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The influence of perceivedconvenience and curiosity oncontinuance intention in mobile Englishlearning for high school students usingPDAsChi-Cheng Chang a , Kuo-Hung Tseng b , Chaoyun Liang c & Chi-Fang Yan da Technology Application and Human Resource Development ,National Taiwan Normal University , Taipei , Taiwanb Graduate Institute of Business and Management , MeihoUniversity , No.23, Pingguang Rd, Neipu, Pingtung , Taiwanc Department of Information Communication , Yuan ZeUniversity , Taoyuan , Taiwand Department of Information Processing, Senior CommericalSchool of Continuing Education , National Taichung Institute ofTechnology , Taichung , TaiwanPublished online: 30 Jul 2013.
To cite this article: Chi-Cheng Chang , Kuo-Hung Tseng , Chaoyun Liang & Chi-Fang Yan (2013)The influence of perceived convenience and curiosity on continuance intention in mobile Englishlearning for high school students using PDAs, Technology, Pedagogy and Education, 22:3, 373-386,DOI: 10.1080/1475939X.2013.802991
To link to this article: http://dx.doi.org/10.1080/1475939X.2013.802991
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The influence of perceived convenience and curiosity oncontinuance intention in mobile English learning for high schoolstudents using PDAs
Chi-Cheng Changa*, Kuo-Hung Tsengb, Chaoyun Liangc and Chi-Fang Yand
aTechnology Application and Human Resource Development, National Taiwan NormalUniversity, Taipei, Taiwan; bGraduate Institute of Business and Management, MeihoUniversity, No.23, Pingguang Rd., Neipu, Pingtung, Taiwan; cDepartment of InformationCommunication, Yuan Ze University, Taoyuan, Taiwan; dDepartment of InformationProcessing, Senior Commerical School of Continuing Education, National Taichung Instituteof Technology, Taichung, Taiwan
(Received 9 January 2012; final version received 29 June 2012)
Mobile learning aims to utilise communication devices such as mobile devicesand wireless connection in combination with e-learning systems, allowinglearners to experience convenient, instant and suitable learning at unrestrictedtime and place. Participants were 125 Taiwanese senior high school students,whose continuance intention was examined after learning English via PDAs(personal digital assistants). The study, using the one-group post-test design,adopted the Technology Acceptance Model and incorporated factors such ascuriosity and perceived convenience. The results indicated that (1) curiosity hada positive effect on continuance intention; (2) perceived convenience had apositive effect on perceived usefulness and continuance intention.
Keywords: continuance intention; mobile English learning; perceivedconvenience; perceived curiosity
1. Introduction
Mobile learning is quite different from e-learning in that it involves the use ofmobile technologies and wireless networks to interact with more devices, so that itsstrong portability and mobility facilitates learning processes by not only breakingdown time and geographical barriers but also bringing substantial convenience,immediacy and suitability (Walton, Childs, & Blenkinsopp, 2005). The study ofChen and Chung (2008) showed that learners substantially benefit from theintegration of mobile devices into personalised English vocabulary learning, whichmakes the process not only effective but also fun. Lu (2008) also exploited Englishvocabulary learning using mobile phones, and Chen and Hsu (2008) investigatedEnglish reading skills via a personalised intelligent mobile learning system.Edirisingha, Rizzi, Nie, and Rothwell (2007) explored English listening comprehen-sion using Podcasting. Some research in English learning has focused on howmobile technology can provide various language learning experiences andoutcomes. Ducate and Lomicka (2009) used Podcasting as an effective tool for
*Corresponding author. Email: [email protected]
Technology, Pedagogy and Education, 2013Vol. 22, No. 3, 373–386, http://dx.doi.org/10.1080/1475939X.2013.802991
� 2013 Association for Information Technology in Teacher Education
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honing language students’ pronunciation. In other words, mobile learning could beinstrumental in enhancing outcomes and motivation for learning English. Recentresearch into the use of technology in language learning has shifted from ComputerAssisted Language Learning (CALL) to Mobile Assisted Language Learning(MALL) (Chinnery, 2006; Kukulska-Hulme, 2009).
To date, a great body of literature has focused on the impact of technology onuser behaviours by looking into attitude or cognitive factors (Chen & Chung, 2008;Chen & Hsu, 2008; Edirisingha et al., 2007; Lapczynski & Calloway, 2006; Lu,2008) and continuance intention (Chiu & Wang, 2008; Lee, 2010; Lee & Kwon,2011; Lin, 2011); however, it is believed that further discussions are still necessary,particularly on newly developed information technologies. It is also suggested thatprospective research on the Technology Acceptance Model (TAM) entails consider-ation of effective external variables in order to gain deeper insights into user behav-iours (Castaeda, MuozLeiva, & Luque, 2007; Chiu & Wang, 2008; Hsu & Lu,2004; Kuo & Yen, 2009; Lee, 2010; Park, Nam, & Cha, 2011). Park et al. (2011)investigated university students’ behavioural intention to use mobile learning. Thestudy used mobile learning self-efficacy, relevance for students’ major (MR), systemaccessibility, and subjective norm as external variables to investigate students’ atti-tude toward and behavioural intention to use mobile learning. Tai and Ting (2011)identified teacher attitudes toward the adoption of mobile technology for languagelearning, but no external variables were used in their study. According to Yoon andKim (2007), perceived convenience plays the role of an external variable in wirelessLAN usage; similarly, perceived convenience was found to exert an influence oncontinuance intention related to the use of Radio Frequency Identification (RFID) inthe study conducted by Hossain and Prybutok (2008). An e-learning environmentinvolves not only the use of mobile devices and wireless networks but the integra-tion of learning systems that enable effective and approachable knowledge acquisi-tion. Therefore, this study attempted to further examine the model by introducingthe factor of ‘convenience’.
In the view of Wang, Baker, Wagner, and Wakefield (2007), it is of great impor-tance for website operators to attract users’ ‘attention’ to excite their ‘interest’ and‘curiosity’, and in turn enhance the intention to use the website. Given that mobilelearning is a relatively new area of learning technology, this study aimed to explorethe ways that maintain learners’ curiosity and continuance intention concerning theuse of an English mobile learning system. As there were very few studies exploringthe factors that affected English mobile learning (Lapczynski & Calloway, 2006;Park et al., 2011; Tai & Ting, 2011), the purpose of the present study was hence toextend the TAM with other external factors (perceived curiosity and convenience)which are important features of mobile learning. The research question is: ‘Arecuriosity and convenience the main determinants of English learners’ continuanceintention to use a mobile learning system?’
2. Literature review and hypothesis
2.1. The Technology Acceptance Model (TAM)
Based on the Theory of Reasoned Action (TRA), Davis, Bagozzi, and Warshaw(1989) developed TAM which classifies the factors influencing attitudes into‘perceived usefulness’ and ‘perceived ease of use’. By removing subjective normsin TRA, TAM assumes that perceived usefulness and perceived ease of use
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determine an individual’s attitude directly related to behaviour intention and systemuse. Despite being crucial determinants of technology acceptance, the two beliefs inTAM – perceived usefulness and perceived ease of use – are thought to beassociated with external variables (Davis, 1989). In explanation of continuanceintention, it is of great importance to extend TAM by incorporating potentialexternal variables (Castaeda et al., 2007; Hsu & Lu, 2004; Kuo & Yen, 2009) thatplay decisive roles in the adoption of information systems.
Studies show that the adoption of Information Technology (IT) is substantiallydriven by continuance intention (Chiu & Wang, 2008; Lee, 2010; Lee & Kwon,2011; Lin, 2011); meanwhile, perceived usefulness and perceived ease of useinteracts to influence continuance intention in a way that the former variable holdsa positive influence on the latter (Lee, 2010). A growing number of research studieson technology adoption behaviour have made use of TAM in analysis of individualbehaviour toward IT use (Ahn, Ryu, & Han, 2007; Bhattacherjee, 2001; Chau,1996; Lai & Li, 2005; Saade & Bahli, 2005; Venkatesh & Davis, 2000; Venkatesh,Morris, Davis, & Davis, 2003) or e-learning (Chiu & Wang, 2008; Gong, Xu, &Yu, 2004; Lee, 2010; Lin, 2011; Saade & Bahli, 2005). Based on TAM, Park et al.(2011) investigated university students’ behavioural intention to use mobilelearning. The results revealed that perceived usefulness and ease of use affecteduniversity students’ attitude toward and behavioural intention to use mobilelearning. Furthermore, perceived ease of use affected perceived usefulness of mobilelearning. Park (2009) introduced three external variables that are considered asimportant factors affecting users’ acceptance of e-learning, including self-efficacy,subjective norms, and system accessibility. Liu, Liao, and Pratt (2009) aimed toidentify the determinants involving learners’ adoption of e-learning from theperspective of media richness and flow experience. Wang et al. (2007) concludedthat continuance intention on mobile learning is positively related to performanceexpectancy and effort expectancy. All these studies above confirmed that ease ofuse affects usefulness and intention, and usefulness affects intention. In this study,the following hypotheses were posited:
H1: Perceived ease of use has a positive effect on perceived usefulness in mobilelearning.
H2: Perceived ease of use has a positive effect on continuance intention in mobilelearning.
H3: Perceived usefulness has a positive effect on continuance intention in mobilelearning.
2.2. Perceived convenience
To examine the convenience of services and products, Brown (1990) proposed afive-dimension framework comprising time, place, acquisition, use and execution.Berry, Seiders, and Grewal (2002) developed a conceptual model, and suggestedthat a service’s convenience can be measured by consumers’ time and effortexpenditure. In their research on wireless LAN, Yoon and Kim (2007) adoptedBrown’s model by excluding the dimensions of acquisition and use and definedperceived convenience as a user’s perception of how convenient the wireless LANis in terms of time, place and process during which a task is accomplished. Recent
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studies on wireless LAN (Yoon & Kim, 2007), RFID (Hossain & Prybutok, 2008)and Online Purchase Decision (Gupta & Kim, 2007) concluded that perceivedconvenience can be one of the influential factors contributing to the acceptance of anew IT. Moreover, it is found in Yoon and Kim’s (2007) research that perceivedease of use has a positive impact on perceived convenience. Therefore, thefollowing hypothesis was posited in this study:
H4: Perceived ease of use has a positive effect on perceived convenience.
Yoon and Kim (2007) also discovered a positive correlation between perceivedconvenience and perceived usefulness. In other words, learners in mobile learningcan benefit from the convenience brought by mobile devices that are unrestricted bytime or place. As learners perceive mobile technology as ‘meaningful’ forknowledge acquisition, they tend to perceive it as ‘useful’ as well. Therefore, thefollowing hypothesis was posited in this study:
H5: Perceived convenience has a positive effect on perceived usefulness.
Gupta and Kim (2007) concluded that perceived convenience is positively related toconsumers’ continuance intention to do online shopping. Likewise, Hossain andPrybutok (2008) noted that perceived convenience has a positive influence on theintention to use RFID technology. Therefore, the following hypothesis was positedin this study:
H6: Perceived convenience has a positive effect on continuance intention in mobilelearning.
Curiosity is derived from the theory of flow that assumes individuals tend tointeract with their environment in the state of ‘flow’ (Csikszentmihalyi, 1975).Hoffman and Novak (1996) argued that the state of ‘flow’ takes place when webusers are fully absorbed in an activity; on the contrary, users may experience bore-dom and anxiety if ‘flow’ fails to occur. That is to say, users are more likely tobecome curious in interaction with an information system when they are in the‘flow’ state. Malone (1981) maintained that curiosity will be aroused as individualsperceive the environment as enjoyable or interesting. Also, ‘novelty’ is seen as anessential component of intrinsic motivation (Ryan & Deci, 2000; Vallerand, 1997).
The key factors that motivate people to explore or visit a website are largely con-tingent on users’ curiosity, rather than their interests, driven by the abundantresources and information on the website. Lee’s (2010) study confirmed that flowexperience affects users’ continuance intention toward e-learning. Wang et al. (2007)found that users’ curiosity plays a crucial role which leads to repeated access to awebsite. In short, in mobile English learning, a user-friendly website will enhancelearners’ curiosity about the content and information available on web pages andthus foster their intention to use. Hence, the relationships between perceived ease ofuse, curiosity and continuance intention were hypothesised as follows:
H7: Perceived ease of use has a positive effect on curiosity.
H8: Curiosity has a positive effect on continuance intention.
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3. Research methodology
The research model of this study was developed based on TAM (Davis, 1989) and‘perceived convenience’ and ‘curiosity’ were included as the determinants thataffect intention to use mobile English learning (Figure 1). Past studies suggest thatindividual behaviour of IT use is linked to continuance intention: continuanceintention positively affects IT adoption behaviours.
3.1. Experimental design
This study adopted the one-group post-test-only design and selected a group ofparticipants to engage in the experiment of mobile English learning. Questionnaireswere collected after the two-week experiment in order to test the hypothesesproposed.
3.1.1. Participants
Participants were 125 11th graders (age ranging from 17 to 20) enrolled in anEnglish course at a Taiwanese high school. Few of the participants had hadexperience with mobile learning, although all of them were familiar with personalcomputers, internet access and e-learning.
3.1.2. Experimental tool
The questionnaire was created in the format of five-point Likert scale with theassistance of two experts in IT and mobile learning. To improve the content validity,the study modified the questionnaire based on expert opinions and problemsreported by the five students who participated in the pre-test of the questionnaire.The questionnaire consisted of five constructs that were adapted from past studies:perceived convenience from Yoon and Kim (2007); perceived ease of use andperceived usefulness from Davis (1989); curiosity; and continuance intention fromTAM research including Davis (1989), Moon and Kim (2001) and Ong, Lai, and
H1H2
H3
H4
H5
H6
H7
H8
Curiosity
Continuance intention
Perceivedusefulness
Perceived convenience
Perceived ease of use
Figure 1. Research model.
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Wang (2004). The constructs were tailored to fit into the context of mobile Englishlearning, and their definitions are shown in Table 1.
3.2. Mobile English learning
The study used a PDA (personal digital assistant) with a 3.5-inch touch screen with320 � 240 pixels, working on Windows mobile system and enabling internet andBluetooth connection. As for the learning system selected, the Mebook was a multi-media ebook system designed by a Taiwanese company, which can be played inMP3 format on MeReader. The Mebook is a mobile ebook that integrates multime-dia functions of texts, voices, images and pictures in a single system. Fitted withMeReader, a special displaying software, the Mebook provides all the directions oflanguage learning programs that guide you to read, to listen, to speak and to write(http://www.mebook.com.tw/).
Besides text–audio synchronous content, the Mebook offers vocabulary learningtools (e.g. one-word translation) and cloze interactive tests. In response to users’needs and cognitive skills, the features of the Mebook also include audio speedadjustment and language switch (Chinese–English). The contents of the materials inthe Mebook are very varied and broad, including daily issues related to politics,social, culture, economy, education, environment, technology, etc. The Englishlearning via the Mebook includes vocabulary, reading, listening and speaking.
3.3. Experimental procedure
The participants were provided with detailed information regarding purposes,procedures and significance of the study before the experiment began, since theywere new to PDAs and mobile English learning. More instructions were also given
Table 1. The operational definition of variables.
Construct Operational definition Source Item
Perceivedconvenience
The degree to which usersperceive that mobile Englishlearning is convenient tocomplete a task in terms oftime, place and the process.
Yoon and Kim(2007)
Con1–Con4
Perceived ease of use The degree to which usersperceive that the system formobile English learning iseasy to use.
Davis (1989) PEU1–PEU5
Perceived usefulness The degree to which usersperceive that learningeffectiveness can be increasedby mobile English learning.
Davis (1989) PU1–PU3
Curiosity The degree to which usersbecome curious in interactionwith mobile English learning.
Moon & Kim(2001)
Cur1–Cur2
Continuance intention The degree to which usersintend to continue to usemobile English learning.
Davis (1989),Moon & Kim(2001); Ong et al.(2004)
ITU1–ITU4
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on how to use the PDAs installed with the English learning system. The readingand listening materials in the system were accessible to the participants any timeand anywhere covering the ‘American Votes’ Unit (Week 1) and the ‘InternationalNews’ Unit (Week 2). To improve their familiarity, the participants were allowed tokeep the PDA for two weeks during which they had about 30 minutes practice inevery two-hour class session and at least one hour’s practice after class.
Every three participants were grouped up with an assigned leader responsiblefor tracking the PDA usage time of each member and writing weekly progressreports. In this manner, the instructor could pay close attention to students withtheir practice time outside the classroom, and take timely action if required lengthof time was not fulfilled. The participants also had to take a 30-minute class quizevery week by downloading test questions from websites to their PDAs. By the endof the experiment, the participants were asked to report their perceptions aboutmobile English learning and complete the questionnaire to indicate how much theyagree or disagree with the survey questions.
4. Data analysis and results
The SmartPLS 2.0 was adopted for this study. As an approach suitable foranalysing complex models (Chin, Marcolin, & Newsted 2003), Structural EquationModelling (SEM) can be categorised into a covariance matrix and component-basedapproach. The Partial Least Square (PLS), a powerful statistical program of compo-nent-based analysis, differentiates itself from other programs by handling both for-mative and reflective indicators, while covariance matrix statistical software (e.g.LISREL or AMOS) can be only used for reflective measurement (Chin, 1998).
The PLS analysis was implemented for the following reasons: (1) its minimaldemands on sample size and data distribution (Gefen, Straub, & Boudreau, 2000);and (2) unlike LISREL, it allows confirmatory and exploratory modelling, evenwith an initial theory (Barclay, Higgins, & Thompson, 1995; Gefen et al., 2000).Therefore, the PLS Bootstrap was adopted to verify the research model in thepresent study.
4.1. The measurement model
The PLS analysis was adopted to examine the appropriateness and quality of themeasurement model because it does not require large sample sizes or MultivariateNormal Distribution (Chin, 1998; Chin, Marcolin, & Newsted, 2003).
Internal consistency can be assured by examining the Composite Reliability(CR) of the constructs (Nunnally, 1978). The CR values in this study, ranging from0.890 to 0.951, were above the recommended level of 0.7 (Bagozzi & Yi, 1988);therefore, the reliability of the measures can be assured.
The Confirmatory Factor Analysis (CFA) was performed to examine the validityof measurement model. Convergent Validity (CV) refers to the degree to whichmultiple items measure one construct. It is considered acceptable with AverageVariance Extracted (AVE) values larger than 0.5 and the factors loadings of allitems higher than 0.5 (Nunnally, 1978). In this study, all these conditions were met,demonstrating acceptable CV of the measurement (see Table 2). The AVE valuesranged from 0.618 to 0.951, surpassing the suggested threshold. All factor loadingsof the items were also significant and above 0.5.
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Discriminative Validity (DV) aims to measure the degree to which a construct isnot similar to other constructs by examining whether the square root of AVE ofeach construct is larger than the correlation between constructs (Chin, 1998). Table 3illustrates the correlation matrix and square root of AVE with diagonal itemsshowing the squared root of AVE and off-diagonal items showing the correlationsbetween constructs. In summary, all square roots of AVE were larger than thecorrelation coefficients between constructs, indicating that each construct hassufficient discrimination validity.
Table 2. The factor analysis and internal consistency.
ItemFactorloading
Compositereliability AVE
Perceived ease of use 0.890 0.618PEU1: It would be easy for me to become skilful at usingthe English learning system.
0.740
PEU2: I find the English learning system to be easy to use. 0.819PEU3: I find it easy to use the PDA and the Englishlearning system to do what I want them to do.
0.724
PEU4: Learning to operate the English learning systemwould be easy for me.
0.831
PEU5: It is easy for me to become skilful at using the PDAand the English learning system.
0.810
Perceived usefulness 0.951 0.866PU1: Mobile English learning enhances my learningefficiency.
0.921
PU2: Mobile English learning enhances my learningeffectiveness.
0.955
PU3: I find mobile English learning useful in learningEnglish.
0.915
Perceived convenience 0.905 0.705CON1: It is convenient for me to complete a task by usingthe English learning system.
0.810
CON2: I have access to the English learning systemeverywhere.
0.747
CON3: It would be convenient for me to fulfil learningactivities by using the English learning system.
0.889
CON4: I find mobile English learning to be convenient. 0.902Continuance intention 0.948 0.820
ITU1: Assuming that I have access to the English learningsystem, I intend to use it.
0.930
ITU2: Given that I have access to the English learningsystem, I predict that I would use it.
0.944
ITU3: I intend to recommend other people to use theEnglish learning system.
0.806
ITU4: I intend to continue to use the English learningsystem.
0.935
Curiosity 0.906 0.951Cur1: Mobile English learning stimulates my curiosity tolearn English.
0.955
Cur2: Mobile English learning leads me to explore English. 0.949Cur3: Mobile English learning arouses my imagination tolearn English.
6.312
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4.2. The structural model
The analysis of the structural model not only tests hypotheses but estimates pathcoefficients of constructs by examining the relationship between the dependent andindependent variables and the amount of variance which can be explained by theindependent variables (R2) as well as by the overall model. Moreover, this studyadopted the bootstrap re-sampling procedure and chose Resamples 150 to examinethe stability of the PLS estimates (Chin, 1998).
Figure 2 shows that H3, H4, H5, H6, H7 and H8 were positive and significant.The results demonstrated that in mobile English learning, (1) perceived usefulnesshad a positive effect on continuance intention with a coefficient of 0.314 (p < 0.05);(2) perceived ease of use had a positive effect on perceived convenience with acoefficient of 0.57 (p < 0.001); (3) perceived convenience had a positive effect onperceived usefulness with a coefficient of 0.652 (p < 0.001); (4) perceivedconvenience had a positive effect on continuance intention with a coefficient of0.410 (p < 0.001); (5) perceived ease of use had a positive effect on curiosity with acoefficient of 0.432 (p < 0.001); and (6) curiosity had a positive effect on continu-ance intention with a coefficient of 0.216 (p < 0.01). Nevertheless, H1 and H2 were
Table 3. Discriminative validity.
ConstructPerceived
conveniencePerceivedease of use
Perceivedusefulness Curiosity
Intention oncontinuous use
Perceived convenience 0.839Perceived ease of use 0.573 0.786Perceived usefulness 0.716 0.487 0.931Curiosity 0.493 0.558 0.558 0.952Continuance intention 0.702 0.413 0.695 0.564 0.906
0.410***t =3.929
0.652***t =9.008
0.574***t =6.691
0.314*t =2.500
0.113t =1.421 -0.068
t =0.814
0.432***t =5.633
0.216**t =2,744
P<0.05, *; p<0.01, **; p<0.001, ***
H1H2
H3
H4
H5
H6
H7
H8
Perceivedease of use
Curiosity
R2=0.187
Continuanceintention
R2=0.600
Perceivedusefulness
R2=0.522
Perceivedconvenience
R2=0.329
Figure 2. Analysis results of the research model.
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not supported as the effects of perceived ease of use on perceived usefulness andcontinuance intention were not significant or positive.
The results of the structural model analysis are illustrated in Figure 2. Overall,the model explained 60% of the variance in continuance intention. Moreover, per-ceived ease of use explained 52.2% of the variance in perceived usefulness, 32.9%in perceived convenience, and 18.7% in curiosity. These results showed a ratherhigh explanatory power of the extended TAM model.
5. Discussion
On the hypotheses involving perceived convenience, our study results, similar toYoon and Kim’s (2007) findings, showed that perceived ease of use positivelyaffects perceived convenience. This implied that users perceive mobile Englishlearning as more ‘convenient’ when it becomes ‘easier to use’. It is also found thatperceived convenience had a positive effect on perceived usefulness, suggesting thatusers perceive mobile English learning as more ‘useful’ when they find it more‘convenient’, and this finding is parallel to Yoon and Kim’s (2007) conclusion. Inagreement with Hossain and Prybutok’s (2008) research, our study indicated thatperceived convenience positively influences continuance intention, i.e. users showstronger intentions to use mobile English learning as it is more ‘convenient’.
With respect to curiosity hypotheses, it is discovered that perceived ease of usehad a positive impact on users’ curiosity that also plays a role in continuance inten-tion. The result is similar to Moon and Kim’s (2001) finding, suggesting that usersshow stronger intention to use mobile English learning when they are more curious;meanwhile, they become more curious as the PDA learning system is perceived as‘easier to use’.
Previous studies have confirmed the applicability of TAM in a wide range of ITsystems (Sun & Zhang, 2006; van der Heijden, 2004). Although the effects ofperceived ease of use on continuance intention and on perceived usefulness werefound insignificant, the other TAM hypotheses proposed in this study weresupported. The results are partially consistent with Venkatesh and Davis’s (2000)findings. While contradictory to a number of studies (Wang, Wu, & Wang, 2009),the positive influence of perceived ease of use on continuance intention was notidentified in this study. Further studies are yet needed to explore whether or notusers’ experience or personality mediates the relationship between external variablesand continuance intention (Castaeda et al., 2007; Venkatesh et al., 2003).
6. Conclusion and implication
6.1. Theoretical implication
Despite being widely accepted, it is found that only 40% of variance can beexplained by TAM (Legris, Ingham, & Collerette, 2003). However, the explainedvariance increased up to 60% as perceived convenience and curiosity for mobileEnglish learning were included in this study. Legris et al. (2003), by implementingthe meta-analysis, discovered that TAM can be used to predict user acceptance of anew technology or IT system, whereas they also argued that there are yetunidentified factors related to behavioural intentions. By adding two constructs toenhance the explanatory power, the explained variance of TAM measured in thisstudy is considerably higher than that in past studies, indicating that the constructs
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(i.e. perceived convenience and curiosity) could be powerful determinantsinfluencing continuance intention to use mobile English learning. Although onewould assume that if they have been given the technology, they would undoubtedlybe prone to say they would like to continue to use it; however, if the technology isnot sufficiently good, users would not say that they would like to continue to use it.
6.2. Practical implication
According to the results of this study, curiosity, ease of use and convenience areinfluential factors linked to intention to use mobile English learning. In other words,it is possible that users’ acceptance of mobile English learning can be significantlyboosted by taking into account these factors. On ‘curiosity’, teachers should notonly guide mobile learners in using the systems but draw their interest in order toenhance the effectiveness and quality of English learning through mobile technolo-gies. When it comes to ‘usefulness’, there is need for more useful and collaborativeapplications for mobile English learning systems, e.g. learning guidance, persona-lised teaching materials and assessment, progress monitoring, etc. It is desirable thatfuture mobile English learning systems should be designed to offer resourceful,helpful and up-to-date information as well as digital contents that meet individualneeds or ability. Beyond providing convenient time and place for users, systemdevelopment should also aim to promote usefulness and continuance intention bysupplying highly accessible tools in terms of purchase, downloading, transmissionor installation.
6.3. Future works
Although not covered in our study, there are other noteworthy variables (e.g.geographic difference or gender) worth further exploration, the understanding ofwhich may be applied to materials development for mobile English learning. Dueto the limitation of time, the data collected from our experiment may vary accordingto the time of use and experience with the learning system (Venkatesh et al., 2003).It is advisable that researchers conduct more dynamic or longitudinal studies byextending the duration of experiment to gain deeper insight into user behaviour andbelief as well as the relations among variables (Wang et al., 2009).
Future studies are recommended to examine other antecedents related toperceived convenience, or seek potential external variables (e.g. instructional materi-als, media sources) in explanation of user acceptance of mobile English learning. Inaddition, the impact of perceived convenience and curiosity on English learning,cognitively and affectively, needs to be investigated, considering that intention playsa role in individual behaviour and attitude. Finally, since the positive effect ofperceived ease of use on continuance intention was not identified in this study,‘whether or not users’ experience with personal computers and mobile learning isinvolved’ is another question deserving careful investigation.
Notes on contributorsDr Chi-Cheng Chang is a distinguished professor at the Department of TechnologicalApplication and Human Resource Development, National Taiwan Normal University, Taipei,Taiwan. He gained his PhD in Workforce Education and Development from thePennsylvania State University, USA. His research interests are focused on e-learning and
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e-portfolio assessment. He is now the president of the Association of Taiwan EngineeringEducation and Management (ATEEM) and the editor of Journal of Technology andEngineering Education.
Dr Kuo-Hung Tseng is a chair professor at the Graduate Institute of Business andManagement, Meiho University, Pingtung, Taiwan, His gained his PhD in Administration inVocational Education from the Northern Colorado University, USA. His current researchinterests are focused on e-learning, knowledge management and STEM.
Dr Chaoyun Liang is a professor at the Department of Bio-Industry Communication andDevelopment, National Taiwan University, Taipei, Taiwan. He gained his PhD inInstructional Systems Technology from the Indiana University, USA. His current researchinterests are focused on creativity and imagination. He is now the vice president of TaiwanAssociation for Educational Communications and Technology (TAECT) and the editor ofJournal of Information Communication. Professor Liang can be reached via [email protected] or [email protected].
Dr Chi-Fang Yan is a senior instructor at the Department of Information Processing, SeniorCommerical School of Continuing Education, National Taichung University of Technology,Taichung, Taiwan. His current research interests are focused on computer education and ICTapplication in education.
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