez & Monge-Lozano, 2012; Gong, Xu, & Yu, 2004; Martins & Kellermanns, 2004; Padilla-Meléndez, Garrido-Moreno & Del Aguila-Obra, 2008; Szajna, 1996; Taylor & Todd, 1995; among others).

Summarizing these approaches, extrinsic and intrinsic motivators have being proposed as factors affecting the acceptance of technology.Extrinsic motivation refers to the performance of an activity for achieving valued outcomes that are distinct from the activity itself, such asimproving job performance, pay, etc. Intrinsic motivation refers to the performance of an activity for no apparent reason other than theprocess of performing it (Deci & Ryan, 1985). As extrinsic motivators, perceived usefulness and ease of use have being considered (Lee et al.,2005). Playfulness, enjoyment and flow have been proposed as intrinsic motivators (e.g. Venkatesh, 2000).

In the context of the TAM, the acceptance of some technological learning platforms, such as WebCT (e.g. Ngai, Poon, & Chan, 2007;Sánchez-Franco, 2010) or Moodle (e.g. Escobar-Rodriguez & Monge-Lozano, 2012; Martín-Blas & Serrano-Fernández, 2009). However, littleis known about students’ perceptions in a blended learning setting (Tselios et al., 2011). TAM is a theoretical framework now considered asappropriate by some authors to predict student satisfaction in blended learning contexts, since it has been shown that the TAM variablessignificantly influence student satisfaction in these environments (Arbaugh et al., 2009). It has been used, for example, in order to inves-tigate university students’ attitudes toward blended learning in different countries (Gong et al., 2004; Tselios et al., 2011).

Consequently, these hypothesis regarding the acceptance and intention to use blended learning systems can be proposed:

H1. Perceived ease of use will have a positive effect on perceived usefulness.

H2. Perceived usefulness will have a positive effect on attitude.

H3. Perceived ease of use will have a positive effect on attitude.

H4. Attitude will have a positive effect on intention to use a BLS.

2.2. Perceived playfulness

Users are not always rational or logical and emotion plays an often-overlooked role in user acceptance of a particular technology (Zhang& Li, 2005). Three different but related approaches have been proposed to include this in the technology acceptance research, particularly inthe TAM model: perceived enjoyment, flow and perceived playfulness. Perceived enjoyment is the extent to which “the activity of usinga specific system is perceived to be enjoyable in its own right, aside from any performance consequences resulting from system use”(Venkatesh, 2000, p. 351). Flow theory emphasizes the role of a specific context rather than individual differences in explaining humanmotivated behaviors and, provided there is not a consensus in how to measure flow, playfulness is a concept that is used most widely to

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measure it (Byoung-Chan et al., 2009). Computer playfulness has been defined as “the degree of cognitive spontaneity in microcomputerinteractions” (Webster & Martocchio, 1992, p. 204). Playfulness is a complex variable, which includes individual’s pleasure, psychologicalstimulation, and interests (Csikszentmihalyi, 1990).

Additionally, playfulness is considered as an intrinsic belief or motivation (Lee et al., 2005), which is shaped from the individual’s ex-periences with the environment (Moon & Kim, 2001). Perceived playfulness represents the intrinsic motivation associated with using anynew system (Venkatesh & Bala, 2008). When individuals are in the playfulness or flow state, they will find the interaction intrinsicallyinteresting, as they are involved in the activity for pleasure and enjoyment rather than for extrinsic rewards (Moon & Kim, 2001). Fur-thermore, playfulness and perceived enjoyment could be considered as a part of the facilitating conditions that determine perceivedusefulness and perceive ease of use, being individual differences, system characteristics and social influence the other three determinants(Venkatesh & Bala, 2008).

As dimensions of perceived playfulness, in the case of web use, there are the extent to which the individual (a) perceives that his or herattention is focused on the interaction with the Web; (b) is curious during the interaction; and (c) finds the interaction intrinsicallyenjoyable or interesting (Moon & Kim, 2001).

Perceived playfulness has been considered together with TAM quite since the beginning of it (e.g. Chung & Tan, 2004; Venkatesh, 2000).Summarizing previous research, several studies have tested the empirical relevance of perceived playfulness as an integrative variable of theTAM model (See Table 1).

It has been studied as a consequence of perceived ease of use (Cheong & Park, 2005; Lee et al., 2005; Liao & Tsou, 2009; Moon & Kim,2001; Tao, Cheng, & Sun, 2009; Terzis & Economides, 2011b) and as a consequence of perceived usefulness (Terzis & Economides, 2011b).However, there are other studies that consider the role of playfulness in the intention to use a system as an antecedent of other factors. Thus,it has being studied as antecedent of perceived usefulness (Hong, Hwang, Hsu,Wong, & Chen, 2011; Yi & Hwang, 2003) and perceived ease ofuse (Çelik, 2008, 2011; Davis & Wong, 2007; Hong et al., 2011; Sun & Zhang, 2008; Venkatesh, 2000; Venkatesh & Bala, 2008; Venkateshet al., 2002; Yi & Hwang, 2003). As a consequence, and having the objective of testing the direct and indirect influence of perceivedplayfulness on the intention to use blended learning systems, these hypothesis were proposed:

H5. Perceived playfulness will have a positive effect on intention to use a BLS.

H6. Perceived playfulness will have a positive effect on perceived usefulness.

H7. Perceived playfulness will have a positive effect on attitude.

H8. Perceived playfulness will have a positive effect on perceive ease of use.

2.3. Gender and TAM

There is a considerable interest in the literature in studying the influence of gender on technology acceptance and use (e.g. Braak, 2004;Chou, Wu, & Chen, 2011; González-Gómez, Guardiola, Martín-Rodríguez, & Montero-Alonso, 2012; Ong & Lai, 2006; Papastergiou &Solomonidou, 2005; Sánchez-Franco, 2006; Schumacher & Morahan-Martin, 2001; Terzis & Economides, 2011a; Thompson & Lim, 1996;Whitley, 1997).

However, the results of these studies have been so far somehow contradictory. For example, Thompson and Lim (1996) examined genderdifferences in the factors related to PC usage and found that females tend to view PCs as being less easy to use comparedwithmales. Whitley(1997), in a study about gender differences in computer-related attitudes and behavior using US and Canadian participants, found thatgender differences in computer-related behaviors were small and did not differ as a function of study population. Nevertheless, Schumacherand Morahan-Martin (2001) analyzed changes in computer experiences among incoming college students using data from two differentsamples (1990 and 1997). They observed that males were more experienced than females with computer programming and games, andconcluded that this greater experience may enhance the technical sophistication of males with computers and account for the greaterdegree of competency and comfort with both the Internet and computers found among male students compared with female students.

Additionally, Braak (2004) found that girls felt less confident with computers than boys did. And Papastergiou and Solomonidou (2005)investigated gender differences in internet use by Greek high school pupils within school and out of school environments, finding that boyshad more opportunities to access the internet and that they used internet for entertainment and Web page creation more than girls do,whereas no other significant gender differences were noted regarding pupils’ other internet activities. Furthermore, Sánchez-Franco (2006)analyzed the web acceptance and usage between males and females, incorporating intrinsic human factors. The empirical results dem-onstrated how males and females differed in their ‘web acceptance and usage’ processes; and highlighted the roles of flow, ease of use andusefulness in determining the actual use of the web between males and females. Similarly, Ong and Lai (2006) explored gender differencesin perceptions and relationships among dominants affecting e-learning acceptance. They found that men’s rating of computer self-efficacy,perceived usefulness, perceived ease of use, and behavioral intention to use e-learningwere all higher thanwomen’s andwomenweremorestrongly influenced by perceptions of computer self-efficacy and ease of use. They also observed that men’s use decisions were moresignificantly influenced by their perception of usefulness of e-learning.

In addition, Terzis and Economides (2011a) identified the constructs that affected male and female students’ behavioral intention to usea computer based assessment. They found that both genders were more likely to use the system if it was playful and its content was clearand relative to the course. Males were also motivated by their perceptions regarding how much useful the system was, and their attitudetoward the system was influenced by their social environment. Females were more likely to use the system if it was easy to use andstimulates their efforts for better final exam preparation. Similarly, Chou et al. (2011) studied college students’ internet-related attitudes andexamined whether gender and grade level made any difference in their attitudes. They found that male students had a more positiveattitude toward the internet-related enjoyment dimension than did female students. Finally, González-Gómez et al. (2012) analyzed genderdifferences in e-learning teaching, trying to determine which aspects of teaching could be improved to boost the satisfaction of female andmale students. They observed significant differences between male and female students in terms of their satisfaction with e-learning

Table 1Summary of empirical studies relating TAM and playfulness.

Reference Specific area of study TAM hypotheses Playfulness related hypotheses PEU / P

PEU / PU PEU / ATT PU / ATT ATT / IU PU / IU PEU / IU P / PU P / PEU P / ATT P / IU

Venkatesh (2000) Employees in three organizations U U U U

Moon and Kim (2001) Users of the www U U U U U U U U

Venkatesh et al. (2002) Employees users of technology U U U U

Yi and Hwang (2003) (*) Blackboard systems acceptance * U U U

Hsu and Lu (2004) On-line games (Flow experience) U U U U U * U

Lee et al. (2005) (*) Students’ acceptance of an Internet-basedlearning medium

U * U U U U U U

Cheong and Park (2005) Use of mobile internet in Korea U U U U U U U U

Davis and Wong (2007) University students using an e-learningsystem

U U U U U

Çelik (2008) Users of internet banking U U U U U * U

Sun and Zhang (2008) General internet users of Web-basedsearch engines

U U U U

Venkatesh and Bala (2008) Technology acceptance in fourcompanies

U U U U

Wang and Wang (2008) Users of online games U

Byoung-Chan et al. (2009) E-learning U U U U

Oh et al. (2009) Virtual store in Korea * U U U U

Liao and Tsou (2009) Usage of SkypeOut U * U U

Sun and Cheng (2009) Virtual reality application based on Webcamera input-interface.

U * U * * U

Tao et al. (2009) Students of higher education U

Wang, Wu, and Wang (2009) Mobile learning users U

Chang (2010) Employment of intelligent agents in aweb-based auction process

U U U U

Çelik (2011) Online shoppers U U U U U

Hong et al. (2011) Digital archives U U U * U U U *Terzis and Economides (2011b) Computer based assessment system U * U U

Notes: U ¼ significant, * ¼ not significant, ATT: attitude toward the use, IU: intention to use, PEU: perceived ease of use, PU: perceived usefulness, P: playfulness (*): These papers studied specifically enjoyment, but they areincluded for their interest for this research.

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teaching. Results indicated that female students assignedmore importance to teachingmethods and planning thanmale students, as well asto fostering active participation in the learning process. In addition, they gave greater value to teacher participation, and took greatersatisfaction from the planning of the educational process and having various ways of contacting the teacher.

2.4. Proposed model

Based on the presented literature review, a research model was proposed including the impact of playfulness on the intention to use theBLS (see Fig. 1). This impact can be direct or indirect, mediated by attitude and also by perceived usefulness and perceived ease of use. Themodel was tested for males and females looking for gender differences according to the intention to use the BLS.

3. Methodology

This research is part of an educational innovation project that aimed primarily to understand what were the factors that influence theadoption and usage of BLS based on Moodle (2012a), (2012b) in a medium-sized Spanish university. Additionally, the project was intendedto promote communication and collaboration between groups of students, encouraging teamwork, and improve the tutorial activity basedon the virtual campus. Regarding learning platforms, there are a variety of them, both commercial and open source. For the study, it wasselected the Moodle (2012b) platform, that has 57,095,569 users around the world, in 219 countries, being Spain the second in the rankingafter the United States. In this sense, the use of Moodle as a platform for teaching/learning is consolidated in Spain and has been analyzed inthe literature in recent periods (Escobar-Rodriguez & Monge-Lozano, 2012; Martín-Blas & Serrano-Fernández, 2009). Moodle is a softwarepackage for producing Internet-based courses and web sites. Moodle is a Course Management System (CMS), also known as a LearningManagement System (LMS) or a Virtual Learning Environment (VLE). A teacher in a Moodle (2012a) course can select items from threedifferent elements that together assist in the learning process: activities, resources and blocks. An activity is a general name for a group offeatures in a Moodle course and usually is something that a student will do that interacts with other students and or the teacher, includingassignments, chat, database, external tools, forum, glossary, lessons, quizzes, SCORM, survey, wiki, workshop, among others. A resource is anitem that a teacher can use to support learning, such as a file or link. Moodle supports a range of resource types which teachers can add totheir courses, such as file, folder, IMS content package, label, page and URL. A block is an item that a teacher can add to the left or right ofa Moodle course page, providing extra information or links to aid learning and can be calendars, comments, community finder, coursecompletion status, course overview, course/site description, Flickr, latest news, login, main menu, online users, recent activity, social ac-tivities, upcoming events, YouTube, among others.

In the analyzed experience, the Moodle platform was used to design several BLS for seven specific subjects of the area of Management.BLS included the use of the following tools: bulletin board, tutoring forum, group work forum, practices forum, content rating with the toolconsultation, proposal of multimedia content through forums, personal tutoring and file sending. Collaborationwas also promoted betweenstudent groups through the use of forums and the creation and development of wikis by students.

A total of 1290 students, coming from seven different degrees, have taken part in the reported experience. This experience has beendeveloped in the context of an educational innovation projects of the university that started in 1998, although the data used in this paperconcern three academic courses (from 2008 to 09 to 2010–11). A web-based questionnaire was completed by undergraduate studentsparticipants in the project of three academic years and a total of 484 valid questionnaires were collected (of a total population of 1290students, response rate 37.52%). The questionnaire was designed based on the literature review and specifically on the studies of Byoung-Chan et al. (2009), Padilla-Meléndez et al. (2008) and Terzis and Economides (2011b). A 7-point Likert scale (1 ¼ totally disagree, 7 ¼ totallyagree) was used to measure the variables of the model.

4. Results and discussion

With the obtained results, descriptive analysis, difference between means, factor analysis and structural equation modeling analysiswere conducted.

4.1. Descriptive statistics and difference between means

About the descriptive analysis (see Table 2), 41.5% of the sample were male and 58.5% female. Most of the respondents were students ofthe Tourism Faculty and Social Sciences and Human Resources Faculty (60.1%) and the remaining were from five different centers of theUniversity.

Fig. 1. Research model.

Table 2Descriptive statistics.

Item No. of cases %

Academic year:2008/2009 128 26.42009/2010 93 19.22010/2011 263 54.3

Gender:Males 201 41.5Females 283 58.5

School or faculty:Tourism 165 34.1Social sciences and

human resources126 26.0

Computer science 64 13.2Management 67 13.8Telecommunications 33 6.8Polytechnic school 21 4.3Sciences 8 1.7

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To see the differences betweenmales and females in the different variables of themodel a means differences analysis was conducted (seeTable 3).

There were significant differences between males and females in playfulness, attitude and intention to use (Table 4). Regarding play-fulness and attitude, females had higher scores on these variables. However, respect to intention to use, males showed a greater intention touse the system than females.

In addition, it was analyzed if therewere significant differences in results between participants that came fromdifferent faculty using theKruskal–Wallis test (see Table 4). The Kruskal–Wallis Test is the nonparametric test equivalent to the one-wayANOVA and an extension of theMann–Whitney Test to allow the comparison of more than two independent groups. It is used when it is needed to compare three or moresets of scores that come from different groups, with non-normal data. Comparing data from the eight different centers, it was observed thatthere were significant differences in the following variables: playfulness, perceived ease of use (PEU4), attitude (ATT1) and intention to use.

To deepen this analysis, faculties were classified into two groups: technical (those who taught engineering degrees such as ComputerScience, Telecommunications, Polytechnic school and Sciences) and the remaining were labeled as non-technical (see Table 5).

In this case, there were significant differences between technical and non-technical faculties in playfulness and intention to use.Regarding playfulness, students from technical faculties had lower ratings on this variable. However, respect to intention to use, theyshowed a greater intention to use the system than students from non-technical faculties did.

4.2. Analysis of validity, reliability, and dimensionality of measurement scale

After confirming that the data availablewere suitable for use in factor analysis, and in order to evaluate themeasurement scale, four basicaspects of the scale were analyzed (Hair, Anderson, Tatham, & Black, 1998): its conceptual definition, validity, reliability, and dimensionality.Firstly, the conceptual definition refers to the theoretical bases considered in the scale development. As it was commented before, themeasurement scale was built based on an extensive literature review about TAM model, perceived playfulness and gender and TAM. Thevalidity of the scale was confirmed by considering its different modalities (content, construct, convergent, discriminant and external). Toensure content validity, a pretest of the questionnaire was made by three experts. Regarding construct validity, the measurement scale used

Table 3Differences between means.

Item Mean Standarddeviation

Mann–Whitney U

Wilcoxon W Significance Differencesbetween means

PlayfulnessP1: I enjoy using the virtual classroom designed with Moodle

(Moodle)3.88 1.397 25503.5 45804.5 0.042 Significant

P2: I feel Moodle use is fun 4.20 1.478 24006 44307 0.003 SignificantPerceived usefulnessPU1: Using Moodle improves my performance in this course 5.19 1.400 26508 46809 0.188PU2: Using Moodle is useful to me in this course 5.74 1.257 25784 46085 0.068PU3: Using Moodle helps me accomplish my learning effectively 5.16 1317 28066 68252 0.797PU4: Using Moodle makes my work easier in this course 5.74 1.248 26707.5 47008.5 0.232Perceived ease of usePEU1: It is easy to get Moodle to do what I need to do 5.72 1.161 26628 46929 0.210PEU2: Moodle is easy to use 6.10 1.063 26316 46617 0.131PEU3: My interaction with Moodle is clear and understandable 5.82 1.146 26823 47124 0.261PEU4: It is easy to become skillful at using Moodle 5.64 1.321 27309.5 47610.5 0.437AttitudeATT1: I like using Moodle 5.06 1.379 23762.5 44063.5 0.002 SignificantATT2: I would recommend Moodle to other students 5.53 1.406 24870 45171 0.015 SignificantIntention to useIU: I plan to use Moodle very often during next course 5.58 1.427 25648.5 65834.5 0.056 Significant

Table 4Differences between means (7 schools/faculties).

Item KruskalWallis H (X2)

Significance Differencesbetween means

P1 15.985 0.025 SignificantP2 18.345 0.011 SignificantPU1 11.276 0.127PU2 9.043 0.250PU3 12.368 0.089PU4 12.196 0.094PEU1 5.097 0.648PEU2 12.488 0.086PEU3 11.307 0.126PEU4 18.023 0.012 SignificantATT1 17.016 0.017 SignificantATT2 8.894 0.260IU 47.636 0.000 Significant

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constructs that were empirically identified and used in previous studies. To ensure the convergent and discriminant validity, the correlationmatrix between all the variables of the questionnaire was examined, verifying that indeed the correlations between variables of the sameconstruct were shown to be higher than correlations between different constructs. Finally, with regard to external validity, the samplingtechnique used (random sampling) allows that the obtained results were generalizable to the population.

To analyze the reliability of the scale, the Cronbach’s alpha was used, being greater than 0.7 in all cases, so the scale used to measure thevarious items was adequate and reliable (Hair et al., 1998).

Finally, in order to analyze the unidimensionality of the scale, a principal components exploratory factor analysis was carried out. Thecriteria used to calculate the number of factors to be extracted was an a priori criterion (the researcher sets the number of factors), based onthe theory and considerations of previous studies. However, it was considered also the latent root criterion, indicating that only the factorshaving latent roots or eigenvalues greater than 1 were significant and should be considered in the analysis (Hair et al., 1998). In this case, thefive considered factors had an eigenvalue greater than unity (justifying the variance of at least one variable). In order to refine the meas-urement scale, it was also tested that the factor loadings of the items and their communalities exceeded recommended thresholds. In thissense, it is assumed that the factor loadings exceeding a value of 0.45 were considered statistically significant, and that communalities mustbe higher than 0.5 (Hair et al., 1998). As it could be observed in Table 6, all themeasurement itemsmet both criteria, so this factorial structurewas assumed to estimate the structural model.

Additionally, the construct validity of the model’s scales was evaluated using confirmatory factor analysis (CFA). The objective of CFA is totest whether the data fit a hypothesized measurement model, so CFA is frequently used as a first step to assess the proposed measurementmodel in a Structural Equation Model. The software EQS 6.1 with maximum likelihood estimation was used to perform the analysis. Severalstatistical tests were used to determine howwell the model fits to the data (c2/df, CFI, IFI, NFI, NNFI, and RMSEA). Due to the restrictivenessof the Model Chi-Square, researchers have sought alternative indices to assess model fit. The relative/normed chi-square (c2/df) is a statisticthat minimizes the impact of sample size on the Model Chi-Square. The value of this index (2.81) was lower than 3, as recommended byKline (2005). In addition, the Comparative Fix Index (CFI) and Incremental Fit Index (IFI) values were 0.930 and 0.932 respectively, indicatinga reasonable fit, because they should approach 1.0 for a well-fitting model. Further, the Bentler-Bonett Normed Fit Index (NFI ¼ 0.889),Bentler-Bonett Nonnormed Fit Index (NNFI ¼ 0.901) and Root Mean Square Error of Approximation (RMSEA) (0.06 � 0.06) showed alladequate levels. Therefore, the proposed measurement model was reasonably acceptable to assess the results for the SEM technique. It wasobserved, in addition, that each item loaded to their respective scale and all of themwere significant. Results of the CFA analysis showed thatthe final scale had the proposed dimensions and had high reliability.

4.3. Structural model testing

Regarding the Structural Equation Modeling analysis, the basic assumptions for applying it were accomplished. Firstly the sample size ofthis study is 484 (>200 recommended observations). Secondly, the sample of data was randomly collected as suggested. Third, it is

Table 5Differences between means (technical versus non-technical studies).

Item Mann–Whitney U

Wilcoxon W Significance Differencesbetween means

P1 19081.00 26102.00 0.046 SignificantP2 18657.50 25678.00 0.022 SignificantPU1 20769.00 27790.00 0.519PU2 21405.00 88566.00 0.203PU3 21267.50 28288.50 0.798PU4 19985.00 87146.00 0.203PEU1 23839.50 27860.50 0.550PEU2 21012.50 28033.50 0.636PEU3 19467.00 26488.00 0.090PEU4 21301.50 88462.50 0.818ATT1 20180.00 27201.00 0.272ATT2 21309.00 88470.00 0.824IU 17993.00 85154.00 0.005 Significant

Table 6Factorial analysis and reliability (*).

Construct Communalities Factorloading

Reliabilitycronbach alpha

Perceived playfulness 0.877P1 0.891 0.944P2 0.891 0.944Perceived usefulness 0.837PU1 0.576 0.759PU2 0.741 0.861PU3 0.675 0.822PU4 0.713 0.824Perceived ease of use 0.834PEU1 0.532 0.730PEU2 0.729 0.854PEU3 0.747 0.864PEU4 0.688 0.830Attitude 0.741ATT1 0.794 0.891ATT2 0.794 0.891Intention to useIU – – –

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necessary not to have collinearity between variables. In this study, the correlationmatrix between the independent variables Xwas analyzed(see Table 7) and it was observed that their values were not high, proving to be less than 0.8, the reference value usually employed to denotea high collinearity. Therefore, it can be assumed that there were no problems of collinearity in the data.

The datawere not normal (the normalizedMardia coefficient of multivariate kurtosis equals 26.5>1.96), so the statistics package EQS 6.1was used to estimate the SEMmodel. This software can be used to estimate robust goodness-of-fit indicators as well as the robust chi-squarestatistic (Satorra–Bentler scaled statistic), which corrects the chi square when the variables are nonnormal (Satorra & Bentler, 1994, 2001).

Themodel was estimated for both samples, females andmales, and using longitudinal data from three different academic years (see Figs.2 and 3).

The model fit indicators presented acceptable values (see Table 8) with the exception of Chi-square indicator (that is not a very good fitindex in practice because it is affected by sample size and distribution of variables). In females, the model explains (see the r-squared) lessthan for males. However, the explanatory power of the presented models is consistent with previous studies, because it is considered thatTAM consistently explains about 40% of the variance in individuals’ intention to use a specific system (Venkatesh & Davis, 2000).

Regarding the hypotheses testing (see Table 9), the positive relationship between perceived ease of use and usefulness was foundsignificant in both samples, so Hypothesis 1 (H1) was supported. H2 examined the links between perceived usefulness and attitude and thisrelation was significant for males and females, supporting H2. It was observed that the relationship between perceived ease of use andattitude was only significant for females, so H3 was not supported in the males’ sample. Attitude showed a direct impact on intention to usethe BLS in both samples, thus H4 was also supported. Respect to the effect of playfulness, it did not show a significant direct effect on theintention to use the system, not supporting H5. It was observed that playfulness directly influenced both perceived usefulness and ease ofuse, so it was an antecedent of these variables in both samples, supporting H6 and H8. Finally, regarding the effect of playfulness on attitude,in females this relationship was significant, but for males, playfulness showed no direct impact on attitude, only an indirect effect mediatedby perceived usefulness. Thus, H7 was only supported in the females’ sample.

Additionally, hypotheses on intensity differences between both males and females were tested by statistically comparing correspondingpath coefficients in both structural models. This statistical comparison was carried out using the procedure suggested by Chin (2000) todevelop amulti-group analysis (Sánchez-Franco & Roldán, 2005). According to this procedure, a t-test was calculated following equation (1),which follows a t-distribution withm þ n � 2 degrees of freedom, where B represent values of paths, SE is the standard error of path in thestructural model m and n are the samples of males and females users group respectively. Results are showed in Table 10.

t ¼ ðBmales� BfemalesÞffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi�SEmales2 þ SEfemales2

�q (1)

Results of the multi-group analysis showed that there existed significant differences only in one path of the proposedmodel. Specifically,the path coefficient from perceived ease of use to perceived usefulness in the structural model for males was significantly stronger than thecorresponding path coefficients in the structural model for females (t ¼ 1.85, p < 0.05). This difference can be explained by the fact that, in

Table 7Correlation matrix.

IU P PU PEU ATT

IU 1P 0.218(**) 1PU 0.435(**) 0.417(**) 1PEU 0.369(**) 0.321(**) 0.590(**) 1ATT 0.362(**) 0.552(**) 0.663(**) 0.548(**) 1

** All correlations were significant at 0.01 (bilateral).

Fig. 2. Estimated model for females (N ¼ 283).

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the case of males, perceived ease of use did not influence attitude directly, but indirectly through perceived usefulness. Consequently, therelationship between perceived ease of use and perceived usefulness is significantly stronger that in the case of females, because this pathincludes also the underlying indirect effect.

However, in the rest of paths of the model, no significant differences were found between males and females. This can indicate that ingeneral terms there is a common behavior pattern in both genders and the proposedmodel seems appropriate to explain it and hence can beextrapolated to the whole population.

4.4. Discussion

After showing the existing research gap in the field of technology acceptance in blended learning environments, this research exploresthis issue stressing the role of playfulness and introducing a gender perspective into the TAM model.

Regarding gender differences in perceived playfulness effects, females’ ratings of perceptions regarding playfulness and attitude werehigher than males’. However, males’ ratings of intention to use the systemwere higher than females’. No significant difference was found inperceived usefulness and ease of use depending on the gender. That could mean that the systemwas perceived as easy to use and useful toimprove the performance in the course for both genders. Additionally, it was analyzed if significant differences between students fromdifferent faculties existed and it was found that students from technical faculties had lower ratings on playfulness than non-technical onesbut showed greater intention to use the system.

The proposedmodel was estimated including data from three academic periods from a number of University centers. It was found in bothsamples (males and females) that playfulness had a direct impact on the variables perceived usefulness and ease of use. However, it wasobserved that the direct relationship between playfulness and intention to use appears to be non-significant. This may indicate that, in thecase of a mandatory-use technology, such as the analyzed system, the fact that technology is more or less enjoyable does not have an impacton their intended use. Thus, contrary to Lee et al. (2005), Roca, Chiu, andMartinez (2006) and Byoung-Chan et al. (2009), among others, thatfound a direct relationship between playfulness and intention to use in e-learning contexts, in this study of a blended learning system suchrelationship was not observed. However, analyzing technology acceptance from a cultural perspective, Sánchez-Franco, Martínez-López,and Martín-Velicia (2009) noted that the playfulness of e-learning does not affect the intention to use the system among Mediterraneaneducators, while the enjoyment of e-learning affects the intention to use it among Nordic educators.

Nevertheless, the effect of playfulness on intention to use is mediated by the individual’s attitude toward using (which is explained by theperceived ease of use and perceived usefulness). This relationship shows some differences from a gender perspective. On the one hand, infemales, the conventional assumptions from TAM have being observed, and playfulness indirectly influence attitude both directly andindirectly (perceived ease of use and perceived usefulness mediate the influence). However, contrary to Lee et al. (2005) findings, perceivedease of use is an important factor for explaining female student attitude toward BLS acceptance and use. On the other hand, the estimatedmodel for males do not show any direct relation between perceived ease of use and attitude, and this seems to be consistent with Teo, Lim,and Lai (1999) that found that the fact of learning how to use the Internet was generally considered easy, so it appears that men consider BLSeasier to use than females. Therefore, similarly to Terzis and Economides (2011a), it was found that ease of use does not play important role

Fig. 3. Estimated model for males (N ¼ 201).

Table 8Goodness-of-fit indicators of the estimated models.

Indicator For females (N ¼ 283) For males (N ¼ 201) Recommendedvalue

Value Value

Satorra-Bentler chi-square P ¼ 0.00099 P ¼ 0.00096 p � 0.05RMSEA 0.049 0.059 �0.05RMSEA confidence interval (0.031, 0.066) (0.037, 0.058) narrowNNFI 0.917 0.913 �0.9IFI 0.943 0.940 �0.9CFI 0.941 0.938 �0.9Normed chi-square 1.67 1.67 >1; <2AIC �17.47 �17.36 Small values

Table 9Summary of the hypotheses testing.

Hypothesis Females Males

H1 PEU / PU 0.433* 0.754*H2 PU / ATT 0.546* 0.762*H3 PEU / ATT 0.341* Not supportedH4 ATT / IU 0.617* 0.930*H5 P / IU N. supported N. supportedH6 P / PU 0.217* 0.183*H7 P / ATT 0.433* N. supportedH8 P / PEU 0.397* 0.301*

Table 10T-tests for multi-group analysis.

Path Bmales Bfemales Bmales–Bfemales

t-Value Significance Differencesbetween paths

PEU / PU 0.754 0.433 0.321 1.85165945 0.03234304 SignificantPU / ATT 0.762 0.546 0.216 1.02145073 0.15377666PEU / ATT 0.061 0.341 �0.280 �1.63622428 0.05122270ATT / IU 0.930 0.617 0.313 1.05692590 0.14553742P / IU �0.222 �0.006 �0.216 �1.15185667 0.12497549P / PU 0.183 0.217 �0.034 �0.46423142 0.32134577P / ATT 0.234 0.219 0.015 0.14880689 0.44088412P / PEU 0.301 0.397 �0.096 �1.02899151 0.15199987

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for men as for women, since they are more confident with the use of technology in general, so they do not give enough attention to ease ofuse. Additionally, the relation between playfulness and intention to use is mediated by perceived usefulness, in the estimatedmodel for menand this is consistent with Venkatesh and Bala (2008), which found perceived usefulness as being the strongest predictor of behavioralintention, and Byoung-Chan et al. (2009) that found perceived ease of use to be a significant antecedent of perceived usefulness. Thus,similar to Ong and Lai (2006), it was found that intention to use of males was more significantly influenced by their perception of usefulnessof BLS. In this sense, Kim (2010) also observed that female users were more likely to use the service if it was easy to use, while male userswere more likely to use the service if they perceived that it was useful, because they are much more goal- and performance-oriented thanfemales.

In the context of e-learning, technology awareness, motivation and changing learners’ behavior have being found to be prerequisites forsuccessful e-learning implementations (Bhuasiri, Xaymoungkhoun, Zo, Rho, & Ciganek, 2012). In this study, results show that both perceivedusefulness and perceived playfulness play an important role in affecting student attitude and intention to use BLS, but it depends on thegender. Surprisingly, perceive ease of use did not posit a direct impact on student attitude toward BLS usage in the case of men. On the otherhand, perceived ease of use influences student intention to use BLS indirectly through perceived usefulness. Additionally, the effect ofplayfulness on intention to use is mediated by the individual’s attitude toward using and it is stronger in the case of female students.

To further explore how the values of significant paths were also statistically different between genders, a multi-group analysis wasperformed. It was observed that only the path coefficient from perceived ease of use to perceived usefulness was significantly stronger formales than the corresponding path coefficients in the structural model for females. However, in the rest of paths of the model, no significantgender differences were found.

5. Conclusions

In this paper, a TAM-based extended model including perceived playfulness as intrinsic motivator for explaining the intention of use ofblended learning systems has been tested. In addition, the differences in the model related to gender, in the context of the TAM, and withstudents users of a blended learning system (BLS) has been analyzed. This research contributes to the literature providing evidence aboutthe acceptance of an underrepresented technology such as Moodle as blended learning systemwith longitudinal data from undergraduates

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enrolled in technical and non-technical degrees. Additionally, it shows the influence of perceived playfulness as an antecedent of perceivedease of use and perceived usefulness and gives some evidence about gender differences regarding those issues.

The main conclusion is that there are significant differences between males and females regarding playfulness, attitude and intention touse, so researchers should take into consideration factors of gender in the development and testing of e-learning theories (Ong & Lai, 2006).Females’ ratings of perceptions regarding playfulness and attitude were higher than males’. However, males’ ratings of intention to use thesystem were higher than females’. No significant difference was found in perceived usefulness and ease of use depending on the gender.According to this, the results obtained show that a successful BLS must therefore consider the components of usefulness and playfulness.Practitioners have to pay special attention to extrinsic motivational factors and intrinsic motivational factors in designing a BLS. Under-standing how this newgeneration of students uses technology to communicate and how it influences their values is the first step inmeetingtheir needs and develop successful learning systems (Junco & Mastrodicasa, 2007).

These findings, therefore, provide practitioners (teachers, course designer and academic institutions) some guidelines on the design andimplementation of the BLS. Perceived usefulness and playfulness are found to be key drivers for the adoption and use of BLS depending ofuser’s gender. Teachers or academic institutions should try to make learning through BLS useful and fun. Accordingly, some guidelines forthe design of BLS could be provided. Firstly, regarding virtual classroom content, teachers now, acting in the role of content managers, cantake advantage of the rich multimedia capability of the BLS to disseminate information using images, videos, and other multimedia re-sources, to facilitate students understanding of the coursematerial. This virtual classroom is a tool that helps student to better organize theirtime and manage the contents of the field. Secondly, related to entertainment, teachers should make use of games, quizzes, and othercreative approaches to introduce more fun and interest in the learning process through BLS. Thirdly, with respect to communication andcollaboration tools, the BLS create a direct channel between teacher and student, without intermediaries, and asynchronous, without relyingon the simultaneous space-time. Teachers maymake use of news forums and discussion forums when students can collaborate and exploretopics, discuss and write together. Fourth, regarding virtual campuses, course designers and academic institutions should adopt standardtechnology to teaching as Moodle, for example, to facilitate the acceptance by teachers and by students. This work shows that in the case offemales perceived ease of use is particularly perceived as a critical factor in the acceptance of BLS.

This study, as any other empirical study has limitations. First, there are other variables apart from the considered ones, such as socialnorms or perceived self-efficacy, which could be added in order to explain better technology acceptance, especially in the case of females,where the explanatory power of the model was lower. However, this study provides a useful framework to analyze playfulness includinggender differences and showing some interesting findings. Second, the use of data coming from another universities, regions or countrieswould contribute to the generalizability of the results. Nevertheless, the studied sample seems appropriate for the field of application.

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