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Integrating mobile multimedia into textbooks: 2D barcodes
Computers & Education 59 (2012) 1192–1198
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Integrating mobile multimedia into textbooks: 2D barcodes Celebi Uluyol*, R. Kagan Agca Department of Computer Education and Instructional Technologies, Gazi University, Ankara, Turkey
a r t i c l e i n f o
a b s t r a c t
Article history: Received 19 December 2011 Received in revised form 11 May 2012 Accepted 16 May 2012
The major goal of this study was to empirically compare text-plus-mobile phone learning using an integrated 2D barcode tag in a printed text with three other conditions described in multimedia learning theory. The method examined in the study involved modifications of the instructional material such that: a 2D barcode was used near the text, the learner scanned the tag with the camera on his/her mobile phone and reached the animation and narration on the mobile phone’s screen. Using this method, we created a new approach that reinforces printed textbooks, which had the poorest retention and transfer results. The results suggest that supporting a printed textbook with camera-equipped mobile devices and 2D barcodes linked to supplemental information, may increase the effectiveness of learning. Ó 2012 Elsevier Ltd. All rights reserved.
Keywords: Mobile learning Multimedia learning 2D barcodes
1. Introduction Nick, a freshman at the Department of Computer Education and Instructional Technologies, goes to the library to study for the final exam of the Computer Networks and Communication course. He starts studying the Open Systems Interconnection (OSI) model, which is a part of the course curriculum and he grasps the basic functions of the model. The model defines a networking framework for implementing protocols that include seven layers. Control is passed from one layer to the next, starting at the application layer in one computer station, proceeding to the bottom layer, passing over the channel to the next station and then back up the layers. A screenshot of the OSI model is given in Fig. 1. Nick also studies the basic functions of the seven layers in the model. Let us imagine that he continues to study for the final exam in this way using only his textbook. Tuna, a classmate of Nick, starts to study the same topic for the final exam using his personal computer. He sits in front of a computer screen, and by using the mouse he asks the computer to explain the OSI model. On the screen he sees the basic functions of the model, principles of the model’s layers and the realization of processes during data transition between the layers. At the same time he hears a corresponding narration of the actions involved between the layers in the model. He has also a chance to stop and re-play the animation at anytime. Now let us imagine that Tuna continues to study for the final exam in this way, using the animation on the web page. The learning situations that are exemplified above are only two instances of multimedia learning experiences. Multimedia learning occurs when learners receive information presented in more than one mode (Mayer, 2001). The term multimedia refers to the presentation of instructional material using both words and pictures. The instructional material can be presented in verbal form, including printed or spoken text. The instructional material also can be presented in pictorial form, including static graphics, illustrations, photographs, graphs or dynamic forms such as animation or video. The research on multimedia learning shows that humans learn better from a combination of image and text than they learn from text alone (Mayer, 2001). In his book, Mayer (2001) declared that learning from books that include both text and illustrations and from computer-based environments that include on-screen text, animations and narrations resulted in better retention/transfer and problemsolving performance compared to learning from text-only books. Similarly, Mayer and Anderson (1992) created three different learning environments: text-only, text-plus-picture and animation-plus-narration. After the experimental study, results showed that text-pluspicture and animation-plus-narration conditions had a significant effect on success (Mayer, 2003). Animation is the popular of today’s multimedia learning environments and many media designers seem to be convinced that animations are instructionally more powerful than static pictures (Rasch & Schnotz, 2009). Recent research has demonstrated that it is more unclear
* Corresponding author. Tel.: þ90 505 815 8764. E-mail addresses: [email protected], [email protected] (C. Uluyol), [email protected] (R.K. Agca). 0360-1315/$ – see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.compedu.2012.05.018
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Fig. 1. A screenshot of the OSI model. The OSI model is a layered model and has seven layers. Every layer has own functionality and standard for both inputs and outputs. These standards are used to create interoperable network devices and software by manufacturing companies.
under which conditions adding an animation to a text will be beneficial for learning (Segers & Verhoeven, 2009). Animation entails structural as well as temporal information, so this may make animation a good candidate for supporting dynamic mental models. Animation can trigger perceptual schemata about natural biological movements. Thus, animation can allow activating such perceptual schemata, which is not as easily possible with illustrations (Schwan & Riempp, 2004). Within computer-based learning environments, animation can also allow the learner to interact with the content. Learner can manipulate the direction of movement and the speed of movement, and has a chance to test of hypotheses about processes under specific conditions by manipulating parameters in the animation. Although animation can be instructionally more powerful than illustrations, and has some advantages mentioned above, some researchers (e.g., Lowe & Schnotz, 2008; Tversky, Morrison, & Betrancourt, 2002) tried to understand under which conditions and why animations can enhance learning more than static pictures. In this context, Rasch and Schnotz (2009) created different multimedia learning environments including interactive and non-interactive pictures. After their experimental study, results showed that students didn’t learn better from animations than from static pictures and didn’t have generally higher learning outcomes. Even though text-only books result in the poorest retention/transfer and problem-solving performance, they are still one of the main learning resources in educational environments. Despite the rapid technological development in e-learning systems, recent studies show that students prefer textbooks rather than e-books (Woody, Daniel, & Baker, 2010). In other words, printed textbooks are still the primary and preferred source of information for learners. Learners go first to printed textbooks (books, journals, etc.) to gain new information. Considering that printed textbooks have been shown to be less effective but still are the primary source of information for learners, how can we reinforce textbooks using mobile technologies? When new text-plus-mobile phone resources are compared to the other conditions presented in the multimedia learning theory, which have the best learning outcomes? Examining the effectiveness of text-plus-mobile phone resources is the major research question of this study. To illustrate this approach, we next discuss how Hatice, a classmate of Nick and Tuna, studies the same topic using her mobile phone to obtain supplementary information. Hatice also begins to study the same topic for the same final exam using her textbook. She quickly grasps the basic functions of the model and the seven layers. Just like Tuna, she has difficulty understanding the seven layers because the written descriptions provided in the textbook are unclear for her. Hatice has access to the same website that Tuna used, but instead of using her laptop to access the animation, she uses a camera-equipped mobile phone because she notices the two-dimensional (2D) barcode tag in the book. She knows that 2D barcode tags can be used to connect to web pages using mobile phones. By starting the scanner and encoder software in her phone, she scans the tag on the book and starts the animation (See Fig. 2.). She follows the animation step by step with the phone’s touch-screen, and goes back and forth between the textbook and her mobile phone’s screen. The learning situation that is exemplified by Hatice’s studying of the topic is usually called mobile learning or m-learning. The last decade witnessed an incredible advance in wireless technologies and their increased impact on our daily lives. Following these developments, various sectors are trying to use mobile devices and the Internet to increase their effectiveness and efficiency. Some educators are eager to adopt these new technologies in educational settings, especially in distance education, where mobile technologies seem to be the perfect media to satisfy distance education’s famous slogan “whenever and wherever” (Churchill & Churchill, 2008; Ozdemir, 2010; Quinn, 2001; Virvou & Alepis, 2005). The attractiveness of mobile learning is that it can make information available independent of time and location. In spite of its great potential, using mobile devices in learning environments is still in its infancy (Motiwalla, 2007). Currently, mobile devices are used mainly to enhance collaboration through short messaging services (SMSs), to access information via the Internet generally, to share files, and to deliver courseware (Churchill & Churchill, 2008; Churchill & Hedberg, 2008; Motiwalla, 2007). The present study aims to contribute to the research on mobile learning and multimedia learning. The basic research question, as introduced in the scenario above, is whether learners achieve better learning outcomes with a camera-equipped mobile phone and employing 2D barcode technology to gain access to supplementary information compared with other types of learning approaches. In the present study, this research question was investigated using an experimental study with four groups of participants in different learning conditions: text-only, text-plus-picture, computer-based (animation-plus-narration) and text-plus-mobile phone. The main goal of this study was to compare the text-plus-mobile phone condition with the other conditions. The learning outcomes were measured by answers to a set of open-ended questions. In the following sections, the theoretical aspects of the study are introduced.
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Fig. 2. Using 2D barcode in a textbook, the first step is to scan the tag by using a camera-equipped mobile device. Once mobile device scans and encodes the information, it automatically gains access to the web page. In this figure, the device connects to the web page and animation starts.
2. Mobile learning There are some definitions of mobile learning that define it purely in terms of its technologies and its hardware, namely that is learning supported or delivered by mobile technologies such as personal digital assistants (PDAs), wireless laptop PCs, tablet computers and smartphones. These definitions, however, are constraining, techno-centric and tied to current technological instantiations (Traxler, 2009). If we take as our starting point in contrast to these definitions of mobile learning, we see that mobile technologies are ubiquitous in many modern societies, and are increasingly changing the nature of knowledge and discourse. This alters both nature of the learning and alters the ways that learning can be delivered. Mobile technologies also alter the nature of work, the balance between training and performance support, especially for knowledge workers. This means that mobile is not a new adjective qualifying the timeless concept of learning; rather, mobile learning is emerging as a new concept alongside the mobile workforce and the connected society. Therefore, it is now clear that mobile learning is not just about learning using portable devices. Portable devices are also now being recognized as pre-eminent vehicle not only mobile learning, but also for wider social change (Traxler & Dearden, 2005). Mobile devices vary in their sizes, prices and abilities. Common abilities of mobile devices are mobility and wireless connectivity. The nature of mobility has the potential to color and enrich learning, because learning is possible while traveling in a bus, ship or airplane. Through the use of mobile technology, learners can access learning materials from anywhere and at anytime. Learners will not have to wait for a certain time to learn or go to a certain place to learn. The worker or learner who frequently travels will similarly use mobile technology to access information and learning materials from anywhere and at anytime (Ally, 2009). Researchers show interest in mobile devices due to their potential to provide the learners with rapid access to online resources, and due to their low cost relative to desktop computers and notebooks (Kukulska-Hulme & Traxler, 2005). For instance, the Short Message Service (SMS) have been employed for delivery of instructional materials to learners (Levy & Kennedy, 2005; Saran, Seferoglu, & Cagiltay, 2009). Mobile devices also can be used alongside conventional paper-and-pencil technology without difficulty, thus facilitating learner’s creating personalized learning experiences (Looi et al., 2009). Researchers emphasize that mobile learning can complement existing learning styles rather than replacing them (Liaw, Hatala, & Huang, 2010). A significant amount of literature presents the potential of mobile technologies for learning, but most of them overlook the pedagogical issues. As Motiwalla (2007) observes, mobile learning is in an embryonic stage and the introduction of mobile devices into the learning pedagogy raises concerns among faculty regarding their usefulness in education. Traxler (2007) states that mobile learning definitions are techno-centric and relatively immature and we should seek to explore the underlying learner experience and ask how mobile learning differs from other forms of education. In the literature, some researchers offer a framework for theorizing about mobile learning with activity theory, conversation theory and transactional distance theory (e.g., Park, 2011; Sharples, Taylor, & Vavoula, 2005; Uden, 2007; Zurita & Nussbaum, 2007). Although some researchers adopt a pedagogical approach for evaluating some frameworks (Yau & Joy, 2009), and some outline mobile Web 2.0 technologies to enhance and engage students in a social constructivist learning paradigm (Cochrane & Bateman, 2009), nevertheless, instructional designers need a solid foundation for m-learning in the educational context, and also more guidance about how to utilize and integrate mobile technologies into teaching more effectively. Learning through mobile devices has some disadvantages because of small screens and keypads. If an educational material is textintensive, due to the necessity of scrolling on a small screen, a learner’s performance, satisfaction and effectiveness may be negatively affected (Jones, Buchanan, & Thimbleby, 2003). Therefore, learning content designed for mobile devices should include less text than what is used for other types of material. To compensate for the reduction in text, more audio can be used to support learning. Moreover, graphics, animations and videos also can be used to develop learning materials for mobile devices. It is clear that further research is needed to illuminate the advantages and limitations of using mobile devices for appropriate learning pedagogies. An appropriate technology that is capable of storing website addresses is 2D barcode, which is introduced in the following section. 3. 2D barcode technologies and their use in education A barcode is an optical machine-readable representation of data, which shows information about the object on which it is found. Originally, barcodes represented data by varying the widths and spacings of parallel lines and may be referred to as linear or onedimensional (1D). Barcodes later evolved into rectangles, dots, hexagons and other two-dimensional (2D) geometric patterns. The information encoded in a 2D barcode can be scanned by mobile phones equipped with built-in cameras and the appropriate software. The encoded information can be text, an SMS, a phone number or URL. Different types of barcodes are presented in Fig. 3. Although 2D barcodes are already used for textbook marketing (Butcher, 2009; Martin, 2011), the use of 2D barcode technologies in educational context has been investigated quite recently (Law & So, 2010; Metcalf & Rogers, 2010; Ozcelik & Acarturk, 2011; Ozdemir, 2010). Law and So (2010) reviewed the use of quick response (QR) code technologies in education. They found that 2D barcodes have been used in library catalogs and printed materials such as handbooks and posters. In a study by Susono and Shimomura (2006), the students sent comments and suggestions about using mobile phones and QR codes. Other researchers have examined similar mobile systems that support communication between students and teachers in a classroom setting (e.g., Al-Khalifa, 2008, pp. 342–346; Chaisatien & Akahori, 2007).
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Fig. 3. Different types of barcodes: A sample linear barcode tag (left), the QR (Quick Response) code (middle) and the High Capacity Color Barcode-HCCB (right). Tags can be blackand-white or full-color, including custom images (e.g., a company logo). For more information visit http://en.wikipedia.org/wiki/Barcode
Laine, Vinni, Sedano, and Joy (2010) used 2D barcode in a mobile learning game platform. Chen and Choi (2010) integrated an online collaborative management platform with printed learning materials in a classroom setting using 2D barcodes. Similar to our study, Seisto, Federley, Kuula, Paavilainen, and Vihavainen (2011) combined printed and digital materials and named it hybrid book, a combination of a traditional school book and a mobile phone. Learning materials were combined into one entity by enabling access to the digital material through using images in the book. As a result, many potential benefits of using mobile phones for learning purposes were reported by the researchers. All of these studies reveal the potential of 2D barcode technology as a multimedia access tool to support education. In contrast to these studies, some commentators (e.g., Ramsden, 2008) already regard 2D barcode current best and most cost effective, but will soon become obsolete technology for mobile learning. The research above consisted mostly of usability evaluations of the learning systems. A systematic empirical investigation measuring learning outcomes is lacking (Ozcelik & Acarturk, 2011). The present study contributes to the research literature on mobile learning by measuring learning outcomes in terms of participants’ answers to open-ended questions. The following section introduces the experimental investigation. 4. Method 4.1. Participants A total of 188 students (95 males and 93 females) from three universities (Middle East Technical University, Gazi University and Ankara University) participated in the experimental study. All of the participants were undergraduate students from the Department of Computer Education and Instructional Technologies with ages ranging from 18 to 26 (M ¼ 21.24, SD ¼ 1.29). The participants were randomly divided into four groups (47 students per group), corresponding to the four experimental conditions: text-only, text-plus-picture, computer-based (animation-plus-narration) and text-plus-mobile phone. 4.2. Instructional materials Four different instructional materials were prepared for the four experimental conditions. The first instructional material was a two-page paper booklet. The basic functions of the OSI model and processes in the layers were introduced in this material. The second instructional material had appropriate pictures near the text in addition to the text material in the first condition. The third instructional material was presented in an online environment. The basic functions of the model, principles of the model’s layers and the realization of processes during data transition between the layers were presented with animation and narration. The learner had a chance to stop and re-play the animation at anytime. The last instructional material was a one-page paper booklet with a 2D barcode on the bottom of the text. In the text portion, the basic functions of the model were presented, and in the second portion, on the mobile device screen, information about how the layers work was presented. The animation was the same as in the computer-based condition, but this time it was formatted to play on the mobile phone screen. The learner also had a chance to stop and re-play the animation at anytime on the phone. The animations for both the
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computer and mobile phone were designed using Adobe Flash CS4. All materials were presented in Turkish, the native language of participants. All of the materials (text-only, text-plus-picture, computer-based, text-plus-mobile phone) were based on the course materials used for a computer networks lesson by professional educators at the university. All materials used in the four different conditions were prepared with the guidance of a professional educator and a technical network administrator. The topic The OSI model was selected for the experiment because all of the participants from the three universities had limited knowledge about computer network systems and the OSI model. A prior knowledge test was conducted before the experiment, and a retention and a transfer test were conducted after the experiment for each participant, as presented below. 4.3. Data collection tools 4.3.1. Prior knowledge test The prior knowledge test consisted of five statements (e.g., “I know the term called OSI”, “I know the layers in the OSI model”), and participants were requested to use a five-point scale ranging from “very little” (score 1) to “very much” (score 5) to assess prior knowledge about the model. Such self-reported tests are commonly used in the learning research (e.g., Mayer & Moreno, 1998). The sum of the scores for each participant formed the prior knowledge test score. 4.3.2. Retention test The retention test included five open-ended questions to measure the extent of content comprehension. Four of these questions required participants to fill in a gap. An example of such a question is “OSI model has layers”. The cases that were used in the retention test were similar to the ones in the instructional materials so that learners could easily answer these questions if they recalled relevant information from the material. The other question in the retention test was “List the OSI layers according to the process of sending data”. Participants were given either 0 or 1 point for each of these questions. The sum of the scores on the five items formed the retention test score. Another rater also independently scored the retention tests of 20 participants (5 from each of the conditions) who were selected randomly for determining inter-rater reliability. The intra-class correlation coefficient (.84, p < .001) showed higher inter-rater agreement. 4.3.3. Transfer test Participants were asked three open-ended questions in the transfer test to assess the extent to which participants applied the learned content to new problems that were not addressed in the instructional materials. An example of a question in the transfer test is “What are the differences between the Transport and the Network layer?”. Each correct answer in the transfer test was given 1 point. Transfer test scores were calculated by summing up received points. The intra-class correlation coefficient (.79, p < .001) showed a high inter-rater agreement. 4.4. Procedure All four conditions were tested individually in a laboratory session lasting approximately 40 min. In the first 10 min, a demographic questionnaire was administrated. Afterward, in the next 10 min, researchers informed participants about the study, and during this time, participants who were randomly assigned to the text-plus-mobile phone condition underwent a short training session to familiarize them with the use of the mobile phone and barcodes. After the training phase, subjects were requested to study the instructional materials as long as they wanted for up to 20 min. Participants who were assigned to the computer-based and the text-plus-mobile phone conditions used headphones so that they would not disturb others in the study. Participants in all four conditions reviewed the material however they wanted. Researchers observed that participants who worked in the computer-based and mobile phone conditions sometimes stopped the animation and then started it again. 4.5. Results To examine whether the participants in the four experimental conditions had different levels of prior knowledge of OSI, an independent samples t-test was run. The results revealed that no significant differences existed between the text-only condition (M ¼ 3.16, SD ¼ 1.11), the text-plus-picture condition (M ¼ 3.29, SD ¼ 1.15), the computer-based condition (M ¼ 3.36, SD ¼ 1.21), and the text-plus-mobile phone condition (M ¼ 3.45, SD ¼ 1.12). This was not surprising because all participants from the three universities were from same department, and these departments accept students who have similar familiar graduate scores. A one-way ANOVA test was used to assess the effect of the four conditions on retention and transfer. The effect of condition was significant for both retention (F(1-170) ¼ 4.9, p ¼ .003) and transfer (F(1-170) ¼ 6.9, p ¼ .000). To test for effects between groups, a Scheffe test was used. First, a significant effect was found between the text-only and text-plus-mobile phone conditions and between the text-pluspicture and text-plus-mobile phone conditions for retention scores. Second, a significant effect was found between the text-only and text-plus-mobile phone conditions and between the text-plus-picture and text-plus-mobile phone conditions for transfer scores. We found no significant difference in retention or transfer scores between the paper-plus-mobile phone condition and the computer-based condition (See Table 1). Excluding the text-plus-mobile phone condition, the computer-based condition had the highest average retention and transfer scores and the text-only condition had the lowest. Of the four conditions, the text-plus-mobile phone condition had the highest score on both retention (M ¼ 4.02, SD ¼ 1.11) and transfer (M ¼ 1.26, SD ¼ 0.92) scores. After the experimental study, participants in the text-plus-mobile phone condition were asked to honestly report what they were thinking about that method of learning, including their thoughts about advantages, disadvantages, and their likes and dislikes. All of the text-plus-mobile phone participants said that it was the first time that they had approached learning in that way. Most of them said the situation was interesting or enjoyable for them. Additionally, they emphasized that information could be reached at anytime and anywhere
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Table 1 Mean scores and standard deviations for four conditions on retention and transfer tests. Condition
Text-only Text-plus-picture Computer-based Text-plus-mobile phone
Retention
Transfer
M
SD
M
SD
3.24 3.26 3.61 4.02
1.12 0.91 1.41 1.11
0.54 0.59 1.00 1.26
0.70 0.79 0.95 0.92
using this method. In contrast, some of the students emphasized that using the mobile phone component is a risk for the educational system at this point in time because of high Internet prices in the country. Moreover, some of them said there were no learning materials for mobile devices available now, and they also felt that the small screen size is still a problem for mobile learning. As we have seen, some opinions of the participants were favorable toward mobile learning, but some of them were not. The following section discusses the experimental findings in light of the theoretical frameworks mentioned in the previous sections. 5. Discussion According to multimedia learning theory (Mayer, 2001), “learners can better understand an explanation when it is presented in words and pictures, rather than when it is presented in words alone” (p:1, 63). Here, a combination of words and pictures including printed text, on-screen text, static pictures, animated pictures, videos and audio can be considered multimedia. Mayer (2001) also declares that although learning from text-only books results in the poorest retention and transfer performance, learning from books that include both text and illustrations and from computer-based environments that include on-screen text, illustrations, animations and narrations results in better performance. Although text-only books are not as effective alone as they are with supplementary materials, they are still one of the main learning resources for educational environments. Therefore, integrating mobile multimedia into printed textbooks with the help of 2D barcode technologies could facilitate deeper and meaningful learning (Ozdemir, 2010). The major goal of this study was to empirically compare text-plus-mobile phone learning using an integrated 2D barcode tag in a printed text with three other conditions described in multimedia learning theory. The results of our experimental study revealed that the participants in the text-plus-mobile phone condition had higher retention and transfer scores than the participants in the other three conditions. Similarly, we found significant differences between the text-plus-mobile phone condition and the text-only and text-plus-picture conditions on retention and transfer scores. First, retention results indicated that the participants who studied text-based instructional materials with mobile phones recalled more information than the participants who studied the materials with text-only or text-plus-picture materials. Second, transfer results indicated that the participants who studied text-based instructional materials with a mobile phone applied knowledge in new situations more than the participants who studied the materials with text-only or text-plus-picture. We found no significant difference in retention or transfer scores between the text-plus-mobile phone condition and the computer-based condition. The method examined in this study involved modifications of the instructional material such that: a 2D barcode was used near the text, and the learner scanned the tag with the camera on his/her mobile phone and reached the animation and narration on the mobile phone’s screen. Using this method, we created a new approach that reinforces printed textbooks, which otherwise had the poorest retention and transfer results but still are used as learners’ primary source of information. A benefit of using 2D barcode technology on text or printed materials with mobile devices is “just-in-time information presentation for accomplishing a task” (Kester, Kirschner, van Merrienboer, & Bäumer, 2001; Ozcelik & Acarturk, 2011). Previous research has shown that learning is enhanced when relevant information is immediately available (e.g., Kester, Kirschner, & van Merrienboer, 2004). In addition to enhanced learning, the integration of 2D barcode technologies into textbooks has the potential to reduce certain types of cognitive loads such as split attention (Sweller, 1999). Mayer and Moreno (2003) indicates that learners can process a limited amount of input from verbal and visual channels at a given time. Meaningful learning can require intensive cognitive processing to select, organize and integrate both the words and images. In a computer-based learning environment, in which text and pictures are placed at different positions, a learner’s attention may be split between the two. He/she cannot read or view these inputs at the same time. Mayer and Moreno (2003) offer the solution of text narration which allows a learner to use his/her dual channels. Bradley, Haynes, and Boyle (2006) explored the use of audio and found that using more auditory input than textual information is particularly beneficial. 2D barcode technologies provide an easy way to access multimedia content such as audio, animation, pictures, and videos to support learning from textbooks. By simply scanning a printed barcode from a camera-equipped mobile phone, a learner can quickly access any multimedia content, including educational materials, via the Internet. However, there currently are not enough learning objects that will work on mobile devices. This emphasizes the importance of instructional technology specialists. Additionally, the challenges of using mobile technology in educational contexts, such as the smaller size of the mobile phone screen, did not turn out to be a problem in this study. Therefore, learning content designed for mobile devices should include less text and more audio in place of textual information. Graphics, animations and videos can also be used to develop learning content for mobile devices (Bradley et al., 2006). Moreover, mobile devices should help a learner to make meaning of complex information within the context of the task at hand (Albers & Kim, 2001). It is clear that further research is needed to further show the advantages, challenges and limitations of mobile devices for learning and for appropriate learning pedagogies. 6. Conclusion Despite the amazing technological advances in electronic systems, students still prefer textbooks rather than e-books (Woody et al., 2010). Although text-only books have shown not to be as effective as other learning resources, they are still one of the main learning resources for traditional face-to-face and distance education environments. The present study showed that integrating mobile multimedia
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into printed textbooks with the help of 2D barcode technologies can facilitate meaningful and deeper learning. The findings obtained in the present study suggest that supporting a printed textbook with camera-equipped mobile devices and 2D barcodes linked to supplemental information, including narration to depict visuals such as pictures, graphics and animations, may increase the effectiveness of learning. Using this approach, printed materials are supported and reinforced. The present study also showed that mobile devices have further advantages through learning with multiple information sources, which is compatible with the existing theoretical framework of multimedia learning. References Albers, M., & Kim, L. (2001). Information design for the small-screen interface: an overview of web design issues for personal digital assistants. Technical Communications, 49(1), 45–60. Al-Khalifa, H. S. (2008). Mobile SRS: A classroom communication and assessment service. Proceedings of the international conference on innovations in information technology. Al Ain: IEEE. Ally, M. (2009). Introduction. In M. Ally (Ed.), Mobile learning: Transforming the delivery of education and training (pp. 1–6). AU Press, Athabasca University. Bradley, C., Haynes, R., & Boyle, T. (2006). Design for multimedia mlearning. Retrieved May, 2011, from. http://newsletter.alt.ac.uk/e_article000552781.cfm. Butcher, D. (2009). First 2D bar code on book links to Amazon.com. Retrieved April, 2012, from. http://www.mobilemarketer.com/cms/news/commerce/3160.html. Chaisatien, P., & Akahori, K. (2007). Demonstration of an application on 3G mobile phone and two dimension barcode in classroom communication support system. In C. Montgomerie, & J. Seale (Eds.), Proceedings of world conference on educational multimedia, hypermedia and telecommunications EDMEDIA (pp. 3330–3336). Chesapeake, VA: AACE. Chen, X., & Choi, J. H. (2010). Designing online collaborative location-aware platform for history learning. Journal of Educational Technology Development and Exchange, 3(1), 13–26. Churchill, D., & Churchill, N. (2008). Educational affordances of PDAs: a study of a teacher’s exploration of this technology. Computers & Education, 50(4), 1439–1450. Churchill, D., & Hedberg, J. (2008). Learning object design considerations for small-screen handheld devices. Computers & Education, 50(3), 881–893. Cochrane, T., & Bateman, R. (2009). Transforming pedagogy using mobile Web 2.0. International Journal of Mobile and Blended Learning, 1(4), 56–83. Jones, M., Buchanan, G., & Thimbleby, H. (2003). Improving web search on small screen devices. Interacting with Computers, 15(4), 479–495. Kester, L., Kirschner, P. A., & van Merrienboer, J. J. G. (2004). Timing of information presentation in learning statistics. Instructional Science, 32, 235–252. Kester, L., Kirschner, P. A., van Merrienboer, J. J. G., & Bäumer, A. (2001). Just-in-time information presentation and the acquisition of complex cognitive skills. Computers in Human Behavior, 17, 373–391. Kukulska-Hulme, A., & Traxler, J. (Eds.). (2005). A handbook for educators and trainers. Open and flexible learning series. London: Routledge. Laine, T. H., Vinni, M., Sedano, C. I., & Joy, M. (2010). On designing a pervasive mobile learning platform. Research in Learning Technology, 18(1), 3–17, (ALT-J). Law, C.-Y., & So, S. (2010). QR codes in education. Journal of Educational Technology Development and Exchange, 3(1), 85–100. Levy, M., & Kennedy, C. (2005). Learning Italian via mobile SMS. In A. Kukulska-Hulme, & J. Traxler (Eds.), Mobile learning: A handbook for educators and trainers. Abingdon: Routledge. Liaw, S. S., Hatala, M., & Huang, H. M. (2010). Investigating acceptance toward mobile learning to assist individual knowledge management: based on activity theory approach. Computers & Education, 54, 446–454. Looi, C. K., Wonga, L. H., So, H. J., Seow, P., Toh, Y., Chen, W., et al. (2009). Anatomy of a mobilized lesson: learning my way. Computers & Education, 53(4), 1120–1132. Lowe, R. K., & Schnotz, W. (Eds.). (2008). Learning with animation. Research implications for design. New York: Cambridge University Press. Martin, C. (2011). Book publishers ready for 2D Barcodes?. Retrieved April, 2012, from. http://www.thirdscreenrevolution.com/mobile/2011/05/book-publishers-ready-for-2dbarcodes/. Mayer, R. E. (2001). Multimedia learning. Cambridge University Press. Mayer, R. E. (2003). The promise of multimedia learning: using the same instructional design methods across different media [electronic version]. Learning and Instruction, 13(2), 125–139. Mayer, R. E., & Anderson, R. B. (1992). The instructive animation: helping students build connections between words and pictures in multimedia learning [electronic version]. Journal of Educational Psychology, 84, 444–452. Mayer, R. E., & Moreno, R. (1998). A split-attention effect in multimedia learning: evidence for dual processing systems in working memory. Journal of Educational Psychology, 90, 312–320. Mayer, E. R., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. Metcalf, D., & Rogers, D. (2010). Contextual learning and memory retention: the use of near field communications, QR codes, QBIC, and the spacing effect in location based learning. In T. T. Goh (Ed.), Multiplatform e-learning systems and technologies: Mobile devices for ubiquitous ICT-based education (pp. 309–320). Hershey, New York: Information Science Reference. Motiwalla, L. F. (2007). Mobile learning: a framework and evaluation. Computers & Education, 49(3), 581–596. Ozcelik, E., & Acarturk, C. (2011). Reducing the spatial distance between printed and online information sources by means of mobile technology enhances learning: using 2D barcodes. Computers & Education, 57(3), 2077–2085. Ozdemir, S. (2010). Supporting printed books with multimedia: a new way to use mobile technology for learning. British Journal of Educational Technology, 41(6), 135–138. Park, Y. (2011). A pedagogical framework for mobile learning: categorizing educational applications of mobile technologies into four types. The International Review of Research in Open and Distance Learning, 12(2), 78–102. Quinn, C. (2001). Get ready for m-learning. Training and Development, 20(2), 20–21. Ramsden, A. (2008). Are QR codes the future of mobile learning?. Retrieved May, 2012, from. http://mlearning.edublogs.org/2008/03/27/andy-ramsden-are-qr-codes-thefuture-of-mobile-learning/. Rasch, T., & Schnotz, W. (2009). Interactive and non-interactive pictures in multimedia learning environments: effects on learning outcomes and learning efficiency. Learning and Instruction, 19, 411–422. Saran, M., Seferoglu, G., & Cagiltay, K. (2009). Mobile assisted language learning: English pronunciation at learners’ fingertips. Eurasian Journal of Educational Research, 97–114. Schwan, S., & Riempp, R. (2004). The cognitive benefits of interactive videos: learning to tie nautical knots. Learning and Instruction, 14, 293–305. Segers, E., & Verhoeven, L. (2009). Learning in a sheltered internet environment: the use of WebQuests. Learning and Instruction, 19(5), 423–432. Seisto, A., Federley, M., Kuula, T., Paavilainen, J., & Vihavainen, S. (2011). Involving the en-users in the development of language learning material. International Journal of Mobile and Blended Learning, 3(2), 43–56. Sharples, M., Taylor, J., & Vavoula, G. (2005). Towards a theory of mobile learning. Retrieved May, 2012, from. http://www.mlearn.org.za/CD/papers/Sharples Theory of Mobile.pdf. Susono, H., & Shimomura, T. (2006). Using mobile phones and QR codes for formative class assessment. InMéndez-Vilas, A., Solano Martín, J. A. A., González, M., & González, J. M. (Eds.). (2006). Current developments in technology-assisted education, Vol. 2 (pp. 1006–1010). Badajoz, Spain: Formatex. Sweller, J. (1999). Instructional design in technical areas. Camberwell, Australia: ACER Press. Traxler, J. (2007). Defining, discussing and evaluating mobile learning: the moving finger writes and having writ. International Review of Research in Open and Distance Learning, 8(2), 1–12. Traxler, J. (2009). Current state of mobile learning. In M. Ally (Ed.), Mobile learning: Transforming the delivery of education and training (pp. 9–24). AU press, Athabasca University. Traxler, J., & Dearden, P. (2005). The potential for using SMS to support learning and organisation in Sub-Saharan Africa. Proceedings of Development Studies Association Conference. Milton Keynes. Tversky, B., Morrison, J. B., & Betrancourt, M. (2002). Animation: can it facilitate? International Journal of Human-Computer Studies, 57, 247–262. Uden, L. (2007). Activity theory for designing mobile learning. International Journal of Mobile Learning and Organization, 1(1), 81–102. Virvou, M., & Alepis, E. (2005). Mobile educational features in authoring tools for personalized tutoring. Computers & Education, 44(1), 53–68. Woody, W. D., Daniel, D. B., & Baker, C. A. (2010). E-books or textbooks: students prefer textbooks. Computers & Education, 55(3), 945–948. Yau, J. Y., & Joy, M. (2009). A mobile context-aware framework for managing learning schedules: data analysis from an interview study. International Journal of Mobile and Blended Learning, 1(4), 29–55. Zurita, G., & Nussbaum, M. (2007). A conceptual framework based on activity theory for mobile CSCL. British Journal of Educational Technology, 38(2), 211–235.
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Computers & Education journal homepage: www.elsevier.com/locate/compedu
Integrating mobile multimedia into textbooks: 2D barcodes Celebi Uluyol*, R. Kagan Agca Department of Computer Education and Instructional Technologies, Gazi University, Ankara, Turkey
a r t i c l e i n f o
a b s t r a c t
Article history: Received 19 December 2011 Received in revised form 11 May 2012 Accepted 16 May 2012
The major goal of this study was to empirically compare text-plus-mobile phone learning using an integrated 2D barcode tag in a printed text with three other conditions described in multimedia learning theory. The method examined in the study involved modifications of the instructional material such that: a 2D barcode was used near the text, the learner scanned the tag with the camera on his/her mobile phone and reached the animation and narration on the mobile phone’s screen. Using this method, we created a new approach that reinforces printed textbooks, which had the poorest retention and transfer results. The results suggest that supporting a printed textbook with camera-equipped mobile devices and 2D barcodes linked to supplemental information, may increase the effectiveness of learning. Ó 2012 Elsevier Ltd. All rights reserved.
Keywords: Mobile learning Multimedia learning 2D barcodes
1. Introduction Nick, a freshman at the Department of Computer Education and Instructional Technologies, goes to the library to study for the final exam of the Computer Networks and Communication course. He starts studying the Open Systems Interconnection (OSI) model, which is a part of the course curriculum and he grasps the basic functions of the model. The model defines a networking framework for implementing protocols that include seven layers. Control is passed from one layer to the next, starting at the application layer in one computer station, proceeding to the bottom layer, passing over the channel to the next station and then back up the layers. A screenshot of the OSI model is given in Fig. 1. Nick also studies the basic functions of the seven layers in the model. Let us imagine that he continues to study for the final exam in this way using only his textbook. Tuna, a classmate of Nick, starts to study the same topic for the final exam using his personal computer. He sits in front of a computer screen, and by using the mouse he asks the computer to explain the OSI model. On the screen he sees the basic functions of the model, principles of the model’s layers and the realization of processes during data transition between the layers. At the same time he hears a corresponding narration of the actions involved between the layers in the model. He has also a chance to stop and re-play the animation at anytime. Now let us imagine that Tuna continues to study for the final exam in this way, using the animation on the web page. The learning situations that are exemplified above are only two instances of multimedia learning experiences. Multimedia learning occurs when learners receive information presented in more than one mode (Mayer, 2001). The term multimedia refers to the presentation of instructional material using both words and pictures. The instructional material can be presented in verbal form, including printed or spoken text. The instructional material also can be presented in pictorial form, including static graphics, illustrations, photographs, graphs or dynamic forms such as animation or video. The research on multimedia learning shows that humans learn better from a combination of image and text than they learn from text alone (Mayer, 2001). In his book, Mayer (2001) declared that learning from books that include both text and illustrations and from computer-based environments that include on-screen text, animations and narrations resulted in better retention/transfer and problemsolving performance compared to learning from text-only books. Similarly, Mayer and Anderson (1992) created three different learning environments: text-only, text-plus-picture and animation-plus-narration. After the experimental study, results showed that text-pluspicture and animation-plus-narration conditions had a significant effect on success (Mayer, 2003). Animation is the popular of today’s multimedia learning environments and many media designers seem to be convinced that animations are instructionally more powerful than static pictures (Rasch & Schnotz, 2009). Recent research has demonstrated that it is more unclear
* Corresponding author. Tel.: þ90 505 815 8764. E-mail addresses: [email protected], [email protected] (C. Uluyol), [email protected] (R.K. Agca). 0360-1315/$ – see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.compedu.2012.05.018
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Fig. 1. A screenshot of the OSI model. The OSI model is a layered model and has seven layers. Every layer has own functionality and standard for both inputs and outputs. These standards are used to create interoperable network devices and software by manufacturing companies.
under which conditions adding an animation to a text will be beneficial for learning (Segers & Verhoeven, 2009). Animation entails structural as well as temporal information, so this may make animation a good candidate for supporting dynamic mental models. Animation can trigger perceptual schemata about natural biological movements. Thus, animation can allow activating such perceptual schemata, which is not as easily possible with illustrations (Schwan & Riempp, 2004). Within computer-based learning environments, animation can also allow the learner to interact with the content. Learner can manipulate the direction of movement and the speed of movement, and has a chance to test of hypotheses about processes under specific conditions by manipulating parameters in the animation. Although animation can be instructionally more powerful than illustrations, and has some advantages mentioned above, some researchers (e.g., Lowe & Schnotz, 2008; Tversky, Morrison, & Betrancourt, 2002) tried to understand under which conditions and why animations can enhance learning more than static pictures. In this context, Rasch and Schnotz (2009) created different multimedia learning environments including interactive and non-interactive pictures. After their experimental study, results showed that students didn’t learn better from animations than from static pictures and didn’t have generally higher learning outcomes. Even though text-only books result in the poorest retention/transfer and problem-solving performance, they are still one of the main learning resources in educational environments. Despite the rapid technological development in e-learning systems, recent studies show that students prefer textbooks rather than e-books (Woody, Daniel, & Baker, 2010). In other words, printed textbooks are still the primary and preferred source of information for learners. Learners go first to printed textbooks (books, journals, etc.) to gain new information. Considering that printed textbooks have been shown to be less effective but still are the primary source of information for learners, how can we reinforce textbooks using mobile technologies? When new text-plus-mobile phone resources are compared to the other conditions presented in the multimedia learning theory, which have the best learning outcomes? Examining the effectiveness of text-plus-mobile phone resources is the major research question of this study. To illustrate this approach, we next discuss how Hatice, a classmate of Nick and Tuna, studies the same topic using her mobile phone to obtain supplementary information. Hatice also begins to study the same topic for the same final exam using her textbook. She quickly grasps the basic functions of the model and the seven layers. Just like Tuna, she has difficulty understanding the seven layers because the written descriptions provided in the textbook are unclear for her. Hatice has access to the same website that Tuna used, but instead of using her laptop to access the animation, she uses a camera-equipped mobile phone because she notices the two-dimensional (2D) barcode tag in the book. She knows that 2D barcode tags can be used to connect to web pages using mobile phones. By starting the scanner and encoder software in her phone, she scans the tag on the book and starts the animation (See Fig. 2.). She follows the animation step by step with the phone’s touch-screen, and goes back and forth between the textbook and her mobile phone’s screen. The learning situation that is exemplified by Hatice’s studying of the topic is usually called mobile learning or m-learning. The last decade witnessed an incredible advance in wireless technologies and their increased impact on our daily lives. Following these developments, various sectors are trying to use mobile devices and the Internet to increase their effectiveness and efficiency. Some educators are eager to adopt these new technologies in educational settings, especially in distance education, where mobile technologies seem to be the perfect media to satisfy distance education’s famous slogan “whenever and wherever” (Churchill & Churchill, 2008; Ozdemir, 2010; Quinn, 2001; Virvou & Alepis, 2005). The attractiveness of mobile learning is that it can make information available independent of time and location. In spite of its great potential, using mobile devices in learning environments is still in its infancy (Motiwalla, 2007). Currently, mobile devices are used mainly to enhance collaboration through short messaging services (SMSs), to access information via the Internet generally, to share files, and to deliver courseware (Churchill & Churchill, 2008; Churchill & Hedberg, 2008; Motiwalla, 2007). The present study aims to contribute to the research on mobile learning and multimedia learning. The basic research question, as introduced in the scenario above, is whether learners achieve better learning outcomes with a camera-equipped mobile phone and employing 2D barcode technology to gain access to supplementary information compared with other types of learning approaches. In the present study, this research question was investigated using an experimental study with four groups of participants in different learning conditions: text-only, text-plus-picture, computer-based (animation-plus-narration) and text-plus-mobile phone. The main goal of this study was to compare the text-plus-mobile phone condition with the other conditions. The learning outcomes were measured by answers to a set of open-ended questions. In the following sections, the theoretical aspects of the study are introduced.
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Fig. 2. Using 2D barcode in a textbook, the first step is to scan the tag by using a camera-equipped mobile device. Once mobile device scans and encodes the information, it automatically gains access to the web page. In this figure, the device connects to the web page and animation starts.
2. Mobile learning There are some definitions of mobile learning that define it purely in terms of its technologies and its hardware, namely that is learning supported or delivered by mobile technologies such as personal digital assistants (PDAs), wireless laptop PCs, tablet computers and smartphones. These definitions, however, are constraining, techno-centric and tied to current technological instantiations (Traxler, 2009). If we take as our starting point in contrast to these definitions of mobile learning, we see that mobile technologies are ubiquitous in many modern societies, and are increasingly changing the nature of knowledge and discourse. This alters both nature of the learning and alters the ways that learning can be delivered. Mobile technologies also alter the nature of work, the balance between training and performance support, especially for knowledge workers. This means that mobile is not a new adjective qualifying the timeless concept of learning; rather, mobile learning is emerging as a new concept alongside the mobile workforce and the connected society. Therefore, it is now clear that mobile learning is not just about learning using portable devices. Portable devices are also now being recognized as pre-eminent vehicle not only mobile learning, but also for wider social change (Traxler & Dearden, 2005). Mobile devices vary in their sizes, prices and abilities. Common abilities of mobile devices are mobility and wireless connectivity. The nature of mobility has the potential to color and enrich learning, because learning is possible while traveling in a bus, ship or airplane. Through the use of mobile technology, learners can access learning materials from anywhere and at anytime. Learners will not have to wait for a certain time to learn or go to a certain place to learn. The worker or learner who frequently travels will similarly use mobile technology to access information and learning materials from anywhere and at anytime (Ally, 2009). Researchers show interest in mobile devices due to their potential to provide the learners with rapid access to online resources, and due to their low cost relative to desktop computers and notebooks (Kukulska-Hulme & Traxler, 2005). For instance, the Short Message Service (SMS) have been employed for delivery of instructional materials to learners (Levy & Kennedy, 2005; Saran, Seferoglu, & Cagiltay, 2009). Mobile devices also can be used alongside conventional paper-and-pencil technology without difficulty, thus facilitating learner’s creating personalized learning experiences (Looi et al., 2009). Researchers emphasize that mobile learning can complement existing learning styles rather than replacing them (Liaw, Hatala, & Huang, 2010). A significant amount of literature presents the potential of mobile technologies for learning, but most of them overlook the pedagogical issues. As Motiwalla (2007) observes, mobile learning is in an embryonic stage and the introduction of mobile devices into the learning pedagogy raises concerns among faculty regarding their usefulness in education. Traxler (2007) states that mobile learning definitions are techno-centric and relatively immature and we should seek to explore the underlying learner experience and ask how mobile learning differs from other forms of education. In the literature, some researchers offer a framework for theorizing about mobile learning with activity theory, conversation theory and transactional distance theory (e.g., Park, 2011; Sharples, Taylor, & Vavoula, 2005; Uden, 2007; Zurita & Nussbaum, 2007). Although some researchers adopt a pedagogical approach for evaluating some frameworks (Yau & Joy, 2009), and some outline mobile Web 2.0 technologies to enhance and engage students in a social constructivist learning paradigm (Cochrane & Bateman, 2009), nevertheless, instructional designers need a solid foundation for m-learning in the educational context, and also more guidance about how to utilize and integrate mobile technologies into teaching more effectively. Learning through mobile devices has some disadvantages because of small screens and keypads. If an educational material is textintensive, due to the necessity of scrolling on a small screen, a learner’s performance, satisfaction and effectiveness may be negatively affected (Jones, Buchanan, & Thimbleby, 2003). Therefore, learning content designed for mobile devices should include less text than what is used for other types of material. To compensate for the reduction in text, more audio can be used to support learning. Moreover, graphics, animations and videos also can be used to develop learning materials for mobile devices. It is clear that further research is needed to illuminate the advantages and limitations of using mobile devices for appropriate learning pedagogies. An appropriate technology that is capable of storing website addresses is 2D barcode, which is introduced in the following section. 3. 2D barcode technologies and their use in education A barcode is an optical machine-readable representation of data, which shows information about the object on which it is found. Originally, barcodes represented data by varying the widths and spacings of parallel lines and may be referred to as linear or onedimensional (1D). Barcodes later evolved into rectangles, dots, hexagons and other two-dimensional (2D) geometric patterns. The information encoded in a 2D barcode can be scanned by mobile phones equipped with built-in cameras and the appropriate software. The encoded information can be text, an SMS, a phone number or URL. Different types of barcodes are presented in Fig. 3. Although 2D barcodes are already used for textbook marketing (Butcher, 2009; Martin, 2011), the use of 2D barcode technologies in educational context has been investigated quite recently (Law & So, 2010; Metcalf & Rogers, 2010; Ozcelik & Acarturk, 2011; Ozdemir, 2010). Law and So (2010) reviewed the use of quick response (QR) code technologies in education. They found that 2D barcodes have been used in library catalogs and printed materials such as handbooks and posters. In a study by Susono and Shimomura (2006), the students sent comments and suggestions about using mobile phones and QR codes. Other researchers have examined similar mobile systems that support communication between students and teachers in a classroom setting (e.g., Al-Khalifa, 2008, pp. 342–346; Chaisatien & Akahori, 2007).
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Fig. 3. Different types of barcodes: A sample linear barcode tag (left), the QR (Quick Response) code (middle) and the High Capacity Color Barcode-HCCB (right). Tags can be blackand-white or full-color, including custom images (e.g., a company logo). For more information visit http://en.wikipedia.org/wiki/Barcode
Laine, Vinni, Sedano, and Joy (2010) used 2D barcode in a mobile learning game platform. Chen and Choi (2010) integrated an online collaborative management platform with printed learning materials in a classroom setting using 2D barcodes. Similar to our study, Seisto, Federley, Kuula, Paavilainen, and Vihavainen (2011) combined printed and digital materials and named it hybrid book, a combination of a traditional school book and a mobile phone. Learning materials were combined into one entity by enabling access to the digital material through using images in the book. As a result, many potential benefits of using mobile phones for learning purposes were reported by the researchers. All of these studies reveal the potential of 2D barcode technology as a multimedia access tool to support education. In contrast to these studies, some commentators (e.g., Ramsden, 2008) already regard 2D barcode current best and most cost effective, but will soon become obsolete technology for mobile learning. The research above consisted mostly of usability evaluations of the learning systems. A systematic empirical investigation measuring learning outcomes is lacking (Ozcelik & Acarturk, 2011). The present study contributes to the research literature on mobile learning by measuring learning outcomes in terms of participants’ answers to open-ended questions. The following section introduces the experimental investigation. 4. Method 4.1. Participants A total of 188 students (95 males and 93 females) from three universities (Middle East Technical University, Gazi University and Ankara University) participated in the experimental study. All of the participants were undergraduate students from the Department of Computer Education and Instructional Technologies with ages ranging from 18 to 26 (M ¼ 21.24, SD ¼ 1.29). The participants were randomly divided into four groups (47 students per group), corresponding to the four experimental conditions: text-only, text-plus-picture, computer-based (animation-plus-narration) and text-plus-mobile phone. 4.2. Instructional materials Four different instructional materials were prepared for the four experimental conditions. The first instructional material was a two-page paper booklet. The basic functions of the OSI model and processes in the layers were introduced in this material. The second instructional material had appropriate pictures near the text in addition to the text material in the first condition. The third instructional material was presented in an online environment. The basic functions of the model, principles of the model’s layers and the realization of processes during data transition between the layers were presented with animation and narration. The learner had a chance to stop and re-play the animation at anytime. The last instructional material was a one-page paper booklet with a 2D barcode on the bottom of the text. In the text portion, the basic functions of the model were presented, and in the second portion, on the mobile device screen, information about how the layers work was presented. The animation was the same as in the computer-based condition, but this time it was formatted to play on the mobile phone screen. The learner also had a chance to stop and re-play the animation at anytime on the phone. The animations for both the
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computer and mobile phone were designed using Adobe Flash CS4. All materials were presented in Turkish, the native language of participants. All of the materials (text-only, text-plus-picture, computer-based, text-plus-mobile phone) were based on the course materials used for a computer networks lesson by professional educators at the university. All materials used in the four different conditions were prepared with the guidance of a professional educator and a technical network administrator. The topic The OSI model was selected for the experiment because all of the participants from the three universities had limited knowledge about computer network systems and the OSI model. A prior knowledge test was conducted before the experiment, and a retention and a transfer test were conducted after the experiment for each participant, as presented below. 4.3. Data collection tools 4.3.1. Prior knowledge test The prior knowledge test consisted of five statements (e.g., “I know the term called OSI”, “I know the layers in the OSI model”), and participants were requested to use a five-point scale ranging from “very little” (score 1) to “very much” (score 5) to assess prior knowledge about the model. Such self-reported tests are commonly used in the learning research (e.g., Mayer & Moreno, 1998). The sum of the scores for each participant formed the prior knowledge test score. 4.3.2. Retention test The retention test included five open-ended questions to measure the extent of content comprehension. Four of these questions required participants to fill in a gap. An example of such a question is “OSI model has layers”. The cases that were used in the retention test were similar to the ones in the instructional materials so that learners could easily answer these questions if they recalled relevant information from the material. The other question in the retention test was “List the OSI layers according to the process of sending data”. Participants were given either 0 or 1 point for each of these questions. The sum of the scores on the five items formed the retention test score. Another rater also independently scored the retention tests of 20 participants (5 from each of the conditions) who were selected randomly for determining inter-rater reliability. The intra-class correlation coefficient (.84, p < .001) showed higher inter-rater agreement. 4.3.3. Transfer test Participants were asked three open-ended questions in the transfer test to assess the extent to which participants applied the learned content to new problems that were not addressed in the instructional materials. An example of a question in the transfer test is “What are the differences between the Transport and the Network layer?”. Each correct answer in the transfer test was given 1 point. Transfer test scores were calculated by summing up received points. The intra-class correlation coefficient (.79, p < .001) showed a high inter-rater agreement. 4.4. Procedure All four conditions were tested individually in a laboratory session lasting approximately 40 min. In the first 10 min, a demographic questionnaire was administrated. Afterward, in the next 10 min, researchers informed participants about the study, and during this time, participants who were randomly assigned to the text-plus-mobile phone condition underwent a short training session to familiarize them with the use of the mobile phone and barcodes. After the training phase, subjects were requested to study the instructional materials as long as they wanted for up to 20 min. Participants who were assigned to the computer-based and the text-plus-mobile phone conditions used headphones so that they would not disturb others in the study. Participants in all four conditions reviewed the material however they wanted. Researchers observed that participants who worked in the computer-based and mobile phone conditions sometimes stopped the animation and then started it again. 4.5. Results To examine whether the participants in the four experimental conditions had different levels of prior knowledge of OSI, an independent samples t-test was run. The results revealed that no significant differences existed between the text-only condition (M ¼ 3.16, SD ¼ 1.11), the text-plus-picture condition (M ¼ 3.29, SD ¼ 1.15), the computer-based condition (M ¼ 3.36, SD ¼ 1.21), and the text-plus-mobile phone condition (M ¼ 3.45, SD ¼ 1.12). This was not surprising because all participants from the three universities were from same department, and these departments accept students who have similar familiar graduate scores. A one-way ANOVA test was used to assess the effect of the four conditions on retention and transfer. The effect of condition was significant for both retention (F(1-170) ¼ 4.9, p ¼ .003) and transfer (F(1-170) ¼ 6.9, p ¼ .000). To test for effects between groups, a Scheffe test was used. First, a significant effect was found between the text-only and text-plus-mobile phone conditions and between the text-pluspicture and text-plus-mobile phone conditions for retention scores. Second, a significant effect was found between the text-only and text-plus-mobile phone conditions and between the text-plus-picture and text-plus-mobile phone conditions for transfer scores. We found no significant difference in retention or transfer scores between the paper-plus-mobile phone condition and the computer-based condition (See Table 1). Excluding the text-plus-mobile phone condition, the computer-based condition had the highest average retention and transfer scores and the text-only condition had the lowest. Of the four conditions, the text-plus-mobile phone condition had the highest score on both retention (M ¼ 4.02, SD ¼ 1.11) and transfer (M ¼ 1.26, SD ¼ 0.92) scores. After the experimental study, participants in the text-plus-mobile phone condition were asked to honestly report what they were thinking about that method of learning, including their thoughts about advantages, disadvantages, and their likes and dislikes. All of the text-plus-mobile phone participants said that it was the first time that they had approached learning in that way. Most of them said the situation was interesting or enjoyable for them. Additionally, they emphasized that information could be reached at anytime and anywhere
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Table 1 Mean scores and standard deviations for four conditions on retention and transfer tests. Condition
Text-only Text-plus-picture Computer-based Text-plus-mobile phone
Retention
Transfer
M
SD
M
SD
3.24 3.26 3.61 4.02
1.12 0.91 1.41 1.11
0.54 0.59 1.00 1.26
0.70 0.79 0.95 0.92
using this method. In contrast, some of the students emphasized that using the mobile phone component is a risk for the educational system at this point in time because of high Internet prices in the country. Moreover, some of them said there were no learning materials for mobile devices available now, and they also felt that the small screen size is still a problem for mobile learning. As we have seen, some opinions of the participants were favorable toward mobile learning, but some of them were not. The following section discusses the experimental findings in light of the theoretical frameworks mentioned in the previous sections. 5. Discussion According to multimedia learning theory (Mayer, 2001), “learners can better understand an explanation when it is presented in words and pictures, rather than when it is presented in words alone” (p:1, 63). Here, a combination of words and pictures including printed text, on-screen text, static pictures, animated pictures, videos and audio can be considered multimedia. Mayer (2001) also declares that although learning from text-only books results in the poorest retention and transfer performance, learning from books that include both text and illustrations and from computer-based environments that include on-screen text, illustrations, animations and narrations results in better performance. Although text-only books are not as effective alone as they are with supplementary materials, they are still one of the main learning resources for educational environments. Therefore, integrating mobile multimedia into printed textbooks with the help of 2D barcode technologies could facilitate deeper and meaningful learning (Ozdemir, 2010). The major goal of this study was to empirically compare text-plus-mobile phone learning using an integrated 2D barcode tag in a printed text with three other conditions described in multimedia learning theory. The results of our experimental study revealed that the participants in the text-plus-mobile phone condition had higher retention and transfer scores than the participants in the other three conditions. Similarly, we found significant differences between the text-plus-mobile phone condition and the text-only and text-plus-picture conditions on retention and transfer scores. First, retention results indicated that the participants who studied text-based instructional materials with mobile phones recalled more information than the participants who studied the materials with text-only or text-plus-picture materials. Second, transfer results indicated that the participants who studied text-based instructional materials with a mobile phone applied knowledge in new situations more than the participants who studied the materials with text-only or text-plus-picture. We found no significant difference in retention or transfer scores between the text-plus-mobile phone condition and the computer-based condition. The method examined in this study involved modifications of the instructional material such that: a 2D barcode was used near the text, and the learner scanned the tag with the camera on his/her mobile phone and reached the animation and narration on the mobile phone’s screen. Using this method, we created a new approach that reinforces printed textbooks, which otherwise had the poorest retention and transfer results but still are used as learners’ primary source of information. A benefit of using 2D barcode technology on text or printed materials with mobile devices is “just-in-time information presentation for accomplishing a task” (Kester, Kirschner, van Merrienboer, & Bäumer, 2001; Ozcelik & Acarturk, 2011). Previous research has shown that learning is enhanced when relevant information is immediately available (e.g., Kester, Kirschner, & van Merrienboer, 2004). In addition to enhanced learning, the integration of 2D barcode technologies into textbooks has the potential to reduce certain types of cognitive loads such as split attention (Sweller, 1999). Mayer and Moreno (2003) indicates that learners can process a limited amount of input from verbal and visual channels at a given time. Meaningful learning can require intensive cognitive processing to select, organize and integrate both the words and images. In a computer-based learning environment, in which text and pictures are placed at different positions, a learner’s attention may be split between the two. He/she cannot read or view these inputs at the same time. Mayer and Moreno (2003) offer the solution of text narration which allows a learner to use his/her dual channels. Bradley, Haynes, and Boyle (2006) explored the use of audio and found that using more auditory input than textual information is particularly beneficial. 2D barcode technologies provide an easy way to access multimedia content such as audio, animation, pictures, and videos to support learning from textbooks. By simply scanning a printed barcode from a camera-equipped mobile phone, a learner can quickly access any multimedia content, including educational materials, via the Internet. However, there currently are not enough learning objects that will work on mobile devices. This emphasizes the importance of instructional technology specialists. Additionally, the challenges of using mobile technology in educational contexts, such as the smaller size of the mobile phone screen, did not turn out to be a problem in this study. Therefore, learning content designed for mobile devices should include less text and more audio in place of textual information. Graphics, animations and videos can also be used to develop learning content for mobile devices (Bradley et al., 2006). Moreover, mobile devices should help a learner to make meaning of complex information within the context of the task at hand (Albers & Kim, 2001). It is clear that further research is needed to further show the advantages, challenges and limitations of mobile devices for learning and for appropriate learning pedagogies. 6. Conclusion Despite the amazing technological advances in electronic systems, students still prefer textbooks rather than e-books (Woody et al., 2010). Although text-only books have shown not to be as effective as other learning resources, they are still one of the main learning resources for traditional face-to-face and distance education environments. The present study showed that integrating mobile multimedia
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into printed textbooks with the help of 2D barcode technologies can facilitate meaningful and deeper learning. The findings obtained in the present study suggest that supporting a printed textbook with camera-equipped mobile devices and 2D barcodes linked to supplemental information, including narration to depict visuals such as pictures, graphics and animations, may increase the effectiveness of learning. Using this approach, printed materials are supported and reinforced. The present study also showed that mobile devices have further advantages through learning with multiple information sources, which is compatible with the existing theoretical framework of multimedia learning. References Albers, M., & Kim, L. (2001). Information design for the small-screen interface: an overview of web design issues for personal digital assistants. Technical Communications, 49(1), 45–60. Al-Khalifa, H. S. (2008). Mobile SRS: A classroom communication and assessment service. Proceedings of the international conference on innovations in information technology. Al Ain: IEEE. Ally, M. (2009). Introduction. In M. Ally (Ed.), Mobile learning: Transforming the delivery of education and training (pp. 1–6). AU Press, Athabasca University. Bradley, C., Haynes, R., & Boyle, T. (2006). Design for multimedia mlearning. Retrieved May, 2011, from. http://newsletter.alt.ac.uk/e_article000552781.cfm. Butcher, D. (2009). First 2D bar code on book links to Amazon.com. Retrieved April, 2012, from. http://www.mobilemarketer.com/cms/news/commerce/3160.html. Chaisatien, P., & Akahori, K. (2007). Demonstration of an application on 3G mobile phone and two dimension barcode in classroom communication support system. In C. Montgomerie, & J. Seale (Eds.), Proceedings of world conference on educational multimedia, hypermedia and telecommunications EDMEDIA (pp. 3330–3336). Chesapeake, VA: AACE. Chen, X., & Choi, J. H. (2010). Designing online collaborative location-aware platform for history learning. Journal of Educational Technology Development and Exchange, 3(1), 13–26. Churchill, D., & Churchill, N. (2008). Educational affordances of PDAs: a study of a teacher’s exploration of this technology. Computers & Education, 50(4), 1439–1450. Churchill, D., & Hedberg, J. (2008). Learning object design considerations for small-screen handheld devices. Computers & Education, 50(3), 881–893. Cochrane, T., & Bateman, R. (2009). Transforming pedagogy using mobile Web 2.0. International Journal of Mobile and Blended Learning, 1(4), 56–83. Jones, M., Buchanan, G., & Thimbleby, H. (2003). Improving web search on small screen devices. Interacting with Computers, 15(4), 479–495. Kester, L., Kirschner, P. A., & van Merrienboer, J. J. G. (2004). Timing of information presentation in learning statistics. Instructional Science, 32, 235–252. Kester, L., Kirschner, P. A., van Merrienboer, J. J. G., & Bäumer, A. (2001). Just-in-time information presentation and the acquisition of complex cognitive skills. Computers in Human Behavior, 17, 373–391. Kukulska-Hulme, A., & Traxler, J. (Eds.). (2005). A handbook for educators and trainers. Open and flexible learning series. London: Routledge. Laine, T. H., Vinni, M., Sedano, C. I., & Joy, M. (2010). On designing a pervasive mobile learning platform. Research in Learning Technology, 18(1), 3–17, (ALT-J). Law, C.-Y., & So, S. (2010). QR codes in education. Journal of Educational Technology Development and Exchange, 3(1), 85–100. Levy, M., & Kennedy, C. (2005). Learning Italian via mobile SMS. In A. Kukulska-Hulme, & J. Traxler (Eds.), Mobile learning: A handbook for educators and trainers. Abingdon: Routledge. Liaw, S. S., Hatala, M., & Huang, H. M. (2010). Investigating acceptance toward mobile learning to assist individual knowledge management: based on activity theory approach. Computers & Education, 54, 446–454. Looi, C. K., Wonga, L. H., So, H. J., Seow, P., Toh, Y., Chen, W., et al. (2009). Anatomy of a mobilized lesson: learning my way. Computers & Education, 53(4), 1120–1132. Lowe, R. K., & Schnotz, W. (Eds.). (2008). Learning with animation. Research implications for design. New York: Cambridge University Press. Martin, C. (2011). Book publishers ready for 2D Barcodes?. Retrieved April, 2012, from. http://www.thirdscreenrevolution.com/mobile/2011/05/book-publishers-ready-for-2dbarcodes/. Mayer, R. E. (2001). Multimedia learning. Cambridge University Press. Mayer, R. E. (2003). The promise of multimedia learning: using the same instructional design methods across different media [electronic version]. Learning and Instruction, 13(2), 125–139. Mayer, R. E., & Anderson, R. B. (1992). The instructive animation: helping students build connections between words and pictures in multimedia learning [electronic version]. Journal of Educational Psychology, 84, 444–452. Mayer, R. E., & Moreno, R. (1998). A split-attention effect in multimedia learning: evidence for dual processing systems in working memory. Journal of Educational Psychology, 90, 312–320. Mayer, E. R., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. Metcalf, D., & Rogers, D. (2010). Contextual learning and memory retention: the use of near field communications, QR codes, QBIC, and the spacing effect in location based learning. In T. T. Goh (Ed.), Multiplatform e-learning systems and technologies: Mobile devices for ubiquitous ICT-based education (pp. 309–320). Hershey, New York: Information Science Reference. Motiwalla, L. F. (2007). Mobile learning: a framework and evaluation. Computers & Education, 49(3), 581–596. Ozcelik, E., & Acarturk, C. (2011). Reducing the spatial distance between printed and online information sources by means of mobile technology enhances learning: using 2D barcodes. Computers & Education, 57(3), 2077–2085. Ozdemir, S. (2010). Supporting printed books with multimedia: a new way to use mobile technology for learning. British Journal of Educational Technology, 41(6), 135–138. Park, Y. (2011). A pedagogical framework for mobile learning: categorizing educational applications of mobile technologies into four types. The International Review of Research in Open and Distance Learning, 12(2), 78–102. Quinn, C. (2001). Get ready for m-learning. Training and Development, 20(2), 20–21. Ramsden, A. (2008). Are QR codes the future of mobile learning?. Retrieved May, 2012, from. http://mlearning.edublogs.org/2008/03/27/andy-ramsden-are-qr-codes-thefuture-of-mobile-learning/. Rasch, T., & Schnotz, W. (2009). Interactive and non-interactive pictures in multimedia learning environments: effects on learning outcomes and learning efficiency. Learning and Instruction, 19, 411–422. Saran, M., Seferoglu, G., & Cagiltay, K. (2009). Mobile assisted language learning: English pronunciation at learners’ fingertips. Eurasian Journal of Educational Research, 97–114. Schwan, S., & Riempp, R. (2004). The cognitive benefits of interactive videos: learning to tie nautical knots. Learning and Instruction, 14, 293–305. Segers, E., & Verhoeven, L. (2009). Learning in a sheltered internet environment: the use of WebQuests. Learning and Instruction, 19(5), 423–432. Seisto, A., Federley, M., Kuula, T., Paavilainen, J., & Vihavainen, S. (2011). Involving the en-users in the development of language learning material. International Journal of Mobile and Blended Learning, 3(2), 43–56. Sharples, M., Taylor, J., & Vavoula, G. (2005). Towards a theory of mobile learning. Retrieved May, 2012, from. http://www.mlearn.org.za/CD/papers/Sharples Theory of Mobile.pdf. Susono, H., & Shimomura, T. (2006). Using mobile phones and QR codes for formative class assessment. InMéndez-Vilas, A., Solano Martín, J. A. A., González, M., & González, J. M. (Eds.). (2006). Current developments in technology-assisted education, Vol. 2 (pp. 1006–1010). Badajoz, Spain: Formatex. Sweller, J. (1999). Instructional design in technical areas. Camberwell, Australia: ACER Press. Traxler, J. (2007). Defining, discussing and evaluating mobile learning: the moving finger writes and having writ. International Review of Research in Open and Distance Learning, 8(2), 1–12. Traxler, J. (2009). Current state of mobile learning. In M. Ally (Ed.), Mobile learning: Transforming the delivery of education and training (pp. 9–24). AU press, Athabasca University. Traxler, J., & Dearden, P. (2005). The potential for using SMS to support learning and organisation in Sub-Saharan Africa. Proceedings of Development Studies Association Conference. Milton Keynes. Tversky, B., Morrison, J. B., & Betrancourt, M. (2002). Animation: can it facilitate? International Journal of Human-Computer Studies, 57, 247–262. Uden, L. (2007). Activity theory for designing mobile learning. International Journal of Mobile Learning and Organization, 1(1), 81–102. Virvou, M., & Alepis, E. (2005). Mobile educational features in authoring tools for personalized tutoring. Computers & Education, 44(1), 53–68. Woody, W. D., Daniel, D. B., & Baker, C. A. (2010). E-books or textbooks: students prefer textbooks. Computers & Education, 55(3), 945–948. Yau, J. Y., & Joy, M. (2009). A mobile context-aware framework for managing learning schedules: data analysis from an interview study. International Journal of Mobile and Blended Learning, 1(4), 29–55. Zurita, G., & Nussbaum, M. (2007). A conceptual framework based on activity theory for mobile CSCL. British Journal of Educational Technology, 38(2), 211–235.