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The evolution of teaching and learning

Whether implicit or explicit, we all have a theory of teaching and learning. This gets expressed and enacted in how we engage with our students, the tools we use (or don’t use), and even where we stand in the classroom (F2F or virtually). Traditional theoretical frameworks can be broadly grouped into four domains: instructivism, critical theory, constructivist approaches and andragogy (or adult learning). But the rise of many-to-many, decentred and non-linear networking and communication channels have given rise to corresponding advances in frameworks for teaching and learning in the global classroom.

The 1.0 Classroom

education 1_0

Instructivism as a standard approach to teaching emerged from positivist and post-positivist paradigms. Characterized by the traditional “chalk and talk” style, instructivist pedagogy is premised on a transmission model of learning. Learning outcomes and curricula are pre-determined and delivered in a primarily didactic fashion. The same information is provided to all learners regardless of their pre-existing knowledge and skills.

 

 

Teaching 2.0

education 2_0Constructivism marked a shift from teacher-centred to student-centred learning, deemphasizing informing (memorizing facts) in favour of transforming: locating, critiquing and synthesizing knowledge in a culture of collaboration and sharing. Curriculum development is based on student query, which acknowledges that students learn more by asking questions than by answering them. In this model, students critically engage with course material by posing questions that further group reflection and debate. Adult learning (andragogy) and critical approaches extend and complement contructivist learning models.

 

Education 3.0

Over the last decade, two models have emerged to challege our existing paradigms: heutagogy (Blaschke, 2012, Hase and Kenyon, 2000) and paragogy (Corneli and Danoff, 2011). These extend constructivist, critical and adult learning theories offering models of learning that are (1) self-determined, (2) peer-led,
education 3_0 (3) decentred and (4) non-linear. These characteristics map onto social media applications and the democratization of knowledge and information. Heutagogical and paragogical approaches also extend traditional andragogical and adult learning frameworks by emphasizing meta learning, or learning how to learn.

 

Andragogy, Heutagogy and Social Media

Andragogy (Self-directed) Heutagogy (Self-determined) Parallels with Social Media
Competency development Capability development Knowledge curators
Linear design of curricula Non-linearity in curricula Hyper-learners
Instructor/learner directed Learner directed Autonomous digital communities
Content focus (what is learned) Process focus (meta learning, learning how to learn) Online collaboration, sharing, crowd-sourcing

 

This shift is radical in challenging the implicit notion that we (educators) know best what students need to learn. As Morris (2013) puts it, the issue of how to modify or reinvent teaching in higher education “can create anxiety, uncertainty, and even resentment toward a shift in the culture of learning that we’ve had little control over, that’s come at us from outside our own domain; for others, this new landscape appears inviting, exciting, and full of possibility”.

Radically self-determined and networked learning approaches (like heutagogy and paragogy) affirm individuals as the experts in their lives and learning trajectories. Nothing less than what has always been.

 

 

Note: Images depicting Education 1.0, 2.0 and 3.0 were adapted from a blog post by Jackie Gerstein: Experiences in Self-Determined Learning: Moving from Education 1.0 Through Education 2.0 Towards Education 3.0

This post was adapted from a previous article.

 

 

 

 

 

 

 

 

 

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The Future of (Online) Learning

 

I’ve been teaching a fully online graduate course for the past 13 years. It’s been interesting seeing the cutting-edge become mainstream (with some caveats). MOOCS have made their mark on the learning landscape, and the democratization of education is blossoming. Are exemplars like Khan Academy, TEDEd, YouTubeEDU and iTunesU the disruptive innovation for higher education?

These are not easy times for bricks-and-mortar institutions, grappling with a challenging funding climate and a competitive enrollment landscape, alongside student-as-consumer expectations of outstanding service (and sometimes grades). If that’s not enough, a massive cohort of faculty and administration who grew up in “traditional” classrooms come with a decidedly instructivist slant despite our constructivist intentions (I include myself in this). Maybe that’s why most classrooms are still oriented to a podium at the front, even in new builds. What happens when the hyper-connected, online-all-the-time iGen takes over?

Predicting the future is perilous, and I’m no fortune-teller. But my read on the state of higher education leads me to posit the following, “VUCA“-informed, present-vs-future, higher learning trends for 2015 and beyond:

 

Then and Now Up-and-Coming
Instructor-generated content (Instructivism, Constructivism) User-generated content (Paragogy, Heutagogy)
Lesson Plans Gamification
Episodic assessment (occurs throughout a course) Embedded assessment (assessment is “in the water”)
eLearning mLearning, PLNs, Virtual World
Multimedia Immersive multimedia
Siloed Content APIs
Same content delivered to all learners Prescriptive (customized) content
Opaque Transparent
Learning feels like work Learning feels like play

 

 

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“At the edge of the digital ocean”

 

A recent publication titled Impacts of the Digital Ocean on Education (DiCerbo & Behrens, 2014) talks about our transition from “digital desert” (limited, ephemeral and fragmented data collection systems and processes) to “digital ocean” (massive and exponentially-increasing reservoirs of data). Our day-to-day actions and movements generate a continuous exhaust cloud of data. The ‘Internet of Things’ will make data-gathering even more ubiquitous, personal and pervasive. How can this inform our granular understanding of students’ learning processes and learning needs?

Looking into the future digital ocean, we can imagine schools and individual learners harnessing ubiquitous and naturally generated data to support decisions about learning. In this emerging space…learning is personalised based on learners’ knowledge states and trajectories, and the creators of the systems improve them over time as data helps them to understand the processes of learning. (DiCerbo & Behrens, 2014:2)

DiCerbo and Behrens predict a shift from episodic, individual assessments that are disconnected from ‘real life’, toward seamlessly integrating assessment with learning processes. Learning is inherently collaborative, non-linear, self-determined. A new ‘language’ of assessment means harnessing “data in the wild”:

The digital ocean “is a world in which data are a side-effect, not the primary goal of interesting and motivating activity, and perhaps a world where ‘testing’ is a rare event, but assessment is ‘in the water.” (DiCerbo & Behrens, 2014:15)

The idea of assessment being “in the water” is, in many ways, the killer app for educators, given how hard it is to develop valid tools to measure authentic learning. For example, are multiple choice exams really relevant to 21st Century education and learning? They’re still widely used, and even when we use alternate assessment tools, we’re used to segregating learning from assessment. A data-saturated learning environment makes us uneasy, especially if we’ve grown up in the digital desert. It’s like seeing the real ocean for the very first time: beautiful and scary.

Of course, insitutional Learning Management Systems already harvest data about how often students log into the online environment, what they do, how much time they spend, and how much they contribute. Imagine extending this to seeing how students engage with the e-textbooks used in our courses? We can look at what text they ‘highlight’, where they go back and review, which pages are electronically marked and which are ignored, and how long it takes students to read a page. Game-based environments offer even richer data about time on task, interconnectedness and collaboration, persistence, and motivation. What’s ahead? The classroom is a computer. The lived environment is a computer. Everything we touch and do is a data point.

Right now, our systems are largely disconnected and siloed. But once they work together to present rich and textural understanding of student activities we are really into some serious conversations about ethics and boundaries related to privacy and data ownership. We also run the risk of conflating data with meaningful knowledge, and designing learning environments driven by data-gathering imperatives, versus students’ learning needs.

Like any good discussion paper, DiCerbo and Behrens pose more questions than they answer. That’s a good thing, because this might be right at the top of the education field’s most critical dialogues. Our feet are wet and the tide is coming in.

 

 

Related:

educateria: Higher education’s biggest challenge? 

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education = meta-learning + change

 

I’ve been looking at the 2015 NMC Horizon Report: Higher Education Edition, which charts the biggest near- and longer-term trends across the post-secondary landscape. One of the key directions is advancing highly flexible and innovative learning environments..

With change comes challenge. According to the NMC Report, post-secondary institutions will struggle with how to create these flexible, customizable and personalized learning environments (as students increasingly want and demand). Related challenges include: teaching complex thinking in the context of digital information proliferation, and addressing/resolving competing models of what higher education should/does look like.

The mainstreaming of radically student-centred learning represents a massive disruption to the traditional “broadcast” model of education (one instructor + many students). Just as one-to-many “Web 1.0” gave way to many-to-many social sharing, collaboration and self-curated content consumption (“Web 2.0”), will higher ed institutions see a similarly tectonic shift?

And yet…moving toward student-centred and customizable learning may bring us closer to education in its truest sense. Carl Rogers, the influential humanistic psychotherapist, education theorist and founder of client-centred therapy, stated:

“The only person who is educated is the one who has learned how to learn and change.”

Learning how to learn – the capacity to curate and critically reflect on new information and knowledge – is especially crucial at a time when ‘data never sleep’ (check out this infographic showing what happens during one minute on the Internet).

And, at its heart, all learning is really about change.

In other words: education = meta-learning + change.

welcome woodburned

 

Learning is up to the learner, but teaching is up to the teacher

 

It’s one thing to teach, and quite another to learn. Learning is up to the learner, not the teacher. Just like the old saying: “You can lead a horse to water, but you can’t make him drink.”

But…here’s the thing: You can make him thirsty!

So the question is, how do we create environments that make learners “thirsty”? In other words, how can we foster learner engagement? Herewith, my personal Top 10. Some are prosaic and some can be incredibly challenging. And that’s a good thing, because we are all learners and we’re all teachers.

1. Start as you mean to go on: Begin every workshop, class, course, etc. with a question. Establishing right at the outset that our learning journey will be collective and collaborative is key, and especially early on I make a point of explicitly praising and otherwise rewarding any and all signs of positive engagement on the part of individuals/groups.

2. Incentivize participation: We want learners to take risks and make mistakes. When a person volunteers for something high risk, reinforce the desired behaviour. I don’t advertise it ahead of time, but whoever comes to the front of the room to do a role play with me is going to go back to his or her seat with some small token. It doesn’t even really matter what it is (think $ store).

3. Provide normative feedback: Using in-class mobile polling or an audience response system (like iClickers) lets learners compare their own knowledge/opinions/beliefs/assumptions with others in the room.

4. Establish relevance: Learners what to know “what’s in it for me?” Creating learning activities that help people bridge curricula to their own lives = good. Co-constructing learning activities that address/solve real-world problems = better.

5. Show your sense of humour: It’s hard to be serious all the time. Make it fun and mix it up! Shared laughter builds group cohesion.

6. Affirm autonomy: Let’s face it. Some days we are more fired up than others about our life’s work, and it’s no different for our students. When individuals or groups just don’t seem to be getting on board, I find that stating out loud (with 100% sincerity and with 0% judgement) that how/when/if folks engage is entirely their choice seems to free up some good energy for engagement.

7. Deploy multiple “engagement channels”: Individuals come to learning environments with a range of different learning preferences and a range of preferred ways of participating and engaging. Some people like the limelight, others need time to process and formulate a thoughtful response, and many are more comfortable sharing in a smaller group. The more choices we can offer about how to participate the better, including: verbal/written, large group/small group, synchronous/asynchronous, classroom-based/online, and more.

8. Evoke affect:  Research about emotion (affect), memory, and implications for learning suggest that teaching needs to go beyond engaging at a purely intellectual (cognitive) level, and touch peoples’ feelings (for example, Sylwester, 1994; and more recent perspectives that encompass academic technology and affective/cognitive learning, Calvo & D’Mello, 2011). Create learning activities that pair new knowledge and skills acquisition with positive affect, like surprise, delight, excitement, curiosity for deeper and more durable learning.

9. Show them you care: Authentic care and concern can go far in building good will and fostering mutual respect and support for one another’s learning and achievement.

10. And last but not least – know when to break the rules (and go ahead and break them). Like the time I called it a day and took the group shopping. 

 

 

Related articles

Five Reasons why Reality TV is not a Waste of Time: How reality TV can inform teaching best practices

Seven Essentials for 21st Century Education and Teaching: Stuff it took me 20 years to learn and I’m still trying to figure out

Rules of Engagement: The “Top 4” preconditions for learner engagement

 

 

 

Toy Circus

 

 

 

 

 

 

 

 

 

 

Stuff it took me 20 years to learn – and I’m still trying to figure out

 

1. Learning is volitional. It cannot be mandated. We can teach, but each person decides for him- or herself what will be absorbed and integrated.

 

2. What’s taught in the classroom is only the starting point for knowledge-acquisition and skill mastery. Deep learning happens when class is over – the space for real world application and practice.

 

3. Motivation to learn influences how much work a person is willing to put into self-directed learning and mastery.

 

4. People are most motivated to learn things that are of direct interest and relevance.

 

5. Motivation is a state, not a trait. Motivation is largely a product of how we (instructors) engage students.

 

6. We can amplify students’ engagement by giving them an authentic and substantive voice in co-creating curricula.

 

7. Paragogy and heutagogy, emerging theories of teaching and learning, point to decentred learning, self-determination, and peer-to-peer learning as core to 21st Century education.

 

What might paragogical teaching look like in a post-secondary classroom? In this Acclaim interview with Maegan Stephens (Public Speaking as an “Interactive Democracy”), Professor Stephens describes how:

I give them a ballot of issues to vote on, including the content of the speeches they will give, how they will be graded, and class policies on cell phone use and on attendance. I also ask them if they would prefer to spend class time doing activities, watching speeches, hearing me lecture, or a combination.

I try to ask as more as more of a moderator and facilitator than as a lecturer. This kind of interaction, advances the aspects of debate and speaking oriented pedagogy on day one. It is not so much about flipping the classroom as it is about reversing the authority and changing the professor student dynamic, and encouraging my students to take more responsibility for their classroom.

 

 

Love it. Can’t wait to try it.

 

 

 

 

 

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Bridging the research-practice gap

At a recent conference I attended, one idea was especially  “sticky“:

To know and not to use

Is not yet to know

(Buddhist saying)

Knowledge transfer (KT)  is (rightly) a major concern among researchers, funders and practitioners. Somehow these words really brought home why.

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