Mc²
Purpose or Promise
This model is designed to reframe where learning happens and what counts as evidence of growth by treating home, school, and community as equally legitimate learning environments. It addresses a persistent problem in secondary education: many students disengage when learning feels abstract or disconnected from their lived experience. Here, students build knowledge and durable skills / competencies through real responsibilities, community-based work experiences, and interest-driven projects, supported by strong advising relationships and targeted instruction. Learning is documented through portfolios and competency evidence rather than seat time alone. What makes this model distinctive is its intentional use of everyday life and an ecosystem of community contribution as primary drivers of learning, supported by AI-enabled evidence collection and reflection.
Key Measurable Outcomes
Student growth is tracked through a competency-based framework that emphasizes development over time rather than one-time performance, drawing from the competency matrix and portfolio evidence:
- Agency and self-management: ability to plan routines, reflect on learning, set goals, and persist through challenges (e.g., portfolio reflections, advisor notes, consistency of engagement).
- Technical or domain-specific understanding: application of literacy, computational thinking, and durable skills in real contexts (e.g., interdisciplinary projects, application of empirical reasoning or systems thinking connected to community-based work with industry professionals ).
- Critical thinking and problem-solving: use of evidence, inquiry, and iteration to address authentic problems (e.g., project artifacts, annotated maps, data analysis).
- Communication and collaboration: participation in group work, discussions, and presentations to real audiences (e.g., discussion contributions, interviews, community feedback).
- Community contribution: production of work that has value beyond school (e.g., partner feedback, documented impact, sustained community involvement).
Evidence is curated in a living portfolio, with AI-supported tools surfacing patterns and growth while educators verify and coach young people to identify ways to expand learning, challenge growth, deepen exposure to passions, and determine next steps.
Learning Environment
Learning is intentionally distributed across home, school, and community, with each setting serving a clear purpose. Students begin the day grounded in real responsibilities at home—caregiving, routines, self-management—which are treated as legitimate evidence of growth in independence and wellness. These experiences are captured through short reflections, photos, or voice notes and contribute to a broader picture of the learner rather than functioning as compliance tasks. School functions as a stable “hub” or “basecamp” where students are known well and supported as they explore community and industry-based experiences.
At school, students are part of small advisories and mixed-grade cohorts that prioritize relationship-building, planning, and reflection. Interdisciplinary cohort blocks anchor learning in big questions connected to students’ interests and local issues, allowing content to emerge as a catalyst for continuous learning and inquiry. Targeted studios—such as computational thinking or literacy—are intentionally small, non-shaming, and responsive, focusing on specific gaps or needs in the context of current projects. Instruction is adaptive and paced to the learner, with adults and AI tools working together to support—not replace—human feedback.
Community-based learning is a core, not peripheral, component. Students spend regular time at partner sites where they apply learning in authentic contexts, document processes, and contribute to real work. Adults at these sites function as mentors and collaborators, while school-based educators help students connect experiences back to competencies and growth opportunities. A typical day blends advisory, cohort learning, targeted studios, portfolio work, and community engagement. Over time, students come to see themselves as capable contributors with agency to design their futures.
Day in the Life
Time, Space, and Resources
Key design features:
- Flexible daily schedules that allow for home-based routines, extended learning blocks, and off-campus community experiences.
- Advisory structures with low student-to-adult ratios to support reflection, planning, and competency progress tracking.
- Targeted studios (e.g., computational thinking, literacy) organized around learner need rather than age or course sequence.
- Digital portfolio systems supported by AI-enabled evidence harnessing, with educator verification.
- Community and industry partnerships that function as active learning sites, not add-ons.
Conditions that would need to be true to bring this model to life:
- Policies that allow learning to occur outside traditional classrooms and recognize portfolio-based evidence in place of seat time.
- Strong adult capacity in advising, competency-based assessment, and project facilitation.
- Trust-based systems for documenting learning that balance AI support with professional judgment.
- Transportation, scheduling, and partnership infrastructure to support regular community-based learning.
- Family engagement strategies that position home life as an asset rather than a deficit.