Michigan Virtual https://michiganvirtual.org Thu, 14 Aug 2025 20:26:40 +0000 en-US hourly 1 https://wordpress.org/?v=6.8.2 https://michiganvirtual.org/wp-content/uploads/2021/10/cropped-mv-favicon-32x32.png Michigan Virtual https://michiganvirtual.org 32 32 Have You Considered AI in Your Classroom? A Khanmigo Pilot Story https://michiganvirtual.org/blog/have-you-considered-ai-in-your-classroom-a-khanmigo-pilot-story/ Wed, 13 Aug 2025 20:17:10 +0000 https://michiganvirtual.org/?p=97099

In a two-phase pilot across Michigan schools, educators used Khanmigo, an AI-powered tutor and teaching assistant, to explore how AI might support teaching and learning. Their reflections surfaced both opportunities and challenges. The big takeaway? AI has potential, but only with intentional support.

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A Pilot Rooted in Curiosity

What happens when AI becomes a teacher’s assistant, a student’s tutor, and a school’s data collector—all in one? We wanted to find out. We wanted to explore what might be possible. 

What would happen if teachers and students were given the opportunity to test an AI tool with structure, some support, and space to play? What might they discover?

Curious, Not Convinced: Why We Tried Khanmigo

Like many educators, we were hearing a lot about AI—its potential, its risks, and its growing presence in classrooms. But figuring out how to explore AI in a thoughtful, low-stakes way isn’t necessarily easy. 

We were curious about Khanmigo, an AI-powered tutor and teaching assistant developed by Khan Academy, because it offers both student- and teacher-facing tools. It has features for lesson planning and idea generation, and it provides real-time student support. 

What stood out was that Khanmigo isn’t focused on delivering quick answers. Instead, its prompts often encourage students to think through problems, explain their reasoning, and reflect as they arrive at the answer independently. Because it is integrated into Khan Academy’s content-rich platform covering subjects like math, history, coding, and computer science, it also offers some built-in structure for classroom use. 

A Glimpse at the Khanmigo Pilot

Over two pilot phases, Michigan Virtual’s Research and Development team partnered with several Michigan school districts to see what might happen if teachers and students explored Khanmigo together.

Pilot 1—Spring 2024:

  • 19 teachers, 687 students, 14 school districts
  • Focused on Algebra I (9th-grade)
  • Emphasis on Khanmigo as a math tutor and support tool

Pilot 2—Fall 2024-Spring 2025:

  • 24 teachers, 1102 students, 8 school districts
  • Open to all subjects and grade levels
  • Greater emphasis on teacher-facing tools, instructional use cases, and student behavior

We gathered pre- and post-survey data, facilitated professional learning sessions, and asked participants to reflect on their experience. Their feedback about Khanmigo and AI tools in general helped us understand how comfortable they were with using AI tools, how frequently they used them, and where AI tools had the biggest impact in their teaching and their classrooms. 

Real Feedback, Real Classrooms

So what did educators have to say? 

Teacher Tools? Surprisingly Helpful. 

Khanmigo proved especially valuable for brainstorming questions, writing lesson hooks, reviewing content, and suggesting student activities.

“I used it to get ideas for introducing new concepts and making learning more applicable to the real world. It felt like having a planning partner.”

While the survey participants differed, teachers who responded in Spring 2025 expressed more confidence in using AI for planning than those in Fall 2024. By the end of the second pilot, all responding teachers reported at least some confidence in lesson planning, with the number of teachers reporting they felt “very confident” increasing from pre- to post-survey across several categories, including:

  • Supporting diverse learners
  • Drafting emails & communication
  • Content creation & curation
  • Grading, assessment, & feedback
  • Lesson planning

Students? Curious…But Complicated. 

From the teacher’s perspective, student engagement with Khanmigo varied. Some students, particularly quieter students or those working independently, embraced it and used it productively. Others saw it as a workaround—a way to get answers quickly or to check their work, rather than a tool to deepen their understanding. 

“My students struggled to ask Khanmigo the correct question. They didn’t know what they didn’t know—where to start or what to ask.” 

Several teachers described this as less of a problem with the actual tool, but more of a reflection of student readiness and maturity. Still, several agreed that with clear modeling and structure, students were more likely to engage with it as intended. 

“We have to teach kids how to use it and how not to use it—and be clear about the intended purpose.”

What the Data Told Us

  • According to the teachers who responded in the Fall of 2024, compared to those in the Spring of 2025, student use of AI tools increased, moving from monthly to weekly use for most classrooms.
  • Teachers’ familiarity with AI tools grew, with a jump in the number who reported using AI several times a week, and one even reported daily use.
  • Professional learning priorities included personalizing learning, lesson planning, and supporting diverse learners.

Some Speed Bumps Along the Way 

Not everything worked perfectly. Technical challenges like typing equations or interpreting math prompts made things clunky at times. Some students were frustrated with how “chatty” Khanmigo’s AI chatbot tutor was. Others were quick to use it for shortcuts.

And some challenges weren’t technical—they had more to do with timing and student mindset. Teachers noted the importance of starting the year with an AI tool like Khanmigo, rather than trying to integrate it midway through the semester. Teachers also emphasized the importance of setting clear expectations and guidance as to when and why to use the tool, key to ensuring students have the foundational knowledge to understand how to use Khanmigo and other AI tools appropriately.

“Students don’t want to use it how we would like them to. We have to model appropriate usage for them consistently.” 

“It worked better for older or more self-motivated students.”

“AI may need to be taught progressively, with different levels of understanding increased gradually from year to year in school.”

So, Where Do We Go From Here? 

Throughout the two pilots, one thing became clear: there is real potential, but only if we stay intentional.

Teachers told us they want help with things like:

  • Personalizing learning (top interest in both pilots)
  • Using AI for lesson planning and brainstorming
  • Supporting diverse learners with more targeted content

But they also flagged what’s missing:

  • Clearer policies and norms for student use
  • Tools that are more visual and interactive, especially in math
  • Better examples of what “good AI use” looks like

So, now we’re asking big questions:

  • Is AI a shortcut or a scaffold? 
  • How do we teach students to use it ethically and wisely? 
  • What kind of support do teachers need to make the most of it?

If you’re a district leader, teacher, or coach wondering how AI could support your work, know you’re not alone. These are big, complex questions. But trying something small, with proper support, can make a world of difference.

We’re not claiming Khanmigo, or AI in general, is the answer. But AI might be one exciting tool in a growing toolbox. And maybe, just maybe, it can help make learning a little more personal, creative, and supported—if we use it with care and intentionality. 

Your Turn: What Role Should AI Play? 

We’d love to hear how your school approaches AI—cautiously or creatively. We’re happy to share what we’ve learned, what we’d do differently, and what we’re still figuring out.

Because this conversation is just beginning.

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Out of Order, Still Out of Reach: Variations in Pacing among World Language Students https://michiganvirtual.org/blog/variations-in-pacing-among-world-language-students/ Fri, 25 Jul 2025 12:31:03 +0000 https://michiganvirtual.org/?p=96345

Cuccolo & Green’s (2025) report highlighted the relationship between students’ assignment submission patterns and final course scores. Given that pacing has important implications for student performance, knowing what assignment submission patterns look like across schools with varying demographics could help prompt early identification and intervention. As such, this blog explores students’ assignment submission patterns based on school-level demographic information.

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Pacing and progression in online learning

In virtual learning, students are often told they can learn and complete coursework “any time, any place, any pace.” However, previous research suggests that the timing of students’ assignment submissions (their pace), in fact, does matter (Kwon, 2018; Zweig, 2023). For example, students who submitted an assignment within the first week of a course had higher final course scores than students who missed this window (Zweig, 2023). 

In addition to the timing of assignment submissions, it is also important to consider the order in which students submit their assignments. Because the content in many courses is scaffolded, moving through a course sequentially should help students build foundational skills, receive timely feedback on their comprehension, and understand instructor expectations before moving on to increasingly complex topics. 

The impact of deviations from course pacing guides

Across two reports (linked below), researchers from the Michigan Virtual Learning Research Institute examined how the order of students’ assignment submissions was related to course performance by benchmarking student progress against Michigan Virtual’s course pacing guides, which are provided to help students stay on track in their courses. Both reports identified that as students become increasingly out of alignment with course pacing guides, final course scores tend to decline. 

Diving deeper into this relationship, researchers divided students into four equal groups based on how much they deviated from course pacing guides—students who deviated the least were in the first group, and students who deviated the most were in the fourth group. In the first report, which focused on Michigan Virtual’s STEM courses, researchers found a 9.5-point difference in final course score (out of 100) between students in group 1 (the least out of order) and group 4 (the most out of order). In the second report, which focused on Michigan Virtual’s World Language courses, this difference was 9.6 points. Effectively, this translates to about a letter grade difference. Across both reports, final course scores steadily decreased as students’ deviation from course pacing guides increased. 

It is important to be able to identify student characteristics that may be related to virtual course outcomes, as this could help teachers more quickly identify students who may need additional support. While pacing is associated with students’ final course scores, Michigan Virtual’s 2023-2024 Effectiveness Report highlights differences in virtual course pass rates by poverty level and race/ethnicity. For example, Freidhoff and colleagues (2025) note that the virtual pass rate for students in poverty was 58% while students not in poverty had a pass rate of 77%. Given that deviating from course pacing guides is associated with lower final course scores, understanding the extent to which groups with varying demographic characteristics complete assignments out of sequence could help inform proactive supports and interventions. As such, using data from the second report, this blog (part of a blog series exploring the impact of student assignment submission patterns) examines pacing guide deviation based on the demographic makeup of students’ home school buildings.

Methodology snapshot

Student-level assignment and performance data and building-level demographic data were analyzed for students enrolled in Michigan Virtual World Languages courses in Spring 2024. Variables were created to measure the amount and the extent to which students submitted assignments out of alignment with course pacing guides. The “percentage of assignments completed out of order” variable reflects the number of assignments students submitted out of the intended pacing guide order out of all assignments submitted. The “average magnitude” variable refers to the average difference between the intended submission order of consecutively submitted assignments for all of the assignments submitted by a student. For a complete description of the study methodology, please review the full report.

To get a better sense of how the poverty level of schools might be associated with pacing behaviors, schools were categorized based on the percentage of all learners at the school (not just virtual learners) who qualified for free or reduced-price lunch:

  • Low Poverty (≤25%)
  • Mid-Low Poverty (>25% to ≤50%)
  • Mid-High Poverty (>50%)1

School-level poverty data were available for 1,674 students. Approximately 45% (n = 748) were students from “Mid-Low Poverty (>25% to ≤50%)” buildings. In contrast, 23% (n = 385) came from “Mid-High Poverty (>50%)” buildings. 

To better understand how school demographics may relate to pacing, schools were also categorized by the percentage of Non-White students.

  • Non-White School Population ≤25%
  • Non-White School Population >25% and ≤50%
  • Non-White School Population >50%2

Data on the Non-White School Population was available for 1,676 students. Approximately 68% (n = 1140) were from buildings where the Non-White School Population was ≤25%. Just under 10% (n = 164) of students came from buildings where the Non-White School Population was >50%.

Connecting pacing patterns to school demographics

Cuccolo and Green’s report (2025) revealed that most students (97%) deviate from course pacing guides at least once. When examining pacing guide deviations by the poverty level of students’ home schools, the percentage of students who submitted at least one assignment out of the intended order remained remarkably consistent (approximately 97%), varying by only about one percentage point. Further highlighting the commonality of moving out of sequence, almost 98% of students from Mid-High Poverty (>50%) buildings went out of sequence at least once. Review Table 1 for a detailed breakdown of sequencing behaviors by school poverty level.

 Table 1. Pacing Groups by School’s Poverty Level 

Poverty LevelnIn-SequenceOut-of-Sequence
Low Poverty (≤25%)5413.88%96.12%
Mid-Low Poverty (>25% to ≤50%)7482.41%97.59%
Mid-High Poverty (>50%)3852.34%97.66%

A similar pattern was observed when analyzing pacing guide deviations by the Racial/Ethnic makeup of students’ home school buildings. About 97% of students attending schools where the Non-White population was ≤25% submitted at least one assignment out of order. While students from these schools submitted assignments out of sequence most frequently, this value is within two percentage points of those observed in the other categories. Further, the percentage of students who submitted at least one assignment out of order was within .02% across schools where the Non-White student population was between >25% and ≤50%, and >50%. Review Table 2 for more details.

Table 2. Pacing Groups by Percent of Schools’ Non-White Population 

%Non-White CategorynIn-SequenceOut-of-Sequence
Non-White School Population ≤25%11402.54%97.46%
Non-White School Population >25% and ≤50%3724.03%95.97%
Non-White School Population >50%1643.05%96.95%

Connecting pacing patterns to school poverty level

Inspecting the average frequency of course pacing guide deviation by school poverty level revealed that the percentage of assignments submitted out of order was highest among students from Mid-High Poverty (>50%) buildings, on average (M = 47.15, SD = 24.39). This was approximately two to four percentage points higher than the other categories. Overall, the average percentage of assignments submitted out of order was fairly comparable across economic categories (approximately 43-47%).

The average magnitude variable provided a look at how “off” pace students were when they submitted assignments out of order. While there was consistency in average magnitude values across economic cateogories, students from Low-Poverty (≤25%) buildings had the largest values on average (M = 3.74, SD = 3.12) while students from Mid-Low Poverty (>25% to ≤50%) buildings had the smallest values on average (M = 3.39, SD = 2.95). It is worth noting the similarity of these means, as they are within 0.35 percentage points of each other. Taken together, across economic categories, the extent to which students are “off” pace is typically between three and four assignments. Review Table 3 for the average percentage of assignments submitted out of order and the average magnitude for each group of students.

Table 3. Out of Order Assignments and Average Magnitude by School’s Poverty Level

Economic CategoryMean (SD)MinMedianMax
Percentage Out of Order
Low Poverty (≤25%)45.02 (26.17)0.0048.1597.22
Mid-Low Poverty (>25% to ≤50%)43.55 (25.05)0.0046.1197.70
Mid-High Poverty (>50%)47.15 (24.39)0.0050.0095.38
Average Magnitude
Low Poverty (≤25%)3.74 (3.12)0.002.9313.89
Mid-Low Poverty (>25% to ≤50%)3.39 (2.95)0.002.5014.16
Mid-High Poverty (>50%)3.42 (2.81)0.002.6214.56

Connecting pacing patterns to the percentage of schools’ Non-White population

Breaking down the percentage of assignments submitted out of order by the school’s Non-White population suggested that students from school buildings where >50% of the population was Non-White submitted the greatest percentage of assignments out of order, on average (M = 48.99, SD = 26.91). On the other hand, students from buildings where the Non-White School Population was >25% and ≤50% had the lowest percentage of assignments submitted out of order, on average (M = 43.81, SD = 25.97). Overall, this was fairly similar to the trends observed across poverty levels, as the percentage of assignments submitted out of order varied by approximately one to five percentage points across ethnic/racial categories. 

There was remarkable consistency in magnitude values when looking across schools’ Non-White populations. The highest average magnitude values were noted among students whose school had a Non-White population of >50% (M = 3.76, SD = 3.01), which was only 0.3 percentage points greater than the values observed in the two remaining categories. Across buildings with various Non-White populations, students were approximately three and a half to four assignments “off” pace on average. Review Table 4 for the average percentage of assignments submitted out of order and the average magnitude for each group.

Table 4. Out of Order Assignments and Average Magnitude by School’s Non-White Population

%Non-White CategoryMean (SD)MinMedianMax
Percentage Out of Order
Non-White School Population ≤25%44.54 (24.81)0.0047.1197.70
Non-White School Population >25% and ≤50%43.81 (25.97)0.0045.9497.22
Non-White School Population >50%48.99 (26.91)0.0054.2395.00
Average Magnitude
Non-White School Population ≤25%3.47 (2.98)0.002.5814.56
Non-White School Population >25% and ≤50%3.48 (2.94)0.002.7012.22
Non-White School Population >50% 3.76 (3.01)0.003.0013.95

Key findings

On average, students from schools with varying economic and racial/ethnic makeups deviated from pacing guides by approximately 3-4 assignments and submitted just under half of the course content out of order. While this was a near-universal behavior, several patterns stood out:

  • High prevalence of out-of-sequence submissions: Over 95% of students from schools in every demographic group submitted at least one assignment out of order.
  • Pacing trends by poverty level: There was consistency in the percentage of assignments submitted out of order across poverty levels, with a difference of approximately four percentage points between the group with the lowest and highest values. On average, students submitted just under half of their assignments out of order, regardless of building type.
  • Pacing trends by percentage of schools’ Non-White population: There was consistency in the percentage of assignments submitted out of order across buildings with varying Non-White student population percentages—a difference of approximately five percentage points between the group with the lowest and the highest values. Across buildings with varying makeups, students submitted just under half of their assignments out of their intended order. 
  • Extent of deviation: Across building types, students were typically between three and four assignments “off” the intended assignment sequence, on average.
  • Performance thresholds: Cuccolo & Green (2025) found that a drop in final course scores may occur when students submit over 25% of assignments out of order or are more than one assignment “off” from pacing recommendations—on average, all demographic groups exceeded these thresholds.

Implications for educators

These trends suggest that pacing guide deviations are common, but not trivial, among students whose schools have a variety of demographic makeups. Since students who stray from their course pacing guide tend to earn lower grades, early identification is key. Mentors and instructors can support students by:

  • Actively monitoring gradebooks for early signs of pacing issues
  • Reinforcing pacing expectations clearly and consistently
  • Offering feedback and support targeted at helping students stay, or get back, on track

It is important to note that a variety of student, course, and school factors likely interact to contribute to students’ pacing behavior. Although school demographics do not cause pacing behaviors, understanding these patterns may help educators intervene sooner and do so more effectively.

You can check out the full reports below: 

References

Cuccolo, K. & DeBruler, K. (2024). Out of Order, Out of Reach: Navigating Assignment Sequences for STEM Success. Michigan Virtual. https://michiganvirtual.org/research/publications/out-of-order-out-of-reach-navigating-assignment-sequences-for-stem-success/ 

Cuccolo, K. & Green, C. (2025). Out of Order, Still Out of Reach: Navigating Assignment Sequences for MV World Language Courses. Michigan Virtual. https://michiganvirtual.org/research/publications/navigating-assignment-sequences-for-mv-world-language-courses/ 

Freidhoff, J. R., DeBruler, K., Cuccolo, K., & Green, C. (2025). Michigan’s k-12 virtual learning effectiveness report 2023-24. Michigan Virtual. https://michiganvirtual.org/research/publications/michigans-k-12-virtual-learning-effectiveness-report-2023-24/

Kwon, J. B. (2018). Learning trajectories in online mathematics courses. Lansing, MI: Michigan Virtual University. Retrieved from https://michiganvirtual.org/research/publications/learning-trajectories-in-online-mathematics-courses/

Zweig. J. (2023). The first week in an online course: Differences across schools. Michigan Virtual. https://michiganvirtual.org/research/publications/first-weeks-in-an-online-course/

  1. Due to low ns, the ‘High Poverty >75%’ category was combined with the ‘Mid-High Poverty (>50% to ≤75%)’ category to form the existing ‘Mid-High Poverty (>50%)’ category.
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  2. Due to low ns, the ‘Non-White Population >75%’ category was combined with the ‘Mid-High Poverty (>50% to ≤75%)’ category to form the existing ‘Non-White School Population >50%’ category. ↩︎
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From Curiosity to Career: Exploring Possibilities with VR https://michiganvirtual.org/blog/from-curiosity-to-career-exploring-possibilities-with-vr/ Tue, 15 Jul 2025 14:52:16 +0000 https://michiganvirtual.org/?p=96731

Explore how immersive VR simulations helped students step into real-world roles: from EMTs to chefs, all without leaving the classroom.

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Guiding students to discover their passion and contribute their unique skills to a future career is no easy task. Even when students are engaged with the curriculum, providing opportunities to experience real-world job responsibilities isn’t always possible. To help address this challenge, Michigan Virtual partnered with Transfr to provide an immersive Virtual Reality (VR) pilot to five districts across the state.

Why consider virtual reality?

Virtual Reality isn’t exactly new, but it’s certainly having a moment in education. With declining costs, improved equipment, and a rapidly expanding library of educational content, more educators are exploring the potential impact VR could have in their classrooms. What makes VR so exciting is its ability to let students experience a situation. For hands-on learners in particular, this kind of immersive interaction can truly help the content stick. It feels meaningful, memorable, can lead to more complex thinking and reflection, and is, indeed, far more engaging than a worksheet.

Another great reason to explore VR in education is its increasing relevance beyond the classroom. As more industries adopt this technology, companies are turning to VR to train employees through realistic simulations, allowing them to build skills and receive feedback in a safe, controlled environment. These experiences help new employees gain confidence when starting a new career.

A student in a black vest, tan pants, and a baseball cap uses a VR headset and controllers in a classroom. He is standing near brown floor chairs, pointing with one hand while holding a controller in the other. Other students are seated at tables in the background, working or observing.
A student wearing a white hoodie and black athletic pants uses a VR headset and handheld controller in a classroom setting. Behind him, other students are seated at desks working on laptops or talking. The room is warmly lit with string lights and posters on the wall that say “Empathetic” and “Respect.”

PC: Pilot participants from Portland High School

Pilot design and findings

Once we confirmed strong industry interest in VR, Michigan Virtual set out to find the right fit for a program to pilot. We ultimately selected Transfr’s career exploration bundle because it offered a wide variety of simulations tailored to students across multiple age groups. A total of 5 Michigan K-12 school districts participated, providing over 600 students in grades 8 through 12 with the opportunity to access VR simulations within their own classrooms. 

Each simulation highlighted a common skill required in a selected field that could be completed in around six minutes, and concluded with an option for students to rate their experience. Some examples of simulations that students were able to experience were creating a signature dish as a chef and restoring power to an entire town as a transmission line worker. For students who were interested in taking their VR experience to the next level, Transfr’s career exploration portal offered additional opportunities for students to dive deeper into interested career paths. 

Pre-pilot survey results showed that while most participants felt somewhat uncomfortable with the technology—or didn’t currently have access to it in their districts—they still recognized real potential in VR. Many believed it could help guide students toward future workforce expectations and responsibilities, while also supporting more effective instruction by enabling learning experiences that wouldn’t otherwise be possible.

Post-pilot results indicated that, although using VR technology was a bit out of their comfort zone and had a learning curve, the majority viewed it as extremely useful for teaching career readiness. They also saw it as a highly effective tool for preparing students for future workforce demands. Student feedback revealed that their favorite simulations included assisting with a knee surgery as a surgical technologist and responding to a car crash as an EMT. Perhaps we will have an abundance of healthcare enthusiasts in our future! 

What comes next?

We all know that technology is constantly evolving, and there is no doubt that VR will continue to benefit from these advancements. While this pilot was focused on a specific content area, many VR solutions offer a breadth of in-depth simulations that can lead to industry-recognized credentials, as well as a wide range of other educational content. 

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The AI Horizon: Case Studies in Michigan Education’s Transformation (Part 2) https://michiganvirtual.org/blog/the-ai-horizon-case-studies-in-michigan-educations-transformation-part-2/ Fri, 13 Jun 2025 14:40:12 +0000 https://michiganvirtual.org/?p=96063

The work to integrate artificial intelligence in Michigan schools is gaining momentum. In Part 1 of this series, we looked at how four districts are building their own foundations through task forces, learning councils, and student-centered strategies. But that was just the beginning. In this next set of stories, we highlight four more districts that...

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The work to integrate artificial intelligence in Michigan schools is gaining momentum. In Part 1 of this series, we looked at how four districts are building their own foundations through task forces, learning councils, and student-centered strategies. But that was just the beginning.

In this next set of stories, we highlight four more districts that are putting bold ideas into action. From hands-on educator workgroups to county-wide capacity building, each is shaping its own thoughtful approach to AI. These case studies offer a closer look at how local leadership, clear planning, and strong partnerships are driving meaningful progress across Michigan.

Chelsea: Cultivating Innovation Through an AI and Computational Thinking Workgroup

Chelsea School District is taking a proactive and integrated approach to fostering innovation by focusing on the interconnected areas of AI, computational thinking, and computer science. The district’s Director of Curriculum, Instruction, and Assessment is leading an “Innovative Workgroup” comprised of teachers and other staff from across the district. This initiative recognizes the importance of empowering educators to become leaders in exploring and implementing these transformative concepts.

Each month, the Workgroup meets to engage in training sessions centered on AI, computational thinking, and computer science. This regular engagement provides a sustained opportunity for teachers to deepen their understanding and develop practical skills in these areas. A unique aspect of Chelsea’s approach is that the content and focus of these sessions are directly driven by the participants’ completion of Project Tomorrow’s TRAACT assessments. These assessments provide valuable data on the teachers’ existing knowledge and skills, allowing the training to be tailored to their specific needs and areas for growth.

Michigan Virtual provides support by co-planning and facilitating each monthly session. Participants have gotten hands-on and practical experiences testing different AI tools, and are provided updates on new advancements in the field of AI each month. As a result, the Workgroup has developed a set of AI guidance documents tailored to both teachers and students at different grade levels—offering realistic, developmentally appropriate tools and strategies.

Beyond the core Workgroup, the district is taking steps to expand access to AI learning. Michigan Virtual has led introductory training sessions for both teaching and paraprofessional staff, and is now partnering with Chelsea to build a comprehensive district-wide professional learning plan for the 2025–26 school year. With educator leadership, outside expertise, and a foundation of meaningful data, Chelsea is laying the groundwork for sustained innovation across its schools.

Hartland: Developing Policy and Delivering Training for AI Integration

Hartland Consolidated Schools is taking a multi-faceted approach to integrating AI, recognizing the need for both strategic planning and practical implementation. The district’s efforts are being led by the Assistant Superintendent of Curriculum and Instruction, highlighting the administrative prioritization of this initiative.

A key component of Hartland’s strategy involves active participation in the LESA AI Task Force meetings at the county-wide level. This engagement allows Hartland’s team to stay informed about regional discussions, share insights with other districts, and contribute to the development of a broader understanding of AI in education within Livingston County. This collaborative approach ensures that Hartland’s efforts are aligned with wider county initiatives and benefits from shared learning experiences.

In addition to participating in the county-wide task force, Hartland has also developed its own specific policies and guidelines for AI use within the local school district. This proactive step is crucial for establishing a clear framework for responsible and effective AI integration, addressing ethical considerations, and ensuring alignment with the district’s values and educational goals. Furthermore, Hartland is committed to delivering comprehensive training on AI for staff at different levels within the district. This recognition of the need for differentiated professional learning acknowledges that various roles within the school system will interact with AI in different ways and require tailored training to maximize its potential.

Michigan Virtual‘s primary support for Hartland Consolidated Schools is centered around the delivery of this crucial training. Leveraging their expertise in AI in education, Michigan Virtual has worked directly with Hartland’s staff to build their understanding of AI fundamentals, explore practical applications for teaching and learning, and equip them with the skills necessary to confidently integrate AI into their practices.

St. Clair County: Leading the AI Conversation Across the County

St. Clair County Regional Educational Service Agency (SCCRESA) is taking a proactive leadership role in fostering a county-wide dialogue and strategy around the integration of AI in education. The Superintendent and Director of Education Services at SCCRESA have organized an “AI Leaders Task Force” to spearhead this crucial conversation, both for the benefit of internal RESA staff and for the constituent districts within St. Clair County. This initiative highlights SCCRESA’s commitment to supporting the educational community in navigating the rapidly evolving landscape of artificial intelligence.

Michigan Virtual is helping to co-plan and facilitate specialized monthly learning sessions, each aligned to a specific domain of the AI Integration Framework, for SCCRESA staff and any interested leaders from districts within the county. Participating RESA staff members also serve as an internal advisory group, developing a deeper understanding of AI and its implications for education and providing valuable insights to guide the agency’s broader efforts. This train-the-trainer approach aims to build internal capacity within SCCRESA to effectively support the wider educational community.

SCCRESA’s commitment to leading the AI conversation is further underscored by its existing role in providing a wide range of services to local districts, including technology support and professional development. This established infrastructure and network of relationships position SCCRESA as a natural leader in guiding the county’s local districts in their exploration and adoption of AI technologies. SCCRESA is additionally planning a county-wide professional learning opportunity on AI in the spring of 2026, open to all staff and facilitated by Michigan Virtual’s AI Strategists.  The partnership with Michigan Virtual, leveraging their specialized expertise in AI in education, will help SCCRESA achieve its goals of raising awareness, building capacity, and fostering a collaborative approach to AI integration across St. Clair County.

Wyoming Public Schools: Shaping an Implementation Pathway for AI to Support Mastery-Based Learning

Wyoming Public Schools is taking a thoughtful and deliberate approach to integrating AI, aligning its exploration with the district’s existing pedagogical priorities. The Director of Secondary Teaching & Learning is spearheading an AI advisory group composed of a diverse range of stakeholders, including teaching staff, building principals, and central administrators, ensuring that multiple perspectives inform the district’s strategy.

The primary focus of this AI advisory group is to learn more about the capabilities and implications of AI and to collaboratively shape an implementation pathway for AI technology within the district. Notably, Wyoming Public Schools recently completed a strategic planning process and has placed a significant emphasis on mastery-based learning. This pedagogical focus serves as a key lens through which the AI advisory group is approaching its work. The group is particularly eager to explore how AI technology might effectively support the district’s mastery-based learning efforts. This targeted inquiry suggests that Wyoming Public Schools is not viewing AI as a standalone technology but rather as a potential tool to enhance and further their existing educational goals.

To facilitate this important work, the AI advisory group is convening for monthly hour-long meetings throughout the spring of 2025, facilitated by an AI Strategist from Michigan Virtual. These dedicated meetings provide a structured forum for learning, discussion, and planning. The initial goals of these meetings include crafting a clear vision statement for AI integration within the district and beginning the crucial work of developing practical guidance for staff. This foundational work will provide a roadmap for the district’s future AI initiatives.

Looking Ahead: New Partnerships on the Horizon

The momentum is building. In addition to the districts featured here, Michigan Virtual is launching new AI collaborations with St. Joseph Public Schools, Allen Park Public Schools, Wayne-Westland Community Schools, Muskegon Public Schools, Garden City Public Schools, Grosse Ile Township Schools, Portage Public Schools, Crestwood Schools, Hamtramck Public Schools, Oxford Community Schools, Jackson Public Schools, and Haslett Public Schools. Each of these partners brings a new perspective—and a new opportunity to learn and lead.

Conclusion: A Shared Vision for Michigan’s Educational Future

What unites these stories is not a single model, but a shared mindset: one of curiosity, collaboration, and student-centered innovation. Whether through district-led task forces, cross-county learning communities, or teacher-driven workgroups, Michigan schools are approaching AI with care, vision, and urgency.

The future of education in Michigan is being shaped not by technology alone, but by the educators, leaders, and students who are asking the right questions and doing the thoughtful work. As these efforts continue to grow, Michigan Virtual is proud to be a partner and thought leader in this statewide movement.

We’ll continue to share these stories as more districts begin their journeys. If your school is exploring AI and looking for guidance, we’d love to connect.

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The AI Horizon: Case Studies in Michigan Education’s Transformation (Part 1) https://michiganvirtual.org/blog/the-ai-horizon-case-studies-in-michigan-educations-transformation-part-1/ Fri, 13 Jun 2025 14:33:19 +0000 https://michiganvirtual.org/?p=96054

The integration of Artificial Intelligence (AI) is rapidly shifting the landscape of education, presenting both unprecedented opportunities and novel challenges for K-12 institutions. Across Michigan, a wave of innovation is taking shape as K-12 schools, districts, and ISDs explore how to use AI thoughtfully to enhance student learning, empower educators, and prepare for a tech-forward...

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The integration of Artificial Intelligence (AI) is rapidly shifting the landscape of education, presenting both unprecedented opportunities and novel challenges for K-12 institutions. Across Michigan, a wave of innovation is taking shape as K-12 schools, districts, and ISDs explore how to use AI thoughtfully to enhance student learning, empower educators, and prepare for a tech-forward future. While challenges remain, the proactive and collaborative efforts unfolding across the state offer a hopeful and strategic view of what’s possible.

Michigan Virtual has partnered with districts to facilitate this learning journey, not by prescribing solutions, but by helping schools build the internal capacity to lead their own efforts. From professional learning communities to district-wide task forces, these case studies highlight how Michigan schools are putting students first while approaching AI integration with both curiosity and care.

Livingston County: Forging a County-Wide Path for AI in Education

The Livingston Educational Service Agency (LESA) is taking bold, coordinated action to prepare its schools for the age of AI. With districts across the county operating at various levels of readiness, LESA recognized an opportunity to unite stakeholders and ensure every district had a voice in the process. To do this, they launched a county-wide AI task force that included a diverse mix of central administrators, building leaders, and classroom educators from all five districts.

From February to December 2024, Michigan Virtual supported this initiative by facilitating monthly task force meetings. These sessions went beyond routine updates. They created a focused space for district leaders and educators to build their understanding of AI and consider its role in teaching and learning. Each district team completed a self-assessment to evaluate their readiness and establish a baseline, setting the stage for thoughtful planning. Over time, these conversations evolved into the development of customized AI vision statements for each district, anchoring their work in local context and priorities.

By fall 2024, the task force had transitioned from planning to action. Each district identified its top priorities, ranging from staff training and policy development to student AI literacy and curriculum planning. This allowed for a highly personalized approach, where districts could focus their energy on what mattered most to their schools.

Looking ahead, LESA is shifting into a more distributed model with the creation of an “AI Network” in spring 2025. This next phase will be powered by district-level champions who will work directly with students and continue piloting AI strategies in classrooms. It represents a hands-on, sustainable evolution of the initial planning work—one where educators become practitioners of what they’ve learned.

Notably, LESA is also thinking beyond the school walls. Their co-sponsorship of a Parent Summit on AI, featuring speakers from both LESA and Michigan Virtual, signals a broader commitment to community engagement. By bringing families into the conversation, LESA is laying the groundwork for transparency, trust, and long-term impact.

Their story demonstrates how a collaborative, systems-level approach—with room for local flexibility—can create the conditions for meaningful and lasting AI integration across an entire county. 

Westwood: A Focused Approach to AI Integration Through Strategic Task Force Development

Westwood Community Schools is taking a hands-on, purposeful approach to AI integration, led by the district’s Curriculum Director. Recognizing the transformative potential of AI, the district is leading the charge by assembling a dedicated task force. This proactive step underscores the district’s commitment to systematically exploring and implementing AI technologies.

To support this early work, Michigan Virtual partnered with the district to design a foundational staff survey. This assessment helped determine educators’ starting points—their familiarity with AI tools and their comfort levels using them. The responses informed the task force’s initial planning and ensured their strategy was grounded in real-time insights from the people who would ultimately put it into practice.

Westwood launched the 2024–25 school year by setting the tone early: an all-staff professional development day on AI, facilitated by Michigan Virtual. With energy and direction in place, the task force then codified its core goals, backed by measurable outcomes. Among them: achieving baseline AI literacy for 80% of staff, which the district defined as using three different AI tools and writing effective prompts; developing a clear and comprehensive set of AI use guidelines to present to district leadership by the end of the year; and ensuring that at least one-third of staff are actively integrating AI into instruction or administrative work.

Equity is another pillar of Westwood’s plan. The district is intentional about ensuring that all students and educators—not just early adopters—have access to the tools and training they need. To keep momentum strong, Westwood is scheduling regular task force meetings and offering monthly learning opportunities. Feedback loops are built into the process, allowing the district to stay nimble, responsive, and aligned with its long-term goals.

Grosse Pointe: Cultivating Internal Expertise with an AI Learning Council

Grosse Pointe Public School System (GPPSS) is tackling the challenge of AI in education by building knowledge from the inside out. Instead of starting with a top-down plan or one-size-fits-all solution, the district chose to create an AI Learning Council that reflects the voices of its own school community. Led by the Executive Director of Learning, Technology & Strategic Relations, this group includes teachers, administrators, and community members—bringing together a variety of perspectives to shape their shared understanding of AI.

The primary focus of the AI Learning Council is to engage in ongoing learning and robust discussions around what GPPSS’s specific approach to AI will entail. This internal focus suggests a desire for the district to develop a vision for AI integration that is deeply rooted in its own context, values, and educational goals. Notably, Grosse Pointe takes a highly self-directed approach to this learning process. District leadership independently plans and delivers almost all of the council’s sessions, demonstrating a strong sense of ownership and a wealth of internal capacity. These internally developed sessions are thoughtfully aligned with the domains of Michigan Virtual‘s comprehensive integration framework. This alignment indicates that while Grosse Pointe is leading its own learning, it is still grounding its efforts in promising practices and a recognized structure for considering the various facets of AI integration. Additionally, a district-wide professional learning opportunity on AI will be offered in the spring of 2025 to further build foundational understanding among staff.

While Grosse Pointe values its self-directed learning approach, they also know when to tap into external expertise. Michigan Virtual serves as a sounding board, offering feedback and resources to support the Council’s work. It’s a thoughtful blend of independence and collaboration that’s helping the district make informed, locally driven decisions about AI integration. 

Ann Arbor: Embracing a Student-Centered Approach to AI Adoption

Ann Arbor Public Schools (AAPS) is placing students at the center of its journey into AI. Instead of beginning with policy or tools, the district has focused on understanding how AI can directly benefit student learning and classroom engagement. That vision began taking shape during the 2023–24 school year, when the Director of Instructional Technology and two Instructional Technology Consultants launched an AI Study Group. The goal was simple: explore, learn, and gain firsthand experience with emerging AI technologies. This exploratory phase gave educators space to experiment and understand the real-world potential—and limits—of these tools before crafting a formal plan.

Now, in 2024–25, the district is channeling those lessons into a comprehensive, student-centered AI strategy. This explicit focus on the student perspective suggests that Ann Arbor is prioritizing how AI can directly enhance student learning, engagement, and overall educational experiences. To ensure that this plan truly reflects the needs and voices of students, AAPS is carrying out a number of different activities, including the formation of student panels, providing a platform for students to share their perspectives and insights on AI; convening a community task force to collaboratively identify the guiding principles and core beliefs that will underpin the district’s approach to AI; establishing an AI action research team, empowering educators to investigate the impact of AI in their own classrooms; the official adoption of paid AI tools that have demonstrated value in the initial experimentation phase; and the provision of targeted professional learning opportunities for staff to equip them with the skills and knowledge needed to effectively integrate AI in a student-centered manner.

While AAPS is taking the lead and building strong internal capacity, the district continues to collaborate with Michigan Virtual for guidance and expertise when needed. This approach—locally driven, but thoughtfully supported—ensures that Ann Arbor’s work remains grounded, student-focused, and sustainable as the role of AI in schools continues to evolve.

What’s Next?

As these stories show, there’s no one-size-fits-all solution when it comes to bringing AI into schools. Some districts are launching large-scale initiatives across an entire county, while others are starting small with tightly focused teams. But across the board, what stands out is the commitment to learning together, making intentional choices, and prioritizing both educator and student needs.

In Part 2, we’ll continue this journey with stories from Chelsea, Hartland, St. Clair County, and Wyoming—districts building their own blueprints for AI integration and setting the stage for what’s next as new collaborations take shape.

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Mastering Change: Coaching as the Lever for Transformation in Education https://michiganvirtual.org/blog/mastering-change-coaching-as-the-lever-for-transformation-in-education/ Tue, 10 Jun 2025 15:54:21 +0000 https://michiganvirtual.org/?p=96137

Originally published in the Spring 2025 issue of the MASB Leaderboard Magazine. Introduction A few years ago, I came across Master of Change by Brad Stulberg, and it couldn’t have landed at a more fitting time. Personally and professionally, I was navigating big transitions—shifts in my role in education, family and health challenges, and the...

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Originally published in the Spring 2025 issue of the MASB Leaderboard Magazine.

Introduction

A few years ago, I came across Master of Change by Brad Stulberg, and it couldn’t have landed at a more fitting time. Personally and professionally, I was navigating big transitions—shifts in my role in education, family and health challenges, and the dizzying pace of change unfolding all around us. Change wasn’t just happening to me; it was happening within me. I’m sure you’ve felt this too, the way life’s only constant seems to be change itself.

But what is change, really? And how can we define it in a way that’s meaningful for both our work in education and our own lives?

The truth is, change isn’t just an event. It’s a process, a force, sometimes a companion we didn’t invite but who shows up anyway. We experience it personally, collectively, gradually, and/or all at once.

When change is everywhere and all the time, we need ways to make sense of it. For me, having a skilled coach beside me was a game-changer, but I’ll come back to that shortly. First, let’s zoom out and explore change through different lenses. I believe that when we do this, we’ll see the key isn’t to resist change, but to master it, and the right coaching can help us do exactly that.

Understanding change through allostasis and rugged flexibility

To lead well through change, we first need to understand it more deeply. For decades, we leaned on the concept of homeostasis, the belief that systems work best when they return to a stable balance. I get it, we crave stability in life. But let’s be honest: in today’s complex world, especially in education, “going back to normal” isn’t always possible, or even desirable.

Instead, modern science introduces a more realistic, helpful model: allostasis. Unlike homeostasis, allostasis acknowledges that stability can be maintained by continuous adaptation. It is the science of stability through change, adapting and creating a “new normal” as circumstances shift. That idea really resonates with me, especially as I reflect on the sheer volume of change we all experience. Stulberg (2022) points out that the average person encounters 36 life-disrupting events. Think about that: a big disruption roughly every 18 to 24 months. I know you’re likely already doing that math for your own life, and yes, it adds up quickly.

In education, where change comes from shifting policies, technologies, student needs, and societal pressures, it’s essential that we, as leaders, develop mindsets, skills, and identities that help us not just endure change but use it as a catalyst for growth.

One concept Stulberg offers that’s helped me tremendously is rugged flexibility. It’s about holding firm to essential values, such as equity, student success, and instructional excellence, while remaining open to new methodologies, strategies, and approaches that better serve the changing needs of schools. I’ve found that rugged flexibility doesn’t just help me as a leader, it creates space for innovation and resilience across entire systems. And while it’s powerful on its own, there are additional tools we can use to navigate change with even more clarity and intention.

Mindsets, behaviors, and identities that support change

Change is inevitable, but how we respond to it is where choice comes in. In my own leadership journey, I’ve realized that how we navigate change is shaped by an interplay of mindset, behaviors, and identity.

Mindset: The lens through which we view the world. Certain mindsets have helped me—and many leaders I’ve coached—lean into change with confidence:

  • A growth mindset reminds us that intelligence and capacity aren’t fixed; we can grow (Dweck, 2006).
  • Embracing the impermanence of life helps us find comfort amid uncertainty or ambiguity (Dalai Lama, Tutu, & Abrams, 2016).
  • A curiosity mindset pushes us to ask deeper questions and explore creative connections (MacKenzie & Bathurst-Hunt, 2018; Vance, 2022).
  • An innovator’s mindset reframes challenges as opportunities and encourages bold thinking (Couros, 2015).

In my experience, watching leaders live these mindsets and being coached to adopt them myself has shaped how I see and respond to complexity.

Behaviors: Mindset alone isn’t enough. Our actions need to align. One of my favorite reminders comes from Henry Ford: “If you always do what you’ve always done, you’ll always get what you’ve always got.”

Here are three behaviors I encourage all leaders to practice and that I do myself:

  1. Prioritize regular self-reflection. Create time to ask, what truly matters to me? What am I doing that is helping or hindering my transformation?
  2. Foster authentic human connections. Have real conversations, not just surface-level exchanges.
  3. Rely on intentional, defined processes aligned to long-term values for effective decision making, even when short-term pressures push on us all the time.

📋 Take a quick pulse-check:

How often have you lived these behaviors recently? Go to your calendar. Start to examine the frequency and depth at which each behavior—reflection, connection, and processes for choice-making has occurred. How many of these behaviors did you do in the past week? Do you need to go back further than a week? How about the past month? Now look at your calendar going forward, can you block out time to intentionally ensure you are practicing these behaviors? Remember, what you pay attention to gets done.

Identity

Finally, how do you see yourself? Do you view yourself as a change agent, a leader with the power to influence meaningful transformation? Titles might hint at this role, but the deeper driver is your core values. When we internalize identities like “architect of transformation,” we bring energy and courage to the work ahead.

Mindsets fuel behaviors, behaviors reinforce identity, and identity acts as a multiplier in our change journey. Yet, no one leads change alone. Sustainable transformation is also shaped by context, culture, and community—external forces we’ll explore next.

External Factors: The role of context and professional learning

Even the most adaptable leaders can’t create lasting change in isolation. Schools are living ecosystems influenced by politics, funding, and community expectations. That’s why personal adaptability needs to be paired with structural and cultural support.

Cynthia Coburn’s work (2003) reminds us that context matters when scaling or sustaining change. Schools don’t operate in a vacuum, they’re part of interconnected systems. As leaders, we must account for both internal and external influences as we design and evolve change efforts.

But here’s the thing: navigating change in education isn’t just about implementing an initiative; it’s about scaling it in a way that’s both meaningful and sustainable. And that’s where many well-intentioned people and efforts typically fall short.

Scaling change in schools: Depth before breadth

The challenge in education is not just adapting to change but also scaling it effectively. Coburn challenges us to rethink what it means to scale. It’s not just about how fast or far an idea spreads, it’s about how deeply it takes root. Coburn (2023) claims that scalable and sustainable change rests on three key principles:

  • Depth: Ensuring that shifts in practice are deeply understood and embedded individually and/or in small groups before expanding them across a larger system.
  • Pacing: Recognizing that real transformation takes time. Avoid rushing for quick wins that don’t last. Respect when timing is out of your control, but don’t stop moving either!
  • Breadth/cultural integration: True change aligns with the values and behaviors of the entire organization, and is done with people, not to them.

I often hear myths like “If a change didn’t go systemwide, it wasn’t successful” or “If it didn’t happen on schedule, it failed.” But the real impact doesn’t always follow neat timelines or show up in spreadsheets. Sometimes, helping one person, one team, or one school take a transformative step forward is enough to spark a ripple effect. By utilizing a broader definition of scalability, as well as debunking these myths about scalability of change, sustainability, and impact, individuals like school leaders, groups like boards of education, and districts as communities can authentically navigate change together. And this is where coaching becomes invaluable, it creates the space for leaders (with all different titles) to think deeply, plan intentionally, and navigate change in ways that stick.

Professional learning to address change

Navigating change isn’t just an individual challenge, it’s a collective one. That’s why professional learning is so essential. In education, where complexity is the norm, leaders need high-quality learning experiences to strengthen their capacity to lead through uncertainty.

Jay Bennett (2023) spotlighted the Learning Forward Standards for Professional Learning, which emphasize that learning should be ongoing, collaborative, embedded in daily work, and data-informed. These principles don’t just apply to teachers and students; they’re critical for leaders, too.

While workshops, courses, and peer learning communities all play important roles, in my experience, coaching is one of the most powerful forms of professional learning. Coaching provides personalized, ongoing, just-in-time support that helps leaders build resilience, sharpen strategies, and sustain meaningful change.

Coaching for Change: The power of human connection

Coaching has been a game-changer for me, not just professionally, but personally. At its core, coaching is a relationship built on trust, reflection, and intentional dialogue. It’s about helping leaders like you and me surface ideas, challenge assumptions, and strengthen both mindset and action.

I draw from the work of researchers like Costa, Garmston, Knight, Aguilar, and others, but here’s my personal take:

  • Coaching is an intentional set of conversations leveraging structured but authentic dialogue, growing an individual’s self-reflection, exploration of ideas, and the development of new perspectives and skills.
  • Coaching occurs in a one-on-one environment, establishing a trusting relationship and a safe space to take risks and be honest. It is also customized based on the unique context (district, community, etc.) and needs of the individual.
  • Coaching takes time but is most likely to sustain changes in behavior and mindset in a way that exceeds stand-alone professional development or other forms of learning.

From my own lived experience and research, I’ve seen four clear benefits that coaching brings to the change process:

  1. By talking with another person, thinking is made visible, more real, and more actionable.
  2. Repeated talking with a trusted person over time increases a person’s internal accountability and external sustainability of a transformation at multiple levels.
  3. By engaging with others of various viewpoints and perspectives, new ideas are more likely to be generated. Exposure to different viewpoints challenges assumptions and encourages creative solutions.
  4. By spending time in reflection with others, learning deepens, beliefs and mindsets solidify into behaviors, and effective decision-making processes increase.

Also, good coaching is customized to your unique role, your district, and your community. And while it takes time, it creates lasting shifts, far beyond what stand-alone professional development can do.

I know, I’ve lived it. I’ve been coached and have coached others for years. During my time as the Director of Learning Services and Instruction at the Jackson County Intermediate School District, with goals as a leader and a strategic vision for innovation, I found I wanted and needed a trusted person to push my mindset, co-build action and accountability for small steps of change, and much more. So, I invested in an external coach for myself as well as coaching for some leaders on my team. The results? Tangible, meaningful transformation—not just in me, but across the entire organization.

Today, I’m a champion of Leadership Coaching for Innovation, a model designed specifically for education leaders managing complex change and striving for innovation that will make a difference in our schools. Grounded in research and tailored to each leader’s unique context, this coaching approach has helped me and many others harness change as a lever for positive impact.

Conclusion

Change in education isn’t just inevitable—it’s essential. But it doesn’t have to feel overwhelming. When we understand models like allostasis, adopt the right mindsets, and engage in intentional behaviors, we start turning disruption into progress.

And when we add coaching to the equation? That’s when things really shift. Coaching provides the reflection, structure, and human connection that helps leaders like us move from reacting to change to mastering it.

I’ve lived this journey. I’ve seen how coaching has helped me, and countless others, build resilience, deepen purpose, and lead with clarity, even in uncertain times.

So, here’s my invitation to you: Don’t just navigate change. Learn to master it—with support, with intention, and with a coach by your side. Because when you do, change becomes more than something to survive. It becomes your greatest opportunity to lead, grow, and transform your community.


References

Bstan-ʼdzin-rgya-mtsho., Tutu, D., & Abrams, D. C. (2016). The book of joy: Lasting happiness in a changing world. Avery, an imprint of Penguin Random House.

Coburn, C. E. (2003). Rethinking scale: Moving beyond the numbers. Educational Researcher, 32(6), 3-12.

Couros, G. (2015). The innovator’s mindset: Empower learning, unleash talent, and lead a culture of creativity. Dave Burgess Consulting.

Dweck, C. S. (2006). Mindset: The new psychology of success. Random House.

Learning Forward. (2023). Standards for professional learning. Retrieved from https://learningforward.org/standards-for-professional-learning/

MacKenzie, T., & Bathurst-Hunt, R. (2018). Inquiry mindset: nurturing the dreams, wonders, & curiosities of our youngest learners. EdTechTeam Press.

Michigan Virtual. (n.d.). Leadership coaching for innovation. Retrieved from https://michiganvirtual.org/consulting/leadership-coaching-innovation

Spivey, M. & Shulberg, B. (2024, Jan. 2). Podcast: How to make your resolution stick, with ‘Master of Change’ author Brad Stulberg. Retrieved from https://www.spiveyconsulting.com/blog-post/brad-stulberg-podcast

Stulberg, B. (2022). Master of change: How to excel when everything is changing – Including you. HarperOne.

Vance. J. (2022). Leading with a lens of inquiry: Cultivating conditions for curiosity and empowering agency. Elevate Books Edu.

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Out of Order, Still Out of Reach: An Interview with a Researcher https://michiganvirtual.org/blog/out-of-order-still-out-of-reach-an-interview-with-a-researcher/ Wed, 04 Jun 2025 18:52:31 +0000 https://michiganvirtual.org/?p=96044

In this blog, MVLRI researchers synthesize the key findings from two research studies about student assignment submission patterns in Michigan Virtual online courses.

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Self-paced asynchronous online courses offer students significant flexibility in when and where learning occurs. Recent research by the Michigan Virtual Research Institute examined how student pacing, particularly the order in which they submit assignments, is related to online STEM and World Language course performance. Understanding students’ pacing behavior and its relationship to course performance can help inform the strategies educators and mentors use when working with students in self-paced online courses.  

In the following interview from our “Interview with a Researcher” blog series, the lead researchers behind Michigan Virtual Learning Research Institute’s (MVLRI) STEM and World Languages reports synthesize some take-home messages about students’ assignment submission patterns. 

Why is it important to consider online learners’ assignment submission patterns? 

Assignment submission patterns are a part of a set of student behaviors called pacing—how students progress through a course. Pacing has traditionally been thought of as the timing of students’ assignment submissions. When conceptualizing pacing in this way, we often ask questions like, Are students waiting until the last minute to submit assignments? Are they submitting assignments early or late? Are they submitting a lot of assignments close together? It’s well-established that the timing of student assignment submissions is related to course outcomes. However, our team wanted to know more about the possible impact of out-of-order assignment submissions because, anecdotally, this was a pattern Michigan Virtual (MV) instructors were noticing within these asynchronous courses. Assignment sequencing is the term we gave to describe the order in which students submit their assignments. When we looked at this behavior across two domains (STEM and World Languages), we found evidence that it is related to course outcomes. Specifically, as students submit more assignments out of their intended course order, final course scores tend to decline.  

Why did you feel like it was important to look at assignment sequencing in World Language courses?

Great question! The original hypothesis that prompted this research was that submitting assignments out of their intended order would be detrimental to student performance because it would undermine the scaffolding built into the courses. So, based on this hypothesis, our first study on assignment sequencing used a sample of students enrolled in Michigan Virtual STEM courses since they are highly scaffolded. Of course, scaffolding is likely to vary by subject area and course, so we felt it was important to expand our research. After preliminary analyses of assignment sequencing in several other subject areas, World Language had a high percentage of students who moved out of alignment with course pacing guides and is a distinct subject area from STEM, making it an ideal choice for expanding our previous research. Looking across these two subject areas also allows us to understand the generalizability of our findings, compare and contrast key differences, and provide data-backed recommendations to instructors and mentors of students in these subject areas. 

What did students’ assignment submission patterns look like in World Language courses? Could you explain the relationship between students’ assignment sequencing and their final course scores?

We found that it was really common for students to deviate from course pacing guides! 97% of students submitted at least one assignment out of alignment with their course pacing guide. Among these students, approximately 45% of completed course assignments were submitted out of order. While the volume of assignments submitted out of order was fairly high, students were about three assignments “off” from the intended pacing guide order.

Looking across the spectrum of student performance, we observed that students’ final course scores steadily declined as their assignment submissions became increasingly out of order, both in terms of the number of assignments submitted out of order and how far “off” students were from the pacing guide expectation. To put this in perspective, students who submitted the fewest assignments out of order had average final course scores as much as a full letter grade higher than students who had the greatest number of assignments submitted out of order. 

You mentioned that the first study in this series looked at assignment sequencing in online STEM courses. Were there any notable differences between that study and this one? Did you see any patterns across these two studies?

The general pattern of results was similar across the two studies in that students’ assignment submission patterns had a relationship with final course scores. The biggest difference, however, was in the percentage of students who went out of order in each subject area. While both studies showed high rates of out-of-sequence behavior, 93% of students went out of order in the STEM study compared to 97% in World Languages. Across both studies, course scores steadily declined as students submitted a greater percentage of assignments out of order and strayed further from the intended assignment sequence. In STEM courses, there was a 9.5 point difference in average final course scores between students with the fewest and greatest number of assignments submitted out of order, whereas in World Language courses, there was a 9.6 point difference. The relationship between assignment sequencing and final course scores was really similar across the two studies, which suggests that monitoring and encouraging proper pacing is important for student performance in both subject areas.

Based on your findings across these two studies, what recommendations do you have for online instructors and mentors?

Our findings indicate that it is common for students to deviate from course pacing guides at least once during their time enrolled in MV online asynchronous courses. Some deviation is to be expected and is unlikely to negatively impact student performance, especially if that deviation is infrequent or small (e.g., within a unit). However, if students are consistently moving between units or submitting a high volume (more than 25%) of their assignments out of order, online instructors may want to flag these behaviors (and students) and monitor for performance declines. 

In general, adhering to best practices for online teaching and mentoring is recommended to help online learners be as successful as possible. Communicating course expectations early on (informing students of the structure, workload, pacing, and demands of self-paced online learning) may help students adjust their expectations and approach to their course(s). Regularly checking the gradebook and benchmarking student progress against course pacing guides can help teachers and mentors identify students who may be struggling with course pacing. Mentors and instructors should also communicate regularly about students’ progress and work collaboratively to address pacing issues.

It is also possible that submitting assignments out of order may have a greater impact on some students’ performance than others. For example, students with less content knowledge may miss key benefits of built-in scaffolding when submitting assignments out of order, which may negatively impact course performance. Further, because the design of these studies limits our ability to make cause-and-effect statements, it is likely that other factors interact with pacing to affect student performance. In particular, encouraging the development of metacognitive, time management, and self-regulated learning skills may help students reflect and make adjustments to their own learning behaviors. In this regard, providing students with personalized feedback may be useful.

Final Thoughts

Across two reports, the relationship between pacing and final course scores has consistently shown that final course scores decline as students become increasingly out of alignment with their course pacing guides. Instructors and mentors can help students succeed by paying particular attention to students’ pacing within their online courses. 

You can check out the full reports below: 

Out of Order, Out of Reach: Navigating Assignment Sequences for STEM Success

Out of Order, Still Out of Reach: Navigating Assignment Sequences for Michigan Virtual World Language Courses

In addition, this blog is part of a blog series exploring the impact of student assignment submission patterns.

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What If These Iconic Movie Heroes Had a Leadership Coach? https://michiganvirtual.org/blog/what-if-these-iconic-movie-heroes-had-a-leadership-coach/ Tue, 27 May 2025 14:25:41 +0000 https://michiganvirtual.org/?p=95926

Leadership in movies takes many forms; sometimes loud and inspiring, sometimes subtle and behind the scenes, but it’s always evolving. Now, imagine how some iconic characters’ stories might have changed if they had access to Leadership Coaching for Innovation, like the kind offered by Michigan Virtual. This unique coaching model develops transformational leaders by helping...

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Leadership in movies takes many forms; sometimes loud and inspiring, sometimes subtle and behind the scenes, but it’s always evolving. Now, imagine how some iconic characters’ stories might have changed if they had access to Leadership Coaching for Innovation, like the kind offered by Michigan Virtual.

This unique coaching model develops transformational leaders by helping them know, do, and be the change agents their systems need, especially in complex, shifting environments hungry for innovation. Let’s explore how coaching could have reshaped their journeys!

🎓 Tony Stark (Iron Man): Coaching for an Innovator’s Mindset

In Iron Man 2, Tony Stark spirals. He’s reckless, secretive, and resistant to help. Faced with his mortality and legacy, he makes unilateral decisions that strain relationships and destabilize his company. He’s brilliant but reactive, solving problems in isolation and letting ego drive his leadership.

Leadership Coaching for Innovation could have helped Tony reframe innovation from being about individual genius to a shared vision. A coach might prompt reflective questions like:

  • Who else should be at the table?
  • What assumptions are you making about your role as a leader?
  • How might your innovations be more inclusive and sustainable?

Over time, Tony could build psychological safety within his team, allowing diverse perspectives to surface and grow. He might have shifted from burnout-fueled heroics to empowerment and succession planning, as we eventually see with Peter Parker. With coaching, his arc could accelerate from tech-obsessed soloist to a systemic change agent who fosters a culture of curiosity and capacity-building.

💡 Princess Leia (Star Wars): Coaching for Strategic Innovation

Leia Organa continually led through unprecedented challenges, uniting a fragmented Rebel Alliance, coordinating the complex evacuation of Echo Base, and nurturing the next generation of leaders within the Resistance. Leadership Coaching for Innovation would specifically have helped Leia cultivate innovative strategies rather than reacting to immediate threats. Reflective coaching questions might have included:

  • How can we leverage collective intelligence to foster innovative solutions across Rebel factions?
  • What innovative rapid-response frameworks can we prototype to enhance resilience?
  • How might we intentionally build innovation capacity within emerging Resistance leaders?

Through innovation-focused coaching, Leia would move from managing crises to proactively developing resilient, creative, and strategically agile systems, ensuring the long-term strength and adaptability of the Alliance and Resistance alike.

🧠 John Keating (Dead Poets Society): Coaching for Inclusive Innovation

Clearly, Keating was a bold, passionate educator urging students to “seize the day,” to break free from outdated norms and rediscover their voices. He fostered curiosity, inspired creativity, and ignited a love for learning, but within a system that didn’t always recognize or reward risk-taking and was unprepared for his methods, he’s perceived as disruptive.

He knew change was needed, but the path forward seemed lonely, even perilous. What if a coach had been there to ask:

  • How might you extend your impact beyond one classroom, without losing your voice or your values?
  • What structures or allies could help you protect creativity in an environment built for compliance? Can we co-construct change rather than work around others or exclude them?
  • How can you lead innovation in ways that invite others to explore, rather than defend?

A coach wouldn’t have told Keating what to do; they would have held space for the big questions, helped him move from intuition to intentional strategy, and supported him in designing change that inspires without isolating. With a true thought partner, Keating could have shifted from being a solo act of rebellion to a catalyst for collective transformation, rooted in reflection, guided by values, and amplified through strategy and design. This Leadership Coaching for Innovation approach not only sparks imagination but also builds durable innovation networks, so the work doesn’t leave with Keating. It accelerates sparks of vision into concrete, systemic influence.

🌊 Moana (Moana): Coaching for Collaborative Inquiry

In Moana, the eponymous heroine faces ecological decline, cultural inertia, and the burden of leadership, all without formal preparation. She knows the way forward lies in reclaiming her ancestors’ voyaging legacy, but her efforts are initially met with fear and resistance. Leadership Coaching for Innovation would support Moana in navigating adaptive challenges, rather than just technical ones. A coach might help her:

  • Map the system she’s trying to influence (elders, youth, family traditions)
  • Use collaborative inquiry cycles to surface community wisdom
  • Build coalitions of support that anchor change in shared identity

Imagine Moana co-facilitating intergenerational story circles to reconnect the village to its seafaring past. Or co-designing exploratory journeys with her peers, embedding shared leadership and distributed responsibility from the start. Coaching turns her lone quest into community-powered transformation, showing that courage plus systems thinking equals sustainable impact.

🕊️ T’Challa (Black Panther): Coaching for ‘Next-Horizon’ Innovation

Wakanda is a highly advanced, hidden African nation, possessing extraordinary technological advancements due to its exclusive access to the precious metal Vibranium. Historically, Wakanda maintained secrecy and isolation, deliberately hiding its technological superiority to avoid exploitation or conflict. King T’Challa wrestles with Wakanda’s tradition of isolation versus the ethical imperative to aid global communities and share their advancements. Coaching with an embedded element of collaborative inquiry could have provided structured support for him to:

  • Strategically engage diverse internal groups (tribal elders, council members, Wakandan citizens) and external international communities
  • Use collaborative inquiry methods to ensure inclusivity and shared ownership of the transformative vision

Beyond that, a coach could have challenged T’Challa one-on-one with questions like:

  • What might you need to consider (or do) if Vibranium is no longer Wakanda’s greatest advantage? How might you future-proof your leadership and nation beyond your current strengths?
  • If success means more than security, what new metrics or milestones might you use to measure Wakanda’s progress in becoming a global force for good?
  • What adaptive challenges do you anticipate as you shift from secrecy to openness, and how will you prepare yourself and others to lead through that uncertainty?

Leadership Coaching for Innovation takes leaders from good to GREAT. By leaning into the power of collective intelligence and future-focused journeys, T’Challa would be seen as that “next level” leader that Wakanda needs for generations to come.

🎬 What These Stories Teach Us

While these characters (mostly) aren’t educators, their challenges mirror those of real-life school and district leaders: navigating complex systems, inspiring others, managing change with adaptive approaches, and building sustainable innovation. Transformational leadership doesn’t happen in a vacuum; it grows from intentional reflection, collaborative problem-solving, and strategic risk-taking.

Michigan Virtual’s Leadership Coaching for Innovation equips leaders to meet the moment with clarity and courage as well as make the moments that matter. Through personalized, systemic, and reflective coaching, we help leaders:

  • Be curious, uncover, and envision the possibilities
  • Reflect deeply on their practice
  • Navigate uncertainty with confidence
  • Co-create meaningful change within their systems
  • Champion innovation that not only advances education into the 21st century but also creates a joyful, purposeful future

Leadership isn’t about having all the answers or being the hero—it’s about asking the right questions, making space for others, and creating conditions where everyone can thrive. Movie magic aside, that’s the kind of leadership that truly changes the world.

✏️ Ready to Lead Your Own Sequel?

You don’t need a movie moment to become a transformational leader. You need a thought partner, an intentional coaching process, and a system that believes in your growth. Michigan Virtual’s Leadership Coaching for Innovation is ready to walk with you; one conversation, one cycle, one courageous act at a time.

👉 Start your coaching journey today.

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Now What? Bringing It All Together—and Taking Your Next Step Toward Innovation https://michiganvirtual.org/blog/now-what-bringing-it-all-together-and-taking-your-next-step-toward-innovation/ Tue, 13 May 2025 18:16:26 +0000 https://michiganvirtual.org/?p=95670

If you’ve made it this far in the series, chances are something about Leadership Coaching for Innovation has sparked your curiosity—or maybe even your courage. You’ve seen how it works, who it’s for, and why it stands apart from traditional PD. So now what? The next step is simple—but meaningful: act on that spark. Whether...

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https://open.spotify.com/episode/2sP9oPIKS4TWC270dDE2Pa?si=07bd240fc29947f4

If you’ve made it this far in the series, chances are something about Leadership Coaching for Innovation has sparked your curiosity—or maybe even your courage. You’ve seen how it works, who it’s for, and why it stands apart from traditional PD. So now what?

The next step is simple—but meaningful: act on that spark.

Whether you already have an idea you’re chasing, a challenge you’re navigating, or just a feeling that there’s something more you could do to serve students, this is your invitation to take the leap.

Because here’s the truth: innovation rarely comes from a lightning bolt. It comes from small, intentional steps—shifting your thinking, testing an idea, reflecting deeply, and trying again. And that kind of work doesn’t happen in isolation. It happens in conversation. In partnership. In practice.

That’s what Leadership Coaching for Innovation offers: not a prescription or a playbook, but a trusted thought partner to help you navigate the messiness of change and discover what’s possible in your own context.

In the MiSoundBoard podcast, Don Wotruba and I talked about how lonely leadership can be—and often innovation can feel even lonelier unless you intentionally reach out. So many leaders are doing heroic work behind the scenes, but without anyone to think with, push them, or hold space for their learning. That’s the gap this coaching service is designed to fill.

So, whether you’re ready to define your next move—or just wondering what’s possible—know this: you don’t have to do it alone.

Reach out. Start the conversation. Let’s explore what Leadership Coaching for Innovation could look like for you.

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When, Where, and How Does Leadership Coaching for Innovation Work—and Why Is It More Effective Than Traditional PD? https://michiganvirtual.org/blog/when-where-and-how-does-leadership-coaching-for-innovation-work-and-why-is-it-more-effective-than-traditional-pd/ Tue, 06 May 2025 17:08:09 +0000 https://michiganvirtual.org/?p=95664

We’re all familiar with the typical rhythms of professional development: workshops, webinars, maybe a conference or two. While these experiences can spark ideas, they often fall short when it comes to real, lasting transformation. That’s because true change doesn’t happen in a single day. It happens over time, in context, and through trusted relationships. That’s...

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We’re all familiar with the typical rhythms of professional development: workshops, webinars, maybe a conference or two. While these experiences can spark ideas, they often fall short when it comes to real, lasting transformation. That’s because true change doesn’t happen in a single day. It happens over time, in context, and through trusted relationships.

That’s where Leadership Coaching for Innovation stands apart.

This service isn’t confined to a training calendar or a specific time of year. It’s designed to be timely, responsive, and completely flexible to meet your needs. Whether you’re preparing to launch a new initiative, struggling with implementation, or still brainstorming your vision, the coaching adapts to your pace, not the other way around.

You choose the cadence. Some leaders engage in weekly or bi-weekly conversations during high-stakes moments. Others check in monthly as they build toward a bigger shift. What matters most is that it’s ongoing, not a one-and-done session. The work evolves alongside you.

And where does it happen? Wherever you are. Leadership Coaching for Innovation can be delivered virtually, one-on-one, so your coach can meet with you in your space and schedule. No travel. Or, we can come to you, wherever you feel comfortable. Again, make the best out of your time and resources, and just how you like it.

In my conversation with MASB’s Don Wotruba on the MiSoundBoard podcast, we talked about how this coaching model offers something that traditional PD simply can’t: internal accountability and external sustainability. It helps you think through problems, generate new ideas, and—most importantly—stick with it. The coaching relationship provides a space for honest reflection, real-time course correction, and a rhythm of learning that supports long-term transformation.

When you’re leading change, timing matters. Support matters. Having someone who’s just for you, at just the right time, matters most.

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