Perceived Variables

Perceived Usefulness and Perceived Ease of Use are two variables in the TAM

model used to explore the adoption of technology (Davis, Bagozzi, & Warshaw, 1989;

Davis, 1986, 1989, 1993). Perceived variable is a kind of psychological sense. In a

great number of researches about extended TAM model, perceived variable is mainly

used to measure the perception and belief created when a user adopts some kind of

technology. For examples: Perceived enjoyment (Lee, Cheung, & Chen, 2005; Teo,

Lim, & Lai, 1999; Igbaria, Iivari, & Maragahh, 1995; Yu et al., 2005; Hwang & Kim,

2007), perceived playfulness (Venkatesh & Davis, 2000; Moon & Kim, 2001; Lin, Wu,

& Tsai, 2005; Tao, Cheng, & Sun, 2009; Roca & Gagne, 2008), perceived interactivity

(Cyr, Head, & Ivanov, 2009; McMillan & Hwang, 2002). In Cyr et al. (2009)’s paper,

the goal of the investigation is to examine perceived interactivity in a proposed model

which explores usages of different web-poll interfaces. In McMillan & Hwang

(2002)’s research, it validated a measure of perceived interactivity, offering

researchers a tool for measuring consumer perception. The developed Measures of

Perceived Interactivity for a web-based interactivity investigation focused on a user’s

perception. The concept of perceived interaction was proposed by Newhagen, Cods,

& Levy (1995). It indicates a psychological sense in the interaction between message

senders and receivers. And the concept of perceived interaction is primarily based on

efficacy. This concept focuses on describing the relationship between a reader’s

psychological sense toward efficacy and an audience’s perceived interaction toward

media system. In addition, Wu (1999) defines perceived interaction as two types of

concepts: User’s browsing behavior and system response. He further examined two

e-cards websites, discovering that there was a positive relation between users’

perceived interaction and his/her evaluation toward the website.

In this study, we include a third variable, Perceived Interaction, in our proposed

model and examine its relationship with and impact on each of the other variables,

and whether or not it affects the Intention to Use an Online Learning Community.

2.5.1 Perceived Ease of Use and Perceived Usefulness

In TAM, the behavioral intentions of users regarding technology are affected by

two variables: Perceived Ease of Use and Perceived Usefulness. The former affects

the latter, which means that if users feel the system is easy to use, they will feel that

online learning is useful and they will be prepared to use the technology. The causal

relationship that exists between these two variables has been confirmed by a number

of empirical studies (e.g., Davis, 1989, 1993; Venkatesh & Davis, 1996). The

Technology Acceptance Model proposed by Davis predicts whether users will adopt a

general purpose technology, without focusing on a specific topic (Pituch & Lee, 2006).

In contrast, the current study extends TAM by focusing on specific topics and

exploring the Intention to Use an Online Learning Community. Moreover, certain

parts of Davis and Wiedenbeck’s (2001) proposed model, consider the relationship

between Perceived Ease of Use and Interaction. In their empirical study, they define

several kinds of interaction styles and demonstrate that the two factors have a

statistically significant relationship. Therefore, we also examine the relationship

between both factors in the proposed model.

2.5.2 Perceived Interaction

ICT-supported learning in education has been popular for a long time, and the

electronic media have improved in parallel with the development of technology.

Initially, audio, video, and CD-ROM teaching aids were used as the main online

tuition methods, but they have gradually been replaced by Web-based systems.

Viewed from the level of interaction, the process has evolved from one-way

human-system interaction to two-way instructor-learner interaction. The participants

enhance the communication of knowledge and sharing by interaction with others in

the online learning community. It has been suggested that knowledge is created

through a series of processes whereby individuals interact with each other to share,

recreate, and amplify knowledge (Nonaka & Nishiguchi, 2001). If learners are willing

to increase interaction with their instructors or peers, they will build on their

knowledge construction and have the opportunity to get to know each other. Such

interaction also affects the behavioral intention to use e-learning (Liaw et at., 2007).

Moreover, Cantoni et al. (2004) stressed that interaction between learners could be

improved by using games, quizzes, chat rooms, discussion boards, instant messenger

and email during online learning.

In this study, Perceived Interaction is defined as follows. When learners join an

online learning community, they perceive two types of interaction: human-system

interaction and interpersonal interaction. The former derives from the operating

environment of the online course; and the latter is the result of interaction with peers

and instructors. We focus on the characteristics of online learning, and try to develop

an online learning community from the perspective of the two types of interaction.

Thus, we put forward the following hypotheses:

H9. Perceived Ease of Use will positively affect the Perceived Usefulness of an online

learning program.

H10. Perceived Ease of Use will positively affect the Perceived Interaction with an

online learning program.

H11. Perceived Usefulness will positively affect the Intention to Use an Online

Learning Community.

H12. Perceived Ease of Use will positively affect the Intention to Use an Online

Learning Community.

H13. Perceived Interaction will positively affect the Intention to Use an Online Learning Community.