Using RSS to Support Mobile Learning Based on Media Richness Theory1-s2.0-S0360131510000758-Main

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Using RSS to support mobile learning based on media richness theory

Yu-Feng Lan*, Yang-Siang Sie

Department of Information Management, National Formosa University, 64, Wunhua Road, Huwei Township, Yunlin County 632, Taiwan

a r t i c l e i n f o

Article history:Received 18 September 2009

Received in revised form

4 March 2010

Accepted 5 March 2010

Keywords:

RSS

Email

SMS

Mobile learning

Media richness theory

a b s t r a c t

With the rapid development of mobile technologies, mobile learning has become a new trend in

education. A better understanding of how to effectively use communication technologies to improve

mobile learning is important. The purpose of this paper is to evaluate the media richness of variousmessage delivery methods in the proposed m-learning environment based on media richness theory.

Regarding the implications of the media richness theory, this study has identified four factors to evaluate

a content in respect to the media richness among SMS, Email, and RSS: timeliness, richness, accuracy and

adaptability. By the repeated-measures one-way ANOVA analysis, the results show that: (1) SMS has

better performance than Email and RSS on content timeliness; thus SMS may be appropriate for

immediate information delivery such as notifying or reminding of some time-sensitive matters; (2) Email

has better performance than SMS and RSS on content richness and so may be applied in exhaustive

information delivery; (3) RSS has better performance than SMS and Email on content accuracy and

adaptability; thus RSS is more appropriate for supporting various front-end mobile devices to access and

present the content in a mobile learning environment. According to the results, this study suggests

developer and designer of an m-learning environment could adopt suitable information delivery

medium to support the corresponding learning activities in a mobile learning environment; moreover,

current general e-learning systems, particularly those intending to provide a mobile learning environ-

ment, can take advantage of RSS techniques to support mobile access and achieve the goal of mobile

learning anytime and anywhere.

2010 Elsevier Ltd. All rights reserved.

1. Introduction

With the rapid development of mobile technologies, mobile devices are becoming smaller with stronger functionalities and more

popular. The portability and immediate communication properties of mobile devices influence the learning activities in peer interaction,

resource acquirement, and content delivery. Chen, Chang, and Wang (2008a) pointed out students with smart phones and PDAs logged into

the academic reminder system twice as much as those with desktop or laptops. Using mobile devices to support learning activities offers

several benefits according to the findings of prior research (BenMoussa, 2003; Evangelos, Elissavet, & Anastasios, 2008; Huang, Huang, &

Hsieh, 2008; Huang, Jeng, & Huang, 2009; Huseyin, Nadire, & Erinc, 2009). These include the ability to: (1) improve communication and

collaborative interaction, (2) provide more learning opportunities for geographically dispersed persons and groups, (3) encourage active

learning, (4) enhance learners feedback process, (5) emphasize time on task, and (6) acquire content quickly.

In previous research, many studies have been conducted on the influential factors related to mobile learning performance such as usingtechnology, pedagogy and learning strategy (Fernandez, Simo, & Sallan, 2009; Huang, Huang, & Hsieh, 2008; Huang, Jeng, & Huang, 2009;

Wurst, Smarkola, & Gaffney, 2008). Apart from these factors, several studies found media richness can be regarded as an external variable on

the use intention toward on-line learning (Agarwal & Prasad,1999; Al-Gahtani & King,1999; Davis, Bagozzi, & Warshaw, 1989; Huang, 2005;

Liu, Liao, & Pratt, 2009; Seyal, Rahman, & Rahim, 2002). Also, Sun and Cheng (2007) suggest the delivery of the media selection should be

a critical issue of providing potential benefits and supporting various reader devices for on-line learning.

M-learning (Mobile learning) is a kind of learning model allowing learners to obtain learning materials anytime and anywhere using

mobile communication, mobile devices and the Internet. In the past, the ducting of the information delivery medium, particularly in the

* Corresponding author. Tel.: 886 5 6315745; fax: 886 5 6364127.

E-mail address: [email protected] (Y.-F. Lan).

Contents lists available at ScienceDirect

Computers & Education

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p e d u

0360-1315/$ e see front matter 2010 Elsevier Ltd. All rights reserved.

doi:10.1016/j.compedu.2010.03.005

Computers & Education 55 (2010) 723e732
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m-learning environment, almost involved Email or SMS (i.e., short message services) to inform learners of the latest learning activity news

such as new material, new proclamation or new discussion topic ( Chen, Chang, & Wang 2008b; Huang et al., 2007; Markett, Sanchez,

Weber, & Tangney, 2006; Meurant, 2007). Among them, Markett et al. (2006) indicated SMS is a low-threshold application used widely

by learners to quickly send concise, text-based messages at anytime; however, it is not particularly user-friendly because it has a content

limitation in terms of the maximum allowed characters. On the other hand, many studies showedEmail is a useful channel for both teaching

and learning (Huang, 2001; Malaga, 2002). However, the content sent by Email does not automatically notify the receiver to acquire the

latest news. Most importantly, Huang, Huang, et al. (2008), Huang, Kuo, et al. (2008) pointed out the curriculum developer and designer

should be aware of how to use lower bandwidth to send learning content in a mobile learning environment. Additionally, the other factors

related to content presentation, media richness, and transmission efficiency would also affect the learning process and the acceptability or

interest of the learner in the learning activity. Therefore, a better understanding of how to adopt a suitable information delivery medium to

solve the above issues is important.

As mentioned above, the common purpose of these studies was to adopt information delivery mechanisms to enhance learning

performance. With this in mind, the objective of this study is to develop an m-learning environment, which originally is a web-based

learning system, and to evaluate media richness of various message delivery methods in the proposed m-learning environment. In the m-

learning environment, message delivery methods include SMS, Email, and RSS, to improve learning activities. Here, this study would try to

answer the following research question:

In the proposed m-learning environment, which medium is more suitable to improve learning activities among SMS, Email, and RSS

based on media richness theory?

The rest of the paper is organized as follows: Section 2 gives reviews of the theoretical foundations and related work. Then, Section 3

describes the system implementation and the learning process framework of this study. Section 4 presents the research methodology

used in this study, including research instrument, experiment, data analysis and results. Finally, discussion and concluding remarks are

made in Section 5.

2. Theoretical foundations underpinning this research

Some theoretical perspectives and related work that indicate why this study would be beneficial and could improve learning activities

are briefly described with regard to learning theories, m-learning, RSS, media richness theory.

2.1. Learning theories

The efficiency of a learning environment is determined by the adapted learning strategy used in the environment (Khalifa & Lam, 2002).

Although current learning environment has many tools to assist learners in various learning strategies, it still lacks an appropriate pedagogy

and learning strategy to improve learning performance in an m-learning environment ( Chen, Kao, & Sheu, 2003; Motiwalla, 2007; Tsai,

2008).

The conventional teaching strategy learning process generally uses objectivism (instructor-centric). In objectivism, learners passively

receive knowledge from an instructor. Instructor should prepare learning materials in advance and learners study in class at the same time.An alternative teaching strategy is constructivism (learner-centric), allowing learners to control the pace of their learning and construct

personal knowledge. The constructivism theory asserts knowledge is actively constructed by each individual, and social interactions with

others are also influential in the constructive process (Brooks & Brooks, 1993; Tsai, 2001). Recently, constructivism has become an important

paradigm for guiding research and practice in education (Bopry, 1999; Fosnot, 1996; Terwel, 1999; Wen & Tsai, 2003).

Increasingly, more portable devices are integrated into the constructivist learning environment. Constructivist learning activities were

needed to encourage effective use of portable devices in an m-learning environment (Wurst et al., 2008). Further, Tsai (2008) indicated

several educators have proposed developing a constructivist learning environments for students.

It is notable the constructivism theory stresses the idea an instructor needs to carefully consider learners prior knowledge as well as

individual differences, and properly encourage learners as well as students-to-teacher interactions ( Tsai, 2008). To avoid the prior defect of

only adopting constructivism in teaching strategy, Johannes (2006) reported a combined learning process composed of objectivism and

constructivism learning theories. According to Johanness teaching strategy, in the first part the instructor gives learners the foundational

knowledge to support the upcoming learning activities based on objectivism learning theory. After having enough basic prior knowledge,

then learners could construct their advanced knowledge according to constructivism. Through these two steps of the learning process,

learners could avoid wasting time trying to understand the foundational knowledge and could efficiently construct their knowledge.

According to this view, this study adopted Johanness learning process to support learning strategies in the proposed m-learning

environment.

2.2. M-learning

Currently, mobile devices have become more and more popular. Many mobile applications also have been developed to aid teaching and

learning strategies (Chen et al., 2008a). A learning environment is called m-learning if learners could use mobile devices to obtain learning

materials and to support their learning activities anytime and anywhere. Wang, Ci, Zhan, and Xu (2007) described a mobile learning

environment enabling people to learn at anytime and any place. Additionally, Chen et al. (2008a) pointed out an m-learning environment

allows the learners to learn with a PDA, Smartphone, WebPad, Tablet PC or laptop, in indoor, outdoor, individual, and group situations. The

object of m-learning is to provide an educational environment in which students can learn without any limitation of time, place, or device,

thereby realizing a more creative and learner-centered educational process (Joo & Kim, 2009).

Although the above studies show several significant advantages of m-learning, few researchers have discussed how to integrate feasible

components into a web-based learning environment to cover most learning processes by generating an m-learning environment ( Chen

Y.-F. Lan, Y.-S. Sie / Computers & Education 55 (2010) 723e732724


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et al., 2008a). To this end, this study attempted to develop an m-learning environment integrating the RSS techniques into an existing web-

based learning system to support diverse front-end mobile devices in learning activities.

2.3. RSS (really simple syndication)

RSS is an XML (i.e., extensive markup language) application, originally developed to enable the channels delivery. The main idea behind

RSS is to enable users to be informed when the information on the Internet has changed. Inside of XML, there has an opportunity to include

a description of the methods required to use the data, along with the data itself (Cold, 2006). Further, RSS feeds have great potential to be

used for public-opinion gathering (Glance, Hurst, & Tomokiyo, 2004). Because RSS uses XML to glean relevant information related to user s

needs, RSS may well become the universal method to mine information from the Internet (Cold, 2006). As the concise RSS formats allow

relatively low-bandwidth data gathering, even for several different sources, RSS is becoming a mobile technique for notifying the users of

new content, particularly, in frequently updated web sites, such as blogs and news portals (Prabowo, Thelwall, & Alexandrov, 2007). In

addition, there is another benefit to using RSS for supporting learning activities. Students subscribing to information sources via email will

soon find their email box filled with spam. Other portals contain pop-ups and advertising. In contrast, spam and advertising do not come

through RSS feeds. Students only receive relevant information related to their learning topic.

Currently, three major types of RSS exist: version 0.92, 1.0, and 2.0. This study focuses on version 2.0 because it is the most flexible and

expandable version. The RSS specification defines a container structure. For receiving RSS-based content, the RSS feed could contain one or

more channels for one RSS document. The channels and items are composed of a title, a description, a URL, and a publishing date. Therefore,

users can easily access and classify the received contents and then manage them through different RSS feeds.

2.4. Media richness theory

Media richness theory, originating from information processing theory, was developed by the organizational scientists Daft, Lengel, andTrevino (Daft & Lengel, 1984; Daft, Lengel, & Trevino, 1987). Media richness has been proved as two concepts related to communication

performance and interpersonal relationships (Daft et al., 1987). The first refers to the ability of information to change understanding within

a time interval or provide substantially new consensual understanding and the latter refers to the degree to which a person is perceived as

a real person in mediated communication (Daft & Lengel, 1986). In other words, media richness refers to its capacity to facilitate shared

meaning and understanding (Daft & Lengel, 1984). The richness of a media is based on the following four criteria (Daft et al., 1987).

1. Capacity for immediate feedback: This refers to the speed and quality of common interpretation transmitted through the medium.

2. Capacity to transmit multiple cues: An array of cues, including physical presence, voice inflections, body gestures, words, and numbers,

even graphic symbols, facilitate conveyance of interpretation information.

3. Language variety: It means the level of concept convection. For example, numbers and formulas could provide greater precision; but

natural language conveys a broader set of concepts and ideas.

4. Capacity of the medium to have a personal focus: This refers to either the conveying of emotions and feelings, or the ability of the

medium to be tailored to the specific needs and perspectives of the receiver.

According to the above four characteristics of criteria, the richest communication medium is face-to-face because it can provide

immediate feedback, multiple cues through body language and tone of voice. Additionally, message content is expressed in natural

language. However, the personal text document is the leanest medium because it cannot provide immediate feedback. It only provides text-

messages and tables.

As far as we are aware of the media richness theory, there is relatively little research on supporting learning activity, but well known in

the organizational and MIS (management information system) related literature. Shaw, Chen, Harris, and Huang (2009) investigated the

impacts of hypermedia, multimedia and hypertext to increase information security awareness among the three awareness levels including

perception, comprehension and projection. The above results confirm the existence of positive correlations between the degree of media

richness and the improvement of security awareness levels. Sun and Cheng (2007) applied and tested media richness theory regarding the

effectiveness of multimedia instructional material design, as well as media on a learners performance and satisfaction. Their research shows

the use of rich media in e-learning should fit the characteristics of the course unit under consideration. In addition to studying the fitness

between media and instructional content, media richness theory has been widely applied in other issues such as the effects of media

richness on task satisfaction, decision quality, and decision time (Kahai & Copper, 2003; Mennecke, Valacich, & Wheeler, 2000; Purdy & Nye,

2000; Rice,1992), organization system design (Daft & Lengel, 1984, 1986), conflict management, marketing (Klein, 2003), and the predictionand explanation of the media selection and usage in organizations (Allen & Rodger, 1997; Daft et al., 1987; Markus, 1994; Whitfield, Lamont,

& Sambamurthy, 1996). In sum, the media richness theory has been applied in a wide variety of issues with success in both theoretical

analyses and empirical studies.

2.5. Research model

From the above description on the media richness theory, this study attempted to take advantage of media richness theory to analyze the

capabilities of media richness among SMS, Email, and RSS in the proposed m-learning environment. For answering the research question of

this study, four factors of a media among SMS, Email, and RSS were identified to evaluate delivery performance: content timeliness, content

richness, content accuracy, and content adaptability. Conceptually, these factors correspond to the four criteria in terms of the richness of

a media, above discussed. According to these factors, Table 1 provides the research variables and definitions, as well as their corresponding

strategies of supporting learning activity to verify these variables effect.

Based on the above analyses, this study proposes a research model and four major hypotheses relative to the media selection of

information delivery way in a mobile learning environment as shown in Fig. 1. Four major hypotheses are described as follows.

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H1 : RSS is more appropriate as a delivery medium than Email and SMS in a mobile learning environment regarding content timeliness.

H2 : RSS is more appropriate as a delivery medium than Email and SMS in a mobile learning environment regarding content richness.

H3 : RSS is more appropriate as a delivery medium than Email and SMS in a mobile learning environment regarding content accuracy.

H4 : RSS is more appropriate as a delivery medium than Email and SMS in a mobile learning environment regarding content adaptability.

3. System implementation

Windows Server2003 was selected as the operating system for the proposedm-learning system. Also, IIS 6.0 was used as the Web Server,

SQL Server 2003 was served as the system database, and ASP scripts were selected as the system development language. Originally, the

platform is a web-based learning system specifically for the personal computer, and users could access the site resources through the

relevant browser software, such as Internet Explorer, through the Internet. Aside from the original learning platform, this study focuses on

integrating the RSS function into the original system to achieve an m-learning environment. To rely on the m-learning environment and

mobile learning model of this research, learners could use mobile device technology to surf the curriculum content and to receive their

learning status related to learning activities. Also, the instructor could participate in the m-learning system to guide learners to access

accumulated resources and learning materials.

To assess which medium is more appropriate in the m-learning system, the experiment was designed to let learners to receive

curriculum message through RSS, SMS, and Email. The detail experiment process was described in next section. Additionally, to make each

Table 1

Research variables and definitions regarding the capabilities of media richness.

Research variable Definition Strategies of supporting learning activity to verify the variable effect

Con tent ti mel in ess Degree to wh ic h user thi nk a rec eiv ed

message is time-sensitive or have

immediate feedback

C When the instructor posts a class announcement, learners

could receive this message immediately.

C When peer replies a discussion topic, learners could

receive the replied message automatically.

C The learning platform could regularly provide the reports

and these messages could reflect their learningstatus immediately.

Content richness Degree to which user think a received

message includes various media typesC The class announcement could be presented in text mode.

C The discussion topic could comprise text and picture

to describe a question.

C The instructor and learners could integrate text, picture,

and audio into an instructional material and their

homework, respectively.

Content accuracy Degree to which user think a

message can be explicitly expressed

or easy to be comprehend

C The instructional material can use hypertext,

multimedia, or hypermedia to show the

importance of content.

C The instructor can inform learners of

future teaching plan.

C The report of statistic analysis can fully

comprise various learning status to reflect

learner metacognition.

Con tent adaptabil it y Degree to wh ic h user thi nk a messagecan be adapted to other formats

C The original curriculum material can bepresented in different viewing modes.

C The learners can demonstrate their

homework in different results.

C The list of discussion topic can be chosen

in text or picture mode to show the subject.

Information delivery ways:

1. RSS

2. Email

3. SMS

Capabilities of media richness:

1. Content timeliness

2. Content richness

3. Content accuracy

4. Content adaptability

H1

H2

H4

H3

Fig. 1. Research model.



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learner aware of his or her current learning status, the system will regularly inform learners of the statistics message related to the results of

their participation in learning activities such as accesswebsite, read announcement, read messages, reply message, and read coursework.By

providing the report of peers learning status for learners, it is expected they could be aware of their learning status and be engaged in

learning activities.

When the instructor provided new learning material or students respond, learners could use a mobile RSS reader to receive the

information synchronously. Meanwhile, according to individual preference, learners could organize and manage the received learning

materials by themselves for future reference.

4. Methodology

Beforethe experiment, a computer experience survey is used to assesslearners computerexperience. According to the result, all learners

have a computer at home with an Internet connection. And then, with regard to the frequency of computer use, all learners answers were

made daily. However, 70% of learners did not have experience using RSS. Thus, before the experiment, learners have to study how to use the

RSS reader to correctly receive the RSS messages.

To explore the research issues, this study analyzed which information delivery method is more suitable to support learning activities in

the m-learning environment among RSS, Email and SMS based on media richness theory. In the following, the experiment was designed to

answer the research question.

4.1. Experiment and participants

The purpose of this experiment is to compare RSS, Email and SMS in terms of content timeliness, content richness, content accuracy, and

content adaptability. Through this experiment, the results could evaluate which medium is more appropriate to support learning activities

in an m-learning environment. The participants of this experiment were 52 freshmen attending the Basic Programming Design course atthe Information and Management Department of National Formosa University, Taiwan.

4.2. Procedure

Fig. 2 shows the procedure of the experiment. This experiment was conducted with repeated-measures design. Random sampling was

used to assign students to three groups. Before the experiment, all participants should be familiar with RSS, Email, and SMS through

mobile devices in the proposed m-learning environment. When the learning system had a new message related to learning activities (e.

g., new material, new proclamation, replied message, or new discussion) provided by the instructor or peers during the learning process,

first, all members of each group received the message content including the presentations with RSS, Email and SMS, respectively. The

principle of this experiment design adopts a counterbalance of the order of treatments to avoid the progressive errors. The order of

treatments uses the Latin Square mechanism. That is, the presentation type of the use delivery media differed among the groups. Group

1 received the content with presentation type in the sequence of SMS, Email, and RSS. Group 2 received the content with presentation

type in the sequence of Email, RSS, and SMS. Group 3 received the content with presentation type in the sequence of RSS, SMS, and

Email. Additionally, sufficient time was considered to minimize carryover effects among treatments. Notably, there is no control group inthis experiment. With this in mind, the object of this experiment is to compare SMS, Email, and RSS in terms of media delivery

performance; therefore, all participants had the same treatments except the order of using message delivery way. After the curriculum

finished, all participants had to fill out a questionnaire. The content of the questionnaire was related to the capabilities of media richness

and reported in the Appendix. Each item was evaluated on a five-point Likert scale (one is strongly disagree and five is strongly agree).

Then, a repeated-measures one-way ANOVA analysis was utilized to explain the differences among RSS, Email and SMS in this

experiment.

4.3. Measurements

The independent variable was the media selection of information delivery way, including SMS, Email, and RSS, in the proposed m-

learning environment. The dependent variable of this experiment was related to the capabilities of media richness, including content

timeliness, content richness, content accuracy, and content adaptability. As far as we known, there is no suitable instrument to measure this

construct. Hence, based on media richness theory, this study developed a media richness instrument. This study used four 13-item scales as

measures of the media richness including content timeliness, content richness, content accuracy, and content adaptability based on mediarichness theory. The construct reliability and validity of the survey instrument were evaluated. Cronbach s alpha was calculated for each

scale to ensure internal consistency among the items. The scale reliabilities were reported in Table 2. Factor reliabilities, as represented by

Cronbachs alpha were between 0.86 and 0.92 for each factor and total reliability was 0.753. Analysis of the herein-considered sample

showed a reasonable level of reliability (alpha> 0.70). Factor analysis also confirmed that the construct validity of the scales could be carried

out adequately. Using the principal component method with varimax rotation, construct validity was examined. Table 2 reports the factor

loadings and explains the variance for each of the factors. The factor loadings for all items exceeded 0.79 and indicated that the individual

items also had discriminant validity.

4.4. Data analysis and results

In previous research, quite a few experiments were conducted on the effect of adopting various information delivery ways in m-

learning. It is well known that messages can be delivered by SMS or Email in an m-learning environment. This research aims to use

RSS to deliver messages. Essentially, each media has unique characteristics. To evaluate which information delivery way is more

suitable to support learning activities in an m-learning environment among RSS, Email and SMS based on media richness instrument,



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the experiment of this research treats all participants to receive the messages through RSS, Email, and SMS. After the curriculum

finished, all participants had to write a questionnaire. To test the hypothesis H1eH4 regarding the effects of the media richness and

information delivery way on supporting learning activities, this study conducted four repeated-measures one-way analyses ofvariance. Table 3 presents the relevant descriptive statistics among RSS, Email and SMS regarding content timeliness, content

richness, content accuracy, and content adaptability. Furthermore, an analysis of ANOVA was summarized in Table 4. The results

revealed there exists significant effects of the media richness, regarding content timeliness (F-value 107.273, P0.000), content

richness (F-value 280.682, P0.000), content accuracy (F-value 72.294, P 0.000), and content adaptability (F-value 61.707,

P 0.000), and information delivery way. This implies the use of different information delivery ways has signi ficant effect on the

degree of media richness. Furthermore, regarding media richness, to evaluate which media is more appropriate as a delivery medium

among SMS, Email and RSS in a mobile learning environment, a post hoc multiple comparisons with LSD method analysis was

conducted and the results were summarized in Table 5. According to the result of post hoc comparisons, regarding content timeliness

in receiving the message, SMS had a higher performance than Email and RSS. In terms of content richness, Email had the highest rate

among them. For the rest of scales, RSS had the highest performance among them. As a result, hypotheses H3 and H4 were supported.

That is, RSS is more appropriate as a delivery medium than Email and SMS in a mobile learning environment regarding content

accuracy and content adaptability. However, the results of this experiment does not support hypothesis H1eH2, that is, RSS is not

appropriate as a delivery medium than Email and SMS in a mobile learning environment regarding content timeliness and content

richness.

Computer experience survey

Instructor teaching

Announcing learning

materials or questions

Sending message through RSS Sending message through SMSSending message through

Email

Learner interact with

peers or instructor

Semester finishing?

Questionnaire

Yes

No

Sending message through SMS

Sending message through

Email

Sending message through

Email

Sending message through RSS

Sending message through RSS

Sending message through SMS

Group 3 Group 1 Group 2

Fig. 2. Procedure of the experiment.



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5. Discussion and conclusion

After the experiment, about 70% of learners indicated they usually received the RSS message on the computer and 30% of learners

pointed out they usually received the RSS message on mobile devices. This is roughly consistent with Evans (2008) study in which 20% used

a mobile device and 80% used a computer. However, the learners indicated using a mobile device to receive an RSS message is very

convenient. Some learners are even accustomed to reading news through RSS on their mobile device every day.

According to the results ofTable 5, SMS has higher transmission efficiency regarding content timeliness, but the content presented with

SMSonly has text-based messages.Therefore, SMSmay be appropriate for immediate information delivery such as notifying or reminding of

some time-sensitive matters. In contrast, Email does not provide an automatic notification function and does not support various front-end

mobile devices, but it still has superior content richness. Therefore, Email may be applied in non-time-sensitive information noti fication or

in exhaustive information delivery such as providing learning materials and the reports related to learning status. Last, RSS has the similar

advantages to SMS sending message synchronously and as Email with content richness. Fortunately, RSS differs from SMS in showing

content. RSS can provide rich content presentation including various media types such as text, picture, animation, and audio into one

document (i.e., one RSS feed). In addition, learners generally agreedthey can explicitly understand the RSS-basedmessages and the received

messages can be also presented in different viewing modes to reveal the difference of specifi

c subject. Consequently, learners couldimmediately browse more meaningful RSS-based materials through various mobile devices and participate in learning activities anytime

and anywhere.

The practical implications of the results are each media has self-outstanding characteristics and developer and designer of an m-learning

environment could adopt suitable information delivery medium to support the corresponding learning activities in a mobile learning. In

other words, they could adopt RSS to support various front-end mobile devices to access and present the content because RSS has superior

content accuracy and adaptation in mobile web browsing; moreover, they could adopt SMS to notify the learners of the latest news,

particularly, in frequently updated information. Last, Email may be applied in exhaustive information delivery.

The present study also suggests current e-learning system can integrate mobile devices, wireless network, and RSS techniques to

construct a mobile learning environment. It could not only support learning activities anytime and anywhere, but also improve several

deficiencies in the e-learning system. For example, front-end equipments are still limited in the PC computer, the pleasure of user expe-

riences is insufficient for learners, the e-learning system messages are usually delayed and cannot be classified by learners, and the

instructor-learner interaction is insufficient. In summary, mobile devices, wireless networks, and RSS techniques could greatly support

learning activities and achieve the goal of mobile learning.

Several limitations and futureresearch directions can be drawn from this study. Onelimitation was the data sets. The experimental result

may differ according to different participants characteristics such as prior m-learning experience, information literacy, media selection

preference, and gender. As an example, according to prior researchers ( Anastasios & Grousopoulou, 2009; Tsai, 2008), males use mobile

technologies such as SMS and Email more than females. Therefore, other samples with different characteristics should be considered to

confirm and to assess instruments reliability and validity. Second, instructors teaching style and pedagogy were not measured. However,

Table 2

Scale reliabilities and factor loadings for measures of constructs.

Scale Content timeliness Content richness Content accuracy Content adaptability

Cronbachs alpha0.900

CT Q4 0.896

CT Q2 0.811

CT Q3 0.806

CT Q1 0.796

Cronbachs alpha0.921CR Q2 0.840

CR Q3 0.833

CR Q1 0.818


CAC Q1 0.932

CAC Q2 0.904

CAC Q3 0.881


CAD Q2 0.890

CAD Q3 0.842

CAD Q1 0.800

Note: CT, content timeliness; CR, content richness; CAC, content accuracy; CAD, content adaptability.

Table 3

The descriptive statistics on analysis of media richness among SMS, Email and RSS.

Research variable SMS Email RSS

Mean SD Mean SD Mean SD

Content timeliness 4.60 0.495 3.42 0.667 4.31 0.466

Content richness 2.40 0.495 4.50 0.505 4.10 0.298

Content accuracy 4.02 0.641 3.42 0.499 4.67 0.648

Content adaptability 3.29 0.457 3.5 0.505 4.40 0.495



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these limitations may lead to different degree of content timeliness. For instance, when the instructor adopts different interaction strategies

as teaching pedagogy in learning activities, learners will have different opportunities to interact with their instructor (Arbaugh, 2002; Offir,

Lev, & Bezalel, 2008). This implies the frequency of interaction between instructor and students depends on what medium was used to

connect them; these differences need to be explored further. Third, the proposed m-learning environment was developed and designed by

the authors. Generally, each m-learning environment has different characteristics such as user interface, compatibility, and functionality. To

implement m-learning, Attewell (2005) suggested five broad categories of technology to consider: transport, platform, delivery, media

technologies, and development languages. Those characteristics may be possible not only to affect users learning way, but also to result in

different content presentation style (Huang, Huang, et al., 2008; Huang, Kuo, et al., 2008). Consequently, these limitations may lead to

different degree of content richness and adaptability. Therefore, for future development, other m-learning platforms may be tested to

evaluate the relative issues of this study. How to effectively improve student satisfaction is also an important topic in m-learning. Finally, this

paper also points to a potentially interesting direction in improving m-learning student satisfaction from the information delivery ways

perspective.

Table 4

The ANOVA analysis of media richness among SMS, Email and RSS.

Research variable Source SS df MS F-value

Content timeliness Between subject 27.814 51 0.545 107.273*

Within subject (error) 57.333 104

Effect 38.859 2 19.429

Error 18.474 102 0.181

Total 85.147 155

Content richness Between subject 6.667 51 0.131 280.682*Within subject (error) 152 104

Effect 128.628 2 64.314

Error 23.372 102 0.229

Total 158.667 155

Content accuracy Between subject 26.436 51 0.518 72.294*


Effect 40.654 2 20.327

Error 28.679 102 0.281

Total 95.769 155

Content adaptability Between subject 6.026 51 0.118 61.707*


Effect 36.50 2 18.25

Error 30.167 102 0.296

Total 72.693 155

Table 5

Post hoc multiple comparisons (LSD method).

Dependent variable (I) Media (J) Media Mean difference (IJ) Std. error Sig. 95% Confidence interval Post Hoc analysis

Lower bound Upper bound

Content timeliness SMS Email 1.173* 0.105 0.000 0.962 1.385 SMS> Email

SMS>RSS

RSS> Email

RSS 0.288* 0.063 0.000 0.161 0.416

Email SMS 1.173* 0.105 0.000 1.385 0.962

RSS 0.885* 0.076 0.000 1.037 0.732

RSS SMS 0.288* 0.063 0.000 0.416 0.161

Email 0.885* 0.076 0.000 0.732 1.037

Content richness SMS Email 2.096* 0.117 0.000 2.332 1.861 Email> SMS

RSS> SMS

Email>RSS

RSS 1.692* 0.065 0.000 1.822 1.563

Email SMS 2.096* 0.117 0.000 1.861 2.332

RSS 0.404* 0.092 0.000 0.219 0.589RSS SMS 1.692* 0.065 0.000 1.563 1.822

Email 0.404* 0.092 0.000 0.589 0.219

Content accuracy SMS Email 0.596* 0.107 0.000 0.381 0.813 SMS> Email

RSS> SMS

RSS> Email

RSS 0.654* 0.109 0.000 0.874 0.434

Email SMS 0.596* 0.107 0.000 0.812 0.381

RSS 1.250* 0.095 0.000 1.440 1.060

RSS SMS 0.654* 0.109 0.000 0.434 0.874

Email 1.250* 0.095 0.000 1.060 1.440

Content adaptability SMS Email 0.212* 0.104 0.047 0.420 0.003 Email> SMS

RSS> SMS

RSS> Email

RSS 1.115* 0.098 0.000 1.312 0.919

Email SMS 0.212* 0.104 0.047 0.003 0.420

RSS 0.904* 0.117 0.000 1.139 0.668

RSS SMS 1.115* 0.098 0.000 0.919 1.312

Email 0.904* 0.117 0.000 0.668 1.139

*The mean difference is signifi

cant at the 0.05 level.



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Appendix. Scales and items

The research variables related to the capabilities of media richness. Note: (R) reverse coded.

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Research variable Item Source

Content timeliness 1. When instructor posts a class announcement,

I can receive the message immediately.

2. When peer replies a discussion topic, I can

receive the replied message automatically.3. I can regularly acquire the reports of

learning status from the learning system.

4. Overall, I think that the received messages

are immediate.

Self-development

Content richness 1. I think that the received messages are

only presented in text-based mode. (R)

2. The received message consists of text

and image media types to describe a

learning activity.

3. Overall, I find that the received messages contain

various media types (e.g., text, image, sound, or animation).

Content accuracy 1. I think that the received messages are clear.

2. I can easily understand what I received messages.

3. Overall, I think that the received messages are explicit

and easy to understand.

Content adaptability 1. I think that the received messages can be presented

in different viewing modes to reveal the difference

of specific subject.

2. I think that the received message can be demonstrated

in different results based on same subject.

3. Overall, I think that the received messages can be

adapted to other formats for supporting different presentation.

Note: (R) reverse coded.

http://www.mlearn.org.za/CD/papers/Attewell.pdfhttp://www.mlearn.org.za/CD/papers/Attewell.pdf


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Using RSS to Support Mobile Learning Based on Media Richness Theory1-s2.0-S0360131510000758-Main