BCcampus Digital Learning Strategy Forum 2025

 

Taruna Goel Vodcast with Britt and Tracy

If AI were a song, movie, or book title, what would it be?

Well… I definitely have an answer, but you will have to watch the vodcast to hear it! I had such a great time chatting with Britt Dzioba, M.Ed. and Tracy Roberts about digital literacy, AI, and all the ways educators are trying to make sense of this moment. We reflected, we geeked out a little… and yes, I revealed my favourite tool too. 

Watch the vodcast here:  Taruna Goel Vodcast with Britt and Tracy

But that was just the warm-up.

Last week, over three days, the BCcampus Digital Learning Strategy Forum 2025 brought together more than 400 educators, leaders, and practitioners from BC and beyond. The theme was "Human-Centered Design in Digital Learning Environments" and every presentation, every conversation and every question was on point.

A huge thank you to the Program Committee, to every speaker who shared their expertise, and to all the participants who joined the conference. My session on "AI Literacies for Educators: From Fear to Fluency" was reflective, practical, and full of the competency-based goodness you know I adore :) We discussed the UNESCO AI Competency Framework for Educators and identified ways to include it into our teaching and learning practice. 

Here is a copy of my slides: 2025 DLSForum-TarunaGoel-Slides_18Nov25

I am leaving the forum feeling inspired and hopeful about where BC’s post-secondary community is heading. And if your team or institution wants to dig deeper into AI literacy, competency frameworks, or building skills-first pathways, I would be glad to continue the conversation.

If you made it this far, what is your answer to: 

"If AI were a song, movie, or book title, what would it be?"

#BCcampus #AILiteracy #AICompetencies #DigitalLiteracy #DigitalStrategy #BCPostSecondary #Educators #Teachers #Competencies #Skills #ArtificialIntelligence #CriticalAILiteracy #UNESCOAICompetencyFramework #UNESCO

From Choice to Judgment: Redefining Self-Directed Learning for the AI Era

This reflection emerged from a recent discussion with fellow post-secondary educators, where we explored how Universal Design for Learning (UDL) principles come alive in real courses and programs. In the ongoing conversations about choice and voice, I often find myself returning to a simple truth:

Choice doesn’t automatically lead to better learning.

One of the goals of UDL and of any learner-centered design is to nurture learner agency. But so many learners, including adults returning to formal education, people engaging in continuing education, or professionals participating in corporate upskilling programs, are not accustomed to navigating multiple pathways. I have seen how giving too many options can quickly shift from being empowering to being confusing or even overwhelming.

What we don’t talk about enough are the self-directed learning behaviours that make any “choice” meaningful. Things like learning how to learn, how to self-assess and reflect, and how to connect content or information with purpose. In courses and in organizations, we tend to assume the existence of these meta-learning skills, and we don't put as much energy behind developing these skills more intentionally.

This is where leadership in learning design matters.

Our role isn’t just to provide choice and flexibility; it is to create guided structures or scaffolds that help people build confidence in making informed decisions about their own learning.

Image by wal_172619 from Pixabay

 

At the course level, guided choice-making is about helping learners make purposeful micro-decisions within the context of specific learning outcomes. In practice, within a course, this might mean offering guided choice-making. For example, providing a choice of recommended readings and additional resources, but framing those with brief cues such as:
- “If you’re curious about the theory behind this concept, explore this reading.”
- “If you want to apply it in your work context, try this one.” At the organizational level, the same principle scales up to how we design learning systems that balance autonomy with direction, where we enable people to self-direct their growth without being lost in choice overload.

In competency-based or skills-first organizations, guided choice can show up in multiple ways. For example:
- Curated, purpose-linked learning pathways: Organizations must offer guided learning pathways based on roles, competencies, or career aspirations. This can be aided by providing employees with self-assessment tools that map to these learning pathways. For example, the results of a self-assessment may show strong technical expertise but lower leadership competencies, and that might be an area the employee may explore next in terms of purposeful and meaningful learning experience.
- Recognition systems that reward reflective choices: Recognition systems can be designed to reward, nurture, and encourage reflective learning. For example, when an employee chooses a professional development activity, they could be asked to articulate why they chose it, how they intend to apply it, etc. Over time, these reflections can help people identify and recognize their own learning and develop the meta-skill of learning how to learn.
- Adaptive learning with human guidance: If an organization is developing skill platforms that use AI-driven recommendations, guided choice-making can mean connecting the algorithmic suggestions with human judgment, such as manager notes and recommendations, peer feedback, or self-reflection diaries or assessments that bridge the gap between machine personalization and meaningful human guidance.

Small design choices like these create big shifts. And we need these big shifts.

The next evolution of self-directed learning is already here. We need to start moving from making choices within a course towards making informed, ethical, and purposeful choices about our learning in an AI-augmented world.

As educators and learning leaders, we have to support people to not just exercise choice but to develop the judgment to use it well, and this capability feels even more critical in the age of AI. In many ways, building choice and supporting self-directed learning behaviours isn’t just about learner autonomy anymore; it is about helping people learn how to think with AI without outsourcing their thinking to AI.

AI won't teach us how to learn; that's still our job!

#UDL #LearningDesign #AILiteracy #CriticalThinking #HumanizingAI #LifelongLearning #LearnerAgency #LeadershipInLearning #AdultLearning #LearnerAgency #InstructionalDesign

The Real Work of Training Lies Beyond Knowing and Telling

Image by Manfred Steger from Pixabay

Recently, I was researching some academic papers on effective "Train-the-Trainer" models, and this statement from one of the papers stopped me in my tracks:

"Though individuals can be taught teaching techniques, not everyone is able to teach."

YES! 'Knowing' something isn’t the same as being able to 'teach' it and as Harold D. Stolovitch and Erica J Keeps famously put it: “Telling Ain’t Training.”

The real work of training lies beyond knowing and telling. 

Teaching and training involves way more than subject matter expertise. It demands empathy, patience, curiosity, inspiration and listening. While it may seem counterintuitive, I have found that most training is about listening rather than talking, and this also means listening for what's not always said! 

Training is about recognizing who is in the room, including their prior learning, experiences, interests, motivations, biases, and assumptions. 

I've been doing this for over 25 years but before I step into any 'training' room and while I am in it, I ask myself:

- How do I check my assumptions about “what good learning looks like”?

- How do I challenge my biases about language, culture, confidence, or professionalism?

- How do I simplify something without dumbing it down? 

- How do I resist the urge to talk too much when silence might work better?

- How do I stay present and flexible instead of always sticking to my plan?

- How do I resist giving answers and hold spaces for others’ growth? 

- How do I help people lean into their own voice?

- How do I make it less about the showcase of my content knowledge and more about the facilitation of their learning?

And while I will continue to design Train-the-Trainer programs and frameworks that are about structure, tools, and approaches, what I truly want to nurture is to:

Help trainers make the shift from knowledge holders to learning facilitators

It’s a nuanced shift and a hard one to capture in a conceptual framework.

So, let me ask you. What makes someone a good trainer? Is it something we can teach or something we need to nurture? 

#Trainers #TrainTheTrainers #TellingAintTeaching #Training #Facilitating #EffectiveTraining