A Project-based Creative Product Design Course using Learning

Management System

Janus S. Liang

National Taiwan Normal University, 162, Heping East Road Section 1, Taipei, Taiwan

Keywords: Creative Product Design, Project-based Approach, Learning Management System, Pedagogical Issues.

Abstract: This study presents an effective mode for creative product design learning through practical tasks generation

by learner groups in a face-to-face course. This mode integrates project-based learning, and learning

management techniques and tools. We include a quasi-experimental study in which the results of four

academic years are analyzed. In this study we analyze phases such as exam grades, exam dropout rates,

exam passing rates, and class attendance. Meanwhile, we also investigate the use of LMS, distinguishing

between informational use and communicational use. The predictive model further involves: utility, user

interface, subjective criterion, personal innovativeness in the domain of information technology and internal

ICT support at school aspect. Learners that followed this active learning approach gained better results than

those that followed a traditional strategy. In addition, the experience of the introduction of such a method in

a student subgroup positively influenced the whole group. Finally, information use was found to be a

precursor for communicational use, perceived user interface of the LMS is the strongest predictor in LMS

acceptation. Internal ICT support has a direct effect on the information use of the LMS and on subjective

criterion.

1 INTRODUCTION

Instructional methods traditionally used for

computer-aided creative product design involve

expositional lectures, and closed and hands-on

laboratories. We will refer to this as “traditional

mode” in the rest of the study. Nevertheless, some

researches proposed that this mode seems to be

problematic or even ineffective for the abstract and

complex domain of creative product design (Howard

et al., 2008; de Vere et al., 2010). One promising

method in this field is based on the development of

projects (Howard et al., 2008). Project-based

learning (PBL) is a constructivist pedagogy that

intends to bring about deep learning by allowing

learners to use an inquiry based approach to engage

with issues and questions that are rich, real and

relevant to the topic being studied. It is designed to

be used for complex issues that require learners to

investigate in order to understand (Barron, 1998).

Within this type of learning, learners are expected to

use technology in meaningful ways to help them

investigate or present their knowledge. Technology

is infused throughout the project to reflect the

emphasis on technological and academic content.

PBL framework differs from inquiry-based activity

in its emphasis on cooperation between team

members. Cooperation refers to the practice of

working in line with commonly agreed goals and

possible methods, instead of working separately in

competition. The several different approaches in

project-based learning (ChanLin, 2008), which differ

in project duration, number of team members, and in

the way the learners cooperate. In summary, there

are many benefits of PBL covered in the literature,

For example, the possibility of increasing

motivation, of connecting learning with reality,

promoting problem-solving and teamwork, among

others.

Project management is the application of

knowledge, techniques, skills, and tools to meet

project requirements (Project Management Institute,

2008). To integrate both perspectives of a project as

an effective creative product design learning

method, using PBL with aim of undertaking a

software project that covers all the activities. The

result of this integration should benefit from both

PBL techniques and professional practices.

Furthermore, we also organize, mange and controls

the development of project tasks and their

S. Liang J..

A Project-based Creative Product Design Course using Learning Management System.

DOI: 10.5220/0004304500050014

In Proceedings of the 5th International Conference on Computer Supported Education (CSEDU-2013), pages 5-14

ISBN: 978-989-8565-53-2

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

deliverables through the adoption of learning

management systems (LMS) in a face-to-face

course, in order to reduce the management time. The

last objective is to investigate the results of two

academic years using PBL approach and the

technology acceptation of LMS.

2 COMPUTER’S ROLES:

COURSE SOFTWARE AND LMS

Several of the project tasks need the use of three

software programs for their development, computer-

aided design system, a text editor, and a data store

system. We present, in laboratories, their main

functions, accessible from the graphical tool

Management Studio. This makes it possible to deal

with physical design in a subsequent task. Through

the realization of these tasks, learners face several

real-world features such as product specification,

design constraints, data editing and storing, backups,

etc. Furthermore, we adopted the institutional and

commercial LMS tool Blackboard/WebCT Learning

System



(Blackboard, 2012), other similar solutions,

of course, could be also useful for our goals. This

tool is applied as a support of a face-to-face course.

This tool has been used to meet several primary

requirements:

(1) Task management: this tool collect the

deliverables, automatically registers the

submission date and time, and allows for

delivering several versions for the same task.

Once delivered, it is possible to send the

feedback to the group and also to assess the

task. We use this tool as an organized

repository. Both learners and instructors have

access to the repository that can be checked in

case of conflict.

(2) Group management: This tool allows us to

update the group composition and automatically

create a kind email distribution list useful for

communication with the groups. It also to assign

the groups to panels. Learners identify

themselves when starting a session and the LMS

uses this identify for all its tools. We also use

the evaluation module to collect the individual

report of the time spent on each task.

(3) Communication: there are several

communication modules provided:

announcement, calendar, email and panel

modules. With the announcements the learners

read instructor news at the beginning of a

session. The calendar displays all the interesting

events related to the project, as task deadlines.

These events are easily created as part of the

task definition. E-mail allows personal

communication, for instance between a learner

and the instructors. The panels permit the

participation of authorized learners and

instructors. To meet several purposes, three

types of panels are used in this tool: (i) a public

inter-groups panel for all group members. It

should be used for general questions and to

explain possible mistakes or problems. (ii) a

private intra-groups panel is built for each

group. It should be used for communication

purposes among group members. (iii) a private

intra-project panel is defined for each project

domain. The panel is anonymous and

constitutes the only communication channel

between both groups. We look for a similar

mechanism to moderated distribution lists. In

this way, the instructor could superintend the

contents of each message before publishing it in

order to avoid inappropriate contribution.

(4) Description of learning method: Presented here

are the general rules, the acquired agreements,

the assessment method, the enumeration of the

different tasks, including the estimated tasks

deadlines and workload and the course schedule

(involving lectures and labs).

At the beginning of the first project task, the

participants have access to the first task description

through the task module. The rest of the tasks are

gradually incorporated through this module.

Whenever a new task is available, the module

highlights this to the students with a graphical

representation on the main page. Each task includes

a detailed description of what should be delivered

before its deadline. Tasks can also be sent for a

while after the time limit. Instructors and students

can consult all the past tasks and easily access their

deliverables during the whole project. Furthermore,

group management workload was reduced as a result

of LMS. We have shown its usefulness for

interchanging instructions, asking and replying to

questions, providing feedback, receiving and storing

work results, and so on. The module requires a brief

reconfiguration for each course: assigning task

deadlines, defining the groups, adding new groups to

the panels and tasks, etc. However, most of the work

is reused from previous courses: method description,

generation of panel, task presentations and

definitions, and so forth.

CSEDU2013-5thInternationalConferenceonComputerSupportedEducation

3 RESEARCH HYPOTHESES

3.1 Project-based Method

The following hypotheses make conjectures on

student results. These results include aspects such as

dropout rates, exam passing, and class attendance.

Better results mean more valuable learning

outcomes for the students. The several hypotheses

that we wish to examine are:

H1a: Students that follow the project-based method

will obtain better results than their

counterparts with a traditional method.

H1b: The project-based method will influence the

whole student group: the results of the entire

group when some students follow the new

method will be better than the results of the

group when everybody follows a traditional

method.

H1c: The project-based method will influence the

students that only follow a traditional method:

these students will improve their results

compared with groups of students where all

their members follow a traditional method.

3.2 The Informational LMSuse

Malikowski, Thompson and Theis (2007)

distinguish several layers of adoption with respect to

CMS features: Layer 1, consisting of the most

commonly used CMS features such as transmitting

course content; Layer 2, comprising features with

moderate adoption such as evaluating learners,

courses and instructors; and Layer 3, including the

least adopted features like creating class discussions

and computer-based instruction. Features of layer 1

can be seen as features focusing on what Hamuy and

Galaz (2010) refer to as the informational phase,

while layer 2 and 3 correspond with the

communicational phase (Hamuy and Galaz, 2010).

Malikowski et al. (2007) concluded that CMS

features for evaluating students or creating

discussions are adopted much less often than

transmitting content, so the flowchart suggests

categories containing these features are adopted after

instructors have transmitted content in a CMS. All

these observations and arguments have in common

that a basic usage phase of specific technologies, is

required to foster the adoption of more advanced

type of technology use. Hence, within the context of

the study about LMS usage, we expect information

use of the LMS to be a precursor of

communicational use.

H2: Informational use will be a precursor of

communicational use.

3.3 Perception of LMS

The perception of utility is defined as the degree to

which a person believes that using a particular

system will enhance job performance (Ware, 2004).

In most TAM-studies, perception of utility has been

the strongest predictor for behavioral intention.

Therefore, King and He (2006) conclude their meta-

analysis with the statement: “if one could measure

only one independent variable, perception of utility

would clearly be the one to choose”. But even if

users think their performance will benefit from

technology usage, they do not necessarily actively

engage with the technology. Ware (2004) explains

this as follows: “they may, at the same time, believe

that the system is too hard to use and that the

performance benefits of usage are outweighed by the

effort of using the application” (p. 320). In this

respect, the variable, perception of user interface,

plays a role. It refers to an individual’s believe that

using a system or technology is free of effort.

Meanwhile, the variable, subjective criterion, refers

to the social influence of important others (Ma et al.,

2005). Though Ware (2004) did not include social

influence as a direct determinant of behavioral

intention, Venkatesh and Davis (2000) reconsidered

this variable in the TAM2 model, especially in

settings where a particular technology usage is

mandatory. Van Raaij and Schepers (2008) refer in

this context to LMS environments when they have to

be used in order to complete the course. This

reconfirms the position of subjective criterion in the

present study. There are several hypotheses included

in our model.

H3a: Perception of utility has positively affects

informational use.

H3b: Perception of user interface has positively

affects informational use.

H3c: Perceived user interface positively affects

perceived utility.

H3d: Subjective criterion positively affects

perception of utility.

3.4 Personal Innovativeness toward IT

Van Raaij and Schepers (2008) consider personal

innovativeness as a form of openness to change.

They agree with Schillewaert et al. (2005) that

“being used to adapting to new systems and

processes might indicate the utility and user

interface more quickly to an innovative person than

to a non-innovative person”. As reported by

Schillewaert et al. (2005), it is not only possible to

distinguish a direct relation between personal

AProject-basedCreativeProductDesignCourseusingLearningManagementSystem

innovativeness and technology adoption, but also an

indirect relation through perception of utility and

user interface. They concluded that a person’s

predisposition toward technology plays an important

role. In this respect, we expect that a learner with a

higher level of technological innovativeness will

more readily use an LMS, and this up to the

communicational phase.

H4a: Personal innovativeness toward IT positively

affects communicational use.

H4b: Personal innovativeness toward IT positively

affects perception of utility.

H4c: Personal innovativeness toward IT positively

affects perception of user interface.

3.5 Internal Support toward IT

Technical support is one of the most essential factors

in the acceptance of educational technology (Wu,

Hiltz & Bieber, 2010). Ngai et al. (2007) also stated

a strong – indirect – effect of technical support on

attitude, thus underscoring the importance of user

support and training on the perceptions of users and

ultimately their use of system. This is confirmed by

the significant and strong association between user

perceptions of school-based ICT support and actual

classroom use of ICT in the study of Tondeur, van

Keer et al. (2008). Thus, we can assume that internal

ICT support will influence the perceptions of the

learners and the use of the LMS.

H5a: Internal support toward ICT positively affects

informational use.

H5b: Internal support toward ICT positively affects

subjective criterion.

4 METHOD

4.1 Participant

This is a quasi-experimental study based on a face-

to-face course on creative product design with one

team of students per academic year. We will identify

each academic year by its final year. For example,

we will refer to the academic year 2010/2011 as

2011. The sample corresponds to four successive

courses, from year 2008-2011, with 78, 85, 96, and

93 students attending the course, respectively. From

year 2010 the project-based method was provided as

an alternative and was optional to all the students.

All the interested members were admitted. A total of

116 students followed this method (56 in 2010 and

60 in 2011) organized in 29 groups. All the groups

had four members.

4.2 Research Design

For each academic year the two instructors were the

same. Each lecturer was responsible for the same

portions each year. The subject contents, books and

written materials were also substantially the same.

To investigate the previous hypotheses (H1a – H1c)

we use the exam grades, which constitute the

common assessment procedure for both learning

methods. All the exams follow a common structure.

They all are composed of the same set of exercise

with very similar difficulty level among them. We

also consider the number of students that did not

take the exam and the student class attendance.

Individual declarations of time spent have been

taken into record in order to measure workload and

to detect free-riders. The “contamination” between

traditional and PBL subgroups is inevitable when we

work with a single group. In addition, we considered

their random division into experimental and control

subgroups unethical. For these reasons we decide to

propose the PBL experience as a voluntary option.

Then, the possible bias included by the voluntary

factor should be carefully taken into consideration.

However, and taking into account the null variance

in contents, exam and instructors, we still can

compare the condition of the whole group before

and after the introduction of the PBL experience. An

alternative study would consider only voluntary

learners and organize randomized groups with them.

As has been mentioned, students either know the

required computer tools from previous courses or

can learn them in specific laboratories. The whole

group uses the LMS for accessing materials. The

project subgroup uses some additional tools in order

to consult and deliver tasks, but there is no essential

difference in both subgroups from a learning point

of view.

Furthermore, a survey instrument was generated.

It focused on the construct as represented in the

proposed research model (as shown in Figure 1).

Ten items assisted to determine the phase of

informational use and communicational LMS use.

Items about announcements, document publishing,

receiving assignments, the agenda, and learner

tracking module are linked to informational LMS

use. Items about the use of the chat environment, the

discussion forum, assessment module, and learning

paths are connected to communicational LMS use.

Participants were asked to indicate on a five-point

Likert scale to what extent they did actively use the

particular LMS tool or functionality. Based on

several previous researches (Chau and Hu, 2001;

Dong, 2009; Venkatesh et al, 2003), we adopted the

four-item performance expectancy scale for

CSEDU2013-5thInternationalConferenceonComputerSupportedEducation

perception of utility and the four-item effort

expectancy scale for perception of user interface.

For subjective criterion, the two-item scale based on

Armitage and Christian (2003) is used. Personal

innovativeness toward IT is assessed with the four-

item scale from Rosen (2004). Internal ICT support

is based on the four-item scale by Tondeur, Valcke,

et al. (2008). All of these items are measured on a

five-point Likert-scale, ranging from “very disagree”

(one score) to “very agree” (five score).

Figure 1: Proposed research model.

5 RESULTS AND DISCUSSION

5.1 Effects in Both Learning Methods

Table 1 compiles the data obtained comparing

traditional and PBL methods in courses 2010 and

2011. Also means comparison tests or Person’s chi-

square tests are included. The exam results

correspond to the grade (from 0 to 10) obtained in

the final exam of the course. The dropout rates were

measured by the absence of mark in this exam. This

exam was passed obtaining at least five points.

Attendance of lectures and labs was not compelled.

We controlled, however, the attendance of practical

classes (15 in 2010 and 17 in 2011). Learners were

informed that this control was only for statistical

purpose. We find that attendance has a direct

correlation with success in the exam (r = 0.402, p <

0.05). As shown in Table 2, the data allow us to

identify a better attitude towards the course in the

PBL group. We observe that participants of the

project group obtained better exam grades, passed

the exam, and attended more classes than their

fellows of the traditional group in a significant way.

The findings seem to support the hypothesis H1a.

Table 1: Results in PBL and traditional approach in 2010

and 2011.

PBL

group

Traditional

group

Statistical test

Sample N (%)

116 (61) 73 (39)

Grade Mean (SD)

6.47

(1.82)

5.06 (1.78) t = - 4.579

Dropout rates % 7.3 21.85

= 12.726, df

= 1

Pass exam % 77.5 28.6

= 35.143, df

= 2

Attendance Mean

(SD)

9.65

(3.85)

4.87 (3.92) Z = -4.862

p < 0.001

The PBL experience was a bit different when we

analyze each of the last two courses. The mean

grade (SD) obtained in course 2010 by all members

was 5.45 (2.10) whereas in 2011 it was 4.62 (1.82) (t

= -2.734, p < 0.05). In 2010 the mean grade (SD) for

the project-based group was 7.05 (1.46) and in the

traditional method group it was 5.02 (1.74) (t = -

4.892, p < 0.001). Nevertheless, in 2011 those data

were 5.18 (1.62) and 4.48 (1.80), respectively (t = -

1.902, p = 0.076). Although both courses showed

better grades in PBL than in the traditional approach,

in course 2010 only a trend to a statistical significant

difference is observed. This means that the

hypothesis H1a could be only partially supported. A

long-term study may possibly illustrate if this

current tendency is a permanent factor. Table 3

includes exam results and dropout rates gained from

the whole group from 2008 to 2009 (traditional

learning method) and from 2010 to 2011 (traditional

and PBL). The class attendance has not been

involved because it was not measured the first two

years. From the introduction of the project-based

method the results of the whole group have

increased. Table 2 reveals better percentages of

members that passed and took the exam than in

previous courses. We can also appreciate certain

improvement in exam grades, although not in a

significant way. All these results seem to sustain the

hypothesis H1b. If analyze each of the last two

courses we obtain that is 2010, 35.1% of the

members did not attend the exam and 39.8% passed

it. These data were 33.8% and 26.3% in 2011,

respectively. However, only the dropout rate

maintains during the two last courses. There is not a

clear tendency in exam grades. This means that the

hypothesis H1b would be only partially supported.

AProject-basedCreativeProductDesignCourseusingLearningManagementSystem

Table 2: The results before and after PBL introduction.

Group

(2008– 2009)

Group

(2010– 2011)

Statistical

test

Sample N (%) 163 (46) 189 (54)

Grade Mean

(SD)

4.76 (2.36) 4.96 (2.12) t = - 1.368

Dropout rates

48.9 31.2

= 14.648,

df = 1

Pass exam % 23.6 32.7

= 8.256,

df = 2

p < 0.001,

< 0.01

To analyze the influence in traditional students of

classmates following PBL, the first column of Table

1 and the first column of Table 2 should be

considered. While there were no differences in the

grade nor in the percentage of members who passed

the exam, the dropout rate decreased (χ

= 4.925, df

= 1, p < 0.05). The project-based method influenced

the traditional group, at least in the aspect of

attending the exam (Keogh-Brown et al., 2007).

Meanwhile, mean grades obtained by the traditional

group before and after the introduction of the

project-based method are essentially the same. From

the last two ideas, more people participating with

similar universal results, we can infer a positive

overall success improvement in traditional learning

students. Therefore, these results seem to support the

hypothesis H1c. However, the mean mark remained

flat throughout the four courses and decreases the

last year although not in a significant way. This

indicates that the hypothesis H1c could be only

partially sustained.

Participants revealed to have spend a mean (SD)

of 35 (11.6) hours of individual work developing the

project, almost double the estimation (18 h). This

reflects a negative aspect of PBL, a workload

increase for both learners and instructors (Martínez

& Duffing, 2007; Van den Bergh, et al., 2006).

However, there are two interpretations of the

estimated time. The PBL project viewpoint uses the

task as a way to learn (constructing internal

structures by discussing and understanding concepts,

and so on). The software perspective assumes that an

engineer will apply knowledge previously acquired

to solve problems. The time scheduled corresponds

to the second interpretation, whereas the time

declared could include aspects related to the first

aspect. These individual time declarations have not

helped to identify the free-riders presence (Van den

Bergh, et al., 2006). The coincidence in the spent

time in all group members is probably due to the

teamwork scheme. Obviously, all group members

used to meet to fulfill their tasks collectively.

Therefore, we have no idea of the level of

contribution of each particular member from this

data. Instructor workload has increased compared to

the traditional method, although we did not

systematically measure this item. The LMS has been

revealed to be a very useful tool that significantly

mitigates the work related to document, schedule,

and communication management. In addition,

students need quick feedback, especially in the first

steps. The group tutorship and task feedback and

assessment also increase the instructor workload.

We have also identified other benefits of PBL that

were not measured, including reflective thinking

(more critical contributions, noticeable interest

towards the subject topics, improved quality of

questions, etc.), development of work skills

(developing a full creative product design, fulfilling

a set of rules and deadlines, and so on), and social

skills (collaborating with the rest of the group

members, unbroken teams, and so forth.).

5.2 Psychometric Quality of the

Research Instrument

To examine the psychometric quality of the

instrument section focusing on the identification of

types of an LMS usage, a two-step validation

procedure was adopted. The sample (N = 116) was

divided into two sub-sample to evaluate the

construct validity. We have used SPSS version 18 to

conduct an exploratory factor analysis on the data of

the first sub-sample (n = 56), using Maximum

Likelihood estimation with oblique rotation. The

Kaiser-Meyer-Olkin (KMO) measure of sampling

adequacy was 0.87, exceeding the suggested

threshold for factor analysis of 0.6 (Manly, 2004).

The Bartlett’s test of sphericity was – as required –

significant at 0.001 level. The number of factors was

determined by a parallel analysis (O’Conner, 2000)

and an examination of the scree-plot. On the basis of

a first EFA, a two-factor solution was found, but two

items (student tracking module and the agenda) were

deleted due to communality values exceeding the

threshold. A second EFA was performed on the 8

remaining items. A two-factor was performed on the

nine remaining items. A two-factor solution

emerged, accounting for 61.2% of the common

variance among the items, with eigenvalues of 4.06

and 1.38. As illustrated in Table 3 and marked in

italic and bold, two substantially different constructs

can be distinguished and are in line with the findings

of Hamuy and Galaz (2010). Releasing

announcements, publishing document, uploading

exercise and receiving student works can be

considered as indicators of an informational phase in

LMS usage. Learning path, chat, forum, assessment

modules and social support can be marked as

indicators of the communicational phase in LMS

usage.

CSEDU2013-5thInternationalConferenceonComputerSupportedEducation

Table 3: Exploratory factor analysis of the dependent

variables.

Factor

Informational

use

Communicational

use

Releasing

announcements

0.952

-0.0051

Publishing document

0.725

-0.022

Uploading exercises

0.575

0.176

Receiving student

works

0.480

0.235

Learning path -0.075

0.802

Chat -0.122

0.720

Forum 0.185

0.628

Assessment modules 0.136

0.572

Social support 0.085

0.526

Next, AMOS (an add-on module for SPSS) was used

to perform a confirmatory factor analysis (CFA) on

the data of the second sub-sample (n = 60) and

building on the two-factor structure resulting from

EFA. The following indices were calculated, taking

into account criteria for the evaluation of goodness-

of-fit indices (Byrne, 2009): Chi-square/degrees of

freedom is less than 3 (2.32), the root mean square

error of approximation is higher than 0.05, but lower

than 0.08, reflecting a reasonable fit. The

comparative fit index (0.96), the normed fit index

(0.94), and the Tucker-Lewis index (0.96) reflect

good fit values since they are close to 0.95. To

conclude, on the base of the EFA and CFA, we can

report that the instrument to determine LMS use

reflects good construct validity. Construct validity

was evaluated for the other variable measured with

the instrument. Exploratory factor analysis (n = 56)

using Maximum Likelihood estimation with oblique

rotation was performed. The Kaiser-Meyer-Olkin

(KMO) measure of sampling adequacy is 0.87,

exceeding the suggested threshold for factor analysis

of 0.6 (Manly, 2004). The Bartlett’s test of

sphericity was – as required – significant at 0.001

level. The number of resulting factors is in line with

specific variables that were intended to be measured.

All values are close to 0.85, exceeding the threshold

value (Marcoulides & Raykov, 2011). Besides,

correlations between all variables are listed. A

correlation matrix approach was used; most values

are low among the different constructs. All

mentioned values suggest adequate validity of

measurements.

5.3 Analysis of Research Model

As described earlier, the hypothetical relationships

between the variables were tested on the base of

structural equation modeling, using AMOS. The

following fit indices were obtained. Chi-

square/degree of freedom is slightly higher than 3

(3.05), the root mean square error of approximation

is close to 0.05, suggesting a good fit. The

comparative fit index (0.96), the normed fit index

(0.92), and the Tucker-Lewis index (0.89) have

value close to 0.9 or approach the benchmark of

0.95. All common goodness-of-fit indexes exceeded

or approached their respective common acceptance

levels, suggesting that the research model exhibited

an acceptable fit with the data. Properties of the

causal paths, including standardized path

coefficients and p-values are shown in Figure 2.

Figure 2: The result of research model testing.

As to the assumption that informational use can be

considered as a precursor for communicational use

(H2), this hypothesis was sustained (β = 0.32, p <

0.001). The traditional TAM elements appeared in

four hypotheses. Perception of utility has a positive

significant effect on informational use (H3a, β =

0.41, p < 0.001). Perception of user interface in a

significant and positive way informational use (H3b,

β = 0.35, p < 0.001) and perception of utility (H3c, β

= 0.28, p < 0.001). Subjective criterion is found to

be a significant factor in determining perception of

utility (H3d, β = 0.25, p < 0.001). In line with other

TAM studies, all hypotheses constituting the TAM-

framework (H3a, H3b, H3c and H3d) are confirmed.

The findings indicate that personal innovativeness

toward IT has a direct positive effect on perception

of utility (H4b, β = 0.18, p < 0.01) and on perception

of user interface (H4c, β = 0.31, p < 0.001). The

effect on communicational use is significant but

rather weak (H4a, β = 0.08, p < 0.01). Hypotheses

H5a and H5b postulated the impact of internal ICT

support on informational use and subjective

criterion. The analysis results show that internal ICT

support has a positive significant effect on

informational use (H5a, β = 0.12, p < 0.05) and a

significant effect on subjective criterion (H5b, β =

0.30, p < 0.001). The whole model is able to explain

52% of the variance in formational use and 31% of

the variance in communicational use.

In summary, the study contributes to the

literature in a number of ways. Firstly, the use of

AProject-basedCreativeProductDesignCourseusingLearningManagementSystem

LMS by college students has been further explored

and refined. Secondly, the study focused on the

acceptance of the LMS by college students. Further,

the operationalisation of an LMS use into

informational use and communicational use

appeared to be valid. The research model is able to

explain 52% of the variance in informational use and

31% of the variance in communicational use. As

hypothesized, informational use seems to be a

precursor of communicational use. Meanwhile, we

could successfully generate on perception of utility,

user interface and subjective criterion as predictors

from the original TAM-framework. Both perception

of utility and perception of user interface were found

to have a strong effect on informational use. This

means that in order for a college student to use his

LMS in informational way, the utility and user

interface of the LMS will be both taken into

consideration. However, since we found a

significant effect of perception of user interface and

subjective criterion on perception of utility, we can

additionally postulate that the user interface of the

LMS should be a critical initial variable, followed

next by learners’ perception of the system’s

performance.

Another finding is the direct effect from internal ICT

support on informational use and on subjective

criterion. This result implies that supporting learners

at the school level will not directly influence

personal use, but especially impact the opinion of

important others. More important, as also indicated

by Tondeur, van Keer, et al. (2008), the impact of

internal ICT support suggests the school level

variables are important to understand technology

acceptation. The adoption of the variable internal

ICT support makes the TAM model congruent with

the real – school – world setting and conditions as

requested by Sun and Zhang (2006) and Ong et al.

(2004). Also important is the positive effect of

personal innovativeness on perception of user

interface. This reveals that innovative learners are

more easily convinced about the user interface of the

LMS. On the other hand, the impact of

innovativeness on utility was low, meaning that

being innovative does not automatically result in a

positive belief about a system’s performance. This is

also confirmed by the impact of personal

innovativeness toward IT on communicational use.

Being innovative is clearly not enough to start using

an LMS for communicational use. Based on the

importance of the participant’s perception of the user

interface of their LMS and the availability of

support, school manager or LMS coordinators can

consider the following practical recommendations:

(i) Introduction sessions can be considered and

manuals provided. If applicable, a proper translation

of the LMS to the native language of the learner and

clarification on specific design characteristics should

be foreseen. (ii) Some learners are not familiar with

functionalities like the social support or the learning

path module. Best practices, adaptive guides and

easy access to support will definitely be valuable for

the learner and might be that extra little thing to get

them inspired.

6 CONCLUSIONS

AND LIMITATIONS

The use of LMS with PBL approach has been

suggested for creative product design learning as a

more effective way for students to obtain the

essential knowledge and skills. On the other hand

the development of projects corresponds with the

main activity of a graduate on Mechanical

Engineering and Information Systems. This study

presents an approach that integrates both

perspectives of a project as a useful creative product

design learning method that tries to overcome

several problems of PBL applications. Our approach

focuses on the development of projects where

students, organized in groups, design and build real

product. Certain scaffolding is offered to reduce

both the project complexity and the uncertainly

inherent in the beginning of the tasks, and also to

motivate learners. Participants propose the project

topics and the imposition of some constraints in the

first task achieves the complexity balance control.

The communication with end-users is emulated

throughout role-playing between pairs of student

groups. The computer is essential tool to put this

method into practice, from the point of view both of

the creative product design and task management.

An LMS is a powerful solution in order to minimize

the necessary effort to organize the information

shown to the learners, group management,

deliverable collection and communication with and

among students. There are not many works about

PBL effectiveness for creative product design

learning. We have explored the results of two

academic years using the proposed project-based

learning approach. This quasi-experimental study

shows that on the one hand, learners that follow this

method obtain better results than members that

follow a traditional learning method. And on the

other hand, the introduction of such an approach in a

student subgroup positively influences the whole

group.

Furthermore, the purpose of this study was

twofold: (i) developing a better understanding of

college student acceptation of an LMS and (ii)

investigating the way this group of students actually

uses an LMS in their learning setting. Though the

CSEDU2013-5thInternationalConferenceonComputerSupportedEducation

result, discussed above have clearly helped to attain

our research aims, a number of limitations are to be

considered. Firstly, instead of reported use of an

LMS, we expect that using log files could lead to

more accurate LMS related data. However this was

not feasible practically in the current study, given

the number of respondents and the difficulties in

getting access to log files. Secondly, our study

validates the categorization of LMS-interactions as

defined by Hamuy and Galaz (2010). However,

additional LMS functionalities, such student

tracking module and the agenda had to be removed

during the factor analysis process. Future research

should continue to focus on the refining of LMS

usage categories. Thirdly, we were able to explain

52% of the variance in informational use, but only

31% of the variance in communicational use.

Further research should focus on identifying

additional variables to explain the adoption and

implementation of communicational use. The latter

could be for instance linked to beliefs of instructors

about the types of learning strategies that are linked

to the adoption of these LMS functionalities.

ACKNOWLEDGEMENTS

This study is supported in part by the National

Science Council in Taiwan for the financial support

and encouragement under Grant No. NSC 101-2511-

S-132-001-MY2, NSC 101-2631-S-003-010-CC3,

and NSC 100-2511-S-132-002-MY2.

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CSEDU2013-5thInternationalConferenceonComputerSupportedEducation