Table of contents
1. Introduction .. 2
2. Technology Acceptance Model (TAM) .. 3
3. Culture factor .. 3
4. Research methodology .. 3
5. Data Analysis .. 4
i. Analysis Result of Part I .. 4
ii. Analysis Result of Part II .. 4
6. Conclusion .. 5
Many studies have scrutinized the benefits of m learning. Somehow, it is still necessary to comprehend the dissatisfaction of certain learners towards m-learning experience. Thus, this research aims to investigate the factors that might affect the acceptance of m learning among university students: quality of service, uncertainty avoidance and trust. Portability and access to countless activities are among the advantages of mobile devices, and these foster and ease ubiquitous learning. This study scrutinizes the theories and cognitive techniques to offer individualized, motivated and valuable experience of mobile education for transfer to the subsequent word learning and reading comprehension. As surveys and forms are the data sources, the quantitative methodologies are employed. Twenty six (26) items from diverse research domains were constructed in the questionnaire to measure six constructs, and undergraduate and postgraduate students of the university in Doubi were selected as respondents. Two hundred (395) completed questionnaires were obtained.
Keyword: Mobile Learning, Culture factor, Technology Acceptance Model (TAM)
Meanwhile, social influence is the degree to which an individual believes that significant others believe he or she should employ the new system (Cruz et al., 2014). Comprehending the aspect of social influence is crucial within the context of student’s interest in m-learning. In fact, the previous studies have reported that the decision of a student often times is affected by their peers or by significant others including parents and instructors (Miller et al., 2003; Abual-aish & Love, 2013). Also, the mobile learning market is increasingly becoming global. As such, cultural difference is now a crucial factor. Therefore, universities or training organizations must understand cultural difference or otherwise, they could not obtain substantial competitive edge (Ariffin & Dyson, 2012). As such, better and more meaningful services’ development in higher education realm is attainable when the model of technology acceptance (TAM) and the innovation diffusion theory (IDT) are extended
2. Technology Acceptance Model (TAM)
TAM is one of the most widely employed models of individual acceptance and use of technologies. The model was initially developed and tested in the 1980s (Davis, 1989; Davis et al., 1989). Subsequently, the model has been extensively validated across a variety of settings and subjected to theoretical extensions (Venkatesh & Davis, 2000; Venkatesh et. al., 2003; Davis et al., 1989). TAM consisted of perceived ease of use (PEOU), perceived usefulness (PU), attitude toward using (ATU), behavioral intention to use (BI), and actual system use (AU). PU and PEOU are the two most important determinants for system use. The ATU directly predicts users’ BI which determines AU. PEOU refers to the degree to which a user believes that using a particular service would be free of effort while PU is defined as the degree to which an individual perceives that using a particular system would enhance his or her job performance (Fred D. Davis, 1989). However, PEOU and PU are the key beliefs leading to user acceptance of information technology (Liu & Han, 2010). Many studies used the TAM model to investigate the factors that affect the M-learning. The results of these study was positive and acceptable in scholar debate such as (Gloria .2013 &Hassan, 2009).
3. Culture factor
Aspects of culture could help to improve the usability of the mobile learning user interface. Current research deals with the usability aspects and cultural aspects of the web sites but not many research results could be found for mobile learning, on appropriate local culture. Sources for mobile learning interface usability that relate to the culture issues are also rarely to be founded. The popular and well known Hofstede cultural dimensions model brings 5 principles: Individualism / collectivism, Uncertainty Avoidance, Power Distance, Masculinity / Femininity and Long Term Orientation. (Shamsul, 2011). Culture and IT are linked in many studies. Tricker (1988) provides an excellent framework linking IS and culture using Hofstede's work. Also, Ein-Dor et al. (1993) lists cultural factors in IS, which includes attitude towards technology progress, interpersonal relations and social commitment, and social norms. In another study, Hassan and Ditsa (1999) observed that culture factor is probably the most difficult factor to isolate, define, and measure.
4. Research methodology
The most important objective of this study is to examine the culture factor that drive m-learning acceptance in Al-Madinah International University and it’s perceived ease of use as well as it’s perceived usefulness m-learning on students’ studies. The study is a quantitative study using survey approach. The key instrument for data collection is the questionnaire. The sample of the current study is based on the population which contains the students in Al-Madinah International University The sample of the current study is students who are using m-learning services for their learning settings. Random sampling approach will adopt to identify the respondents. The questionnaire will divide into four sections, culture factors, perceived usefulness, perceived ease of use and m-learning acceptance. This research employed 300 students.
5. Data Analysis
This section divided into two parts, first part is analysis results for demographic data of students and second part analysis data for Correlation analysis as following:
i. Analysis Result of Part I
The respondents’ profile is illustrated in Table 1.1 below. As indicated, most of the respondents which accounts for 187, were female while the remainder (113) were male. Aside from that the majority of the respondents were from the science and business group at 121 and 99, respectively, while respondents from the art studies group made up the smallest fraction 80. As far as education level is concerned, most respondents had Bachelor’s degree (90.12%), while the smallest fraction of respondents were PhD holders at only 5. As for the master’s degree holder, it accounted to 30 of the respondents. Thus, as indicated by the respondents’ education level, this study’s findings are representative to the varying student levels.
[Table is omitted from this preview]
Table 1.1: The demographic data of students (N=300)
ii. Analysis Result of Part II
Correlation analysis is conducted to assess the relationship between six main factors and behavioral intention to use m-Learning. As a summary, each zero-order correlation test of each of the hypotheses demonstrates significance. As such, all the hypotheses are supported at this level. Also, culture, perceived usefulness, and perceived ease of use factors demonstrate positive indirect relationships with the behavioral intention to use of m-learning. All factors in the proposed model are illustrated in table 1.2.
[Table is omitted from this preview]
Table 1:2 Path Coefficients and t-Values of the Hypothesis
Nowadays, m-learning services are interesting and very recent addition as a new vital platform for the higher education environment. Nevertheless, Student’s perspective is very important to investigate the use behavior of m-learning. M-learning in the higher education environment. Combination of education channels and alternatives helps students to be in touch with their educational environment anywhere and anytime. The present study suggests the TAM has been widely used model to help understand and explain user behavior in an information system. The article has explained the technology acceptance model with the culture factor.
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