Shuler, C. (2009). Pockets of potential: Using mobile technologies to promote children's learning. New York: Joan Ganz Cooney Center at Sesame. Workshop.
학습자중심교과교육연구 http://dx.doi.org/10.22251/jlcci.2017.17.20.665 Journal of Learner-Centered Curriculum and Instruction 2017. 제17권 제20호, pp. 665-687. Does Gender Still Matter?: The Usage and Acceptance of Smartphones for Learning in Higher Education* Sooyoung Kim(Seoul Women’s University)** Teresa Pyon(Seoul Women’s University)*** Sun Joo Yoo(Seowon University)
The purpose of this study is to examine how students in higher education are using smartphones and to investigate gender difference in students’ acceptance level toward smartphones for learning. Data were collected from 164 undergraduate and graduate students in South Korea between December 2012 and January, 2013. The findings show that students in higher education are using smartphones mostly in order to search the Internet, chat/use mobile messenger, and use Social Networking Sites (SNS). There is no gender difference regarding the purposes for using smartphones. However, the findings show that female students have lower facilitating conditions and higher anxiety than male when using smartphones for learning. These findings suggest that educators should develop learning strategies that can help female students to be more exposed to mobile technology such as smartphones and help them feel more confident in using mobile technology in and out of classroom. « Key words: Smartphones, Technology Acceptance, Gender, Higher Education
* This work was supported by a research grant from Seoul Women's University(2017). ** Lead author. *** Corresponding author: [email protected]
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I. Introduction
It is not hard to spot people staring at their mobile phones inside a subway or on a public bus in South Korea. According to the Korea Internet and Security Agency (KISA), as of July 2016, 88.3% of the Korean population ages three and older have used the Internet at least once in the previous month and 90.2% of these internet users use the Internet ‘at least once a day’ (KISA, 2016:.5). Also, KISA reported that 85.9% of the Internet users connect to the Internet through mobile devices such as smartphones, smart pads or wearable devices, and more specifically, 83.6% of the Internet users use smartphone. Slightly more males (86.7%) used smartphones than females (80.6%). Concerning the purpose for using smartphones, 78.3% of the smartphone users responded that they use the applications for communications such as SNS and chatting programs the most and the applications for pictures and video (62.2%) and news (54.4%) and games (22.7%) were used next (KISA, 2016). As mobile technology is widely disseminating, many researchers and educators have addressed the possibility of using mobile technology as an innovational teaching and learning tool especially in higher education. Using mobile technologies for teaching and learning has brought huge potential to improve student engagement, expand college experiences and innovate teaching and learning practices (Alabdulkareem, 2015; Grosseck et al., 2011). Some researchers have examined mobile technology to facilitate collaborative learning and communicative activities among students in the classrooms (Lim, 2010; Kim & Hur, 2016). Mao (2014) and Menkhoff and Bengtsson (2011) revealed that college students showed more positive attitudes toward peer interaction and academic achievement when they used mobile devices. Examining the users’ level of technology acceptance toward mobile learning, therefore, helps us understand how users utilize mobile technology and how willing they are to use mobile technology in higher education context. By knowing how and why they use mobile technology and how comfortable they feel about the application of new technology in their learning will allow us to create better mobile learning programs and environment. One of the interesting findings from the previous studies on learners’ acceptance of mobile technology in higher education is gender differences (Liu, & Guo, 2017; Liu, Li, & Carlsson, 2010). Different studies indicated that gender
Does Gender Still Matter?: The Usage and Acceptance of Smartphones for Learning in Higher Education 667
differences influenced learners’ perceptions, processing of information, and usage of information technologies such as computer, internet and mobile phones (Lu et al. 2006). Males are more curious than females and therefore more willing to try new technology (Lu et al., 2006). According to Hong and Tam (2006), males also possess greater comfort and confidence with technology while females tend to exhibit more anxiety. With already established infrastructures such as WiFi network and high-speed Internet connection (KISA, 2016), usage of mobile technology for learning has rapidly drawn attention from both researchers and educators in Korea. Yet little is known about how much of mobile technology is being used for learning both in and out of classrooms. Therefore, this study aims to discover how students in higher education use mobile technology, specifically smartphones, and how they perceive using smartphones as a learning tool. Also, the present study focuses on understanding the possible gender differences in the adoption of smartphones in higher education. Therefore, this study examined students’ usage of smartphones and answered the following questions: (1) How do students in higher education use smartphones? (2) Do purposes for using smartphones differ by gender? (3) Do students’ acceptance level towards smartphones for learning differ by gender?
Ⅱ
. Literature Review
1. Mobile Learning and Smartphone Use in Higher Education
Many researchers define mobile learning as an activity of learning where users access information and communicate with others by utilizing mobile technology, wherever they are (Kukulska-Hulme, 2005; O’Malley et al., 2003; Wu et al., 2012). According to Motiwala (2007), mobile learning “combines individualized learning with anytime and anywhere learning” (p.2). Other researchers (Herrington & Herrington, 2007; Valk, Rashid, & Elder, 2010) define mobile learning as learning facilitated by mobile devices. Gikas and Grant (2013) analyzed mobile learning in three specific ways: (1) “learning that is delivered and supported by mobile technology; (2) that is both formal and informal; and (3) that is context aware and authentic for the learner” (p.19).
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Obviously, mobile technology can provide many benefits in learning, especially in the context of higher education. First, it enables students to access information and knowledge anywhere at anytime (Traxler, 2007). That is, students can access course content as well as interact with instructors and their peers no matter where they are (Cavus & Ibrahim, 2009; Kukulska-Hulme & Shield, 2008; Nihalani & Mayrath, 2010). Second, it enables learners to engage in constant connectivity (Cavus, Bicen, & Akcil, 2008; Shuler, 2009), and fosters collaborative learning (Cochrane & Bateman, 2010; Hoffman, 2009; Pang, 2009). Third, it allows students to create personalized and authentic learning experiences (Archambault et al., 2010; Ruta et al., 2010; Shuler, 2009). For these reasons, many educators are using different mobile devices in their classrooms and one of the most used mobile devices is smartphones. For example, Kim and Hur (2016) used three different smartphone applications, i.e., KakaoTalk, Naver Band and Socrative, in their English e-learning class in a cyber university in Korea and compared which program helped the students learn new English vocabulary the most and which were most positively regarded by students. They found the student group that used Band achieved most improvement in terms of vocabulary building followed by Socrative and KakaoTalk group. Though all three groups of students were satisfied with the e-learning class using each smartphone application, the group with Socrative was most satisfied with the class although the group with KakaoTalk expressed most interest in the class (Kim & Hur, 2016). Im (2010) also used four different smartphone applications in a college distance learning class and analyzed the patterns of students’ smartphone use with social network sites (SNS). In this study, students found wiki and web-discussion applications helpful for their learning activities while they used other two applications, multimedia messaging service and microblog, as administrative tools. However, students used smartphones for short messages mostly and for longer discussions or reflection tasks, they preferred desktop or laptop computers (Im, 2010). Examining college students’ perception and usage of smartphone applications for learning in Spain, Vázquez-Cano (2014) also reported that students viewed learning with smartphones as satisfactory experience. On the other hand, Tossell et al. (2015) stated that university students who were given iphones to use them as a learning device for a year reported that the use of iphone was actually distracting for their learning. Although the students expected that the use of iphone would help them achieve better grades and they used
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iphones to get access to school resources in their classrooms, overall, they found iphones were more detrimental than helpful to achieve their learning goal. As smartphones are being tested and used in different learning contexts, how they actually help students’ learning show different results. However, as Merchant (2012) argued, although once the use of smartphone in the classroom was not an acceptable idea, more educators are now recognizing the usefulness of smartphone as a possible learning device. Smartphone as a learning tool is clearly getting more attention and it seems it is showing more promise to create effective and positive learning outcomes even in higher education. 2. Unified Theory of Acceptance and Use of Technology (UTAUT) towards Mobile Learning
The Unified Theory of Acceptance and Use of Technology (UTAUT) was created by Venkatesh and his colleagues (2003) and their model is now being widely accepted in the field of information and communication technology. UTAUT applies four concepts to explain why people use and accept technology: performance expectancy, effort expectancy, social influence, and facilitating condition that together directly influence the behavioral intentions to use technology (Venkatesh et al., 2003). Many researchers are starting to focus more on mobile technology as it penetrates into people’s lives and is being distributed to everyone. In particular, user’s acceptance of mobile learning is one of the interesting topics in this field (Nassuora, 2012; Hwang & Chang, 2011; Wang & Wang, 2010). Cheon, et al. (2012) examined mobile learning readiness in American higher education. A total of 177 students participated in this research and the results showed that attitudes, subjective norm and behavioral control affected the intentions to use mobile learning. Hwang and Chang (2011) also found that in Taiwan, enhancing learner’s satisfaction, encouraging learners’ autonomy, empowering system functions, and enriching interaction and communication activities improved acceptance levels towards mobile phones. Wang and Wang (2010) examined user acceptance of mobile internet in Taiwan. A total of 343 students took part in this research found performance expectancy, effort expectancy, and social influence had a significant influence on behavioral intention to use mobile internet. According to Nassuora (2012), performance expectancy and effort expectancy influence the
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intentions to use mobile technology. Also, social influence and facilitating conditions affect attitude towards mobile technology. In Saudi Arabia, researchers found that attitude towards mobile technology affects intention to use mobile technology (Al-Fahad, 2009). Interestingly, according to a meta-analysis study conducted by Hwang and Tsai (2011), most studies of mobile learning dealt with the motivation, perceptions, and attitudes of students toward mobile and ubiquitous learning. However, most of these available studies were conducted by US-based researchers, followed by researchers in the UK and Taiwan. South Korea is one of the more developed countries in terms of Internet and mobile technology. Most Koreans are using mobile technology regardless of gender and age. According to Liew et al. (2013), who examined a total of 172 students at two universities in South Korea, performance expectancy, social influence, perceived playfulness, and self-management of learning are determinants of mobile learning behavioral intention. Shin, et al. (2011), explored users’ acceptance towards mobile technology and a total of 215 staff, students, and faculty members from 10 universities in Korea participated in this study. They found that perceived usability and perceived quality affected behavioral intention for mobile learning. Another study by Park, Nam, and Cha (2012) examined how students accept technology at Kunkuk University in South Korea. A total of 288 students responded and this study results confirmed that attitude, followed by students' major and subjective norm, is the most important construct in explaining the causal process in the UTAUT model. In the context of mobile learning, social influence (e.g., teachers, parents, peers, etc.) strongly affected younger students’ intention to accept and use mobile devices for learning purposes. That is consistent with the findings of Wang, Wu and Wang (2009) that social influence has a significant effect on usage intention of mobile learning. 3. Gender Differences and Technology
Generally, acceptance level toward a specific technology may differ by gender. Van Deursen, van Dijk, & Klooster (2015) conducted a longitudinal study of what the Dutch do online. They revealed that gender influences the purpose for using the Internet. Male and young people use the Internet the most. For example, males show more competence and less anxiety compared to females when it comes to using technologies (Huang, Hood, & Yoo, 2013). According to Huang,
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Hood and Yoo ,(2013), males and females have different perception toward Web 2.0 applications including blogs, messengers, and online games. Overall, females feel more anxiety towards using Web 2.0 applications than males do. Baker, Lusk, & Neuhauser (2012) examined students perceptions when they use mobile phones. They found that specifically, male students were more accepting of in-class use of technology than were female students. Liu & Guo (2017) examines how gender differences influence the acceptance of mobile computing devices among Asian college students. They found that male college students were significantly influenced by the perceived usefulness and social benefits. On the other hand, female college students prefer social and utilitarian orientations; However, other studies (Serin, 2012; Uzunboylu & Ozdamli, 2011) show that there are no significant differences between genders regarding their perception towards mobile learning. Other studies also reported that males and females exhibit the same on capabilities to use mobile devices in education programs (Fouh et al. 2014; Mac Callum & Jeffrey 2014). Therefore, we propose to investigate gender differences with regard to smartphone adoption among students in higher education using a modified Technology Acceptance Model. By understanding the effects of gender, our aim is to develop appropriate strategies that enhance the adoption and efficiency of mobile technologies in higher education as an innovative teaching and learning tool. We anticipate that this will lead to further research on gender issues in other new forms of mobile devices that target students in higher education globally.
Ⅲ
. Method
1. Participants and Data Collection
Participants were recruited from four classes of four universities in South Korea. In-class announcements were made by lecturers two weeks before the data collection and a research team visited the classes to distribute and collect the survey questionnaires. Data were collected for four weeks from December 2012 to January 2013. A total of 177 Participants voluntarily took part in the survey. Of the 164 completed surveys, 55 of them were completed by males (33.5%) and 109 (66.5%) by female students. The ages of most of the participants range from 18 to 30 years. Most of them are undergraduate students (116,
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70.7%), and 48 of them (29.3%) are graduate students. 2. Instruments
A survey questionnaire is composed of 1) demographic information such as gender, age, and educational level, and 2) daily use of smartphones, 3) choices for purposes of using smartphones, and 4) acceptance levels toward smartphones for learning. The choices of purposes of using smartphones such as searching the Internet, using SNS, chatting/using mobile messenger, reading e-books, checking or sending emails, using educational contents such as e-lecture, for work/business, and listening to podcasts were adapted from Clough et al. (2008)(See Table 1).
Purposes of using smartphones Category Individual
Activity Reading e-books, Checking or sending emails, Using educational contents such as e-lecture, Listening to podcasts Collaborative Chatting/Using mobile messenger, Using SNS Internet Searching Organizational For work/business Adapted from Clough et al. (2008)
To measure the acceptance level towards smart phones, the instrument UTAUT developed by Venkatesh and his colleagues (2003) was selected and modified for the current study. The word “smartphones” was replaced for the word “technology.” The modified UTAUT includes seven constructs: performance expectancy (4 items), effort expectancy (4 items), attitudes (3 items), social influence (4 items), facilitating conditions (2 items), anxiety (2 items) and behavioral intention to use (4 items). The items were rated on a 5-point Likert scale with endpoints of strongly disagree(1) and strongly agree(5). The sample items for each construct are as follows: 1) for performance expectancy, ‘using smartphone enables me to accomplish learning tasks more quickly’, 2) for effort expectancy, ‘I would find smartphone easy to use for learning’, 3) for attitude, ‘Using smartphone is a good idea for learning’. 4) for social influence, ‘People who are important to me think that I should use smartphone for learning’. 5) for facilitating conditions, ‘I have the resources necessary to use smartphone for learning’. 6) for anxiety, ‘I feel apprehensive about using smartphone for learning’.
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The reliability and validity of UTAUT were examined by numerous studies (Oshlyansky et al., 2007; Venkatesh & Davis, 2000). Additionally, the cross-cultural validity of the UTAUT was examined which is robust (Oshlyansky et al., 2007). The reliabilities of all the constructs included in this current study exceed .60, ranging from .64 to .91, which are considered acceptable to excellent (Thompson, Barclay, & Higgins, 1995). See Table 2 for the construct definition and reliabilities.
Constructs and reliabilities Construct Performance Expectancy Effort Expectancy Attitudes Social Influence Facilitating Conditions
Definitions The degree to which an individual believes that using smartphones will help him or her to attain gains in job performance The degree of ease associated with the use of smartphones An individual’s positive or negative feelings about performing the target behavior The degree to which an individual perceives that important others believe he or she should use smartphones The degree to which an individual believes that an organizational and technical infrastructure exists to support use of smartphones Anxiety Evoking anxious or emotional reactions when it comes to performing behavior Behavioral The degree to which an individual wants to Intention to use smartphones and will use what is Use learned in the work context Overall
The survey was distributed to 177 students. Thirteen incomplete data sets were discarded, and a total of 164 data sets were analyzed. Descriptive analyses and correlation analyses were conducted to examine the relationships among age, gender, daily use, and students’ acceptance level toward smartphones. Levene's tests were conducted to assess the equality of variances for a variable for two
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groups and independent t-tests were conducted to compare the acceptance level towards using smartphones in different gender group of students.
Ⅳ
. Results
1.
Students’
Purposes
for
Using
Smartphones
in
Higher
Education and Gender Differences in Purposes
Most students (93.3%) are using smartphones to search the Internet. 78% use smartphones to chat/use mobile messenger, 73.2% to use Social Networking Sites (SNS), and 51.2% to check/send emails (Table 3). There are no gender differences in students’ purpose for using smartphones (Table 3). Frequency analysis show that 93.3% of those aged 18-21, 95.6% of those aged 22-26, and 96.9% of those aged 27 or more are using smartphones to search the Internet.
Frequencies and percentages on various purposes for using smartphones by gender Purpose (total n= Male (# and % Female (# and Overall (# and % of
164) of group) % of group) total) Searching the 50 (92.6%) 103(96.3%) 153 (93.3%) Internet Using SNS 39 (72.2%) 81(75.7%) 120 (73.2%) Chatting/Using 44 (81.5%) 84 (78.5%) 128 (78.0%) mobile messenger Reading e-books 4 (7.4%) 13 (12.1%) 17 (10.4%) Checking or sending 31(57.4%) 53 (49.5%) 84 (51.2%) emails Using educational 13(24.1%) 13 (12.1%) 26 (15.9%) contents such as e-lecture For work/business 8 (14.8%) 13 (12.1%) 21 (12.8%) Listening to podcasts 5(9.3%) 14 (13.1%) 19 (11.6%) Note: Multi-selection was possible for purpose for using mobile technology.
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2.
Gender
Differences
in
Students’
Use
and
Acceptance
Level towards Smartphones
Eighty students (48.8%) are using smartphones daily from 1 to 5 hours, 41 (25%) for 5 to 10 hours, and 27 (16.5%) for 10 to 20 hours (Table 4).
Daily Use of Smartphones (n=164) Variables Daily Use
Less than 1 hour 1 to 5 hours 5 to 10 hours 10 to 20 hours Over 20 hours
Number (N) 9 80 41 27 7
Percent (%) 5.5 48.8 25.0 16.5 4.3
Correlation analysis (Table 5) show that gender is significantly negatively associated with facilitating conditions (r=-.18, p
