Instructional Design Model for E-Learning
Introduction
As e-learning (electronic learning) matures and information and communication technology (ICT) advances at break-neck speed, the intricate complexities of contemporary instructional design for e-learning, becomes apparent. Rapidly shifting e-learning environments and rising diverse adult populations create extensive challenges and opportunities for practitioners and researchers to plan, develop, test, and implement the most superlative instructional models feasible (Engelbrecht, 2003). Innovation and creativity are key elements of 21st Century instructional design model. Sophisticated e-learning models warrant current, comprehensive research, planning, development, and testing, prior to implementation in higher education organizations, specifically, those that offer online degree programs (Snyder, 2009).
"As online learning evolves, distance education is expanding the delivery options and learning strategies available to institutions and students" (Ladd, 2012, p. 236). Zang (2007) purports that designs for contemporary e-learning communities, make available opportunities and alternatives for e-learners and facilitators, to tap into the rhythms of the latest technological expansions. Following this advice, however, may mean merging existing designs with newly developed theoretical models. Alternatively, it may additionally mean, scrapping designs that do not construct expected learner outcomes, in order to assemble entirely new theories and models that fruitfully meet the explicit needs and desires of adult e-learners. "New instructional-design theories are needed to guide the design of instruction using new technologies and tools that the Internet offers" (Snyder, 2009, para 3).
Background
Instructional design models are formulated and constructed via a logical, structured development process. These design models are grounded in and supported by learning theory perspectives. Smith (2007) asserts, "Learning theory is the study of how people learn." Further, Mahon (2012) & Lim & Yeon (2009) emphasize how each instructional design relies heavily on particular theoretical design principles to validate cost of development and prolonged usage in educational settings. Over a decade ago, Garrison (2000) submitted, "... theoretical frameworks and models are essential to the long-term credibility and viability of a field of practice" (para 23), in this case, adult e-learning. E-learning models have established a relevant place in higher education through the speedy evolution of the Internet, multimedia applications, and ICT progress, as well as, adult-learner demand.
Today, universities are tasked with strategic instructional design decisions, which embrace digital learning resources, multimedia tools, and ICT, for optimal coaching and learning prospects. Once the instructional design resources and technology are investigated, planned, selected, and implemented, it is an expense, time-consuming venture to create substantial changes in the model (Bandhana, 2010). Consequently, over the past ten years, a great many universities and colleges offering online degree programs are following an emerging trend: Purchasing pre-packaged, commercially competitive instructional models, instead of developing pertinent learning materials well-suited for diverse learning-communities and specialized degree programs (Lee & Hung, 2012; Mohanna & Waters, 2008).
Uniting Theoretical Frameworks
Theoretical frameworks for instructional design have the capacity to inform, shape, and guide practice, and therefore, are an essential component of formulating instructional design models (Bandhana, 2010). The first aim of designing an instructional model for an adult e-learning environment is to determine the intended audience. For example, novice undergraduates have considerable less experience with collegial concepts, as do graduate learners. In this fashion, the model's design is developed with a specific learning community at the forefront of the proposed design. Understanding the learner-community demographics, prior knowledge and experience, preferences, and needs play an integral role in the development and design process of instruction (Mohanna & Waters, 2008). The second aim of an e-learning instructional model is to establish the type of learning environment involved, asynchronous (encountered at differing times and locations), synchronous (encountered in real-time and possibly, different locations) or a combination of each. Knowing where the learning will take place, guides the third aim, which is, the theoretical perspective, from which the model will operate, as the outline for instruction, delivery, and learning success (Smith, 2007).
The theoretical framework for this study, recommends an instructional design model that finds its basis in Cognitive Load Theory united with Instructional Technology [IT, sometimes referred to in literature, as Instructional Systems Technology (IST); for an adult e-learning environment. (Makki & Makki, 2012)] Predominantly, when educators and researchers consider blending instructional models, an assumed amalgamation is made of e-learning with conventional learning. However, presently there exists a trend toward uniting, research-based, tested learning theories to provide a cohesive instructional model geared toward diverse adult e-learners (Wold, 2011). Instruction, engagement, interaction, learning activities and tasks can be facilitated and managed effectively, when CLT and IT are united, as an approach to improving the e-learning environment of higher education. Electronic learning is not simply a new kind of learning; instead, it involves research, theory, design suppositions, and practice, integrated with instructional technology as its mode (Nam & Smith-Jackson, 2007).
Educational policy-makers and administrators seem to prefer that the instructional design models bond to archaic, systematic design thoroughfares (Weiler, 2011). However, scholars, educators, institutions, and learners involved in e-learning are calling for inventive modifications in instructional designs that align with current and future learning technologies (Ladd, 2012). This study is an experiment in uniting theoretical perspectives to improve instructional designs, which benefit the various stakeholders throughout the e-learning industry, most importantly, the learners.
Cognitive Load Theory
Cognitive Load Theory (CLT) encompasses theoretical concepts and assumptions that yield an array of benefits for adult e-learners. CLT endorses assumptions that human working memory is limited and hindered in its capacity to process valuable learning information when it is overloaded with large quantities of bulky, complex data presentations (Paas, Renkl &Sweller, 2004). Further, CLT is composed of three divergent components: 1) intrinsic, 2) extraneous, and 3) germane loads. Research literature refers to these components as the Cognitive Architecture of CLT, which involves the totality of the human brains capacity for appropriately processing information that leads to learning (Sweller, van Merriënboer & Paas, 1998).
First, Intrinsic Load Theory (ILT) relates to the difficulty and arrangement of instructional design content. For example, instructional content is more advantageous to the learning brain (working memory), when absorbed and processed in bite-size segments, verses large complex masses of information (de Jong, 2010). Further, the ideal principle is to begin instructional content with simple activities and tasks, building toward supplementary complex activities and tasks, as learning progresses. Thus, segments of information gradually form the whole concept, which improves data processing and facilitates genuine learning. "Learning is an active process of filtering, selecting, organizing, and integrating information based upon prior knowledge" (Mayer, 2012).
Second, Extraneous Load Theory (ELT) relates to the load created by instructional matter utilized for the presentation of content. For the e-learning environment, the idea is to employ properly balanced delivery systems and multimedia applications that do not hinder or overload the way in which content is presented (de Jong, 2010). For example, it is superfluous for learners to view large quantities of content materials that contain descriptive text and graphic images within the same visual area, creating redundant content. This format causes the brain to split working memory attention. Case in point, viewing an instructional PowerPoint slide that indicates a textual description of a geometric shape and a diagram illustrating the shape. The theory is that using two or more types of information for the exact same content, overloads the working memory and spits learner attention to a significant extent (Evans, 2012).
Third, Germane Load Theory (GLT) relates to the load required for the entirety of the learning process (de Jong, 2010). GLT is devoted to the construction of knowledge learning and is considered the theoretical effective load theory (Mayer, 2012). GLT should be promoted within the instructional design above ILT and ELT, because it encourages successful learning experiences and knowledge acquisition to meet prescribed learning goals and outcomes (van Merriënboer & Sweller, 2005).
Instructional Technology
Instructional Technology (IT) represents instruments and mediums with technologically inventive, rich learning advancements, which aid e-learners to function from the germane load segment of his or her cognitive capacity. IT formats include, Learning Management Systems (LMS), such as Blackboard, Web 2.0 resources, such as Wikispaces or Blogger, and multimedia applications, such as, podcasts and videos, exemplify a miniature sample of accessible, learning instruments and mediums that can be carefully managed within the e-learning environment to promote germane cognitive load for all learners (Makki & Makki, 2012). Friesen (2009) suggests that IT integration, presents instructional designers with a variety of options to promote real-world learning opportunities, successful learning outcomes, and academic achievement.
Theory in Action
E-learning designs provide optimal circumstances for learners to function with confidence and self-direction, while utilizing instructional technology that best suits his or her preferences and cognitive capacity. Differentiating IT for an adult-learner, who recognizes his or her learning preference for audio-visual information verses textual formats, has the choice to listen and view instructional materials via IT components that affords the learner a fulfilling learning experience, while acquiring imperative instructional content. Alternatively, differentiating IT for an adult-learner, who prefers textually-rich, descriptive information, for his or her content-gathering arrangement, may elect to read, highlight, and take notes digitally via e-text layouts, within the IT design. Therefore, IT is the launch-pad for designing active, meaningful learning experiences in the e-learning environment (Gawande, 2010).
In addition, instructional designers, who unite CLT with IT, create theoretical frameworks that afford e-learners ample choices to interact dynamically with the instructional content, and therefore, encourage active learning, with lower risk of ELT (Cheon & Grant, 2012). When ELT is reduced, GLT is increased, creating a favorable situation for working memory to function at higher capacity (de Jong, 2010). Zimmerman (2012) suggests that interaction with instructional content is the root of effective learning. IT provides the effective means for interaction between content information and the learner, which encourages GLT. These elements provide unique conditions to promote active learning and course completion.
Summary
In order for e-learning to continue its successful journey throughout the 21st Century, it will require endurance and willingness toward changes in theoretical perspectives, research evidence, instructional design frameworks, practices, and methodologies. In addition, e-learning needs to keep considerable pace with future technology and multimedia advancements, as well as, emerging learning theories and models. Although Cognitive Load Theory has a lengthy history in education, it faces new opportunities of usefulness in e-learning instructional design, when united with Instructional Technology. Perhaps, this study will spur a much-needed paradigm shift for the improvement and longevity of instructional designs, which unite Cognitive Load Theory with Instructional Technology.
References
Bandhana, J. (2010). Designing instructional design: Emerging issues. Journal of Education and Practice, 1(3), 1-8. Retrieved from http://www.iiste.org/Journals/index.php/JEP/article/download/1656/1618
Cheon, J. & Grant, M. M. (2012). Examining the relationships of different cognitive load types in relation to user-interface in web-based instruction. Journal of Interactive Research, 23(1), 29-55. Retrieved from http://www.editlib.org.proxy1.ncu.edu/p/34577/paper_34577.pdf
Defazio, J. (2006). Theory into practice: A bridge too far? American Association of Adult and Continuing Education Journal (AACE), 14(3), 221-233. Retrieved from http://www.editlib.org/p/18923/article_18923.pdf
de Jong, T. (2010). Cognitive load theory, educational research, and instructional design: Some food for thought. Instructional Science, 38, 105-129. doi: 10.1007/s11251-009-9110-0
Evans, T. (2012). Cognitive load research & theory: Implications for instructional design. Retrieved from http://www.slideshare.net/tmevans123/cognitive-load-theory-14373581
Engelbrecht, E. (2003). A look at e-learning models: investigating their value for developing an e-learning strategy. Progressio, 25(2), 38-47. Retrieved from http://uir.unisa.ac.za/xmlui/bitstream/handle/10500/4992/engelbrecht.pdf?...1
Friesen, N. (2009). Re-thinking e-learning research. International Review of Research in Open and Distance Learning, 10(3). Retrieved from http://cider.athabascau.ca/CIDERSessions/nfriesen/Introduction%20to%20E-Learning.pdf
Garrison, R. (2000). Theoretical challenges for distance education in the 21st Century: A shift from structural to transactional issues. International Review of Research in Open and Distance Learning, 1(1). Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/2/333
Gawande, V. (2010). Differentiated elearning: The possible approaches. International Journal of the Computer, the Internet and Management, 18(15), 1-15.4. http://www.elearningap.com/eLAP2010/Proceedings/15_Full_Dr.Virendra%20Gawande_Differentiated%20eLearning.pdf
Grant, M. M. (2010). Comparing instructional design models: Retrieved from http://www.slideshare.net/msquareg/comparing-instructional-design-models
Knapp, L.G., Kelly-Reid, J.E., & Ginder, S.A. (2012). Enrollment in postsecondary institutions, (2011 report). National Center for Education Statistics (NCES). Washington, D.C. Retrieved from http://nces.ed.gov/pubs2012/2012174rev.pdf
Ladd, L. (2012). The state of higher education in 2012: Technology will continue to transform your institution. Contemporary Issues in Education Research, 5(4), 235-239. Retrieved from http://journals.cluteonline.com/index.php/CIER/article/view/7268/7337
Lim, C. & Yeon, E. (2009). Review of current studies in instructional design theory in Korea: Major trends and future directions. Asian Pacific Education Review, 10, 357-364. doi: 10.1007/s12564-009-9027-y
Makki, B., & Makki, B. (2012). The impact of integration of instructional systems technology into research and educational technology. Creative Education, 3(2), 275-280. Retrieved from http://search.proquest.com/docview/1011488262?accountid=28180
Mayer, R. (2012). Learning theories: Cognitive theory of multimedia learning. Retrieved from http://www.learning-theories.com/cognitive-theory-of-multimedia-learning-mayer.html
Mohanna, K. & Waters, M. (2008). Multiple perspectives on learning: But which way for
instructional design? Education for Primary Care, 19, 563-568. Retrieved from http://proxy1.ncu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=35156501&site=eds-live
Nam, C. & Smith-Jackson, T. (2007). Web-based learning environment: A theory-based design process development and evaluation. Journal of Information Technology Education, 6, 23-43. Retrieved from http://jite.org/documents/Vol6/JITEv6p023-043Nam145.pdf
Paas, F., Renkl, A. & Sweller, J. (2004). Cognitive load theory: Implications of interaction between information structures and cognitive architecture. Instructional Science, 32, 1-8.
Retrieved from http://www.ucs.mun.ca/~bmann/0_ARTICLES/CogLoad_Paas04.pdf
Schulmeister, R. (2011). eLearning in the usa: The standard? The benchmark? Eleed Journal, 3(1). Retrieved from http://eleed.campussource.de/archive/3/688/metadata
Smith, K. J. (2007). Instructional design theory. Retrieved from http://www.ic.arizona.edu/ic/edp511/isd1.html
Sweller, J., van Merriënboer, J. & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251-296. Retrieved from http://link.springer.com/content/pdf/10.1023%2FA%3A1022193728205
Snyder, M. M. (2009). Instructional-design theory to guide the creation of online learning communities for adults. TechTrends, 53(1), 48-56. Retrieved from http://search.proquest.com/docview/223119414?accountid=28180
U.S. Department of Education. (2006). A test of leadership: Charting the future of U.S. higher education. Retrieved from http://curriculumreform.org/wp-content/uploads/2010/09/US-Secretary-of-Education-Charting-the-Future-of-U.S.-Higher-Education.pdf
van Merriënboer, J. & Sluijsmans, D. (2009). Toward a synthesis of cognitive load theory,
four-component instructional design, and self-directed learning. Educational Psychology Review, 21, 55-66. doi: 10.1007/s10648-008-9092-5
Van Merriënboer, J. & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17, 147– 177. doi:10.1007/s10648-005-3951-0.
Weiler, H. (2011). Knowledge and power: The politics of education. Journal of Educational Planning and Administration, 25(3), 205-221. Retrieved from http://www.stanford.edu/~weiler/Texts11/JEPA_2011_reprint.pdf
Wold, K. A. (2011). Blending theories for instructional design: Creating and implementing the structure, environment, experience, and people (SEEP) model. Computer Assisted Language Learning, 24(4), 371-382. doi: 10.1080/09588221.2011.572900 Zang, C. (2007). Theory and practice: Reviewing technology-mediated research. MWAIS 2007 Proceedings. (paper 25). Retrieved from http://aisel.aisnet.org/mwais2007/25
Zimmerman, T. (2012). Exploring learner to content as a success factor in online courses. The International Review of Research in Open and Distance Learning, 13(4). Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/1302/229
Introduction
As e-learning (electronic learning) matures and information and communication technology (ICT) advances at break-neck speed, the intricate complexities of contemporary instructional design for e-learning, becomes apparent. Rapidly shifting e-learning environments and rising diverse adult populations create extensive challenges and opportunities for practitioners and researchers to plan, develop, test, and implement the most superlative instructional models feasible (Engelbrecht, 2003). Innovation and creativity are key elements of 21st Century instructional design model. Sophisticated e-learning models warrant current, comprehensive research, planning, development, and testing, prior to implementation in higher education organizations, specifically, those that offer online degree programs (Snyder, 2009).
"As online learning evolves, distance education is expanding the delivery options and learning strategies available to institutions and students" (Ladd, 2012, p. 236). Zang (2007) purports that designs for contemporary e-learning communities, make available opportunities and alternatives for e-learners and facilitators, to tap into the rhythms of the latest technological expansions. Following this advice, however, may mean merging existing designs with newly developed theoretical models. Alternatively, it may additionally mean, scrapping designs that do not construct expected learner outcomes, in order to assemble entirely new theories and models that fruitfully meet the explicit needs and desires of adult e-learners. "New instructional-design theories are needed to guide the design of instruction using new technologies and tools that the Internet offers" (Snyder, 2009, para 3).
Background
Instructional design models are formulated and constructed via a logical, structured development process. These design models are grounded in and supported by learning theory perspectives. Smith (2007) asserts, "Learning theory is the study of how people learn." Further, Mahon (2012) & Lim & Yeon (2009) emphasize how each instructional design relies heavily on particular theoretical design principles to validate cost of development and prolonged usage in educational settings. Over a decade ago, Garrison (2000) submitted, "... theoretical frameworks and models are essential to the long-term credibility and viability of a field of practice" (para 23), in this case, adult e-learning. E-learning models have established a relevant place in higher education through the speedy evolution of the Internet, multimedia applications, and ICT progress, as well as, adult-learner demand.
Today, universities are tasked with strategic instructional design decisions, which embrace digital learning resources, multimedia tools, and ICT, for optimal coaching and learning prospects. Once the instructional design resources and technology are investigated, planned, selected, and implemented, it is an expense, time-consuming venture to create substantial changes in the model (Bandhana, 2010). Consequently, over the past ten years, a great many universities and colleges offering online degree programs are following an emerging trend: Purchasing pre-packaged, commercially competitive instructional models, instead of developing pertinent learning materials well-suited for diverse learning-communities and specialized degree programs (Lee & Hung, 2012; Mohanna & Waters, 2008).
Uniting Theoretical Frameworks
Theoretical frameworks for instructional design have the capacity to inform, shape, and guide practice, and therefore, are an essential component of formulating instructional design models (Bandhana, 2010). The first aim of designing an instructional model for an adult e-learning environment is to determine the intended audience. For example, novice undergraduates have considerable less experience with collegial concepts, as do graduate learners. In this fashion, the model's design is developed with a specific learning community at the forefront of the proposed design. Understanding the learner-community demographics, prior knowledge and experience, preferences, and needs play an integral role in the development and design process of instruction (Mohanna & Waters, 2008). The second aim of an e-learning instructional model is to establish the type of learning environment involved, asynchronous (encountered at differing times and locations), synchronous (encountered in real-time and possibly, different locations) or a combination of each. Knowing where the learning will take place, guides the third aim, which is, the theoretical perspective, from which the model will operate, as the outline for instruction, delivery, and learning success (Smith, 2007).
The theoretical framework for this study, recommends an instructional design model that finds its basis in Cognitive Load Theory united with Instructional Technology [IT, sometimes referred to in literature, as Instructional Systems Technology (IST); for an adult e-learning environment. (Makki & Makki, 2012)] Predominantly, when educators and researchers consider blending instructional models, an assumed amalgamation is made of e-learning with conventional learning. However, presently there exists a trend toward uniting, research-based, tested learning theories to provide a cohesive instructional model geared toward diverse adult e-learners (Wold, 2011). Instruction, engagement, interaction, learning activities and tasks can be facilitated and managed effectively, when CLT and IT are united, as an approach to improving the e-learning environment of higher education. Electronic learning is not simply a new kind of learning; instead, it involves research, theory, design suppositions, and practice, integrated with instructional technology as its mode (Nam & Smith-Jackson, 2007).
Educational policy-makers and administrators seem to prefer that the instructional design models bond to archaic, systematic design thoroughfares (Weiler, 2011). However, scholars, educators, institutions, and learners involved in e-learning are calling for inventive modifications in instructional designs that align with current and future learning technologies (Ladd, 2012). This study is an experiment in uniting theoretical perspectives to improve instructional designs, which benefit the various stakeholders throughout the e-learning industry, most importantly, the learners.
Cognitive Load Theory
Cognitive Load Theory (CLT) encompasses theoretical concepts and assumptions that yield an array of benefits for adult e-learners. CLT endorses assumptions that human working memory is limited and hindered in its capacity to process valuable learning information when it is overloaded with large quantities of bulky, complex data presentations (Paas, Renkl &Sweller, 2004). Further, CLT is composed of three divergent components: 1) intrinsic, 2) extraneous, and 3) germane loads. Research literature refers to these components as the Cognitive Architecture of CLT, which involves the totality of the human brains capacity for appropriately processing information that leads to learning (Sweller, van Merriënboer & Paas, 1998).
First, Intrinsic Load Theory (ILT) relates to the difficulty and arrangement of instructional design content. For example, instructional content is more advantageous to the learning brain (working memory), when absorbed and processed in bite-size segments, verses large complex masses of information (de Jong, 2010). Further, the ideal principle is to begin instructional content with simple activities and tasks, building toward supplementary complex activities and tasks, as learning progresses. Thus, segments of information gradually form the whole concept, which improves data processing and facilitates genuine learning. "Learning is an active process of filtering, selecting, organizing, and integrating information based upon prior knowledge" (Mayer, 2012).
Second, Extraneous Load Theory (ELT) relates to the load created by instructional matter utilized for the presentation of content. For the e-learning environment, the idea is to employ properly balanced delivery systems and multimedia applications that do not hinder or overload the way in which content is presented (de Jong, 2010). For example, it is superfluous for learners to view large quantities of content materials that contain descriptive text and graphic images within the same visual area, creating redundant content. This format causes the brain to split working memory attention. Case in point, viewing an instructional PowerPoint slide that indicates a textual description of a geometric shape and a diagram illustrating the shape. The theory is that using two or more types of information for the exact same content, overloads the working memory and spits learner attention to a significant extent (Evans, 2012).
Third, Germane Load Theory (GLT) relates to the load required for the entirety of the learning process (de Jong, 2010). GLT is devoted to the construction of knowledge learning and is considered the theoretical effective load theory (Mayer, 2012). GLT should be promoted within the instructional design above ILT and ELT, because it encourages successful learning experiences and knowledge acquisition to meet prescribed learning goals and outcomes (van Merriënboer & Sweller, 2005).
Instructional Technology
Instructional Technology (IT) represents instruments and mediums with technologically inventive, rich learning advancements, which aid e-learners to function from the germane load segment of his or her cognitive capacity. IT formats include, Learning Management Systems (LMS), such as Blackboard, Web 2.0 resources, such as Wikispaces or Blogger, and multimedia applications, such as, podcasts and videos, exemplify a miniature sample of accessible, learning instruments and mediums that can be carefully managed within the e-learning environment to promote germane cognitive load for all learners (Makki & Makki, 2012). Friesen (2009) suggests that IT integration, presents instructional designers with a variety of options to promote real-world learning opportunities, successful learning outcomes, and academic achievement.
Theory in Action
E-learning designs provide optimal circumstances for learners to function with confidence and self-direction, while utilizing instructional technology that best suits his or her preferences and cognitive capacity. Differentiating IT for an adult-learner, who recognizes his or her learning preference for audio-visual information verses textual formats, has the choice to listen and view instructional materials via IT components that affords the learner a fulfilling learning experience, while acquiring imperative instructional content. Alternatively, differentiating IT for an adult-learner, who prefers textually-rich, descriptive information, for his or her content-gathering arrangement, may elect to read, highlight, and take notes digitally via e-text layouts, within the IT design. Therefore, IT is the launch-pad for designing active, meaningful learning experiences in the e-learning environment (Gawande, 2010).
In addition, instructional designers, who unite CLT with IT, create theoretical frameworks that afford e-learners ample choices to interact dynamically with the instructional content, and therefore, encourage active learning, with lower risk of ELT (Cheon & Grant, 2012). When ELT is reduced, GLT is increased, creating a favorable situation for working memory to function at higher capacity (de Jong, 2010). Zimmerman (2012) suggests that interaction with instructional content is the root of effective learning. IT provides the effective means for interaction between content information and the learner, which encourages GLT. These elements provide unique conditions to promote active learning and course completion.
Summary
In order for e-learning to continue its successful journey throughout the 21st Century, it will require endurance and willingness toward changes in theoretical perspectives, research evidence, instructional design frameworks, practices, and methodologies. In addition, e-learning needs to keep considerable pace with future technology and multimedia advancements, as well as, emerging learning theories and models. Although Cognitive Load Theory has a lengthy history in education, it faces new opportunities of usefulness in e-learning instructional design, when united with Instructional Technology. Perhaps, this study will spur a much-needed paradigm shift for the improvement and longevity of instructional designs, which unite Cognitive Load Theory with Instructional Technology.
References
Bandhana, J. (2010). Designing instructional design: Emerging issues. Journal of Education and Practice, 1(3), 1-8. Retrieved from http://www.iiste.org/Journals/index.php/JEP/article/download/1656/1618
Cheon, J. & Grant, M. M. (2012). Examining the relationships of different cognitive load types in relation to user-interface in web-based instruction. Journal of Interactive Research, 23(1), 29-55. Retrieved from http://www.editlib.org.proxy1.ncu.edu/p/34577/paper_34577.pdf
Defazio, J. (2006). Theory into practice: A bridge too far? American Association of Adult and Continuing Education Journal (AACE), 14(3), 221-233. Retrieved from http://www.editlib.org/p/18923/article_18923.pdf
de Jong, T. (2010). Cognitive load theory, educational research, and instructional design: Some food for thought. Instructional Science, 38, 105-129. doi: 10.1007/s11251-009-9110-0
Evans, T. (2012). Cognitive load research & theory: Implications for instructional design. Retrieved from http://www.slideshare.net/tmevans123/cognitive-load-theory-14373581
Engelbrecht, E. (2003). A look at e-learning models: investigating their value for developing an e-learning strategy. Progressio, 25(2), 38-47. Retrieved from http://uir.unisa.ac.za/xmlui/bitstream/handle/10500/4992/engelbrecht.pdf?...1
Friesen, N. (2009). Re-thinking e-learning research. International Review of Research in Open and Distance Learning, 10(3). Retrieved from http://cider.athabascau.ca/CIDERSessions/nfriesen/Introduction%20to%20E-Learning.pdf
Garrison, R. (2000). Theoretical challenges for distance education in the 21st Century: A shift from structural to transactional issues. International Review of Research in Open and Distance Learning, 1(1). Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/2/333
Gawande, V. (2010). Differentiated elearning: The possible approaches. International Journal of the Computer, the Internet and Management, 18(15), 1-15.4. http://www.elearningap.com/eLAP2010/Proceedings/15_Full_Dr.Virendra%20Gawande_Differentiated%20eLearning.pdf
Grant, M. M. (2010). Comparing instructional design models: Retrieved from http://www.slideshare.net/msquareg/comparing-instructional-design-models
Knapp, L.G., Kelly-Reid, J.E., & Ginder, S.A. (2012). Enrollment in postsecondary institutions, (2011 report). National Center for Education Statistics (NCES). Washington, D.C. Retrieved from http://nces.ed.gov/pubs2012/2012174rev.pdf
Ladd, L. (2012). The state of higher education in 2012: Technology will continue to transform your institution. Contemporary Issues in Education Research, 5(4), 235-239. Retrieved from http://journals.cluteonline.com/index.php/CIER/article/view/7268/7337
Lim, C. & Yeon, E. (2009). Review of current studies in instructional design theory in Korea: Major trends and future directions. Asian Pacific Education Review, 10, 357-364. doi: 10.1007/s12564-009-9027-y
Makki, B., & Makki, B. (2012). The impact of integration of instructional systems technology into research and educational technology. Creative Education, 3(2), 275-280. Retrieved from http://search.proquest.com/docview/1011488262?accountid=28180
Mayer, R. (2012). Learning theories: Cognitive theory of multimedia learning. Retrieved from http://www.learning-theories.com/cognitive-theory-of-multimedia-learning-mayer.html
Mohanna, K. & Waters, M. (2008). Multiple perspectives on learning: But which way for
instructional design? Education for Primary Care, 19, 563-568. Retrieved from http://proxy1.ncu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=35156501&site=eds-live
Nam, C. & Smith-Jackson, T. (2007). Web-based learning environment: A theory-based design process development and evaluation. Journal of Information Technology Education, 6, 23-43. Retrieved from http://jite.org/documents/Vol6/JITEv6p023-043Nam145.pdf
Paas, F., Renkl, A. & Sweller, J. (2004). Cognitive load theory: Implications of interaction between information structures and cognitive architecture. Instructional Science, 32, 1-8.
Retrieved from http://www.ucs.mun.ca/~bmann/0_ARTICLES/CogLoad_Paas04.pdf
Schulmeister, R. (2011). eLearning in the usa: The standard? The benchmark? Eleed Journal, 3(1). Retrieved from http://eleed.campussource.de/archive/3/688/metadata
Smith, K. J. (2007). Instructional design theory. Retrieved from http://www.ic.arizona.edu/ic/edp511/isd1.html
Sweller, J., van Merriënboer, J. & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251-296. Retrieved from http://link.springer.com/content/pdf/10.1023%2FA%3A1022193728205
Snyder, M. M. (2009). Instructional-design theory to guide the creation of online learning communities for adults. TechTrends, 53(1), 48-56. Retrieved from http://search.proquest.com/docview/223119414?accountid=28180
U.S. Department of Education. (2006). A test of leadership: Charting the future of U.S. higher education. Retrieved from http://curriculumreform.org/wp-content/uploads/2010/09/US-Secretary-of-Education-Charting-the-Future-of-U.S.-Higher-Education.pdf
van Merriënboer, J. & Sluijsmans, D. (2009). Toward a synthesis of cognitive load theory,
four-component instructional design, and self-directed learning. Educational Psychology Review, 21, 55-66. doi: 10.1007/s10648-008-9092-5
Van Merriënboer, J. & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17, 147– 177. doi:10.1007/s10648-005-3951-0.
Weiler, H. (2011). Knowledge and power: The politics of education. Journal of Educational Planning and Administration, 25(3), 205-221. Retrieved from http://www.stanford.edu/~weiler/Texts11/JEPA_2011_reprint.pdf
Wold, K. A. (2011). Blending theories for instructional design: Creating and implementing the structure, environment, experience, and people (SEEP) model. Computer Assisted Language Learning, 24(4), 371-382. doi: 10.1080/09588221.2011.572900 Zang, C. (2007). Theory and practice: Reviewing technology-mediated research. MWAIS 2007 Proceedings. (paper 25). Retrieved from http://aisel.aisnet.org/mwais2007/25
Zimmerman, T. (2012). Exploring learner to content as a success factor in online courses. The International Review of Research in Open and Distance Learning, 13(4). Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/1302/229