Session S4F
Using Podcasting to Enhance Learning Experience: A Case Study on Subscription Behavior Simon G. M. Koo1, Sze Wan Kwong2 Abstract - Beginning on the fall of 2005, the Information Technology at Purdue (ITaP) unit of Purdue University has started BoilerCast, a free podcasting service that uses current digital audio delivery technology to deliver classroom audio recordings to the students at their request. Students who subscribe to the service will be able to review lecture material for homework assignments and exam reviews. In this paper, we will first review the background and the technology requirement for podcasting, and then study the feasibility of podcasting from a students’ perspective. Students were surveyed concerning their podcasting subscription behavior, and a modified Theory of Planned Behavior (TPB) model was used as the framework for analyzing such behavior. This model incorporates the original TPB with the Technology Acceptance Model and perceived service quality as a tool to identify important features that students consider important for podcasting to be successful. The results of this study will provide guidelines for future podcasting implementation, and better utilization of the technology in education.
even professional print media are now jumping on this bandwagon to offer regular news, sports, entertainment and cultural programs via podcast feeds [2]. Beginning on the fall of 2005, the Information Technology at Purdue (ITaP) unit of Purdue University, West Lafayette campus, has started Boilercast, a free podcasting service that uses current digital audio delivery technology to deliver classroom audio recordings to the students at their request. Students who subscribe to the service will be able to review lecture material for homework assignments and exam reviews. Figure 1 shows a snapshot of the Boilercast access webpage:
Index Terms – podcasting, distance learning, theory of planned behavior. INTRODUCTION Nowadays, with the increase in popularity of portable mp3 players, and nearly every mobile phone includes an mp3 player that allows the phone user to listen to audio data while on the move, podcasting becomes a popular mean of distributing audio or video contents to a large group of audiences via the Internet. These contents are usually coded in mp3 format, and are either stored on or streamed dynamically to the mobile device. The term “podcasting” combines the words iPod (an mp3 player manufactured by Apple) and broadcasting, which gives name to such novel publishing method. Podcasting distributes audio or video files, such as radio programs or music videos, over the internet using either RSS or Atom syndication [1] for listening on mobile devices and personal computers. Podcasting enables independent producers to create self-published, syndicated “radio shows” and distribute them via the Internet. Listeners may subscribe to feeds using compatible podcasting clients, and their devices will periodically check for and download new content automatically. More and more broadcasting corporations and 1 2
FIGURE 1 SNAPSHOT OF THE BOILERCAST ACCESS WEBPAGE
BoilerCast provides three kinds of services: downloading, streaming, or podcasting. For downloading, users can browse to the course access web page and download the MP3 file of a particular day’s lecture. Faculty members voluntarily participate in the Boilercast project, and currently, over 60 different classes have used Boilercast to podcast their lectures. These lectures are recorded and then post-processed by ITaP and reformatted for podcasting. Students can save the materials to their devices and listen as needed. They are also allowed to stream the material on-demand to their desktop using Windows Media Player or Real Player, so no files will be stored on their computer. The material can be accessed from most PCs, laptops, and PocketPCs. Finally, for
Simon G. M. Koo, Department of Mathematics and Computer Science, University of San Diego, CA 92110.
[email protected] Sze Wan Kwong, Department of Consumer Sciences and Retailing, Purdue University, West Lafayette, IN 47907.
[email protected]
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Session S4F podcasting, the materials can be obtained via automated retrieval using a standard podcasting program such as Apple iTunes, iPodder, jPodder, and other podcast players available on the market. Users can download individual podcast episodes or subscribe to podcasts so the materials are automatically downloaded to the users’ podcasting client when available. It should be noticed that podcasting are different from streaming. Streaming content is delivered in real time over the Internet to one’s streaming media player and no permanent copy of the material is stored on one’s system. On the other hand, podcast episodes are downloaded and stored on one’s computer, and users can transfer them to an iPod or other mp3 compatible personal listening device. The novelty of Boilercast on enhancing learning experience is that it provides a medium for students who want to review a lecture, or those who have missed a lecture, a platform to listen to the materials (again) on demand. However, even though Boilercast is a free service and is available to all students, it is still very helpful to understand from the perspective of students (the target beneficiary) what features are considered to be important for them to subscribe to the service, and how these features are going to enhance their learning experiences. This will improve the subscription rate of the service and more students will be benefited from the service. It is particularly important for service administrators who want to improve the current service, and for other schools who may want to provide this service to their students. In this paper, we investigate the attitudes and behavioral intention of students on the subscription of Boilercast service. We are primarily interested in what are the influences that affect the intention of students’ Boilercast subscription behavior. The findings of the study will allow us to better understand what students want from Boilercast, which in turn attract more subscribers. THEORETICAL FRAMEWORK Our guiding premise is that subscription to Boilercast is a rational and thoughtful behavior rather than being capricious or primarily under the control of unconscious motives. The Theory of Planned Behavior (TPB) [3] provides a suitable framework for conceptualizing such behavior. According to this perspective, students’ behavioral intention, which is to subscribe to Boilercast in this study, can be modeled as the weighted sum of their Attitudes towards the behavior, their Subjective Norm, and their Perceived Behavioral Control. Figure 2 shows the aforementioned relations. Attitude towards a behavior is defined as “a person’s general feeling of favorableness for that behavior” [4]. A person’s attitude towards a behavior is determined by a set of salient beliefs – a small number of beliefs that a person can attend to at any given moment – one holds about performing the behavior. To predict attitude (A) from beliefs, Ajzen and Fishbein modeled attitude as a function of the products of one’s salient belief (b) that performing the behavior will lead to certain outcome, and an evaluation of the outcomes (e)
Attitude towards behavior
Intention
Subjective Norm
Perceived Behavioral Control
FIGURE 2 MODEL FOR THE THEORY OF PLANNED BEHAVIOR
corresponding to that belief. Mathematically, we can defined attitude as: A = ∑ bi ei i
Subjective norm of a person is “the perception that most people who are important to him/her think he/she should or should not perform the behavior in question”. As [4] implied, in forming a subjective norm, an individual takes into account the normative expectations of other sources that are important to him/her. Like attitude, subjective norm (SN) can be modeled as a function of the products of one’s normative belief (NB) and his/her motivation to comply (MC), which can be expressed mathematically as: SN = ∑ NB j MC j j
Perceived behavioral control is “people’s perception of the ease or difficulty of performing the behavior of interest” [5]. The Theory of Reasoned action assumes that one can have total control of his or her behavior, but if behavior is not under complete volitional control, the performers need to have the requisite resources and opportunities in order to perform the behavior. The perception of whether they have the resources will affect their intention to perform the behavior, as well as the successful performance of the behavior. Perceived behavioral control (PBC) can be modeled as a function of control beliefs (CB), which is the perception of the presence or absence of requisite resources and opportunities needed to carry out the behavior, and perceived facilitation (PF), which is one’s assessment of the importance of those resources to the achievement of outcomes [6]. PBC can be mathematically defined as: PBC = ∑ CBk PFk k
We also include a new construct in this study that has not been considered before in TPB on intangible goods such as podcasting service, namely, the perceived quality of service. Service quality has been described as a form of attitude, related but not equivalent to satisfaction, which results from the comparison of expectations with performance [7]-[8]. Service quality is founded on a comparison between what the customer feels should be offered and what is provided. Service quality can be assessed by measuring customer’s expectations and perceptions of performance level for a range of service attributes. Service quality is a measure of how well
1-4244-0257-3/06/$20.00 © 2006 IEEE October 28 – 31, 2006, San Diego, CA 36th ASEE/IEEE Frontiers in Education Conference S4F-4
Session S4F the service level delivered matched customer expectations, and delivering quality service means conforming to customer expectations on a consistent basis. For users’ attitude towards adoption of information technology, the Technology Acceptance Model (TAM) [9], which is derived from the Theory of Planned Behavior, provided two major constructs for consideration, namely perceived ease of use and perceived usefulness. These two construct have been considered immensely in TAM. According to [9], “people tend to use or not use an application to the extent they believe it will help them perform their job better,” and “the degree to which a person believes that using a particular system would enhance his or her job performance.” This work also suggested some important measures to evaluation the perceived ease of use and we will use them in our study. Once again, TPB and TAM, both of which have strong behavioral elements, assume that when someone forms an intention to act, that they will be free to act without limitation. However, in the real world there will be many constraints, such as limited ability, time constraints, environmental or organizational limits, or unconscious habits which will limit the freedom to act [10]. METHODOLOGY AND SURVEY RESULTS Data was collected from students at Purdue University through survey. The students were asked to fill out a survey anonymously and on a voluntary basis. A total of 323 students were surveyed over a three-week period, and a total of 217 completed samples were collected, with a response rate of 67.18% being observed. All incomplete questionnaires were not recorded, and only the information from completed questionnaires was used in the analysis. This sample size concurs with the recommendation by [11], which suggested a minimum sample size of 200 to guarantee robust structural equation modeling. The survey instrument used in this study was adopted from previous research that showed evidence of the reliability and validity of each measurement. There is a total of six items for measuring perceived usefulness (PU), three for measuring perceived ease of use (EoU), four for measuring perceived quality of service (QoS). The reliability for perceived usefulness is 0.92 and the measures were adopted from [12]. The reliability for perceived ease of use is 0.86, and the measures were adopted from [9]. The reliability for perceived quality of service is 0.83, and the measure was adopted from [8]. The measure for attitude (AT) was adopted from [13], which has four items, and a reliability of 0.85. For subjective norms (SN), there are six items, comprising three for normative belief and three for the corresponding motivation to comply. These items were adopted from [12], with reliability 0.95. The measure for perceived behavioral control (PBC) was adopted from [14] which has six items, three for control belief and three for the corresponding perceived facilitation, and the reliability was 0.93. Finally, the measure for behavioral intention (INT) was adopted from [14], and it has four items,
with reliability 0.96. A complete list of survey questions is shown in Table II at the end of the paper. The scales for salient belief, normative belief, and control belief are from -3 to +3, while the rest of the measures have a scale from 1 to 7. The reliability of the survey instruments used in this study will be analyzed using Cronbach’s α test after the data is collected, and the result will be presented in Table I. As the table indicates, the reliability coefficients are all higher than the acceptable level of 0.7 [17], thus confirming the internal consistency and reliability of the scales. TABLE I RELIABILITY OF THE MEASUREMENTS Construct Number of Items Attitude (AT) 4 Perceived Usefulness (PU) 6 Perceived Ease of Use (EoU) 3 Perceived Quality of Service (QoS) 4 Subjective Norm (SN) 6 Perceived Behavior Control (PBC) 6 Behavioral Intention (INT) 4
Cronbach’s α 0.866 0.713 0.737 0.709 0.912 0.712 0.926
The model used for analyzing the survey questions is the structural equation model (SEM). SEM is an extension of the general linear model (GLM) that enables a researcher to test a set of regression equations simultaneously. SEM software can test traditional models, but it also permits examination of more complex relationships and models, such as confirmatory factor analysis (CFA), which is used in this study, and time series analyses [15]. A mixture of fit-indices was employed to assess the overall fit of the measurement models. The ratio of chisquare to degrees of freedom (χ2/df) will be computed, with ratios of less than 3.0 indicating a good fit [16]. The CFA model was analyzed using AMOS, a package of SPSS, and the result is shown in Figure 3. This model adequately reflects a good fit to the data, with χ2/df = 2.193, GFI = 0.907, AGFI = 0.861, IFI = 0.927, TLI = 0.902, CFI = 0.925, and RMSEA = 0.074. (For details about the fitness indices, please refer to [15].) All the items loaded significantly on the construct it was supposed to measure with p < 0.05. All but two of the path coefficients (perceived ease of use → attitude and perceived behavioral control → intention) are estimated with high significant level. The implications of the results will be discussed in the next section. RESULTS INTERPRETATION AND DISCUSSIONS The majority of the results obtained from CFA on the model concurred with the findings in [12] and [18]. In [18], the author studied the subscription behavior of digital music service, a service that sells legitimate songs to consumers in mp3 format. Although Boilercast is a free of charge, the nature of the Boilercast service has significant similarities with digital music service: both services required a subscription and provide digitized audio content to the users for them to play on portable mp3 player or their personal/laptop computers, and both services require the use similar software and technique to operate.
1-4244-0257-3/06/$20.00 © 2006 IEEE October 28 – 31, 2006, San Diego, CA 36th ASEE/IEEE Frontiers in Education Conference S4F-5
Session S4F Perceived ease of use
0.
10
2
0.
0. 5
4 0*
Perceived usefulness
0.271**
54
2*
Attitude towards behavior Perceived Quality of Service
0.613*
0.72 6*
5 0. * 22
Subjective Norm
0.
28
9*
0.371*
0 .0 Perceived Behavioral Control
Intention
73
* p
