06 SES 05, Media Literacy - Digital Competence
Introduction and Objectives
Digital technologies are massively being used in educational institutions and society, and this leads a transforming way of learning not only inside but also outside educational institutions. The so-called “Web 2.0” technologies are becoming increasingly popular among students’ daily life. Learning with digital media is becoming a central part of student’s daily life as a form of informal learning (Selwyn, 2010). The informal learning process and structure is self-directed and characterized by intentional interest (rather than curriculum-based), non-assessment-driven and non-qualification-oriented.
Current research suggests that students have a great diversity of technology use and types of technologies adopted into formal learning (Corrin, Bennett, & Lockyer, 2010), but the understanding of learning with digital media from informal learning perspective is still limited. University students’ lives nowadays are saturated with digital media globally. They develop their experience and knowledge of digital media in out-of-school settings. The way of their learning is clearly different from how they use digital media in school.
The present study aims to determine factors influencing university students’ learning with digital media in informal learning contexts, and also to examine the students’ learning behavior and cultural difference in adopting digital technologies for informal learning, between students from China (Asia) and Belgium (Western Europe). The results provide support for the importance of an intrinsic and extrinsic motivation construct to explain influence on students' digital informal learning behavior. Then the modified TAM 3 model was cross validated. The cross cultural analysis results showed that students’ digital informal learning behavior globally matches the proposed model from different cultural background.
The theoretical basis of this study is based on technology acceptance model (TAM) 3 (Venkatesh & Bala, 2008). The model was adapted to match with the specificity of digital learning processes (see figure 1). First , we replaced the computer self-efficacy latent variable as digital competence variable since digital competence is students’ ability to achieve with digital technology (Hatlevik & Christophersen, 2013), which is more related to students perceived competence to digital media. Informal learning is a learner’s control process, which includes the control over the process and the goals(Naismith, Sharples, Vavoula, & Lonsdale, 2004). Intrinsic motivation is often higher than in formal settings where goals are pre-set(A. C. Jones, Scanlon, & Clough, 2013). Therefore, we also keep perceived enjoyment to explain perceived ease of use since it is more intrinsic related.
In addition, we kept other latent variables based on the theory background and developed new items specific to digital informal learning: 1, Perceived ease of use (Taylor & Todd, 1995), in this study, perceive ease of use refers to students’ feelings and perceptions about the degree of ease associated with the use of digital technologies for informal learning. 2, Compatibility, which describes the degree to which technology adoption fits the task, values, and needs of the user (Roger, 2003). 3, Perceived Usefulness, which is defined as the subjective probability that using digital media will increase his or her job performance. 4, Subjective norms, which describes a person’s perceptions of whether other people believe she/he should or should not perform a particular behavior (Ajzen, 1991). 5, perceive enjoyment, which refers to the extent to which the activity of using digital media for informal learning is perceived to be enjoyable in its own right, aside from any performance consequences resulting from digital informal learning. 6, Behavioral Intention, in this study, which is concerned with motivational factors related to students’ intentions to use digital media in informal learning contexts. 7. Actual Behavior, which describes the extent that actual use of digital media to informal learning (DIL).
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes. Chin, W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion / adoption study. Information Systems Research, 14, 189–217. Corrin, L., Bennett, S., & Lockyer, L. (2010). Digital natives : Everyday life versus academic study. In 7th International Conference on Networked Learning (pp. 643–650). Lai, C., Wang, Q., & Lei, J. (2012). What factors predict undergraduate students’ use of technology for learning? A case from Hong Kong. Computers & Education, 59(2), 569–579. Selwyn, N. (2010). Web 2.0 applications as alternative environments for Informal Learning - a Critical Review. Paper for OECDKERIS Expert Meeting Session 6 Alternative Learning Environments in Practice Using ICT to Change Impact and Outcomes, 1–10. Taylor, S., & Todd, P. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6, 144–176. Thompson, P. (2013). The digital natives as learners: Technology use patterns and approaches to learning. Computers & Education, 65(0), 12–33. Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315.
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