Open Journal of Social Sciences, 2014, 2, 32-40
Published Online May 2014 in SciRes.
How to cite this paper: Chang, C.-H. (2014) Research on Adapting to QR Code by Auto-Repairing Students in Vocational
High School. Open Journal of Social Sciences, 2, 32-40.
Research on Adapting to QR Code by
Auto-Repairing Students in Vocational
High School
Chun-Hsin Chang
Department of Industrial Education, National Taiwan Normal University, Taipei, Taiwan
Received January 2014
QR code as a technology enhanced learning tool is prevailing not only in daily life, but also in edu-
cation settings. The present study aims to explore the usage of QR code as a social medium in
searching and learning profession knowledge of auto-repairing. The experiment contains 3 learn-
ing courses and 3 lessons for 155 students. Moreover, based on the theory of planned behavior,
questionnaires are designed for students to fill out. A total of 153 copies are valid questionnaires.
Confirmatory factor analysis is conducted while structural equation model is established. Re-
search outcome indicates that Internet cognitive capacity correlates with hedonic and epistemic
values, which reflect directly in learning attitudes of auto-repairing students using QR code. As
sustaining intent of usage for QR code has to do with learning attitude of students, the study sug-
gests that instructors should decrease complex contents of QR code before providing them to stu-
dents for learning.
QR Code, Hedonic Value, Utility Value, Learning Attitude, Intenti on
1. Introduction
Instruction of professional course for auto-repairing students in vocational high school tends to be conducted by
instructors according to contents of textbooks. Great amount of photos are used to explain the operational prin-
ciples [1]. Or, self-compiled electronic files are used as course contents instead of traditional course delivery. In
the recent decades, teaching progression and teaching method are forced to change as teachers faced predica-
ment [2]. Auto technology varies along with elapse of time, while teaching materials for auto technology in
school fail to update and fall behind. How can students learn effectively? How can we help students learn dy-
namically in head? The key is not to accumulate knowledge but learn the procedure, which can enable us to
transform knowledge into creative capacity required to make profits. That is, to empower students to apply
knowledge [3 ]. Instructors for auto-repairing should emphasize innovative method to educate and learn, hence
guide students to acquire capacity of multiple learning.
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During educational process, effectively use resources of Internet. Take advantage of this new educational en-
vironment to enhance educational effects, help students learn, and provide students with multiple means of
learning [4]. Many relevant documents point out, combining information with instruction can indeed advance
motivation and effectiveness for learning on the part of students [5]. Thus implement course integrating digital
information and education should be able to help students learn, and elevate their learning effectiveness and sa-
tisfaction. Digital learning materials can indeed facilitate self learning for students.
As medium digitalization becomes reality, the study adopts QR code learning method to support traditional
education. Since students enjoy the course of learning, they develop interest in professional course and become
willing to learn actively. To be specific, the study aims to explore the process in which students adopts QR code,
the relationship between Internet cognitive capacity of students with epistemic value of QR code, learning atti-
tudes of students in learning QR code, and sustaining intent of usage for QR code on the part of student. Sugges-
tions will be made according to research outcome to provide future reference for educators.
2. Literature Review
Development of Internet affords more options for educational methods. As Internet is far-reaching, it increases
interest in learning for students [4]. Teaching via web gradually takes place of traditional teaching [6]. Whether
using QR code in course on gasoline injection engine at vocational high school induces interest from students
becoming a worthwhile subject of discussion.
2.1. Theory of Planned Behavior
Most researches on attitude and behavior are based on theory of reasoned action (TRA) and attitude model [7]
which develops into theory of planned behavior [8]. Therefore, theory of planned behavior includes attitude,
subjective rules and cognitive behavior control. Attitude and subjective rules come from theory of reasoned ac-
tion. Cognitive behavior control is a newly added variable [9]. In theory of reasoned action, Fishbein & Ajzen
infer that intent affects action. Attitude and subjective rules to conduct specific behavior will affect theory model
of behavior intent. Ajzen, 1988 brings up that behavior is not just up to attitude and subjective rules. It is also
affected by control of self will power. Thus Ajzen [10] suggests that one is about to do conduct some behavior,
only if he has capacity, resources and opportunity. Therefore, individual behavior intent is affected by attitude,
subjective rules, and cognitive behavior control.
2.2. Internet Cognitive Capacity
Research confirms that cognitive accessibility of blog website by user will positively affect usage intent of user.
And it further affects the actual degree of usage by user [11]. Exploration of fun factor in cognition for online
games results in discovery that after students develop cognitive interest in experiences, it will have positive in-
fluence on their willingness of usage. The degree of influence tends to be high [12]. Many researchers find that
degree of difficulty in usage affects user considerably. When user encounter barrier in using web, he will lose
confidence and fail in web cognition. Cognitive failure can be defined as activity which ordinary people are able
to accomplish ends with failure and operational mistake [13] . Cognitive failure refers to absent-mindedness and
attention cannot focus in individual self reaction [14]. On the whole, web cognition capacity will directly affect
learning condition and strength of hedonic value on the part of a learner.
2.3. Experiencing Values: Hedonic and Epistemic
Epistemic and economics have similar views on value. They consider consumption rational. Behavior is a
goal-oriented tool [15]. Emphasizing epistemic value means consumer behavior is generally conducted after
careful consideration, and it is efficient. In general, I define epistemic value as problem solution or behavior to
fulfill some goal. Whether such behavior is beneficial to the future of learner, or able to resolve problem en-
countered, has to do with attitude of learning.
In contrast with epistemic value, hedonic value is more subjective and more personalized. Such value often
involves fantasy, feelings, fun, experiences and great amount of significance in learning process [16]. Putting
emphasis on hedonic value and needs often requires attaining excitement, confidence during the learning
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Through aforementioned definition of hedonic value, and follow-up research on it, hedonic value gradually
catches greater and greater attention and appears in researches on different circumstances. Hedonic value is the
main drive to push user to apply new techniques [17]. By using structural equation model to proceed with model
confirmation, the research outcome indicates that consumption behavior of hedonic value indeed produces af-
fection on usage intent.
2.4. Learning Attitude
Good attitude of students should have specific learning goals, high interest in learning, aggressive and sustaining
participation in learning, and problems overcome [18]. Aggressive learning attitude is the basis for ideals. It
enables learner to lean towards fondness and participation. Passive learning attitude will let learner withdraw or
reject learning. Therefore, different learning attitudes will affect learning results of students.
Learning attitude is teaching and learning process for a learner who keeps a sustaining and consistent inner
reaction including interaction among cognition, emotion and behavior. It will further influence academic per-
formance [19]. Attitude of engaging in all learning related activity is a psychological reaction and inclination
developed against person, event and object of learning environment during the learning process [20]. Cheng
Hsiu-ling [1] defines learning as a concept derived from attitude. It is based on contents of attitude, characteris-
tics, and theory causing change. It emphasizes attitude of learning things. Learning attitude, on the other hand, is
during learning related activity, learner develops positive or negative cognition and attitude towards things
learned. Fishbein [7] also points out that “attitude” is positive or negative judgment harbored by individual to-
wards some specific behavior.
2.5. Intent of Sustaining Usage
According to theory model brought up by Ajzen [8], behavior intent refers to subjective judgment whether one
will be likely to conduct some behavior. It also reflects willingness to take action. He also suggests that individ-
ual behavior intent is the best variable to predict behavior. That is, strength of being engaged in specific beha-
vior as self-motivated plan is called behavior intent [21]. Circumstances of the study continue to use intent to
express habitual, continuous, active learning attitude developed by students during the process of learning QR
2.6. Shaping of Research Framework
From the aforementioned theory and relevant researches, it is known that according to Ajzen [8], theory of
planned behavior model shapes main affected aspects resulting in web cognition capacity and its influence on
hedonic and epistemic values. The study primarily draws on student applying QR code to learn auto-related
knowledge. During the usage by students, degree of hedonic value has to do with epistemic value and learning
attitude of QR code. Consequently, QR code learning attitude eventually draws attention to intent of sustaining
usage. Therefore, the study brings up research framework as Figure 1.
According to aforementioned theory and research framework, the study brings up the following hypothesis
while exploring sustaining usage intent relationship model and interaction among all factors:
H1: On web, cognitive capacity of students correlates with epistemic value.
Figure 1. Framework model for the study.
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H2: On web, cognitive capacity of students correlates with hedonic value.
H3: Hedonic and epistemic values correlate for students.
H4: Epistemic value and learning attitude correlate for students.
H5: Hedonic value and learning attitude correlate for students.
H6: Learning attitude and intent of sustaining usage correlate for students.
3. Research Design
Current education requires application of new information technology to acquire knowledge. The study adopts
smart phone or tablet PC to scan QR code via various sensors, then enter the website to begin learning. After
experiment, students are requested to fill out questionnaire on degree of satisfaction for implementing QR code
learning, in order to understand the influence and effectiveness of learning QR code.
3.1. Application of QR Code Learning
Rapid information transformation mechanism, inexpensive market price, easy operation for QR code, along with
mobile communication facility and technology, enable information to circulate conveniently via multiple channels.
Applied to public affairs, QR code can enhance validity, accuracy and effectiveness of confirmation operation.
Applied to learning, it can let learning environment closer to reality and help learners to have immediate access to
information to be acquired. Thus mobile learning is everywhere. Just as Cheng Chi-wen (2010) mentions, if the
production process of QR code can combine with design in follow-up cross-platform learning, and further inte-
grate with high technology mobile or tablet PC, it can indeed become a tool with immedate access to information.
With advent of cloud-based technology, platform of life long learning community can be implemented.
3.2. Research Steps
The study aims at auto-repairing students in Taipei and New Taipei Cities who use smart phones or tablet com-
puters to scan QR codes by various sensors (see Figure 2). After entering web pages, they start learning. Instruc-
tors give students learning checklists. Students fill out checklists according to materials on the web pages.
Through contents of the learning list, instructors can control the progression of learning for students. Students
learn QR code for two hours every week. They continue learning within four weeks. Meanwhile, surveys on
learning satisfaction for QR code are to be filled out by students, in order to know the influence of learning QR
code on course of auto injection engine.
3.3. Example of QR Code Learning Contents—Air-Fuel Ratio Sensor
This experiment teaching unit is on sensor for course of gasoline injection engine required in vocational high
school. The web teaching databse connected to QR code is based on teaching material compiled according to
Ministry of Educaiton course criteria for 2010 class outline on power machinery group. Figure 3 is excerpts of
QR code teaching contents for the study.
Figure 2. QR code is labeled on sensor.
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Figure 3. Example of QR code learning contents—air-fuel ratio sensor.
3.4. Research Object
Objects of this experimental education are 75 senior auto-repairing students in Taipei City and 80 auto-repairing
students in New Taipei City. A total of 155 students undertake experiment. A total of 155 Questionnaires for QR
code learning satisfaction are distributed. Recovered questionnaires amount to 155. Valid questionnaires amount
to 153. Among them, questionnaires filled out by students from Taipei City account for 49.9%, while those by
students from New Taipei City account for 50.1%.
4. Research Tools
The study bases its research framework on collection of relevant theories and documents. It also refers to Gov-
ernment Official e-academy survey on condition of usage [22] and its structural contents. Keeping aspects of
web cognition capacity, hedonic and epistemic values, and intent, it follows planned behavior theory and rele-
vant theoretic basis by Ajzen [8], adds aspects on learning attitude, etc. By giving proper phrases and editing
topics of its aspects, it enables design of questionnaire in accord with terminology of this study. There are 6 as-
pects and 37 questions. Throu gh pre-test and post-check, it is discovered that credibility is too low. So questions
are dereased to 24. Result of second test indicates that Cronbach’s α value for questionnaire is 0.901.
Survey on QR Code Learning Satisfaction
This survey aims to find out attitude and opinion on adopting QR code education for students in course on gaso-
line injection engine. The survey contains 6 aspects including 1) 3 questions on web cognition capacity; 2) 4
questions on hedonic value; 3) 6 questions on epistemic value; 4) 5 questions on learning attitude; 5) 6 questions
on intent of sustaining usage. Measurement for all questions is based on Likert five-point scale.
5. Research Outcome
5.1. Relevant Analysis
The study draws on Cronbach’s alpha credibility analysis to examine if questions in questionnaire are steady.
The result indicates that the overall Cronbach’s alpha coefficient for questionnaires is 0.901. It means the gener-
al credibility for questionnaire is excellent [23].
From Figure 2, it is known according to Pearson relevant analysis coefficient that cognitive capacity corre-
lates with hedonic value, cognitive capacity correlates with epistemic value, hedonic value correlates with epis-
temic value, learning attitude and intent of sustaining usage, hedonic value correlates with learning attitude and
epistemic value, and learning attitude correlates with intent of sustaining usage.
5.2. Appropriateness Analysis for Structural Equation Model
The study confirms relevancy structure of learning satisfaction of QR code with SEM and AMOS (Analysis of
Moment Structures) software package. The cause and result relationship of the six aspects of the study including
learning anxiety, web cognition capacity, epistemic value, hedonic value, learning attitude and intent of sustain-
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ing usage can be found out in Table 1 and Figure 4. Therefore, measurement type degree of appropriateness
indexes established by the study are as follows: RMSEA is 0.058 (<0.08), NFI is 0.798 (<0.9), IFI is 0.912
(>0.9), CFI is 0.908 (>0.9), NNFI is 0.910 (<0.9), RFI is 0.733 (<0.9), GFI is 0.842 (>0.8), AGFI is 0.808 (>0.8).
5.3 Path Analysis
From Table 2 and Figure 4, it is found out that web cognition capacity and epistemic value appear obvious
negative relationship. Its parameter estimate value is 0.132. The more positive students have web cognition
capacity towards QR code, the higher its epistemic value for QR code. The outcome supports Hypothesis 1.
Web cognition capacity and hedonic value appear positive relationship. Its parameter estimate value is 0.147.
The more students have web cognition capacity towards QR code, the higher is its hedonic value for QR code.
The outcome supports Hypothesis 2.
Hedonic and epistemic values appear obvious positive relationship. Its parameter estimate value is 0.608. The
more positive students feel about hedonic value of QR code, the higher is its epistemic value for QR code. Its
outcome supports Hypothesis 3. Epistemic and learning attitude appear obvious positive relationship. Its para-
meter estimate value is 0.283. The more positive students feel about epistemic value of QR code, the higher is
its learning attitude for QR code. This research outcome supports Hypothesis 4. Hedonic value and learning at-
titude appear obvious positive relationship. Its parameter estimate value is 0.658. The more positive students feel
about hedonic value of QR code, the higher is its learning attitude for QR code. The result supports Hypothesis 5.
Learning attitude and intent of sustaining usage appear obvious positive relationship. Its parameter is 0.723. The
more positive students feel about learning attitude for QR code, the higher is its intent of sustaining usage for
Table 1. Relevancy coefficient.
Internet cognitive Utilitarian Hedonic Learning attitude Intention
Internet cognitive 1
Utilitarian 0.040 1
Hedonic 0.031 0.519** 1
Learning attitude 0.125 0.516
Intention 0.009 0.548** 0.712** 0.577** 1
*p < 0.05, **p < 0.01.
Table 2. Path parameter analysis.
Path Path parameter
t test Aspect R
Internet cognitive
utilitarian 0.132 2.062*
Internet cognitive hedonic 0.147 2.022
Hedonic value 0.022
utilitarian 0.608 4.274
Epistemic value 0.363
Utilitarian learning attitude 0.283 2.549* Learning attitude 0.733
Learning attitude intention 0.723 7.029*** Intent of 0.523
*p < 0.05, **p < 0.01.
Figure 4. Confirmation research model.
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QR code. The result supports Hypothesis 6.
6. Discussion
Summarize the aforementioned structural model analysis; it is found out that epistemic value, hedonic value,
learning attitude, and intent of sustaining usage directly influence learning effectiveness for students. It can be
validly applied to learning behavior of QR code for auto-repairing students in vocational high school. The dis-
covery proves the theories: 1) Intent of sustaining usage of QR code comes from learning attitude. 2) It proves
the relationship among learning attitude, hedonic value and epistemic value. 3) It exemplifies that web cognition
capacity, hedonic and epistemic values have interaction and mutual influence. To be specific, QR code learning
model is rather important to learning intent for auto-repairing students.
Structural model analysis of the study results in the following outcome:
Learning QR code by auto-repairing students can be measured by theory of planned behaviour, and concept of
object model, an attitude brought up by [7]. Learning attitude of auto-repairing students and intent of sustaining
usage of QR code have obvious positive relationship. It means the more positive learning attitude the students
have for QR code, the higher its intent of sustaining usage of QR code. The outcome is in accord with research
results of Ajzen [8] and Fishbein [7] et al. The study also discovers that learning attitude of auto-repairing stu-
dents for QR code has positive interaction with epistemic and hedonic values. It means they bear mutual influ-
ences among them.
The research outcome indicates that epistemic and hedonic values correlate with learning attitude. Research
viewpoints of Bruner and Kumar [17]; Wang kai, Chen-yuan [24] are that hedonic value is the main drive to
push user to use new technology. Combine hedonic value and technology reception model, hedonic value can
thus be taken as outer incentive for technology reception model. Epistemic, hedonic values and learning attitude
have obvious positive relationship. It means the higher epistemic and hedonic values are for auto-repairing stu-
dents to use QR code, the higher is the learning attitude. It also means that epistemic and hedonic values are
important factors of influencing learning attitude.
7. Conclusion
The current popularity of QR code application is noticeable in daily life print advertisement, introductions to li-
brary, zoo and botanical garden. It is also widely applied to word automated transmission, download of digital
contents, websites rapid linking, identity differentiation and business dealing [25]. Many domestic scholars
conduct researches on its academic and practical usage. However, there is no application of QR code to auto-
repairing professional education by researchers.
The study scans QR code via devices such as smart phone or tablet PC to allow students to proceed with
learning. It is learned from research outcome that learning interest is affected by influence of positive or nega-
tive learning motivations of students [26]. During the research, student develops interest and curiosity towards
learning QR code, then knowledge learned would carry epistemic value (for example, high grades in exam).
Therefore, elevation in learning attitude enhances intent of sustaining usage for students. For both learning ef-
fectiveness and learning satisfaction, design of QR code learning has great help for au-repairing students.
7.1. Research Contri bution
To sum up, outcome of the study suggests the following: First, web cognition capacity will affect hedonic value
and learning anxiety during QR code learning. Design of the study comes from numerous discussions. It also
designs web interface and learning contents easy to operate and read for students. Student will not experience
learning anxiety and quit learning. Therefore, design of web interface and learning contents is very important.
Secondly, many previous researches are limited to application of multimedia (such as film, animated art, and
web online learning) to auto-repairing professional education. The study offers new technological, innovative
learning method. That is, to learn contents of QR code through smart phone or tablet PC. During learning QR
code, the students experience learning of interest and hedonic value. Therefore, epistemic value and attitude of
learning QR code after learning are considerably elevated. The study establishes correlation among hedonic, ep-
istemic values and learning attitude. At last, the study confirms significance of QR code to student learning. It
strongly reflects the importance of learning attitude of QR code to intent of sustaining usage. It is concluded that
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hedonic value is inevitable to students during learning. Such innovative learning of QR code changes learning
attitude of auto-repairing students towards professional course.
7.2. Suggestion
Instructors for vocation high school should take into account that student learning is not confined to traditional
description and multimedia teaching methods. The research suggests that instructors for vocational high school
ought to offer multiple learning environment and resources. In addition to cultivate professional capacity for
students, teachers should help students generate passion and build confidence. With interesting topics to rouse
curiosity on the part of students, so as to facilitate positive values students have towards professional skills. Via
amiable atmosphere, students will be enabled to generate motivation of self-learning. QR code learning con-
ducted with the help of supporting teaching methods is feasible. As contents of QR code learning is team work,
it is inevitable to cooperate among peers to establish contents of QR code together. Besides, QR code learning is
not just applicable to learning by auto-repairing students. It is also functional to learning by students in technol-
ogy colleges and other courses in vocational high schools. If teachers offer students with QR code learning, they
should pay attention to reduce complexity in QR code contents.
7.3. Research Limitation and Future Research
Limited to manpower, resources and time, the study scope of this research is confined to auto-repairing students
in one engineering school at Taipei and New Taipei City each for individual experiment and research. Sample
deviation is inevitable. Future research should enlarge sampling (to approximately 300 students) so as to in-
crease research accuracy.
In structural model of the study, hedonic, epistemic values and learning attitude bear noticeable differences.
Therefore, hedonic, epistemic values and learning attitude are interfering variable of considerable significance.
In the future, different structural models can be applied to confirm if other aspects will affect learning attitude or
intent of sustaining usage. For instance, research can be done on whether aspects such as contents satisfaction
and interface design correlate with hedonic, epistemic values and learning attitude.
They are numerous researches on QR code learning, but there is none on learning in professional course at
vocational high school. Future research can focus on practical training in individual subject to conduct experi-
ment within a whole semester. Extend time of experiment to 12 weeks to increase reliability of research out-
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