Volume Two - Academic Conferences

Chien-hwa Wang and Cheng-ping Chen
shared construction of knowledge, which is an essential attribute of Web 2.0. Unfortunately, there are
few studies of Web 2.0 learning that focus on learner characteristics. Vandewaetere, Desmet and
Clarebout (2011) also highlighted that current studies on adaptive learning failed to bridge theory with
practice. Therefore, a framework that integrates current and past research results is urgent.
4. Self-directed learning readiness (SDLR)
In a promising development, Hung et al. (2010) verified a five dimensional model of learner
characteristics for online learning environments. The five dimensions were categorized as: selfdirected
learning (SDL), motivation for learning, computer/Internet self-efficacy, and learner control.
These learner characteristics are distinctive and useful for building the research framework of this
study. Considering the limited scope of this study, the first two dimensions were selected as the main
research variables and then examined.
As Long and Agyekum (1983) highlighted, the attributes of self-direction in learning are becoming
increasingly important. Educators have been challenged to assist in the development of SDL skills
and to encourage learners to use self-direction more freely in their learning activities. Long and
Agyekum are not the first researchers to introduce the idea of SDL. Tough (1966) first determined that
SDL involves a person with the ability to learn how to plan and maintain motivation. Knowles (1975)
suggested SDL involves a person with the ability to diagnose their own learning demands, draft
learning objectives, choose appropriate learning strategies, and evaluate the learning effect.
In a major application of SDL, Guglielmino (1977) introduced the term SDLR and developed a selfreport
questionnaire with Likert-type items. Eight factor aspects were included in the SDLR
questionnaire. These eight factor aspects underlying the SDLR ascertain learner readiness for SDL
(McCune and Guglielmino, 1992). The SDLR questionnaire is widely known as the self-directed
learning readiness scale (SDLRS). Though there have been some criticisms of SDLRS, (Brockett,
1987; Field, 1989; Straka and Hinz, 1996), the vast majority of studies have supported the
questionnaire’s reliability and validity (Delahaye and Smith, 1995; Long and Agyekum, 1983; McCune
and Guglielmino, 1991; Russell, 1988). The SDLRS and its self-scoring form, the Learning Preference
Assessment, are the most frequently used methods for assessing SDL readiness (Merriam, Caffarella,
and Baumgartner, 2007).
According to Chang (2006), Guglielmino’s SDLR questionnaire has been translated into Chinese and
carefully revalidated by Teng (1995); the number of questions was reduced from 58 to 55 and the
original eight aspects were reduced to four aspects in consideration of cultural differences. The four
aspects are (1) effective learning (EL), (2) active learning (AL), (3) independent learning (IL), and (4)
creative learning (CL).
With the current information technology advancements, the SDLR can be adapted to a learnercontrolled
eLearning environment. The link between SDLR and eLearning was determined by Warner,
Christie, and Choy (1998). They defined the readiness for online learning as follows: (1) students’
preferences for the form of delivery compared to face-to-face classroom instruction; (2) student
confidence when using electronic communication for learning and, in particular, competence and
confidence in the use of Internet and computer-mediated communication; and (3) ability to engage in
autonomous learning.
5. Learning motivation
Motivation significantly influences learners’ intentions of remaining in a self-regulated, learnercontrolled
eLearning environment. According to Keller (1983), motivation affects individuals’ efforts
and attitudes toward learning. In other words, motivation influences the selection or avoidance of
specific experiences or goals as well as influences the degree of effort learners apply to the
experience or goal. Keller (1983) suggested that learning motivation is affected by four perceptual
components: attention, relevance, confidence, and satisfaction. Each component plays a critical role
in motivating students throughout the learning process. This is the origin of the ARCS model, which
has been wildly employed as the theoretical foundation of various instructional strategy developments.
Keller (1987, 2006) further recognized several categories of motivational factors that may affect the
learning outcome. These factors were used to develop his motivational design models. The models
are categorized into four groups: person-centred models, environment-centred models, interactioncentred
models, and omnibus models. The first two models are in agreement with recent theoretical
848