Since the Open University was founded in 1984, more than 250,000 students have enrolled in courses. The Open University offers courses of study at the bachelor’s and master’s degree levels in cultural studies, education science, law, management, psychology, science and technology. Five of its master’s degree programs were top-ranked in 2017
Learning Tasks — concrete, authentic, whole task experiences that are provided to learners in order to promote schema construction for non-recurrent aspects and, to a certain degree, rule automation by compilation for recurrent aspects. Instructional methods primarily aim at induction, that is, constructing schemata through mindful abstraction from the concrete experiences that are provided by the learning tasks. Design steps:
Design learning tasks
Sequence task practice
Set performance objectives
Supportive Information — information that is supportive to the learning and performance of non-recurrent aspects of learning tasks. It provides the bridge between learners’ prior knowledge and the learning tasks. Instructional methods primarily aim at elaboration, that is, embellishing schemata by establishing nonarbitrary relationships between new elements and what learners already know. Design steps:
Design supportive information
Analyze cognitive strategies
Analyze mental models
JIT Information — information that is prerequisite to the learning and performance of recurrent aspects of learning tasks. Instructional methods primarily aim at compilation through restricted encoding, that is, embedding procedural information in rules. JIT information is not only relevant to learning tasks but also to Part-time practice. Design steps:
Design procedural information
Analyze cognitive rules
Analyze prerequisite knowledge
Part-task Practice — practice items that are provided to learners in order to promote rule automation for selected recurrent aspects of the whole complex skill. Instructional methods primarily aim at rule automation, including compilation and subsequent strengthening to reach a very high level of automatically. Design step:
online learning is most effective when the perceived pedagogical distance between the instructor and students in the course is minimized with increased interaction; Interaction occurs through learner-instructor communication, learner-learner collaboration, and learner-content engagement. All three levels of interaction have important implications for effective online learning
Moore, M. (1972). Learner autonomy: The second dimension of independent learning.Convergence, 5, 76-88.
Moore, M. (1973). Toward a theory of independent learning and teaching. Journal of Higher Education, 44, 661-679.
Moore, M. (1993). Theory of transactional distance. In D. Keegan (Ed.), Theoretical principles of distance education (pp.22-38).New York: Routledge.
Moore, M. G. (1989). Editorial: Three types of interaction. The American Journal of Distance Education, 3 (2), 1-6.
Moore, M. G. (2007). The theory of transactional distance. In M. G. Moore (Ed.), Handbook of distance education (2nd ed.), (pp.89-105). Mahwah, NJ: Lawrence Erlbaum Associates.
Moore, M. G., (2013). Handbook of distance education (3rd ed.). New York: Routledge
Community of Inquiry (CoI)
The Community of Inquiry theoretical framework focuses on the degree of presence in the online learning environment. Presence is vital to student success in online courses. There are three types of presence that must be maintained: 1. Social presence to increase learners’ sense of community in the online environment, 2. Cognitive presence to enable learners to construct meaning from the online experience, and 3. Teaching presence to increase learner perception of the instructor’s ability to provide structure and direction in the online environment
Microlearning is a learning strategy that involves bite-sized learning nuggets (small and focused segments) designed to meet a specific learning outcome. To put it simply, the learning content is chunked to reduce learner’s cognitive overload making it easy for learners to absorb and recall.
An effective microlearning course:
Provides deeper learning on a specific concept or a performance objective
Is bite-sized, effectively chunked and easily digestible
Designed for exact moment-of-need – Right information at right time
Ideal for extended performance support providing a better mobile learning experience
Focused on a single performance objective, concept or idea
Is usually 4 to 5 minutes in length, or shorter
Adobe is trying to reshape an old theory: chunking
Defining Online Education
The term “online education” has been used as a blanket phrase for a number of fundamentally different educational models. Phrases like distance education, e-Learning, massively open online courses (MOOCs), hybrid/blended learning, immersive learning, personalized and/or adaptive learning, master courses, computer based instruction/tutorials, digital literacy and even competency based learning have all colored the definitions the public uses to define “online education.”
online education” as having the following characteristics:
Students who enroll in online courses or programs may reside near or far from the campus(es) providing the course(s) or program.
A student’s course load may include offering where attendance is required in person or where an instructor/students are not required to be in the same geographic location.
Students may enroll in one or more individual online course offerings provided by one or more institutions to that may or may not satisfy degree/program requirements.
Student may pursue a certificate, program, or degree where a substantial number of courses, perhaps all, are taken without being in the same geographic location as others.
Organizational Effectiveness Research Group (OERG),
As the workgroup considered strategies that could advance online education, they were asked to use the primary and secondary sources listed above to support the fifteen (15) strategies that were developed
define a goal as a broad aspirational outcome that we strive to attain. Four goal areas guide this document. These goal areas include access, quality, affordability and collaboration. Below is a description of each goal area and the assumptions made for Minnesota State.
Over twenty percent of existing Minnesota State students enroll in online courses as a way to satisfy course requirements. For some students, online education is a convenient option; for others, online is the only option available
The Higher Learning Commission (HLC) accreditation guidelines review the standards and processes institutions have in place to ensure quality in all of educational offerings, including online.
There are a number of ways in which institutions have demonstrated quality in individual courses and programs including the evaluation of course design, evaluation of instruction and assessment of student
a differential tuition rate to courses that are offered online. If we intend to have online education continue to be an affordable solution for students, Minnesota State and its institutions must be good stewards of these funds and ensure these funds support online education.
Online education requires different or additional services that need to be funded
transparency is important in tuition setting
Distance Minnesota is comprised of four institutions Alexandria Technical & Community College, Bemidji State University, Northland Community & Technical College, and Northwest Technical College) which collaborate to offer student support services, outreach, e-advising, faculty support, and administrative assistance for online education offerings.
strategies are defined as the overall plan used to identify how we can achieve each goal area.
Strategy 1: Ensure all student have online access to high quality support services
students enrolled in online education experiences should have access to “three areas of support including academic (such as tutoring, advising, and library); administrative (such as financial aid, and disability support); and technical (such as hardware reliability and uptime, and help desk).”
As a system, students have access to a handful of statewide services, include tutoring services through Smarthinking and test proctoring sites.
Strategy 2: Establish and maintain measures to assess and support student readiness for online education
A persistent issue for campuses has been to ensure that students who enroll in online course are aware of the expectations required to participate actively in an online course.
In addition to adhering to course expectations, students must have the technical competencies needed to perform the tasks required for online courses
Strategy 3: Ensure students have access to online and blended learning experiences in course and program offerings.
Strategy 4: These experiences should support and recognize diverse learning needs by applying a universal design for learning framework.
The OERG report included several references to efforts made by campuses related to the providing support and resources for universal design for learning, the workgroup did not offer any action steps.
Strategy 5: Expand access to professional development resources and services for faculty members
As online course are developed and while faculty members teach online courses, it is critical that faculty members have on-demand access to resources like technical support and course assistance.
5A. Statewide Faculty Support Services – Minnesota State provide its institutions and their faculty members with access to a centralized support center during extended hours with staff that can assist faculty members synchronously via phone, chat, text/SMS, or web conference
5C. Instructional Design and Technology Services – Establish a unit that will provide course design and instructional technology services to selected programs and courses from Minnesota State institutions.
Strategy 1: Establish and maintain a statewide approach for professional development for online education.
1B. Faculty Mentoring – Provide and sustain faculty mentoring programs that promote effective online pedagogy.
1C. Professional development for support staff – including instructional designers, D2L Brightspace site administrators and campus trainers, etc.)
con?:with the advent of personal assistants like Siri and Google Now that aim to serve up information before you even know you need it, you don’t even need to type the questions.
pro: Whenever new technology emerges — including newspapers and television — discussions about how it will threaten our brainpower always crops up, Harvard psychology professor Steven Pinker wrote in a 2010 op-ed in The New York Times. Instead of making us stupid, he wrote, the Internet and technology “are the only things that will keep us smart.”
Pro and con: Daphne Bavelier, a professor at the University of Geneva, wrote in 2011 that we may have lost the ability for oral memorization valued by the Greeks when writing was invented, but we gained additional skills of reading and text analysis.
con: Daphne Bavelier, a professor at the University of Geneva, wrote in 2011 that we may have lost the ability for oral memorization valued by the Greeks when writing was invented, but we gained additional skills of reading and text analysis.
con: A 2008 study commissioned by the British Library found that young people go through information online very quickly without evaluating it for accuracy.
pro or con?: A 2011 study in the journal Science showed that when people know they have future access to information, they tend to have a better memory of how and where to find the information — instead of recalling the information itself.
pro: The bright side lies in a 2009 study conducted by Gary Small, the director of University of California Los Angeles’ Longevity Center, that explored brain activity when older adults used search engines. He found that among older people who have experience using the Internet, their brains are two times more active than those who don’t when conducting Internet searches.
the Internet holds great potential for education — but curriculum must change accordingly. Since content is so readily available, teachers should not merely dole out information and instead focus on cultivating critical thinking
make questions “Google-proof.”
“Design it so that Google is crucial to creating a response rather than finding one,” he writes in his company’s blog. “If students can Google answers — stumble on (what) you want them to remember in a few clicks — there’s a problem with the instructional design.”
Cognitive load theory is built upon two commonly accepted ideas. The first is that there is a limit to how much new information the human brain can process at one time. The second is that there are no known limits to how much stored information can be processed at one time. The aim of cognitive load research is therefore to develop instructional techniques and recommendations that fit within the characteristics of working memory, in order to maximise learning.
Explicit instruction involves teachers clearly showing students what to do and how to do it, rather than having students discover or construct information for themselves
how working memory and long-term memory process and store information
Working memory is the memory system where small amounts of information are stored for a very short duration (RAM). Long-term memory is the memory system where large amounts of information are stored semi-permanently (hard drive)
Cognitive load theory assumes that knowledge is stored in long- term memory in the form of ‘schemas’ 2 . A schema organises elements of information according to how they will be used. According to schema theory, skilled performance is developed through building ever greater numbers of increasingly complex schemas by combining elements of lower level schemas into higher level schemas. There is no limit to how complex schemas can become. An important process in schema construction is automation, whereby information can be processed automatically with minimal conscious effort. Automaticity occurs after extensive practice
Schemas provide a number of important functions that are relevant to learning. First, they provide a system for organising and storing knowledge. Second, and crucially for cognitive load theory, they reduce working memory load. This is because, although there are a limited number of elements that can be held in working memory at one time, a schema constitutes only a single element in working memory. In this way, a high level schema – with potentially infinite informational complexity – can effectively bypass the limits of working memory
Types of cognitive load
Cognitive load theory identifies three different types of cognitive load: intrinsic, extraneous and germane load
Intrinsic cognitive load relates to the inherent difficulty of the subject matter being learnt.
subject matter that is difficult for a novice may be very easy for an expert.
Extraneous cognitive load relates to how the subject matter is taught.
extraneous load is the ‘bad’ type of cognitive load, because it does not directly contribute to learning. Cognitive load theorists consider that instructional design will be most effective when it minimises extraneous load in order to free up the capacity of working memory
Germane cognitive load refers to the load imposed on the working memory by the process of learning – that is, the process of transferring information into the long-term memory through schema construction
the approach of decreasing extraneous cognitive load while increasing germane cognitive load will only be effective if the total cognitive load remains within the limits of working memory
meetings with Chief Learning Officers, talent management leaders, and vendors of next generation learning tools.
The corporate L&D industry is over $140 billion in size, and it crosses over into the $300 billion marketplace for college degrees, professional development, and secondary education around the world.
Digital Learning does not mean learning on your phone, it means “bringing learning to where employees are.” In other words, this new era is not only a shift in tools, it’s a shift toward employee-centric design. Shifting from “instructional design” to “experience design” and using design thinking are key here.
1) The traditional LMS is no longer the center of corporate learning, and it’s starting to go away.
LMS platforms were designed around the traditional content model, using a 17 year old standard called SCORM. SCORM is a technology developed in the 1980s, originally intended to help companies like track training records from their CD-ROM based training programs.
the paradigm that we built was focused on the idea of a “course catalog,” an artifact that makes sense for formal education, but no longer feels relevant for much of our learning today.
not saying the $4 billion LMS market is dead, but the center or action has moved (ie. their cheese has been moved). Today’s LMS is much more of a compliance management system, serving as a platform for record-keeping, and this function can now be replaced by new technologies.
We have come from a world of CD ROMs to online courseware (early 2000s) to an explosion of video and instructional content (YouTube and MOOCs in the last five years), to a new world of always-on, machine-curated content of all shapes and sizes. The LMS, which was largely architected in the early 2000s, simply has not kept up effectively.
2) The emergence of the X-API makes everything we do part of learning.
In the days of SCORM (the technology developed by Boeing in the 1980s to track CD Roms) we could only really track what you did in a traditional or e-learning course. Today all these other activities are trackable using the X-API (also called Tin Can or the Experience API). So just like Google and Facebook can track your activities on websites and your browser can track your clicks on your PC or phone, the X-API lets products like the learning record store keep track of all your digital activities at work.
3) As content grows in volume, it is falling into two categories: micro-learning and macro-learning.
4) Work Has Changed, Driving The Need for Continuous Learning
Why is all the micro learning content so important? Quite simply because the way we work has radically changed. We spend an inordinate amount of time looking for information at work, and we are constantly bombarded by distractions, messages, and emails.
5) Spaced Learning Has Arrived
If we consider the new world of content (micro and macro), how do we build an architecture that teaches people what to use when? Can we make it easier and avoid all this searching?
Neurological research has proved that we don’t learn well through “binge education” like a course. We learn by being exposed to new skills and ideas over time, with spacing and questioning in between. Studies have shown that students who cram for final exams lose much of their memory within a few weeks, yet students who learn slowly with continuous reinforcement can capture skills and knowledge for decades.
6) A New Learning Architecture Has Emerged: With New Vendors To Consider
One of the keys to digital learning is building a new learning architecture. This means using the LMS as a “player” but not the “center,” and looking at a range of new tools and systems to bring content together.
On the upper left is a relatively new breed of vendors, including companies like Degreed, EdCast, Pathgather, Jam, Fuse, and others, that serve as “learning experience” platforms. They aggregate, curate, and add intelligence to content, without specifically storing content or authoring in any way. In a sense they develop a “learning experience,” and they are all modeled after magazine-like interfaces that enables users to browse, read, consume, and rate content.
The second category the “program experience platforms” or “learning delivery systems.” These companies, which include vendors like NovoEd, EdX, Intrepid, Everwise, and many others (including many LMS vendors), help you build a traditional learning “program” in an open and easy way. They offer pathways, chapters, social features, and features for assessment, scoring, and instructor interaction. While many of these features belong in an LMS, these systems are built in a modern cloud architecture, and they are effective for programs like sales training, executive development, onboarding, and more. In many ways you can consider them “open MOOC platforms” that let you build your own MOOCs.
The third category at the top I call “micro-learning platforms” or “adaptive learning platforms.” These are systems that operate more like intelligent, learning-centric content management systems that help you take lots of content, arrange it into micro-learning pathways and programs, and serve it up to learners at just the right time. Qstream, for example, has focused initially on sales training – and clients tell me it is useful at using spaced learning to help sales people stay up to speed (they are also entering the market for management development). Axonify is a fast-growing vendor that serves many markets, including safety training and compliance training, where people are reminded of important practices on a regular basis, and learning is assessed and tracked. Vendors in this category, again, offer LMS-like functionality, but in a way that tends to be far more useful and modern than traditional LMS systems. And I expect many others to enter this space.
Perhaps the most exciting part of tools today is the growth of AI and machine-learning systems, as well as the huge potential for virtual reality.
7) Traditional Coaching, Training, and Culture of Learning Has Not Gone Away
8) A New Business Model for Learning
he days of spending millions of dollars on learning platforms is starting to come to an end. We do have to make strategic decisions about what vendors to select, but given the rapid and immature state of the market, I would warn against spending too much money on any one vendor at a time. The market has yet to shake out, and many of these vendors could go out of business, be acquired, or simply become irrelevant in 3-5 years.
9) The Impact of Microsoft, Google, Facebook, and Slack Is Coming
The newest versions of Microsoft Teams, Google Hangouts and Google Drive, Workplace by Facebook, Slack, and other enterprise IT products now give employees the opportunity to share content, view videos, and find context-relevant documents in the flow of their daily work.
We can imagine that Microsoft’s acquisition of LinkedIn will result in some integration of Lynda.com content in the flow of work. (Imagine if you are trying to build a spreadsheet and a relevant Lynda course opens up). This is an example of “delivering learning to where people are.”
10) A new set of skills and capabilities in L&D
It’s no longer enough to consider yourself a “trainer” or “instructional designer” by career. While instructional design continues to play a role, we now need L&D to focus on “experience design,” “design thinking,” the development of “employee journey maps,” and much more experimental, data-driven, solutions in the flow of work.
lmost all the companies are now teaching themselves design thinking, they are using MVP (minimal viable product) approaches to new solutions, and they are focusing on understanding and addressing the “employee experience,” rather than just injecting new training programs into the company.
AECT-OTP Webinar: Digital Badges and Micro-Credentials for the Workplace
Time: Mar 27, 2017 1:00 PM Central Time (US and Canada)
Learn how to implement digital badges in learning environments. Digital badges and micro-credentials offer an entirely new way of recognizing achievements, knowledge, skills, experiences, and competencies that can be earned in formal and informal learning environments. They are an opportunity to recognize such achievements through credible organizations that can be integrated in traditional educational programs but can also represent experience in informal contexts or community engagement. Three guiding questions will be discussed in this webinar: (1) digital badges’ impact on learning and assessment, (2) digital badges within instructional design and technological frameworks, and (3) the importance of stakeholders for the implementation of digital badges.
Dirk Ifenthaler is Professor and Chair of Learning, Design and Technology at University of Mannheim, Germany and Adjunct Professor at Curtin University, Australia. His previous roles include Professor and Director, Centre for Research in Digital Learning at Deakin University, Australia, Manager of Applied Research and Learning Analytics at Open Universities, Australia, and Professor for Applied Teaching and Learning Research at the University of Potsdam, Germany. He was a 2012 Fulbright Scholar-in-Residence at the Jeannine Rainbolt College of Education, at the University of Oklahoma, USA
Each student learns differently and assessment is not linear. Learning for different students can be a longer or shorter path.
assessment comes before badges
what are credentials:
how well i can show my credentials: can i find it, can i translate it, issuer, earner, achievement description, date issued.
the potential to become an alternative credentialing system to link directly via metadata to validating evidence of educational achievements.
DB is not an assessment, it is the ability to demonstrate the assessment.
They are a motivational mechanism, supporting alternative forms of assessment, a way to credentialize learning, charting learning pathways, support self-reflection and planning