The Role of Human Interaction in Deep Learning

Do you like “shiny” things as much as I do? If so, don’t fret, as it is human nature.  We often find ourselves captivated by the latest digital tools, such as AI-driven platforms and virtual environments. While these innovations offer incredible potential to scale resources, they frequently miss the most critical component of the educational experience: the human element. Real learning, specifically the kind that supports disruptive thinking and deep cognitive engagement, does not happen in a vacuum of screens and algorithms. It happens through connection.

To truly transform student outcomes, we must shift our focus back to the power of human interaction. Deep learning is not a passive act of consumption; it is an active, social process. When we prioritize human-centered learning experiences, particularly through high-dosage, in-person tutoring, we move beyond simple content delivery and toward a model that prioritizes the whole child.

The Science of Connection and Cognitive Engagement

The importance of human interaction is grounded in more than just sentiment; it is backed by decades of rigorous research. Learning is fundamentally a social endeavor. When students interact with a mentor or tutor in person, they are not just receiving information. They are participating in a feedback loop that stimulates higher-order thinking.

Research has consistently shown that human interaction is the primary driver of academic growth. For instance, Nickow, Hull, and Ritter (2020) conducted a systematic review and meta-analysis of experimental evidence, concluding that tutoring programs consistently yield large positive effects on student learning outcomes across various subjects and grade levels. Their findings emphasize that the structured, personal nature of tutoring is significantly more effective than many other classroom-based interventions.

This effectiveness is rooted in the way humans engage cognitively. According to the ICAP framework, interactive learning, which occurs when students engage in dialogue and collaborative problem-solving with another person, leads to the highest levels of knowledge acquisition. Chi and Wylie (2014) argue that interactive activities are superior to constructive, active, or passive ones because they require students to co-construct knowledge through social mediation. In a virtual-only model, this social mediation is often diluted, resulting in lower cognitive depth.

In-Person vs. Virtual: The Need for Human-Centered Models

While virtual models provided a necessary bridge during the pandemic, the data now clearly shows a preference for the depth that in-person interaction provides. The difference lies in the nuance of communication: the ability of a tutor to read body language, sense frustration before it becomes a barrier, and pivot strategies in real-time. This level of responsiveness is difficult to replicate in a purely digital space.

Disruptive thinking requires a safe environment where students feel seen and supported, something I strongly emphasize in my book Personalize. High-impact, human-centered tutoring creates a space where "failure" is reframed as a necessary step toward mastery. This is particularly vital for students who have fallen behind. Guryan et al. (2023) demonstrated that intensive, in-person tutoring for adolescents can lead to substantial gains in academic performance. This proves that even for older students, the "human touch" can close gaps that traditional instruction struggles to reach.

When we integrate people, curriculum, and technology correctly, the results are transformative. The goal is not to abandon technology but to use it as a scaffold for human interaction. For example, using a proprietary, standards-aligned digital curriculum enables precise data tracking, but the true magic happens when a trained tutor sits beside a student to navigate it together. This hybrid approach, which puts pedagogy and people first and technology second, is what drives sustainable growth.

Evidence-Based Success: A Closer Look

The efficacy of this approach is reflected in recent performance data. During the 2024–2025 school year, students utilizing integrated in-person tutoring models from HeyTutor saw a 160% increase in those testing at or above grade level in Math and a 162% increase in ELA from the beginning to the end of their programs. The impact on English Learners was equally profound, with a 95% increase in Math and a 92% increase in ELA proficiency. 

These results align with the broader consensus on evidence-based reform. Slavin (2018) notes that for educational interventions to be truly effective and scalable, they must be grounded in proven methods that emphasize personalized, small-group instruction. This focus on evidence is why programs that prioritize in-person, small-group interventions such as HeyTutor have been recognized with honors like Stanford University’s National Student Support Accelerator Badge and the 2025 Tech and Learning Awards in Primary and Secondary Education.

A compelling example of this in action can be seen in the SUHSD Case Study, which highlights how the value of in-person learning provides insights that go far beyond what a dashboard can report. It is about the shift in student confidence and the ability to think critically and disruptively about the world around them.

Moving Forward: Prioritizing the Human Element

As we look toward the future of education, we must ensure that our "innovations" do not inadvertently isolate our students. The best solution for deeper student engagement and academic growth remains the intentional connection between a dedicated human being and a learner. By emphasizing in-person, small-group tutoring, we provide students with the social-emotional support and cognitive challenge they need to thrive.

We have the tools, the research, and the data. Now, we must have the leadership to prioritize the human connection in every classroom and every learning session. To see how these principles are being put into practice to drive record-breaking student growth, I encourage you to check out HeyTutor and join the movement toward human-centered educational excellence.

Chi, M. T. H., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49(4), 219-243.

Guryan, J., Ludwig, J., Bhatt, M. P., Cook, P. J., Davis, J. M. V., Dodge, K., Farkas, G., Fryer, R. G., Jr., Mayer, S. E., Pollack, H. A., & Steinberg, L. (2023). Not too late: Improving academic outcomes among adolescents. American Economic Review, 113(3), 738-765.

Nickow, A., Hull, A. F., & Ritter, G. W. (2020). The effects of tutoring on education outcomes: A systematic review and meta-analysis of the experimental evidence. Journal of Research on Educational Effectiveness, 13(3), 397-451.

Slavin, R. E. (2018). Evidence-based reform in education. European Journal of Education, 53(3), 301-312.

Stop Fixing, Start Developing: A Roadmap for High-Impact Coaching

Coaching has been in my blood since my teaching days.  When I got my first position, I was recruited into a freshman football role by one of my former coaches on the varsity staff.  While I was worried about the impact on me as a first-year teacher, those concerns never materialized.  A year later, I took on two additional positions: head varsity ice hockey coach and freshman lacrosse coach.  For me, I wanted to impact as many students as possible both in and out of the classroom. Little did I know that these experiences would profoundly shape me as I built my coaching consultancy many years later.  

In my work with schools across the globe, I have consistently seen that the most significant driver of student outcomes is not a new piece of technology or a trendy curriculum; it is the quality of teaching and leadership. However, effective practices do not happen in a vacuum. It requires a culture of support that moves beyond the traditional, often superficial, evaluative process. To truly move the needle on student learning, we must shift to a coaching culture.

In the latest episode of my podcast, Unpacking the Backpack, I explored the L.E.A.D model designed to guide the growth of effective coaching. By focusing on four specific pillars, we can empower educators to reach new heights of professional excellence.

The Foundation: Listening with Intent

Effective coaching is built on a foundation of trust. Without it, even the most brilliant pedagogical advice will go unheeded. This trust is earned through the practice of listening with intent. Many leaders fall into the trap of "fixing" a teacher's problems before fully understanding the classroom context.

True listening involves a deep engagement with the educator’s perspective. Research supports the necessity of this relational approach. For example, a study by Knight and van Nieuwerburgh (2012) finds that the success of instructional coaching largely depends on the quality of the relationship and the coach's ability to facilitate self-directed learning through empathetic listening. When we listen first, we validate the educator’s experience and create a safe space for the vulnerability that growth requires.

Building the Muscles: Developing Capacity

Once trust is established, the focus shifts to building capacity. In education, we often mistake doing what we are told for actual growth. Capacity, however, is the internal ability to make high-level decisions independently. The goal of coaching is to provide the scaffolding necessary for teachers and administrators to become their own best observers.

This process must be job-embedded and continuous. According to Kraft, Blazar, and Hogan (2018), the impact of coaching is significantly greater than that of traditional professional development because it provides sustained, individualized support directly applicable to the teacher's unique classroom environment. By investing in a shared vision, mission and set of goals, we help educators see not just where they are, but who they can become as practitioners.

The Mirror: Empowering Through Evidence

If capacity building is the "how" of growth, evidence is the "what." We must move away from feedback based on subjective opinions and move toward feedback grounded in objective data. This is where we truly empower our staff. When we use evidence, we are not making a judgment; we are providing a mirror.

Using artifacts such as student work samples, engagement data, or video reflections allows for a more rigorous analysis of practice. Desimone and Pak (2017) emphasize that instructional coaching is most effective when it is content-focused and supported by active learning through the examination of evidence. When an educator can see the direct correlation between their actions and student outcomes, they are more likely to take ownership of the necessary changes. It shifts the conversation from "Am I a good teacher? Am I an effective administrator?" to "Is this strategy working for my students? Is this benefiting my staff?"

The Compass: Aligning Actions

The final component involves ensuring that all moves are aligned with the school’s vision and goals. We have all seen the "initiative fatigue" that occurs when educators feel pulled in multiple directions. A coach serves as an alignment specialist, ensuring that daily practices are coherent and research-based. Alignment creates synergy that drives exponential growth. When the entire district or building is pulling in the same direction, leadership and teaching become more focused and sustainable. We must continually ask whether our coaching cycles directly serve our mission to improve students' lives.

Coaching is the engine of professional growth. By listening with intent, developing capacity, empowering through evidence, and aligning actions, we create a system that supports everyone in being their best. It is about human connection, belief in potential, and a relentless commitment to collective improvement.

Want to learn more about Aspire Change EDU’s L.E.A.D coaching model and how the process can support leaders and educators in your district, school, or organization? Reach out today to set up a complimentary thirty (30) minute Zoom meeting. 

Desimone, L. M., & Pak, K. (2017). Instructional coaching as high-quality professional development. Theory Into Practice, 56(1), 3–12. 

Knight, J., & van Nieuwerburgh, C. (2012). Instructional coaching: A partnership approach to improving instruction. Educational Management Administration & Leadership, 40(1), 100–120. 

Kraft, M. A., Blazar, D., & Hogan, D. (2018). The effect of teacher coaching on instruction and achievement: A meta-analysis of the causal evidence. Review of Educational Research, 88(4), 547–588. 

The Personalized Learning Empowerment Framework

I have been sharing on this blog insights on personalization for the past sixteen (16) years. During my years as a principal, we emphasized a shift from “what” to “who” to help students take greater ownership of their learning.  From using Poll Everywhere to amplify student voice, to flipped lessons in math, and creating the Academies at NMHS, our goal was to create experiences that our students valued and would ultimately improve outcomes, which it did. The journey, however, was anything but easy. 

Moving from a culture of compliance to one of empowerment is the greatest challenge and opportunity facing educational leaders today. For years, our systems have been designed for standardization, often treating students as passive recipients of information rather than active drivers of their own learning. However, as we discussed in our book Personalize, the shift toward personalized learning is not just about technology; it is about pedagogy and the intentional design of experiences that foster agency, mastery, and purpose. Below is our definition:

"Pesonalized learning is all students getting what they need when and where they need it to learn."

The Personalized Learning Empowerment Framework provides a roadmap for this transformation. It moves beyond the "what" of personalization and dives deep into the "how" by focusing on a continuous cycle of growth. By centering the learner, we can ensure that every student has the support they need to succeed in an ever-changing world.

1. Assess and Understand: The Foundation

Effective personalization begins with a deep understanding of who the learner is. We cannot tailor instruction if we do not first establish a clear picture of a student’s strengths, needs, and aspirations. This extends well beyond traditional standardized test data. We must utilize holistic diagnostics that account for social-emotional well-being, cognitive processing, and personal interests.

A critical component of this phase is creating a learner profile. When students document how they learn best, they begin to take ownership of their educational journey. This process is supported by continuous feedback loops that provide real-time insights into student progress. Research indicates that when assessment is used formatively to understand learner variability, it significantly enhances the teacher's ability to provide targeted support (Papadakis et al., 2021). By building this foundation, we move away from a one-size-fits-all diagnostic approach and toward a more human-centered understanding of excellence.

2. Plan and Tailor: The Strategy

Once the foundation is set, the focus shifts to strategic design. Planning in a personalized environment is a collaborative effort between the educator and the student. Co-constructed goals ensure learning objectives are relevant to the student while meeting rigorous academic standards. This partnership is essential for developing student agency, as it gives learners a voice in determining their path to mastery.

Tailoring the strategy requires a commitment to flexible pathways and varied pacing. Not every student needs the same amount of time to master a concept, nor should they all be required to demonstrate their learning in the same way. Providing multiple entry points and methods for demonstrating competency helps create a more equitable classroom environment. Evidence suggests that flexible learning pathways that prioritize student choice lead to higher levels of engagement and cognitive investment (Bernacki et al., 2021). At this stage, the teacher shifts from a dispenser of knowledge to an architect of learning experiences.

3. Engage and Facilitate: The Action

This is where the framework comes to life in the classroom. Engagement is not just about keeping students busy; it is about active learning that challenges students cognitively and keeps them physically engaged. Facilitation involves a delicate balance of targeted instruction, where the teacher works with small groups or individuals based on data, and the use of adaptive tools that provide personalized practice.

In a facilitated environment, the teacher monitors the room, providing "just-in-time" support rather than "just-in-case" lectures. This transition to active learning models encourages students to solve complex problems and collaborate with peers. Studies have shown that technology-enhanced personalized instruction, when combined with strong teacher facilitation, leads to improved outcomes in both literacy and mathematics (Major et al., 2021). The goal is to create a high-energy environment in which the "heavy lifting" of learning is shifted from the teacher to the student.

4. Reflect and Refine: The Growth Loop

The final, and perhaps most important, element of the framework is the growth loop. Learning is not a linear process with a fixed ending; it is a cycle of continuous improvement. Structured reflection enables students to review their work, identify what went well, and determine where they need to improve. This metacognitive practice is what ultimately leads to self-directed learning.

Refinement is also about data-driven adjustments. As students progress through competency-based pathways, they should advance only after demonstrating a genuine understanding of the material. This ensures that no student is left behind due to gaps in foundational knowledge. Research highlights that systematic reflection and the use of data to adjust instructional goals are vital for sustaining long-term academic growth in personalized settings (Walkington & Bernacki, 2020). By closing the loop, we prepare students not only for the next grade level but also for a lifetime of learning and adaptation.

The Personalized Learning Empowerment Framework is more than a conceptual model; it is a catalyst for a systemic shift toward a more human-centered, effective approach to education. By moving beyond the traditional barriers of "one-size-fits-all" instruction, this framework honors every student's unique identity and provides a scalable roadmap for developing true learner agency. When we commit to this continuous cycle of assessment, strategic planning, active facilitation, and purposeful reflection, we do more than just improve test scores. We cultivate the mastery and purpose students need to navigate a complex future. My hope is that this framework empowers educators to stop managing compliance and start inspiring the self-directed, lifelong learners our world desperately needs.

Bernacki, M. L., Greene, J. A., & Crompton, H. (2021). Mobile technology applications in contexts of formal and informal learning. Journal of Computer Assisted Learning, 37(6), 1437-1441.

Major, L., Francis, G. A., & Tsapali, M. (2021). The impact of technology-enhanced personalized learning on student outcomes: A meta-analysis. British Journal of Educational Technology, 52(2), 635-664.

Papadakis, S., Kalogiannakis, M., & Zaranis, N. (2021). Teaching mathematics with mobile devices and the Role of Cognitive Load and Individual Differences. Education and Information Technologies, 26(1), 257-292.

Sheninger, E. C., & Slaugh, N. (2024). Personalize: Meeting the needs of all learners. ConnectEDD Publishing.

Walkington, C., & Bernacki, M. L. (2020). Appraising evidence-based practices in personalized learning: A review of cognitive and social perspectives. Educational Psychologist, 55(3), 156-171.

Moving Toward Meaning: Why Kinesthetic Learning is a Disruptive Necessity

"Learning is not a spectator sport; it is an embodied journey where every step forward strengthens a neural pathway."

In my book, Disruptive Thinking in Our Classrooms, I challenge educators to rethink the traditional "sit and get" model that has dominated instruction for decades.  If we are truly going to prepare students for a future that values agility, creativity, and problem-solving, we must create learning environments that reflect those needs. One of the most overlooked tools in our pedagogical toolkit is not a new app or a faster tablet; it is movement.

The research surrounding the connection between physical activity and cognitive function is overwhelming. Studies have consistently shown that movement increases blood flow to the brain, which in turn enhances executive function and memory (Martin & Murtagh, 2017). When we integrate movement into the core of the lesson, we are not just giving students a break. We are optimizing their brains for high-level thinking. This is where EyeClick stands out as a transformative force in the modern classroom.

The power of this tool lies in its ability to promote embodied learning. This is a pedagogical approach that recognizes the inextricable link between the mind and the body, asserting that cognitive processes are deeply rooted in physical interactions and sensory-motor experiences. By moving beyond passive observation, this method utilizes physical movement, gestures, and environmental engagement to help students internalize abstract concepts and strengthen neural pathways associated with memory and understanding (Stoetzel & Shedrow, 2020). By leveraging the science of embodied learning, EyeClick disrupts the sedentary nature of traditional tech, offering a suite of features that align perfectly with a future-ready pedagogy.

Kinesthetic Cognitive Engagement

In Disruptive Thinking, I argue that the brain is most active when the body is involved (Sheninger, 2021). By utilizing the body as the controller, EyeClick shifts students from passive observers to active participants. Imagine a 4th-grade math class where students are not just solving equations on paper, but are physically stepping on projected answers on the floor to solve for variables. This is embodied learning in action, where students "stealth learn" complex math and science through jumping, stomping, and movement. Research by Chiang and Griego (2017) suggests that this multimodal approach significantly improves the storage and retrieval of memory. It also acts as a positive reset button, channeling excess energy into academic productivity and reducing the behavioral friction that often stems from prolonged sitting.

Eyewiz: The Evolution of Immersive AI

We need to move away from AI that keeps learners tethered to a chair. Eyewiz is what I call "active AI". For district leaders and principals, Eyewiz serves as a tool for equity by scaling high-quality instruction. It empowers educators to transform a simple topic into a physical, immersive lesson instantly. By generating narration and high-quality visuals for movement-based activities, it ensures that technology serves as a bridge to the physical world rather than a wall. This ensures every school can deliver these experiences without increasing teachers' workload, as the AI handles the heavy lifting of content visualization.

Spatial Agility & Learning Environments

To be truly disruptive, we must reconsider our "dead spaces," which include those hallways, cafeterias, and lobbies that often go underutilized. EyeClick offers ultimate spatial versatility, allowing any surface (floors, walls, or tables) to become a high-impact learning hub. This leadership angle allows districts to modernize infrastructure without construction. It is about being agile with our physical environment to create opportunities for collaboration wherever they fit best, transforming the entire school building into a playground for the mind and improving instructional ROI across the system.

Intentional Curricular Depth

Technology is only as good as the pedagogy behind it. EyeClick provides the pedagogical depth required for rigorous instruction, offering 18 versatile templates and a massive marketplace of teacher-created content. This allows leaders to seamlessly integrate movement into STEM and core academics, making abstract concepts tangible. According to a systematic review in Frontiers in Pediatrics (2022), this type of integrated physical activity has a direct positive impact on academic performance across all grade levels.

Collaborative Interconnectivity

One-to-one initiatives should not lead to "one-to-none" social interaction; EyeClick is the "anti-isolation" technology. It necessitates real-time communication, negotiation, and social-emotional growth as students work together in a shared physical space. As Finnan (2015) notes, movement-integrated learning environments develop a sense of community and improve students' ability to maintain positive social relationships. This social-emotional growth is a critical driver of student achievement, as a strong sense of belonging reduces the cognitive load of social anxiety, allowing students to dedicate more mental energy to academic mastery. When students feel connected and physically engaged, they demonstrate increased persistence and improved learning outcomes (Finnan, 2015).

Universal Design & Adaptive Personalization

Equitable learning is at the heart of personalization. With deep customization, this platform ensures every learner has a seat at the table or a spot on the floor. From tabletop modes for students in wheelchairs to adjustable sensory and difficulty settings for special education, it provides a truly inclusive environment where instruction can be modified in seconds to meet specific learner needs.

Final Reflections

If we want our students to be disruptive thinkers, we must be disruptive in how we design the learning experience. Movement is not an "extra"; it is a fundamental requirement for engagement and retention. Leaders need to intentionally design systems that support movement, rather than just asking if it belongs in schools. By moving beyond the screen and utilizing tools like EyeClick, we can create classrooms that are dynamic, inclusive, and deeply focused on the needs of the whole child.

Visit the EyeClick website to see how these solutions work at the district level.

Chiang, I. T., & Griego, L. (2017). The integration of movement in the classroom: A study of memory and social behaviors. Journal of Kinesthetic Learning, 12(3), 45-58.

Finnan, S. (2015). Movement integration and its impact on social-emotional learning in elementary schools. International Journal of Educational Research, 22(1), 102-115.

Frontiers in Pediatrics. (2022). Does learning through movement improve academic performance? A systematic review. Frontiers in Pediatrics, 10, 841582.

Martin, R., & Murtagh, E. (2017). Effect of active lessons on physical activity, academic, and health outcomes: A systematic review. Journal of School Health, 87(12), 940-951.

Sheninger, E. (2021). Disruptive thinking in our classrooms: Preparing learners for their future. ConnectEDD Publishing.

Stoetzel, L., & Shedrow, S. J. (2020). Making the move to embodied learning: A systematic review of movement-integrated literacy instruction. Journal of Research in Reading, 43(4), 512-532.

The Force Multiplier: AI-Assisted Pedagogical Leadership

We are currently standing at a pivotal crossroads in the field of education, as I shared in both Disruptive Thinking and Digital Leadership. On one side, we have the timeless, fundamental principles that make a school function successfully, including leadership, relationships, and sound pedagogy. On the other side, we are witnessing the explosive and rapidly evolving world of artificial intelligence (AI). The question is no longer whether AI will change education because that shift has already occurred. The real question for us as administrators is how we harness this power without losing the human element that defines our profession. We must look at how we use AI to become better pedagogical leaders.

To understand this shift, we need to ground ourselves in the core purpose of our roles. Pedagogical leadership is not about being a manager of a physical building or a processor of paperwork. It is about being a leader of learning. My Framework for Pedagogical Leadership centers on five key domains: developing relationships, providing research and resources, making time for feedback, learning with staff, and analyzing evidence. For years, the biggest barrier to excellence in these areas has been a lack of time. AI changes that math by allowing us to automate the mundane so we can be more present for the profound.

Reclaiming the Human Element

The first pillar of the framework is developing relationships based on trust and mutual respect. Some critics fear that AI is the opposite of human connection, but I argue that it is actually the key to reclaiming the time needed for those connections. When you use AI tools to draft newsletters or summarize meeting notes, you are buying back the minutes required to sit in a classroom and truly support a teacher. Research indicates that when leaders are perceived as supportive and present, teacher self-efficacy and job satisfaction increase significantly. According to Goddard et al. (2015), instructional leadership that fosters a collaborative environment and trust significantly predicts higher levels of collective teacher efficacy. As I noted in my book, digital leadership is about establishing direction, influencing others, and initiating sustainable change through the use of resources and relationships (Sheninger, 2019).

Curating Research and Evidence

The second and fifth pillars involve providing research and resources while analyzing evidence to improve implementation. In the past, being a resource provider meant spending hours scouring journals for strategies. With AI, a pedagogical leader becomes a high-speed curator. You can now use large language models to find research-backed strategies for specific student populations in seconds. One of my favorite tools is Consensus AI. However, the leader must still provide relevance by vetting this output through their professional lens.

AI moves us from being data-rich to being evidence-informed. We can now use technology to look for patterns across massive datasets that would take a human weeks to spot. This allows us to respond to student needs in real time. Research by Liñán and Pérez (2022) highlights how educational data mining and AI can identify students at risk and provide personalized pathways to improve learning outcomes. By using AI to analyze evidence, we ensure that our strategies are actually moving the needle for every learner.

Transforming Feedback and Professional Learning

The third and fourth pillars focus on providing feedback and learning with your team. Feedback must be timely, practical, and specific to be effective. AI-assisted leadership revolutionizes this feedback loop by allowing leaders to organize walkthrough observations into structured formats almost instantaneously. This ensures that the conversation happens while the lesson is still fresh in the teacher's mind. Hattie and Timperley (2007) emphasize that the main purpose of feedback is to reduce discrepancies between current understandings and a goal, and its effectiveness is highly dependent on how it is received and used. AI ensures that facilitation of this feedback is not delayed by administrative friction.

Finally, we must remain the learner-in-chief. Learning with your staff means exploring these new tools together rather than pretending to have all the answers. When we hold Professional Learning Communities (PLC’s), we can use AI to generate prompts that spark deeper pedagogical debates. A study by Chen et al. (2020) suggests that the integration of AI in professional development can help personalize the learning experience for teachers and provide more targeted support for their specific instructional challenges.

AI will not replace leaders, but leaders who use AI will eventually replace leaders who do not. The leaders using AI will have more time for relationships, better access to research, and the ability to provide superior feedback. My framework has not changed because of AI; instead, the technology has made each pillar more attainable. We now have the tools to finally do the work we signed up for which is the work of transforming lives through learning.

For more information on how Aspire Change EDU supports districts, schools, administrators, and educators with AI, click HERE.

Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264-75278.

Goddard, R., Goddard, Y., Kim, E. S., & Miller, R. (2015). A theoretical and empirical analysis of the connections between instructional leadership, teacher collaboration, and collective efficacy scaffolding. Journal of Educational Administration, 53(5), 644-664.

Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81-112.

Liñán, L. C., & Pérez, Á. A. J. (2022). Educational Data Mining and Learning Analytics: differences, similarities, and time evolution. International Journal of Educational Technology in Higher Education, 19(1), 1-21.

Sheninger, E. C. (2019). Digital Leadership: Changing Paradigms for Changing Times. Corwin Press.

The Pivot: From Technical Fixes to Systemic Excellence

Every January, the education world is hit with a familiar tsunami. We return from the break, hopefully rested, only to be met by the relentless "New Year, New Initiatives" cycle. It’s like clockwork: a burst of energy to overhaul grading, pivot to new tech, or rewrite behavior plans. But as I’ve shared in Digital Leadership and Disruptive Thinking, we must confront a hard truth: Novelty is not transformation.

If you are chasing the "new" simply because the calendar flipped, you aren’t leading; you’re reacting. In 2026, reactive leadership is a recipe for burnout. To move beyond the buzzwords, we must evolve our leadership DNA.

Situational Awareness: Matching the Velocity of Change

In a previous post, I discussed the Adaptability Quotient (AQ), but in 2026, AQ is no longer about being "flexible". It is about situational awareness. Variables of school leadership now change monthly, if not weekly. Traditional management often misidentifies cultural shifts as technical glitches. In our 2026 landscape, we must transcend the "fix-it" mentality and adopt a Diagnostic Framework for Agile Leadership. Instead of treating student disengagement or staff burnout as bugs to be patched with a new schedule or a digital tool, we must recognize them as signals for deeper, systemic evolution. This requires a radical redistribution of agency.

As DeMatthews, Kotok, and Knight (2021) argue, effective leadership in crisis or high-velocity environments requires a move toward inclusive, distributive models that empower staff to navigate complex, non-linear problems. By decentralizing authority, we allow those closest to the instructional core to respond to shifting variables in real time.

True pedagogical leadership isn't about being the smartest person at the podium; it’s about creating an ecosystem where everyone is empowered to iterate. By decentralizing authority, we allow those closest to the instructional core to respond to shifting variables in real time. This transforms our schools from static, top-heavy institutions into agile, learning-focused organizations capable of pivoting at the speed of change.

The Rise of AI-Assisted Pedagogical Leadership

We have moved past the "ban it" brigade and the "wild west" of AI. The new frontier is AI-assisted pedagogical leadership. It isn't enough for a leader to be "tech-savvy"; you must be pedagogically fluent. This means distinguishing between learning FROM AI (passive consumption) and learning WITH AI (a feedback-driven partnership).

A current study by Zhang and Cheng (2025) found a significant "familiarity gap" where school leaders often feel more comfortable with AI than the teachers they supervise. This gap creates a friction point in implementation. To lead effectively, we must model fluency by using AI to analyze complex datasets, such as attendance or engagement patterns, to uncover insights that human observation alone might miss. This isn't about replacing human judgment; it is about using AI to amplify high-quality first instruction (HQFI).

The Empathy Paradox in Digitally Augmented Environments

As our schools become more high-tech, our leadership must become more high-touch. I call this the empathy paradox. We are more connected than ever, yet loneliness among staff and students is at an all-time high. Digital emotional intelligence is now a core measurable competency.

Current scholarship in neurocognitive leadership suggests that digitally mediated environments often filter out the rich emotional cues (tone, affect, and presence) essential for affective empathy (Fragouli, 2025). Without intentional "digital empathy," leaders risk creating cultures of shallow, surveillance-based mimicry rather than genuine care. Leading in 2026 requires "reading the digital room" to recognize that a terse Sunday night email creates a cortisol spike in staff that no "wellness" initiative can undo. We must prioritize "no-tech walkthroughs," where the device is left in the office and the focus is entirely on human-to-human validation.

Mission-Aligned Narrative Efficacy

Data without a story is just noise. In Digital Leadership, I introduced the "Storyteller-in-Chief" concept, but today we must focus on narrative efficacy. Stakeholders are increasingly skeptical of institutional claims; they demand evidence grounded in mission-aligned personal stories. Braaten and Farnsworth (2025) highlight that the most effective leaders use "narrative-driven data" to align stakeholder perceptions with actual classroom transformation, ensuring that innovation is seen as a human outcome rather than a clinical metric.

Personal storytelling is a strategic bridge. It’s the difference between reporting a 5% growth in literacy scores and telling the story of a student like "Michael," who found his voice through a specific phonics intervention. Evidence-based storytelling humanizes our roles and reaffirms the values that define our schools. In a world of skepticism, your narrative is your compass.

The Agency Shift: From Compliance to Contribution

Ultimately, the goal of disruptive thinking is to move school culture from compliance to contribution. Compliance keeps the machine running, but it doesn't spark innovation. When we shift toward contribution, we move from "doing school" to "empowering learners." Research by Karakus, Toprak, and Chen (2025) demonstrates that when leaders move from top-down mandates toward fostering teacher agency, organizational commitment and instructional quality rise significantly.

Transformation isn't an event; it's a process of layer-by-layer growth. This year, don't just look for something new, look for something better.

Braaten, M., & Farnsworth, S. (2025). School leaders and AI-driven education: A comparative study of readiness, perceptions, and implementation strategies. Emerald Insight: Journal of Educational Administration, 63(1), 45-62.

DeMatthews, D., Kotok, S., & Knight, D. S. (2021). Adaptive Leadership During a Crisis: A Case Study of a Principal’s Response to COVID-19. Journal of Cases in Educational Leadership, 24(1), 16–29.

Fragouli, E. (2025). Digital empathy and AI: Can machines support employee well-being in the workplace? Journal of Media & Management, 7(7), 1-12.

Karakus, M., Toprak, M., & Chen, J. (2025). From compliance to commitment: A quantitative study of educational leadership's influence on teacher motivation and agency. ResearchGate: International Journal of Educational Leadership, 18(2), 114-131.

Zhang, L., & Cheng, Y. (2025). The rise of AI-assisted instructional leadership: An empirical survey of global school leadership trends. Frontiers in Education, 10, Article 1643023.