Shifts in Educator Roles, Professional Practices, and Organizational Models Driven by eLearning Disruptive Forces

Michael Sandel is an international superstar.  His 2013 tour filled 14,000 person stadiums in places like Seoul Korea.  He was broadcast on national television and became so popular that he was asked to take a place of honor at a national sporting event.  In China his Internet video has been watched over one million times.  If you have not heard of Michael Sandel you might be surprised to hear that he is not the lead singer in a rock band, or a Hollywood movie star.  Michael Sandel is a Harvard philosopher and lecturer.  Sandel’s “show” is a series of lectures on justice and political philosophy, not exactly a topic regarded in the popular mainstream.

Andrew Ng is both a “rock star” and an “edupreneur.”  In October 2011 he offered his Machine Learning course at Stanford for free to anyone in the world.  Over 100,000 people enrolled in that first iteration. His work subsequently led to the founding of business start-up Coursera in 2012.  He is quoted as commenting that to reach that many students within the traditional model he would have to teach for 250 years.

An ecosystem empowered by global telecommunications and Internet technologies is creating the opportunities for some teachers to have a positive impact on significantly more lives and reach unprecedented levels of fame and fortune. Disruptive forces driven by eLearning technologies, “big data”, new human capital strategies of educational institutions, market demands, economic conditions, learning science discoveries, and innovations in professional practice are driving toward new education delivery models.  Some of these models give good lecturers a “bigger stage” without significantly changing the big lecture hall experience for learners. Other models leverage the specialties of a team of education professionals to personalize and optimize student learning.  Market demand for these new delivery models has already begun to impact traditional institutions.

New models of delivery require changes in professional practices. Emerging online learning models, for example, shift the focus from hour-long lectures and textbooks to more interactive shorter cycle learning experiences in which individual learner understanding is checked continuously.  While much of the hype around massively open online courses has been about the number of students watching video lectures, a more important metric is the higher quality that can be achieved with economies of scale and the massive amounts of data that can be mined to optimize student learning.  This data is powerful as a feedback loop for optimization of individual learning experiences and as a means to optimize learning experiences across populations.  This “big data” also supports new research methodologies driving down the cost and time that it takes to do gold standard studies and with greater applicability.

“You can turn the study of human learning from a hypothesis-driven mode to the data driven mode.  You can ask questions like what are some of the misconceptions that are more common and how can we help students fix them.”

(Koller, Daphne; http://www.ted.com/talks/daphne_koller_what_we_re_learning_from_online_education.html, June 2012, downloaded 21 April 2013)

Part of what is giving this "big data" the greatest impact is the adoption of common data vocabularies, such as those defined in the Common Education Data Standards (CEDS), an initiative led by the U.S. Department of education.  CEDS doesn't collect data, it provides common definitions used across organizations and sectors so that data about student learning experiences from one institution may be compared to data from another institution.

Professor Neil Heffernan teaches artificial intelligence at WPI.  Unlike Andrew Ng, however, Heffernan doesn’t lecture to hundreds of thousands of students through a massively open online course.  He is achieving a different kind of fame as an inventor of next generation learning technologies. Heffernan developed intelligent tutoring technology that is bridging research and practice.  He is taking on Benjamin Bloom’s “2-sigma problem.” Bloom found that one-on-one tutoring is two standard deviations more effective than a group lecture, and the problem is that one-on-one tutoring is cost prohibitive at scale…or at least it has been cost prohibitive.  Heffernan’s free-to-the-public ASSISTments platform offers “scaffolding” similar that provided by a tutor for students learning mathematics.  The system can be configured to identify common mistakes/misconceptions and give descriptive feedback to the student just at the right time, but it is not designed to replace teachers, rather it supports a teacher-directed blended learning model.  As a research platform ASSISTments can identify common misconceptions and perform short-cycle studies on the effectiveness of possible interventions in alleviating those misconceptions.

So far we’ve identified three emerging roles in which college professors have gained greater impact, not to mention fame and fortune.  I’ll call them the “rock star”, the “edupreneur”, and the “innovator”.  There are many other roles critical to the success of the emerging eLearning models.  Other roles include the learning experience designer, the producer, the cinematographer, the game-based-learning developer, to name a few.   Online and blended learning models could bring about a renaissance for the education profession with new opportunities and opportunities for greater rewards. 

Disclosure: My current work includes facilitating the Common Education Data Standards (CEDS) an initiative of the U.S. Department of Education, and I’m on an advisory board for WPI’s ASSISTments project.

The Current Future of Learning Infographic

The hyper-linked PDF is here.

Online learning less effective?

Recent studies suggest that online post-secondary courses may have a negative effect, especially for some learners within some subjects, when compared to on-campus courses.  However, decision-makers should not interpret the findings to indicate that online delivery is generally less effective, only that the predominant models for online delivery currently used by the institutions in the study are less effective than currently used on-campus delivery models.

These studies may only confirm, for example, that video lectures 'broadcasted' online can be less effective than in-person lectures in which the lecturer can see the audience and gauge engagement/understanding.  The studies generally analyze data sets about students enrolled in online classes without differentiating online delivery models.  The online delivery model, especially for MOOC-style courses, is too often a less interactive substitute for a lecture series with homework and non-formative assessments.  There is one advantage of a streaming video lecture over the physical lecture hall experience, the learner can pause and review the material again.  However, the streaming video by itself does not have a feedback mechanism to gauge the learner’s understanding and adjust instruction accordingly.  Effective online learning processes, like effective tutors, track individual learner competency and continuously optimize the learning experience.  

The recent studies tend to compare the “place” in which learning takes place, i.e. online vs. in-class, rather than the models of teaching and learning used in the online and physical environments.  The findings raise legitimate concerns about the currently used online models and the implementation of those models at a time when societal and financial pressures are pushing universities more toward online delivery.  So rather than categorically discount online delivery, we should now ask “why” the models are less effective, and “what” are the characteristics of online models that are more effective. 

Decision-makers and practitioners need new research that focuses on the learning model rather than the delivery mode.  Online technology allows for interactive models of online learning that continuously monitor understanding and skills, provide timely feedback, continuously adjust the learning experience within the zone of proximal development, facilitate relationships for learning, and address motivational aspects of learning.  I suspect that the less effective online models are the ones that overlook the individualized feedback, relationships, and motivational aspects of learning.  I also suspect that, in many cases, the online models that address these aspects and leverage technology to overcome time/space/pace constraints will prove to be more effective than traditional fixed place/time course delivery models. 

Next Generation Learning Roles and Human Behavior

Moving to a learner-centric, competency-based, system of learning requires changed attitudes and behaviors. It is not enough to layer innovative models or tools on top of existing behaviors, people must change what they do. One of the most interesting challenges we face in the next few years has to do with the adoption of new roles, professional practices, and learner behaviors required by next generation learning models. We are at the beginning of the learning curve on figuring out what new roles and practices are needed.  The greater challenge will be scaled adoption of these new roles and practices.

This is a good time of year to ponder the topic behavioral change as many of us are trying to better our lives by keeping New Year’s resolutions. Knowing what to do is not enough, habits of practice are difficult to change.  Some observations about the knowing-doing gap:

1.       A change in behavior often requires a change in belief.  Habits of behavior are captive to habits of belief. A new behavior is constrained by what people believe about the problem, themselves, and their ability to overcome the problem. 

A first step is to provide a path and conditions leading to “aha moments” in which people to learn, often by experience, that:

• It is in my best interest to change what I’m doing.
• I have the ability to change what I’m doing.
• If I do this differently, my life will be better, more meaningful, and/or I will better fulfill my calling. 

2.       A change in behavior often requires multiple points of motivation.  It usually takes more than one “aha moment” to adopt new habits of belief and behavior.  It takes a change in priorities over time.  Something needs to become more important and/or less important.  Each person may have a different set of motivators that drive the behavioral change.

Motivational factors include:

•  Purpose, Meaning, Calling
• Accomplishment
• Ownership & Possession
• Feedback / Course Corrections
• Social Pressure
• Scarcity 
• Impatience
• Curiosity
• Avoidance of Loss

Simulations and online game based learning experiences may be designed to include all of these motivational factors.  However, some motivations may be more effective if sources from the real world, e.g. social pressure leveraging a person’s real social network may be more effective than from a simulated peer group. 

3.       Feedback loops are critical for learning and adopting new behaviors.  It is easy to slip back into old habits without long-term, ongoing supports.  Even painful habits are “comfortable” because they are familiar and people will slip back into a destructive habit without continuous feedback loops.  The most effective feedback will be just-in-time, provide the right level of challenge (within the zone of proximal development), and key into the individual’s interests and motivational “hot buttons.”  For example, an automated reminder to exercise may not be as effective as a friend waiting for you at the gym or even sending a private message via Facebook to ask if you exercised today.  Even more effective may be a social network of 20 people working on a goal of 1000 hours of exercise due to the peer pressure for each participant to contribute to the collective goal.

Bringing next generation learning models to scale can be supported by scaled infrastructure, the right economic conditions, technology, and policy enablers.  However, more is needed to help educators and learners to change what they do.  A path to new roles and practices is paved in part with redesigned professional training and development programs for specialized educator roles that develop proficiencies and practices optimized for new learning models.  Effective programs will likely take advantage of digital learning and social networking technologies, and designed to incorporate individualized motivational feedback loops.

Professional Specialization for Educators Emerging from Next Generation Models

Online and blended programs are changing the learner experience by flipping, flexing, and rotating the classroom experience around online/individualized learning. Educators in these programs are adapting professional practices to support the new models, sometimes figuring it out as they go. Some of the more innovative school models are abandoning typical features of schools, such as schedules, grade levels, and classrooms, in order to optimize a learner-centric design. Some models also recognize the need for new professional roles to support the different uses of time, physical space, and modes of learning.

One example is the model used by Cornerstone Charter Health High School in Detroit. The school, a Next Generation Learning Challenges grantee, recognized the need for professional specialization to support individual student learning absent of grade levels and class schedules. Instead of one-size-fits-all classroom teachers, Cornerstone has specialists:

• Relationship Managers ensure students set and meet their daily, monthly, and yearly goals. Similar to a traditional guidance counselor, relationship managers follow a student from enrollment to graduation, helping students craft their individual learning plans and use student data and feedback to ensure students stay on track toward their goals. Relationship managers are the primary contact for parents and guardians. 
• Relevance Managers provide direct instruction and support students in the design and evaluation of real-world projects and internships. 
• Rigor Managers oversee online coursework, providing support and setting standards for mastery. 
• Success Coaches work to help students make the transition to college and career, providing practical advice as students consider life after graduation. 

It is too early to tell whether this is an effective model of professional specialization for the student-centric model, since the school just started in 2011. Other organizations are piloting other models in hopes of optimizing the use of human resources for optimized student learning. Some universities offering scaled online courses have teams of instructional designers, licensing managers, counselors, staff trainers, adjunct professors, and process managers to ensure fidelity of implementation when different students will take the same course with different professors at different times.

This shift to learner-centric models and new educator roles raises questions about educator preparation and certification for these emerging roles.

Innovations in Education Culture Needed to Scale Blended Learning Adoption

This has been a breakthrough year for blended learning models.   Innovation in supporting technologies, policies, and economic/market change agents have pushed the virtual/blended agenda.  With all of the investment and innovation around blended learning, one might expect wider adoption.

A recent comment posted on Tom Vander Ark’s Education Week blog about adoption of blended learning got my attention:

“We implemented a rotation style blended learning program this year at our high school. The biggest challenge that we are overcoming right now is that students aren't ready for taking ownership of their own learning. We didn't realize how conditioned they are to sit, listen, and regurgitate facts back.”

(emphasis added, accessed on 15 November 2012 from:  http://blogs.edweek.org/edweek/on_innovation/2012/11/why_havent_districts_adopted_blended_learning_faster.html)

This rings true with my observations in schools/classrooms implementing several different blended learning models.  The biggest challenges have to do with changes in practice, both personally for students and teachers, and organizationally. 

When blended learning pilots fail to gain traction or fail to deliver the expected outcomes, it is easy to look to imperfections with the virtual technology, with the methodologies being used, or teacher preparation as the root causes. However, these are often only the scapegoat for a deeper root cause, i.e. resistance to change.  When individuals and organizations try to adopt new practices and encounter challenges, they have a proclivity to revert to more familiar patterns of behavior.  

Vander Ark’s blog listed some of the challenges that have slowed district adoption of blended learning including weaknesses in platforms, models, staffing and development, and district capacity.  These more visible factors create the “friction” for the organizational behavioral changes needed for people to put blended learning into practice.

I used the term “cultural inertia” in a session I co-presented at the National School Boards Association annual conference in 2009 to describe this phenomenon in education organizations. “Culture” can be thought of as shared habits of believing and behaving.  Habits are difficult enough to change in individuals…How is your 2012 New Year’s resolution working out?  Changing the culture of a school or district requires changes in the habits of many people.

Change is Worse than Pain

In another blog post I opined on how the education profession is like the medical profession of the early 19^th century, when after the invention of anesthesia it took over 40 years for surgeons to see past preconceived notions about pain.  It took more than 40 years for them to accept that pain was not necessarily a good thing.  It is well known that the way things are done in schools is not working for many students, but many educators, students, and parents cannot image it working any other way.  As the 19^th century surgeons demonstrated, sometimes having the right technology and knowing how to use it is not enough.  It takes something more for people to embrace a new professional practice.  It takes a change in what the professional and professional community believes about themselves and their professional purpose as it relates to the innovation. 

I cannot help but wonder what might have accelerated the timeline for anesthesia adoption by the 19^th century surgeons.  Moreover, I wonder what “soft innovations” might accelerate professional adoption of blended learning practices.

Blended Learning is an Out-of-Comfort-Zone Experience for Most People…at first.

I have had the opportunity to observe at the classroom level and at different stages of adoption for a couple of different blended learning models.  It was apparent that there were some students and teachers that were energized by the change to more individualized learning, some that felt uncomfortable, and some that had a real struggle with the changed model.  In the models I observed, teachers needed to change from being “sage on the stage” to being “guide on the side.”  Students also need to take on a more active role in their own learning.   Teachers often felt less in control when first implementing the new model and student self-efficacy was challenged.

In spite of the very human nature to resist change I've been able to observe some successful educators and students that have worked within the blended learning model long enough to reach an “aha moment”, realizing that teaching and learning under the blended model is better than the old way of doing things, and adopting new habits of behavior.  However, there are many more who have started down the path to blended learning adoption but who have never make it to the “aha moment”.  There are many schools in which one or two teachers embrace the new model, while the rest of the school continues with the status-quo.

Innovations in Education Culture

I see a great opportunity to accelerate adoption of blended learning models by addressing the human aspects of adopting.  Innovations that matter most are often not the technological innovations.  We need better understand of the human and organizational behavior aspects of blended learning models, the “soft” innovations that catalyze changes in organizational culture and professional practice.

Just by paying attention to this aspect of the problem uncovers some potential solutions.  A while ago, I was chatting with a teacher implementing a blended model.  She was telling me about issues faced in her classroom and some solutions that work.  She talked about the blended model requiring her to make a significant change in professional practice, and that took time.  By enduring frustrations, daily problem solving, and coaching she made the transition.  While we were talking, she reflected on struggles that some students had with the new model.  It occurred to her that students also must adopt new practices and that some of the challenges could have been avoided if more time were spent up front preparing students for the new role.

Thanks to the Innosight Institute  and others, in 2012 we understand at a high-level HOW various blended learning models work.   In 2013, I hope to see organizations take a deeper dive into the processes and human interactions contained within each model and the evidence of learner outcomes, i.e. WHY the model works or does not work.   I also hope to see a deeper dive into the organizational change and professional practice models, and discoveries of soft innovations that catalyze accelerated adoption.    

"Big Data" Synergy Across Key Initiatives

This week I had the privileged of presenting on CEDS at the SETDA Leadership Summit along with champions of other key initiatives, SLC, LRMI, Learning Registry, and My Student Download.  The theme was "big data" to support teaching and learning. 

I think there is a bigger story than what any of these initiative is accomplishing on its own. And the session provided a great opportunity to talk about how, from the perspective of an educator or student, the separate initiatives fit together and support the kind of metadata and paradata for optimizing and personalized learning.  The following video is my version of that story prepared for the SEDTA meeting.  The PDF here (http://goo.gl/1qgn5) is a printable "storyboard" of the same.

...the SETDA session and presenters:

Leveraging "Big Data" to Support Digital Age Learning - Roosevelt Room While states have been focusing on building robust longitudinal data systems for accountability and data-based decision making, a number of public-private efforts have recently launched that have the potential to leverage state, local and educator/student-generated education data in new and exciting ways for teaching and learning. These efforts include those focused on solving K-12 interoperability challenges, improving search and discovery of education resources, sharing of intelligence about the use of education resources, increasing transparency and opening access to education data, and personalizing learning. Participants will get an overview of the work underway in this area, share information about their state's priorities, assess gaps and opportunities, and - in so doing - contribute to the production of a summary white paper for states and policymakers.

Facilitators: Neill Kimrey, Division Director, Division of Instructional Technology, North Carolina Department of Public Instruction Lan Neugent, Assistant Superintendent for Technology, Career, and Adult Education and Chief Information Officer, Virginia Department of Education Resource Specialists: Jim Goodell, Senior Education Analyst at Quality Information Partners Henry Hipps, Senior Program Officer, Bill & Melinda Gates Foundation Michael Jay, President of Educational Systemics Steve Midgley, Consulting Adviser, US Department of Education Lyndsay Pinkus, Director, National and Federal Policy Initiatives, Data Quality Campaign