April 2012 Volume 15 Number 2 - Educational Technology & Society

Reflection
Reflection is an intellectual and affective activity in which individuals are engaged in exploring their experiences to
reach new understandings and appreciations (Boud et al., 1985). Additionally, Soloman (1987) viewed reflection as a
harmonic process of an individual’s past experiences, actions and lessons learned. It can help with constructing one’s
knowledge and meaning. In learning processes, reflection plays a major role and is very helpful for promoting
learning performance (McNamara et al., 2006). Consequently, learners can review, test, and modify their own ideas
while engaging in reflective practice.
Additionally, Yukawa (2006) pointed out the reflection process consists of three stages: (1) returning to experience,
(2) attending to feelings, and (3) reevaluating experience. In these activities, collaborative learning environment
plays an important role in providing the potential for applying new teaching and learning strategies. More
specifically, a collaborative environment could stimulate group members to collaboratively reflect (i.e., Coreflection)
on the group performance and reach a shared conclusion about reflection. Co-reflection is defined as ‘‘a
collaborative critical thinking process involving cognitive and affective interactions between two or more individuals
who explore their experiences in order to reach new inter subjective understandings and appreciations” (Yukawa,
2006; p. 206).
According to this view, the present study thus emphasizes the effect of ML on learners’ reflection levels and further
explores the educational implications of traffic violation reflection.
Gender and age
From the viewpoint of traffic violations, research on adults has proposed gender and age differences in compliance
with traffic rules (Chang & Yeh, 2007). Besides, research indicated males expect less negative outcomes concerning
traffic violations than female (Parker et al., 1992). Moreover, previous study has shown male pedestrians violate
more rules than female pedestrians do (Moyano Diaz, 2002).
On the other hand, regarding the gender and age issues for computer-mediated education, it has captured the interest
of computer educators for decades. Several studies have examined the role of gender and age in computer-related
attitudes and the use of newer networked technologies (Shashaani, 1997; Uzunboylu et al., 2009). The results
indicated learners’ characteristics have been regarded as important factors to predict their intention and performance.
However, recent studies suggest the gender and age gap regarding technology use is disappearing (Sieverding &
Koch, 2009; Uzunboylu et al., 2009). Additionally, to date, whether gender and age play a role in ML and traffic
violations have not been investigated.
Based on the above, the present study utilized gender and age as the personal characteristics to understand its
importance in influencing the attitudes toward mobile technology in an ML environment and the level of traffic
violation reflection.
Research purpose and questions
This study was to integrate mobile communication technologies and a global positioning system (GPS) to construct
an instant, convenient report of the mobile network service system named the Mobile Traffic Violation Reporting
System (MTVRS), to improve learners’ traffic violation reflection level. Our evaluation mainly focused on
answering the following four questions: (1) What are the effects of ML on traffic violations? (2) Do the learners’
gender and age affect the usefulness of ML systems for traffic violations? (3) Does the traffic violation reflection
level on the post-test increase more significantly than the pre-test? (4) What are the effects of learners’ gender and
age in group activities while taking different distributions for the reflection levels about traffic violations?
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