Accidental Pedagogy Redux

Several shifts have occurred in the 21st century that have resulted in changes to the design of technology brought into the classroom and course by way of the course management system (CMS). The nature of how courses are delivered is accelerating at a pace reflective of societal changes, technology innovation, and the changing composition of learners now coming to higher education. While late 20th century delivery models were mainly restricted to campus-based classroom approaches, and reflected a digital version of the classroom experience, we now see a broader continuum of course offerings and online pedagogy that have become a mainstay in how higher education offers courses. In response, the CMS that has served as an anchor for these efforts offers a diversity of approach and possibility and is transforming into a learning management system.

In 2005, McGee, Carmean, and Jafari published an edited book examining how course management systems can support deeper learning through learner-centered experiences for the higher education community (Course Management Systems for Learning: Beyond Accidental Pedagogy). This work elaborated on Carmean and Haefner's (2002) work that addressed the use of technology embedded within the standard CMS to support learning. From this work, Jafari, McGee, and Carmean (2006) studied applications of the CMS in beliefs and practices across institutions in the United States. This was done by identifying the needs, practices, and preferences of campus and information technology administrators, faculty, support staff, and students. Over the past 10 years much has changed in the landscape of technology used to support postsecondary course delivery. Not only have alternatives to delivering courses with and through technology proliferated, but also so have available, affordable, and accessible technologies. Course management systems now comprise smart machine learner awareness and diverse third-party technologies that sit under the CMS umbrella.

Systems names vary by sector and function; while “course management system” and “learning management system” are used interchangeably, there is a significant distinction between the two terms. Course management system (CMS) generally refers to the constraint of the immediate semester-based class where students are enrolled into a system, content is disseminated and managed, and students participate in activities, as they turn in assignments and take assessments. Learning management system (LMS) is a broader concept that subsumes the CMS to include integration with human resources and other institutional systems, data tracking at learner, course, and program levels, content development, tracking learners across systems/courses, reporting data to other systems, as well as CMS functions (Carliner, 2005; Watson & Watson, 2007). McGee and Green (2008) found that the most popular L/CMS in higher education in the first decade of the 21st century (i.e., Angel, Blackboard, Moodle, Educator, and WebCT) were conceived at a time when mass markets drove how systems worked in an attempt to provide a one-size fits all service that could take the place of instructor-developed web pages with hyperlinks. As markets shifted from broadcasting to narrowcasting with an emphasis on individuals rather than markets, so did systems become more malleable and customizable with plug-ins and add-ons. The CMS of the turn of the century is slowly becoming the LMS of the 21st century as proprietary systems continue to merge and technologies are increasingly integrated in an attempt to be all things to all people.

This article takes a look at the rapidly changing history of technology use shaped by the adoption of the CMS → LMS → learning platform. It explores design for deeper learning and engagement via the many variations of new environments that are redefining when, where, and the ways we now learn. It traces how the LMS has defined and been defined by new technology-infused practices that liberate learning from the lecture, from the campus, and from the digital boundaries of the course management system.

Twentieth-century CMS models were based on the metaphor of a brick and mortar classroom. Only admitted students could enter, and the door was closed to everyone else. The instructor controlled just about everything: announcements, assignments, assessment, interactions, and discussions. From this familiar structure, the learner responded to well-worn cues and was only allowed to participate in instructor-determined ways. Yet when students were working inside such a system, they were alone and autonomous, at least to the extent that they had no direct supervision, came and went as desired, and made decisions based on their own judgment. It is this dynamic that proved confounding to instructors and learners. Over time, learners recognized the extent of resources and interactions available to them via the Internet at large as they became accidental learners in their quest for information and knowledge, outside of the CMS box. Free, yet confined, alone (Maeroff, 2004) but with everyone (Shirky, 2008). The shift in access to information, people, and resources truly placed learners in control over what and how they learn.

Of all of the impacts claimed to be a result of technology use in education, one is definitive: technology puts the learner in the center of learning. Learner-centeredness is indicated by the focus on purpose-ful interactions, active learning, and teamwork. Much of the pedagogical crafting of twenty-first century instruction has been informed by the American Psychological Association's (1995) 14 learner-centered principles. These principles include factors that are cognitive and metacognitive, motivational and affective, developmental and social, and individual in nature. Educators have often tied these factors to design for outcomes controlled by readings, discussion, and assessment replicating what occurs in the classroom rather than embracing technology enhancements that liberate the learner from traditional pedagogies.

Application within the community moving toward technology as lever were greatly influenced by Arthur Chickering, and with Ehrmann's (1996) thoughtful addition of technology use thereby expanding Chickering's principles so that they could be applied for more engaged and meaningful learning. The challenge lay in crossing deep disciplinary divides: most in higher education were not schooled in pedagogy nor its application in technology. Those in disciplines exploring pedagogy often were distant from technology. Forces aligned to create a CMS that looked and felt like a digital version of the lecture-centric “sage on the stage” (King, 1993) classroom, despite the growing awareness on the part of students that this was in conflict with how they were now seeking knowledge and was perhaps leaving them ill-prepared for the workplace awaiting them (Jafari et al., 2006).

During the late 20th century CMS boom across higher education, society saw equal change in practice across technology adoption in the workplace, in personal lives, and in how we interact with daily life. A rise in smartphones and mobile applications (apps) changed our access to information, making it available all the time (Zheng, 2006); the implementation of collaborative software tools changed the way information workers created workplace knowledge and created greater enterprise value in the practice of knowledge sharing (Cross, 2006); the rise of Facebook, Twitter, MySpace, and tens of social sites for unique interests changed the sense of connectedness and sharing for everyone from preteens to previously technophobic elders (Shirky, 2008). The world changed, and in that change, there was an across-the-board request that higher education begin to change with it. Technology that was social, collaborative, and easy to use had infused itself the fabric of American life. An expectation grew that this change would find its way into the practice of teaching and learning in higher education. An exploration and understanding of the shift from the industrial to the information age was demanded of the Academy if learners were to be adequately prepared for the world they would be facing (Rennie & Mason, 2004). Still, society would need to wait a number of years before they saw the transformation of top-down to participatory influence higher education. Despite the case for value, and research on application to deeper learning, the only technology specifically designed for learning—the LMS—was slow to change its inherent framework of teacher-centric design. Indeed, some claimed only the destruction of the CMS would create the needed shift (Madsen Brooks, 2008). Perhaps the new generation of LMS products—created not by university faculty but by cognitive and learning researchers, instructional designers, and gamers—proved edupunks wrong.

In 2002 Carmean and Haefner produced a meta-framework explaining the heart of deeper learning within technology support learning contexts. The work summarized research on engaged and lasting learning. Conditions described in the work are still reflected in current practices described later in this article. With the learner in the center, using technology as a pipeline and for connectivity, deeper learning is enabled through active practice, contextually relevant content and processes, social interaction, engaged participation, and ownership of learning processes and outcomes. The authors further described these conditions:

Ten years later, we begin to see a shift as the LMS emerges not as a classroom in a digital box, but as a smart, machine-aware portal into varied third party tools for learning. With systems like Instructure's Canvas LMS becoming an open source system and creating as well as allowing open API access to adding new third-party tools, institutions can leverage the power of social and collaborative media to create paths to more open media: Google, Tegrity, Scribblar, Twitter—whether built-in or added-on, the container is no longer closed.

How might this change the way faculty think about learning? What happens when the familiar box begins to look different and embedded in the framework is the ability and psychological suggestion that digital collaboration and consensus has value? That groups should have workspaces, that communication between participants could be 24/7? That designers have access to single-source authentication technology under the LMS umbrella? Could an LMS 2.0 design shift also shift educational practice and make for intentional pedagogy that reflects the needs and practices of the learner? Could access to these tools, and to smart machine analytics under the LMS hood create new, learner-aware modalities in how we see teaching and learning?

Established learning management systems, controlling much of the higher education market, have changed and stayed the same. They have added features, but retained the classroom control view of learning. New LMS systems often find it difficult to break from this framework, and on initial view, seem constructed with a transparency that allows instructors to offer old wine in new bottles. Most systems make an effort to be all things to all people, and to provide a one-stop shop for instruction. We have not yet rethought the announcement-assignment-grade book structure. However, limitations and controls that existed in 2005 have significantly disappeared and in reality, users have autonomy, flexibility, and seemingly endless choices about how, what, and where they learn. Information technology departments, in collaboration with vendors, have implemented central tools that are open and solicitous (e.g., wikis, blogs, RSS feeds, Google Docs) and have forced the institution to look at learning as a collaborative venture that occurs both inside and outside the LMS box.

Clearly the bulky and institutionalized LMS has been refined to virtual death, with little opportunity for users to shape or shift how learning, although technology-enhanced, is any different than it was 200 years ago (Jafari et al., 2006; McGee & Green, 2008). Cloud-based tools, on the other hand, have become more ubiquitous, more malleable and more collaborative. External resources allow users to own, create, share, hide, control, and massage both content and process. The role of external technologies (social media sites, visual media sites, Google Apps, mobile media, third party and cloud-based environments) continues to change this new, digital landscape. The very definition of a learning environment, and whether it can be “managed” by a system, is called into question by those advocating for the personal learning environment (PLE), and for institutional access to self-constructed, open, and individualized learning.

The framework for a new learning environment, explored in Brown and Duguid's (2002) work, depends on the myriad of tools available across technology applications and rests in their rich affordance in social and shared information. The concept of PLE was further explored in Siemens' (2004) writing on the theory of connectivism in which he describes “personal learning networks” to illustrate how learners are connected to each other and knowledge sources through various technologies and that these networks support learning through diversity of thought, currency of information, making connections across information sources, and collaborative decision-making. A PLE is often considered to be a mashup: combinations of different cloud-based tools that are combined to create a unique and personal experience for the engaged learner.

Attwell's (2006) work further defines aspects of design that create the ideal personal learning environment: support for informal exploration, for different learning styles, and for new means of assessing and recognizing what the learner may choose to learn. Each of the definitions depends on ensuring the learner has the digital literacy skills and confidence to seek information in new ways with new and individualized tool selection.

In an age where information is no longer scarce and no longer needs to be organized into containers, the challenge is to leverage the saturated digital world in which learners now live and to assist them in sense-making (Kurtz & Snowden, 2003). In a new knowledge environment, where information is available when you need it, the authors claim it will be more important to learn how to participate in knowledge exchange, decision-making, strategies for understanding information, and policy-making. Learning theorists claim that knowledge is constructed, and this can only be done by the learner in making sense of his or her environment, finding pattern and meaning in information, and making understanding his or her own (Bransford, Stevens, Schwartz, Meltzoff, Pea, & Roschelle, 2006; Greeno, 2006; Schraw, 2006).

PLEs allow learners to bring together information at their disposal, from any place and with any tool at their access. In this environment, the learner can shape information into pattern and meaning. Learners can construct artifacts that demonstrate their understanding and share this understanding for feedback in new containers for social construction of meaning.

Unlike the structured, classroom-replicating tools of the early CMS environments, PLEs become shaped by their creator. Blogs, wikis, multimedia reflections and artifacts, bibliographic annotations, as well as self-reflections on work, peer critiques, and assignments all become possible reflections of the learner's understanding. Each PLE looks as different as the learners in a course. The PLE becomes the reflection of learners’ understanding, interest, and experiences in constructing their path, wherever they are and wherever they do.

The birth of the CMS reflected our dependence on centralized technology and the role of big machines hardwired to plugs and tethered by cables. Overnight, that tethering changed as the world went mobile. Students now carry their technology with them. Using technology for just about everything is iconic of the 21st century student. Smith, Rainie, and Kickhur (2011) in a Pew Internet report tell us:

• Ninety-two percent of undergraduates and 88% of graduate students in four-year colleges connect to the Internet through a wireless device.

• Of undergraduates, 89% own a mobile phone, 69% own portable MP3 players, and 64% own a laptop.

• For graduate students, 96% own cell phones, 88% own laptops, and 84% own portable MP3 players.

Mobile learning tears down the metaphorical course walls, enabling students to collect data, collaborate, practice, and clarify understanding wherever they are and not just necessarily with people they have in their directory. MLearning often involves learning apps that store, push, and help to analyze data over periods of time. It gives the learner the ability to redefine “smart” and to know not by memorizing, but by finding information they need when they need it. It destroys not just the framework of a course as fixed in time or in space, but moves the course to everywhere and all the time.

Conceptualizations of the affordance of mobility vary and are evolving. Pahcler, Cook, and Bachmair (2010) see a sophisticated form of mLearning emerging with a focus on the learner in mixed-reality modes in which students experience augmentation to data present in their real world. Frankfort, Salim, Carmean, and Haynie (2012) see mobility as an opportunity to expand mLearning outside the subject matter domain and into awareness for the whole learner—providing deeper understanding of performance, learning needs, and pacing. Such tools that allow deeply immersive and connected learning are available on some mobile devices now and as they continue to grow will offer expanded opportunities to see types of access that students desire. They expand the LMS container and redefine its reach and form.

A marked shift in system functionality are the design-embedded tools that allow designers and instructors to make paths for learning based on pedagogy rather than management. Systems such the learning activity management assistant offer smart linking of learning activities, and Blackboard's pedagogical templates support LMS-integrated learning organization that supports learners as they engage in course activities. With embedded design features comes less confusion about course organization, more clearly aligned activities, and, when intentionally used, a greater focus on learning. However, just because design tools exist within the container does not mean that better learning is occurring inside the box. Tools that help the learner understand the learning experience provide the greatest contribution to deeper learning.

Examples of smart design that make it easier for learners to think deeply include smart release of new material based on learner performance, notices and reminders based on submissions, ability for instructors to customize messages based on criteria at runtime (e.g., “send this e-mail to all learners who received 70% or less on the last assignment”), and context-sensitive features that change user views. One interesting but simple change that reflects better pedagogical understanding of the potential of technology is a new feature in the Canvas LMS that hides all previous posts in a discussion thread until the learner has submitted their own. Hiding previous comments until a student has posted facilitates original thinking that is less influenced by what has already been stated, offering a new understanding of technology-supported learning and its place in defining new pedagogical practice. Context sensitive menus and responses that result from individualized learning data are changing the “course in a box” design of the old CMS and moving realization of the individual pacing, needs, and psychology of the online learner.

Social technologies are perhaps the most apparent phenomenon to challenge the traditional LMS model of how, when, and where learners interact. Social tools, and our collective response via engagement and shared information and inquiry, have created great possibility and new practices in learner interaction offering just-in-time and -need learning supports. The challenge is to understand and capture these affordances well enough to respond to the demands for digital age outcomes with collective practices (see Table 1).

While the tools of social media will continue to tussle about in the war for dominance, the reliance on and fascination with real time communication is iconic for current college goers in much of their daily life and social interactions. Whether the academy chooses to examine, leverage, and promote sociodigital tools for learning remains the unanswered question.

While institutions are coming to rely on the classroom approach to instruction in the cloud, innovation has emerged in spite of the limited progress towards providing a system that genuinely supports learning. In 2005 we stated that, “Most CMS courses are designed through ‘accidental pedagogy’ (Morgan, 2003) as traditional courses are transferred to the online environments” (McGee et al., 2005, p. xiv). Today LMS offer more sophisticated strategies to organize courses pedagogically, but in general, despite the technical advances, we still see instructor-driven, course management-focused templates. So what has really changed? How are innovative educators and learners using technologies available within the new LMS or incorporated tools to make learning appealing, engaging, and lasting? For the authors, the shifts are significant: from teacher-directed to learner-directed instructional frameworks, as indicated in trends of blended/hybrid delivery models, the flipped classroom, the bring-your-own-technology (BYOT), and the Massive Open Online Course (MOOC). Perhaps the success of the last is the most surprising to traditionalists in higher education.

A MOOC “builds on the active engagement of several hundred to several thousand ‘students’ who self-organize their participation according to learning goals, prior knowledge and skills, and common interests” (McAuley, Stewart, Siemens, & Cormier, 2010, p. 10). MOOCs differ from traditional courses in that they are typically free, do not require expressed proof of prior knowledge or preparedness to learn, have little if no expectations of learner performance and do not confer institutional credits for completion. MOOCs may offer assignments, activities, and assessments that look and feel like those associated with traditional courses. MOOCs are offered by organizations that work with experts or notable faculty to provide no-course classes, such as Udemy, or by universities who share course content at no cost, such as Carnegie Mellon, MIT, Stanford, and Yale. While originally considered only for informal and non-credit learning, the University of Texas System is now envisioning MOOCs as a strategy to limit students’ educational costs and to expedite 4-year graduation rates (Kolowich, 2012). Using the traditional LMS structure, this nontraditional, participant-driven experience demonstrates how learners can drive their experience without the omnipresent and authoritative instructor.

A second example of change to our understanding of container comes with the way in which pedagogical templates fixed in the LMS container have been discarded for loosely connected tools brought to the learning table by instructor and learner. “Free-range” designs encourage and facilitate student ownership of what they know as documented outside the locked-down walls of the LMS. We are shifting to knowledge construction rather than content delivery, and in this new model of use, students are afforded opportunities to organize resources, connections to people, and tools in ways that make sense and are usable to them (Chatti, Jarke, & Frosch-Wilke, 2007).

A third example of innovative practices within and outside of the LMS can be observed in the way that roles of the learner and instructor have shifted, by virtue of delivery models, the ubiquitous access to anything and almost everything, and emerging theories and practice that force everyone to be both learner and instructor. Most prominently is the focus on social interaction and connectivity that is reflected in multiple and enduring learning theories including brain-based learning theory (Jensen, 2008), constructivism (Perkins, 1991), and Connectivism (Siemens, 2004). Tools such as Wiggio allow students to form their own learning communities with all of the necessary tools that are locked down in the LMS. Indeed, when learning is liberated from grades, all kinds of surprising new opportunities arise. The Zite app allows students to create their own collection of resources around topics of relevance to them and to share with anyone, as do Pinterest, Evernote, and Glogster. Students have become the generators of knowledge, not just the recipient of the professor's expertise. Systems, tools, and practice for meaningful learning continue to evolve, forecasting and piloting the design of future systems, or tools that will allow the customization of integrated tools.

The 20th century CMS, now a 21st century LMS, while still a relatively young technology, has reached middle age in a world ruled by youth who prefer systems more portable and flexible. The conflict between generational perspectives about the priority and necessity of the LMS as an institutional fixture requires a negotiated agreement on value, or at least acceptance of use by individual design. This would precipitate a shift from authority by power to authority of consensus within the faculty structure, necessitating a priority on the needs of the learner (Bleed, Brown, Kreis, & McGee, 2004; Carmean & McGee, 2003).

Such a change may not be easy for higher education, but we may be reaching the point where it is a necessity. With learner-centeredness also comes technological relativism (Diaz & McGee, 2005) where previously prescribed ways of learning are not only not accepted they are rejected. Reusability has been core to the LMS, yet relativistic practices prevent scalable reuse as learners make, share, take and modify their representations and documentation of what they know. What can be known changes with each iteration, each learner, and each addition to the shared knowledge experience.

So what happens next? Stepping away from narrow problems and entering the sticky, hard-to-solve ones within domains of culture and change resistance suggests multiple barriers. We know that the shift from an industrial economy to a successful information economy has resulted in a requirement that everyone must be literate in complex ways, and it demands institutional ability to embrace new learning outcomes and new ways of learning. Ito et al. (2008) make the case that a technology-driven information economy has created the need for new, digital literacies. McGee and Green (2008) state that an overabundance of data is surely making an individual's ability to memorize and store data impossible and unfruitful. For these reasons, a learning environment that is balanced and includes experiential learning, guided mentoring, consensus, and collective reflection is highly desirable to the 21st century learner. The academy must change if it is to be responsible to learners and to society's demand for digital fluency and a new way of being in and of the world. Learner-aware, context-sensitive systems, larger in scope than the learning management system but inclusive of its new value as portal to the learner's discovery experience, now exist. They are being used, tested, and validated in personal learning experiences that define the new teaching and learning practices. An accidental pedagogy that grew haphazardly from the marriage of industrial age teaching and information age technology is giving way to the personal, information-rich, and omnipresent sociodigital learning experience. Whether this marriage survives as informed, responsible practice depends on the will and ability of public higher education to recognize its role in producing 21st century citizens and lifelong learners. Time will tell.