AbstractInstructional design (ID) serves only a small part of the entire learning experience. The pace of information development exceeds courses as the primary delivery mechanism of learning, challenging established ID. Alternatives to courses, like learning networks and ecologies, are developing as an informal learning approach. Designers and organizations receive substantial benefits to acknowledging informal learning, and initiating a focused design approach. Effective learning design must recognize different domains of learning. Learning Development Cycle attends to four broad learning domains: transmission, emergence, acquisition, and accretion. Designers focus on different objects during the design process, in order to meet the intended learning goals. Design objects include: instruction, fostering reflection and critical thinking, creating access to resources, and networks and ecologies. IntroductionChanges in technology create a ripple pattern, altering foundational, long-held views. Certain fields are highly susceptible to change, while others are more conservative. In areas of less personal interest, new approaches and techniques are not viewed as a threat. As changes come closer to our core, they take on a greater sense of threat. In no area is this more evident than learning. Our learning institutions have been created in the spirit of research and openness, yet they have acquired their own neurotic tendencies. Most notable is the strong reaction to change in the classic models of distributing learning. Models of courses, programs, and degrees are still central, even though technology and new needs on the part of learners are creating a climate that requires a more dynamic alternative. Traditional learning design is indicative of the learning field's reluctance to change. In spite of advances in neuroscience, collaborative technology, and globalized business climate, learning is still largely based on design theories created during the early 1900's to 1960's. The environment in which we are immersed has changed. Media and technology has changed. The social environment has been altered. The world has become networked and connected. In this environment of colossal change, the design methodologies used to foster learning remain strangely outdated : created for a time and need which no longer exist. Learning Development Cycle (LDC) is a learning design model to bridge the gap between design approaches and knowledge needs of academic and corporate learners. Much of LDC is rooted in more traditional design structures. We are currently still in the beginning stages of societal and technological alterations. The model is intended to simply open doors to new design approaches, while maintaining aspects from previous models that still serve learners. More developed (connectivist-centric models) will be required as we move forward. LDC is a transitory design approach, bridging traditional design and beginning to embrace internet-era design. Different types of learning exist. Learning happens in a variety of ways : from courses, conversations, life experiences, personal thought, or working on a project. Each different type of learning requires a different design process (as the object of the design differs depending on learning type). LDC presents four broad learning categories: transmission, acquisition, emergence, and accretion. These categories will be discussed in greater detail in this paper. Learning today has moved beyond courses (courses serve a static knowledge field). As a result, course-based ID is not as useful for designing alternative modes of learning. The more rapidly knowledge and information climates change, the greater the need for responsive dynamic models. Why do we Need a New Theory of Instructional Design Reigeluth (1993) defines instructional design as "a discipline that is concerned with understanding and improving one aspect of education: the process of instruction." This definition reflects the predominant view of many designers. The underlying assumption views learning as a process that can be created if only the instructional component is properly managed. Proper instruction increases prospects for learning. In many cases (particularly courses) this view of design is valid. Designing instruction becomes less valuable, however, when contrasted with the knowledge needs of employees, or mature learners who prefer to explore and experiment to create their own connections and pursue personal objectives. Learners and learner needs are changing. Oblinger argues (2003) that "new" students, who have been shaped by world events and technology tools, are entering the education system. These students are not passive consumers of educational resources. Oblinger states "colleges and universities may find that understanding : and meeting the expectations of - the "new students" is important to their competitiveness" (p.42). In a similar sense, the activities of corporate training must also be reflective of today's learners. Effective learning design is no longer a formulaic process. It's a rich engagement of learners and their needs. Frand (2000) provides a list of ten factors which are shaping the information-age mindset, including: the internet is better than TV, doing is more important than knowing, multitasking is a way of life, and learning more closely resembles Nintendo than logic. Frand concludes "we need to think in terms of transforming the educational experience so that it is meaningful to the information-age learner" (p.24). Beyond simply creating new environments and challenges, technology impacts, even alters, our brains. Richard Restak (2003) discusses a core understanding of neuroscience: plasticity. "Plasticity refers to the brain's capacity for change" (p. 7). Our brains are constantly changing, evolving, and reacting to transformations within our environment and the tools we use. New tools require more than adaptation on the part of the user; these tools rewire the brains of users. Neuroscience is providing additional insight into what it means to learn. Early indications of research allude to a fundamental shift in how we view functions of knowing, meaning making, and learning. Instead of seeing learning as an information-processing task, learning can be seen as a pattern-recognition process. Restak uses the illustration of chess to communicate learning "The genius of the grand master doesn't depend on the amount of chess information stored in long-term memory, but also on the organization of these memories and how efficiently they can be retrieved…Geniuses in fields other than chess share a similar talent for storing vast amounts of information in long-term memory and then retrieving that information as circumstances demand" (p. 15). Instead of thinking, experts in a field rely on pattern recognition (based on an almost intuitive understanding of the elements within a particular knowledge field). Downes (2005) supports this view:
What is the impact of changing learners and growing understanding, from the field of neuroscience, of how we learn? Learning designers need to alter their approaches to creating learning resources. The brains of learners, due to plasticity, are being constantly altered through new tools and technology. Learners have different needs and expectations (due to changed environment and new affordances of technology). Courses and programs are no longer the only design objects for learning designers. Designers must shift their attention to the more ambiguous, tumultuous learning environment in which learners now function. Designers no longer create only instruction sequences. They must create environments, networks, access to resources, and increase the capacity of learners to function and forage for their own knowledge. Learning design is primarily about creating guideposts, not describing how to walk on a particular path. It is a mistaken assumption that design can create learning. The best that a well designed course, workshop, or work-integrated learning resource can offer is the climate in which a learner can choose to learn. Instructional design theories take structure as the core element in creating effective learning. Kemp, Morrison, and Ross (1994) state the role of objectives as indicating, "what a learner is expected to do after completing a unit of instruction" (p.96). In keeping with many traditional views of instructional design, they assume that a clearly stated objective increases the potential for learning. This notion has some merit, but falters in that the objectives for learning are determined by the designer, not the learner. In our rapidly developing information climate, designer created objectives may be of limited value to learners. Most learners pursue self-created objectives. In an era where courses are no longer the primary mode of delivering learning, objectives are no longer the only starting point for learning design. Instead of courses, designers need to see learning as an activity without beginning or end. Instead of programs, learning needs to be viewed as an activity that occurs within an ecology. In many types of learning, the task of the designer is to create the right environment for continued learning (i.e. design the ecology). Learners themselves will seek and acquire needed elements. To better reflect the centrality of learners, the term "learning design" will be used in place of instructional design. Instructional design is an important component in the design of courses. Designing courses requires set steps and guidelines for instructors and learners to follow. Learning design, in contrast, is concerned with more than simply creating courses. Instead, the intent is to create the constructs within which learning will occur - networks and ecology. Creating networks and permitting learners to form their own connections is more reflective of how learning functions in real life. Informal and life-experience learning are such a significant aspect of an individual's learning that they cannot be left to chance within organizations. Design processes need to be utilized to capture the value of alternative learning formats. Various alternative models of learning, notably problem based learning, also provide potential value in learning environment creation. Effective learning can originate from courses or classrooms, as evidence by effective use of alternative learning models. Designers benefit by expanding their view of the object of their design. Instead of seeing instruction as the only object of design, a designer's perspective can be enlarged by seeing the environment, availability of resources, and learner capacity for reflection, as potential objects of a design process and methodology. Prior Learning Assessment and Recognition (PLAR) is a growing trend in many education institutions. Red River College defines PLAR as "a process in which individuals have the opportunity to obtain credit for college-level knowledge and skills gained outside the classroom and/or through other educational programs. It is a process which compares an individual's prior learning gained from prior education, work and life experiences and personal study to the learning outcomes in college courses." Higher education will likely continue to identify learning with courses. Yet many people now enter a variety of careers over the course of their lives. PLAR acknowledges the value of experiential learning, and seeks to quantify the learning against established objectives of programs and disciplines. In this case, the objectives follow the learning. Using this format, life experiences can be connected with formal education. While PLAR has yet to gain significant mainstream attention, the principle is critical for tighter integration of higher education and corporate learning. Bridging prior learning with academic standards requires (to slightly abuse the term) "triangulation of learning evidence" (TLE). TLE requires that learners verify stated learning through a variety of sources and means. For example, to communicate to an academic institution that the learner understands Java programming language may require examples of programs, documentation of workshops/certificates, and a letter from a previous supervisor. The process is still a bit awkward, but it is important to realize that formal education should not be recast to be like corporate education (or vice versa). Each model of education serves a particular need. Linking need with the right model results in more effective learning. Using a process like TLE, as a subset of PLAR, can serve as a bridging process between informal learning and formal learning. Learner-centred Learner-centred design is intended to serve self-motivated, active network creators. Saskatchewan Education (undated) provides a useful overview of learner-focused learning: "Independent learning requires that people take responsibility for their own learning. Individual responsibility stems from the belief that learning can be affected by effort, and this belief is the critical factor which leads to individuals' perseverance in the face of obstacles." As learning moves from artificial constructs of courses into a format more symbolic of today's work climate, control must shift to the learner. Courses largely seek to communicate what a designer feels a learner should know. Learner-centred design focuses on giving the learner the ability to decide what he/she feels is important and relevant. A more dynamic design approach is more reflective of the types of challenges individuals will face when learning through experience and other informal methods. What is Learning? Learning has long been debated in realms of religion, philosophy, and more recently, psychology. The challenge of creating a comprehensive definition lies in the different interpretations of both intent and method of learning. Most often, learning is used in an ambiguous manner, without clear definition of hidden assumptions and viewpoints. Adherents of different styles of learning see the world (and solutions to existing problems) in an isolated manner. Rather than exploring more deeply the diversity of learning, learning methods, and learning intent, new situations are unfortunately approached with the intent of shaping the situation to the world view and design methodology. Research (particularly in the field of neuroscience) is beginning to indicate that the primary learning component of our brains is pattern recognition, not information processing. Stephen Downes (2005) extends this concept by offering a challenging vision that learning is not a direct causal interaction between teacher and learner. Replacing the causal model of learning (need highlighted, instructional intervention planned, measurement enacted) with "network phenomenon":
Acknowledging that learning is a process beyond simply processing information requires a definition that is valuable in both formal and informal learning activities. Learning is not an isolationist activity without intent or aim. Certain learning experiences build skills; others build attitudes, beliefs, or other "soft knowledge". The ultimate intent of the process is to be able to do or achieve something. In this regard, learning can simply be defined as actuated or actionable knowledge. This definition has two components - knowledge: understanding of an implicit or explicit nature, and actuation: doing something appropriate (defined as contextually aware) with knowledge. The starting point of learning design is to evaluate the existing views of learning types, learning theories, and design approaches. An integrated or holistic view of the diverse learning landscape permits designers and educators to select appropriate models for appropriate means. Most typically, learning theories have not become obsolete in the sense that they do not work. Instead, they are obsolete in the sense that the world around has changed, and new models are required to meet the needs of new situations. Where the learning theory and design approach closely align with a design concern, even "outdated" theories can become valuable. To remain relevant, it is important for designers to account for diminishing half-life of knowledge and increase in information availability (and amount). Views of knowledge as comprising of "know what" (explicit) and "know how" (tacit) are being usurped with "know where". Further compounding learning challenges is the importance of "soft knowledge" : i.e. experiences and encounters which are not entirely functions of our cognitive domain. Serendipity is often not acknowledged in more formal instructional design. Yet most sources of innovation are bricolage-like in nature. The sudden recognition of solutions from other domains, or the innovative application of available resources is important. Silo style learning design limits learner access to other competing or complimentary information sources. Exploratory and networked learning, on the other hand, provide opportunities to encounter knowledge from other experts and domains : knowledge which often informs and creates innovative solutions. John Seely Brown (undated, p. 66) communicates this new dynamic world of learning: "When we look at teaching beyond the mere delivery of information, we see a rich picture of learning, one that embraces the social context, resources, background, and history within which information resides". Learning Domains Prior to engaging in learning design, it is important to clarify terminology and highlight assumptions. The word "learning" is often used to encompass a broad field with many ambiguous components. For example, is improving one's capacity to be tolerant of others the same type of learning as understanding a mathematical formula? Or is an increased capacity to manage and organize personal knowledge the same type of learning as creating a network of contacts and sustained learning resources? Obviously, different aspects of learning require identification and unique approaches. Learning can be classified by various domains. Figure 1 depicts learning as consisting of accretion, transmission, acquisition, and emergence domains, (these terms do not appear to have a clear origin, though they have been used by Wilson (1997) and Calhoun (undated) without clear attribution to the originating source). Classifying learning in these domains assists designers in evaluating the object of each design task by first determining the nature of learning required.
Each unique learning domain serves a different purpose, and carries a different combination of benefits and drawbacks. A designer's first task is to evaluate the nature of the learning required. Different knowledge needs require different models or approaches. For example, someone new to field or in need of compliance training will benefit most from courses. Short-term knowledge needs (requirements which are not a part of particular field, but needed for cross-over understanding when dealing with other professionals or a particular project) can often be provided by more information sources like magazines, websites, journals, and newsletters. More developed knowledge need (but with less structure than a course) can be met through apprentice-models like communities of practice. More advanced and continual learning can best be provided through a networked or ecological view of learning. Capable, self-aware learners are able to identify and meet own knowledge needs. This level of learning often occurs as a result of "living life". The process of living is in itself a learning experience that can result in the creation of a dynamic knowledge network, allowing learners to integrate new information with existing knowledge, enabling more effective decisions in work and personal affairs. Characteristics of Learning Domains
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