Current Instructional Design Models and Principles for Effective E- and Mobile Learning

Transcription

1 Current Instructional Design Models and Principles for Effective E- and Mobile Learning Minjuan Wang San Diego State University & EBTIC Research Fellow Felicia Brown San Diego State University Jason W.P. Ng Etisalat BT Innovation Centre (EBTIC) Chief Scientist Abstract: As an attempt to identify how to effectively design learning activities and content for cloud learning, this paper explores current models and principles for designing effective products for elearning and cloud learning (clearning). In addition, we examine the graphical and programmatic aspects of good online and mobile elearning products. It is clear that more research is needed to fully understand how best to design instruction for mobile and cloud learning experiences. Introduction The root of Instructional Systems Design is a systematic process for creating effective instructional solutions. That is, Instructional Design (ID) is a framework for learning (Siemens, 2002). This framework requires designers to analyze the desired outcomes and content and apply the appropriate design model to achieve the learning outcomes. There are quite a few generic design models that are customizable and highly effective in creating instructional solutions that meet different objectives in learning. However, quite often, these instructional design models are not suited for designing electronic learning (elearning), mobile learning (mlearning), and the newly emerged cloud learning (clearning) ELearning design, including computer-base training, web-based training and other electronic delivery forms of training and teaching (Kurtus, 2000), requires a delicate balance between education and technology to provide a truly effective learning experience. Most often, the instructional designer's role is that of "bridging concepts between the two worlds (Siemens, 2002). The instructional design process for most designers has a primary focus on the learning; however, the design process of elearning instructional design requires a marriage between the

2 pedagogical or andragogical requirements of e-learners, content from the subject matter expert (SME), and the work of graphic designers and web programmers. ELearning has become increasingly more popular in the technological societies of modern age, and, more recently, mobile technologies have exploded in the marketplace to the point where mobile learning (mlearning) has begun to emerge as an important factor in elearning design. The definition for mlearning has evolved from studying with mobile devices to the great learner mobility resulting from the use of mobile technologies (Sharples, Milrad, Sánchez, & Vavoula, 2009; Traxler, 2010; Wang, Shen, Novak, & Pan, 2009). A handful of research has revealed how mlearning can enhance both learning experiences and outcomes. However, elearning designers still need to figure out how to design for mlearning (Wang &Shen, 2011). Surprisingly, while mlearning is important in today s learning, the instructional design principles and models are still undefined. Therefore, the design for mobile devices mirrors that of elearning at this point in time despite the fact that mlearning has its unique benefits and limitations (Wang & Shen, 2011). With the rapid development of cloud computing, cloud learning (clearning) and mobile cloud learning (mclearning) have also come into discussion (Hirsch & Ng, 2010; Wang, 2011). Cloud learning is built on the three services models (infrastructure, platform, and software) but also has various definitions. Here we define cloud learning as a shared pool of learning courses, digital assets and resources, which instructors and learners can access via computers, all types of mobile devices, satellite, and even IP-TV (Wang, 2011). The cloud associated with learning is therefore similar to public utilities, which consumers can plug in and use anytime and anywhere. Figure 1 illustrates the structure of the aforementioned cloud learning. For instance, one type of cloud learning occurs through mobile and social learning via Web. 3.0 technologies, consisting of semantic webs and the intelligent tools (itools). Learners can cooperate anywhere in the Cloud ; they study, experiment, explore, complete tasks, and provide assistance to others. Learners in the Cloud can also select suitable resources and record individual learning outcomes and processes (Wang, 2011).

3 Figure 1. A model for Cloud Learning Mobile Cloud education or Learning (Fig. 2), a novel unification of cloud and mobile learning, is a relatively new concept that holds great promises for the future development of education (Hirsch & Ng, 2011). The two learning modalities can naturally merge, because the characteristics of cloud learning overlaps with mobile learning. The definition of mobile learning has also been evolving, from the early definitions of learning with mobile devices (Kossen, 2001) to the current one that emphasizes learner mobility resulting from the use of mobile devices (Wang et al., 2009). In both definitions, users can acquire learning content from the centralized shared resources and engage in anytime-anywhere context-aware learning via portable devices.

4 Figure 2. The concept of mobile cloud education/learning (Hirsch & Ng, 2010). The purpose of this paper is three fold. First, we will describe the most important and applicable learning theories for elearning solutions. Second, we will describe effective elearning design models and principles. Finally, we will describe the graphical and programmatic aspects of good online and mobile elearning solutions. Learning Theory for elearning solutions The instructional design of elearning solutions must first recognize the learner is not in a traditional classroom setting with a motivational and/or supervisorial instructor facilitating the learning process. Learner motivations, attention to learning content, understanding of the relevance of the subject matter and ability to have social interaction with peers are not as easy to facilitate. Therefore, the most relevant learning theories for elearning solutions seem to include Gagne s 9 events, Piaget s theory of cognitive development, and Vygotsky s social cognitive/development theory.

5 Most current elearning design uses Gagne s theory of learning throughout the design process. According to Gagne, there are nine critical events (e.g., gain attention, inform objectives, stimulate recall, present stimulus, provide guidance, elicit performance, provide feedback, assess performance, enhance retention and transfer) that stimulate processes needed for effective and long lasting learning (Carr, A. M. & Carr, C.S., 2000). ELearning design that emphasizes the attention, motivation and retention and transfer phases of Gagne s 9 events of instruction is able to build the connections between new information and the current knowledge base (Cassarino, 2003). This approach allows instructional designers to effectively organize and sequence instructional content in order to maximize the transfer of knowledge and skills from the learner interface (LI), learning management system (LMS) or content management system (CMS) to the learner without loss of motivation or content understanding. Emphasis on the application of constructivism which provides students with the opportunity to construct their own understanding is growing in the design of elearning solutions (Nichols, 2003). To begin, many elearning instructional designers are applying Piaget s theory of cognitive development. According to Atherton (2011), Piaget proposed that children learned through the development of schema, or ideas, assimilated from the environment. The development of schema must be considered by elearning instructional designers because active learning requires that schema be developed by the learner through experiences. As a result, elearning will be more effective if it provide constructivist learning environments whereby students can actively engage in authentic and applicable projects and problem-solving situations. Allen (in Steen, 2008) also reminded elearning instructional designers that we learn 70% of what we discuss with others, another key feature of constructivism. Vygotsky (2008) theorized that social learning preceded development and that every function in the child s cultural development appears twice: first, on the social level, and later, on the individual level. Social constructivists believe that most learning takes place in a social context, and is facilitated by the interactions that students have with others (Berge, 2002). Therefore, elearning design should

6 build in a high degree of engagement by leveraging Vygotsky s social cognitive/development theory and interaction with the content. ELearning Design Models The best known and most frequently used instructional design model is ADDIE., which has five phases as seen in Figure 3. In this design model, designers progress from distinct phase to the next. The analysis phase places an emphasis on defining what is to be learned, and the design phase places emphasis on how learning will occur. Figure 3: ADDIE process (Chan and Robbins, 2006) The development emphasizes the authoring and creation of the elearning product, and the implementation and evaluation phases emphasize going live and accessing the success or failure of learning (Chan & Robbins, 2006). While ADDIE model is the most frequently used, it is also the most time and labor intensive with respect to elearning instructional design.

7 The Dick and Carey Instructional Systems Design (ISD) model (figure 4) follows closely behind ADDIE in use by elearning instructional designers. This model espouses a systematic method for designing instruction base upon a reductionist model of breaking down instruction into small components. The instructional design targets the specific knowledge and skills that are to be taught; therefore, the appropriate conditions are provided for the learning outcomes. Although this design approach is popular, it has long been considered too rigid and time consuming for the most instructional design projects, especially for the fast-paced elearning design (Clark, 2004). This is clearly indicated in the fact that there are development-focused ten phases while the remainder of the phases refers to a form of planning such as analysis, requirements, design, or evaluation. This design approach works well for classroom instruction where content is presented live and the instructor/teacher can dynamically change instruction while the class is in session. However, this design approach is not appropriate for the student Figure 4: Dick and Carey Instructional Design Model (Clark, 2004) centered (user centered) and distance learning content (Carliner, 2008). An increasingly popular approach to elearning design is to design for a high level of learner motivation. As a result, Keller s ARCS motivational model has become widely used in many instructional circles. ARCS is an acronym for the four elements of learner motivation: attention, relevance, confidence and satisfaction; each of which are critical to successful learning outcomes. Keller (2006) describes his model as a problem solving approach to designing the motivational aspects of learning environments to stimulate and sustain students motivation to learn

8 ( Figure 5 illustrates the motivational design process used by many instructional designers in recent years in real practice. It begins with the course description and audience analysis and ends with an evaluation of learner reactions, along with revisions to ensure that learner satisfaction is met. Berge (2002) reported that although it is not clear from research that interaction improves the quality of instruction in elearning, the research does indicate that interaction is important to learner satisfaction. Therefore, instructional design focusing on elearner satisfaction through increased interaction will ensure that elearning outcomes are met and the instructional product will be effective.

9 Figure 5: Steps in Motivation Design (Balaban-Sali, 2008)

10 User-centered design (UCD) process has also become increasingly popular in elearning design. UCD is defined as an approach to creating experiences for people with their needs in mind where usability is the primary focus with secondary considerations such as desirability, legibility, and learnability (Evans, 2002). The goal is to include users in the decision-making process. In UCD, instructional designers first analyze the instructional need, audience and elearning solution. After this initial phase, instructional designers then begin to actively involve the end-user (learner) in the design process by using various forms of inquiry such as interviews, focus groups and/or questionnaires. The final phase of the design process involves getting feedback on storyboard and navigation systems, etc. In addition, instructional designers must also continually perform prototype testing with users in order to highlight problems with the elearning product and allow users to suggest improvements on the usability (Evans, 2002). The newest and most successful elearning instructional design method in use today is successive approximation or rapid prototyping. This design approach is evolutionary, rapid and allows instructional designers to move quickly through the initial phases of design to a rapid prototype ready for testing. Steen (2008) describes successive approximation as an iterative approach whereby the designer repeatedly applies a three step process of design, prototype, and review in a rapid but controlled process to produce quick but appropriate elearning ( Figure 6: Successive Approximation (Allen, 2003)

11 ELearning Design Principles ELearning design is part art and part science; it uses learning and training theory, relies on a solid understanding of graphic design tools and an understanding of the knowledge and skills to be delivered. And it is a blend of the use of color, style, sound, video, and graphic/web interfaces. In order to be truly effective, first that blend must have the following characteristics: easy accessibility, consistency and accuracy in the message, user friendly, entertaining, being memorable, and relevant (Steen, 2008). Second, it must provide learner activity, feedback, scenario-based learning experiences, proper delivery methodology, sequential context, and influential effects (Brown & Voltz, 2005). Finally, elearning should also emphasize metacognition in the design where learners can guide their own instructional experience. Learners can guide their own elearning experience when designers provide users with feedback so that they know that they are making progress, provide users with navigation maps so that users can find where they are during instruction, provide cues such as maps or menus as advance organizers (Cassarino, 2003). Sound interface design is also important in the instructional design of elearning. First, the interface design should involve attention to detail with respect to graphics and screen design. Second, the navigation bar and instructional bar should be dynamic and change in response to the learner s needs. For example, a change may occur on the navigation in response to a pressed button on the instructional bar. Third, the screen area should allow students to explore instructional content in the presentation frame while still having access to instructional and navigation panels. Finally, a fixed format of should be used in the design and development of the instructional interface (Cassarino, 2003) so that users/learners can predict how to navigate through the instructional content. The fixed format of design for the instructional interface, also known as the graphical user interface (GUI) should be more than just pretty because this is how the designer and instructor communicates content to the user/learner. Metros and Hedberg (2006) state that poor GUI design can place cognitive demands upon the learner that can reduce interest and divert

12 attention away from the primary learning tasks (p. 108). Therefore, elearning instructional designers must be careful to design a functional, communicative and aesthetically pleasing GUI without placing a cognitive overhead (overload) on the user/learner. Cassarino (2003) explains the concept of cognitive overhead as the fact that humans have a limited capacity for information processing. In addition, she suggests, to elearning instructional designers, to provide clear direction on how to move forward and backward which could involve the ability to move, resize or manually open/close windows. The final principles of elearning design are that of basic instructional design. These principles involve an understanding of the following: basic instructional strategies, learner needs, hierarchical content, practice, assessment, and evaluation. These basic principles are then thereby expanded to an elearning context when the instructional designer has considered the appropriate technology for delivery and provided suitable elearning experiences through multimedia applications (Brown & Voltz, 2005). Mobile Learning Design Principles For mlearning to attain its full potential, it is essential to develop pedagogy and instructional design tailored to the needs of this new learning environment. At present, there is a lack of research on message design for mlearning. Wang and Shen (2011) are the very first to explore the principles and processes of message design for mlearning, including the influence of learning and cognitive theories, human computer interaction principles, devices and methodologies. And their article presents a number of practical guidelines for designing instructional messages for mlearning. Message design is the way that information is presented to the learner. Instructional message design is the manipulation and planning of signs and symbols that can be produced for the purpose of modifying the cognitive, affective or psychomotor behavior of one or more persons (Lohr, 2011, p. 1). With the increasing use of technologies in teaching, message design also involves applying a variety of theories (perception, learning, communication and systems) to the design and evaluation of instructional media (Lohr, 2011).

13 Wang and Shen (2011) generate the following Implications for practice: It is important for instructional designers to master the skills required to design multimedia messages that promote meaningful learning (Mayer & Moreno, 2002, p. 107). Design learning based on the learning environment (formal vs. informal). Design content that can be used on different devices based on the typology and the activities these devices can support. Design for learner mobility (use of audio, captions, icons, color and symbols). Use captioning to provide adaptable messages for differing contexts and provide guidelines on both fonts and placement. Use color as an example of cultural considerations in designing for mlearning. In addition, they also raised many questions for future research. In particular, researchers need to explore possible solutions for some of the following pressing issues: How will learning theories influence the development of instructional design strategies for mobile devices, and vice versa? How can instructional designers leverage existing captioning standards into standards that fit the specificities of mobile devices? How will development in network access, device design and information exchange extend the experiential possibilities of mlearning? How will context (including cultural, environment and device) effect the specification of future mlearning systems? The answers to these questions would help instructional designers form a baseline degree of knowledge that can guide future data collection. Equally, they will lead to design and development criteria that will improve mlearning courseware and products. Conclusions The elements of elearning design presented in this paper are built upon a solid foundation of learner needs, learning outcomes, cognitive processes, and instructional strategies. Each of these foundational elements is critical to the creation of effective elearning and involves a strong collaboration between instructional designers, educational technologists,

14 graphic designers, web/software developers, educators and students/users. However, elearning instructional design requires a more dynamic approach than traditional instructional design. Therefore, the need for more dynamics in instruction combined with the high demand for more elearning solutions requires an evolution in elearning design and a higher level of productivity. More use of current user centered and evolutionary design methodologies like that of Agile design, rapid prototyping, and successive approximation instead of the antiquated and less iterative methodologies such as ADDIE will allow elearning designers to create more robust elearning solutions rather than the typical uni-dimensional solutions currently being developed. In addition, in order to meet the need for increased productivity in elearning, it is clear that there should more use of rapid development applications such as Articulate and Presenter over more time consuming applications such as Captivate. The reality is that creating elearning solutions is more time consuming than traditional learning solutions; therefore, using software applications that do not keep up with the high demand for productivity does not allow the actual design to make it into production on regular basis. The focus of this article has been that of elearning design; however, it should be noted elearning design can only be generically applied to mobile elearning (mlearning) and even mobile cloud learning (MCL). Because mobile cloud learning is an emerging instructional area, future targeted research will be required to fully understand how best to design instruction for such new learning experiences. At present, it can be concluded that mlearning and mobile cloud learning will continue to use some of the same software applications (ex. Flash) and more iterative instructional design methodologies in order to keep up with increased demand in the coming years. References Allen, M. (2003). Michael Allen s guide to elearning: building interactive, fun, and effective learning programs for any company. Hoboken, NJ: John Wiley & Sons, Inc. Atherton, J.S. (2011). Learning and teaching; piaget's developmental theory. Retrieved from Balaban-Sali, J. (2008, July). Designing motivational learning systems in distance education.

15 Turkish Online Journal of Distance Education, 9 (3):13, 149. Retrieved from Berge, Z. (2002). Active, interactive, and reflective elearning. Quarterly Review of Distance Education, 3(2), 181. Retrieved from EBSCOhost Brown, A.R. & Voltz, B.D. (2005). Elements of effective elearning design. International Review of Research in Open and Distance Learning, Retrieved from Carliner, S. (2008). Designing and developing elearning projects: a three-tiered approach. In The ELearning Handbook: A Comprehensive Guide to Online Learning. Retrieved from Carr, A.M., & Carr, C.S. (2000). The Nine events of Instruction. Retrieved from Cassarino, C. (2003). Instructional design principles for an elearning environment. Quarterly Review of Distance Education, 4(4), Retrieved from EBSCOhost. Chan, C.H. & Robbins, L.I. (2006). ELearning systems: promises and pitfalls. Academic Psychiatry, 30(6), 491. Retrieved from Clark, D. (2004). The dick and carey Model Retrieved from Evans, M. (2002, October 8). Peter Merholz and Nathan Shedroff on user-centered design. Digital Web Magazine, Retrieved from Hirsch, B., & Ng, J. W.P. (2010). Education beyond the cloud: anytime-anywhere learning in a smart campus environment. Retrieved from Keller, J.M. (2006). What is the arcs model? Retrieved from Kossen, J. S. (2001). When e-learning becomes m-learning" Palmpower Magazine. Retrieved October 1, 2010 from Kurtus, R. (2000). What is e-learning? Retrieved from Learning.pdf Lohr, L. (2011). Syllabus for instructional message design. Retrieved May 1, 2011, from Mayer, R. E. & Moreno, R. (2002). Aids to computer-based multimedia learning. Learning and Instruction, 12, Metros, S. E., & Hedberg, J. G. (2006). Engaging learners through intuitive interface. In D. Hung & M. S. Khine (Eds.), Engaged learning with emerging technologies (pp ). New York: Springer Publishing. Nichols, M. (2003). A theory for elearning. Educational Technology & Society, 6(2),1. Retrieved from Sharples, M., Milrad, M., Arnedillo Sánchez, I., & Vavoula, G. (2009). Mobile learning: Small devices, big Issues. In N. Balacheff, S. Ludvigsen, T. de Jong, A. Lazonder & S. Barnes (eds.) Technology Enhanced Learning: Principles and Products. Heidelberg: Springer, pp

16 Siemens, G. (2002, September 30). Instructional design in elearning. Retrieved from Social development theory (Vygotsky). (2008). Retrieved from Steen, H.L. (2008). Effective elearning design. MERLOT Journal of Online Learning and Teaching, 4(4), 526. Retrieved from Traxler, J. (2010). Distance education and mobile learning: Catching up, taking stock. Distance Education, 31(2), Wang, M. J., Shen, R. M., Novak, D., & Pan, X. Y. (2009). The impact of mobile learning on students' learning behaviours and performance: Report from a large blended classroom. British Journal of Educational Technology, 40(4), Wang, M. J. (Nov. 2011). An Intelligent Learning Model Based on Cloud Computing, Internal report (Intelligent Campus initiative) submitted to Etisalat BT Innovation Centre (EBTIC), Abu Dhabi, UAE. Wang, M. J., & Shen, R. M. (2011). Message design for mobile learning: Learning theories, human cognition, and design principles. British Journal of Educational Technology, 38(2),