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OLC Awards of Excellence

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Home > Awards > Awards > Awards of Excellence

The following OLC Awards of Excellence are bestowed at OLC Accelerate in the fall of each year based on alignment with OLC Dimensions of Quality.*

The evaluation criteria for OLC’s Awards of Excellence were developed within the overarching framework of OLC’s Dimensions of Quality, reflecting core principles of effective, equitable, scalable, and learner-centered digital education. To support clarity, consistency, and alignment across award categories, AI-assisted tools were used in the drafting process, with final criteria reviewed and approved by OLC leadership.

Award for Excellence in AI-Enabled Education

Description: Recognizes outstanding achievements in the thoughtful, ethical, and effective use of artificial intelligence to advance teaching, learning, and student success. Eligible initiatives may include AI-supported research, instructional practices, learner support systems, assessment strategies, institutional policies, or scalable models that reflect innovation grounded in evidence, transparency, and responsible use. The award emphasizes not only technological sophistication, but also pedagogical soundness, learner-centered design, and measurable impact.

 

Who can submit: Individuals, teams, or institutions whose work demonstrates how AI can meaningfully enhance educational experiences, improve learning outcomes, support educators, and promote equitable access in online, blended, and digital learning environments.

Evaluation Criteria

1. Purposeful Use of AI

  • Clear articulation of the educational challenge or opportunity addressed
  • AI is used intentionally to support learning, teaching, or institutional goals
  • The role of AI is transparent and well-defined (not novelty-driven)

Evidence may include: design rationale, problem statements, alignment with learning goals, AI workflow diagrams

2. Educational Impact & Outcomes

  • Demonstrated or well-supported impact on learners, educators, or institutions
  • Evidence of improved outcomes such as engagement, access, persistence, efficiency, or learning effectiveness
  • Use of data, evaluation methods, or research to support claims

Evidence may include: assessment results, analytics, qualitative feedback, research findings, evaluation reports

3. Ethical, Responsible & Inclusive Design

  • Attention to bias, transparency, data privacy, security, and academic integrity
  • Inclusive design practices that consider diverse learners and contexts
  • Alignment with responsible AI principles and/or institutional guidelines

Evidence may include: governance/policy documentation, privacy/security approach, bias testing/mitigation notes, accessibility considerations, integrity guidance

4. Innovation & Creativity

  • Novel or inventive application of AI in an educational context
  • Meaningful integration with pedagogy, curriculum, or learner support (beyond automation)

Evidence may include: comparisons to prior approaches, prototype artifacts, implementation examples, user stories

5. Scalability, Sustainability & Transferability

  • Potential for scaling, adaptation, or replication in other contexts
  • Sustainability plan (resources, training, governance, maintenance)

Evidence may include: implementation model, training plan, sustainability strategy, cost/resource considerations, adoption guidance

6. Reflection & Future Directions

  • Thoughtful reflection on limitations, risks, and improvements
  • Clear roadmap for iteration as AI capabilities and policies evolve
  • Contribution to broader best practices in AI-enabled education

Evidence may include: reflective narrative, roadmap, monitoring plan, continuous improvement cycle, dissemination plans

Can’t decide between AI-Enabled Education and Innovation Award?

The Award for Excellence in Digital Learning Innovation and the Award for Excellence in AI-Enabled Education recognize different—but sometimes overlapping—approaches to advancing digital learning. This decision tree is designed to help you determine which award best aligns with the primary focus of your work.

Apply for Excellence in Digital Learning Innovation if:

  • Your work advances digital or online learning broadly
  • Innovation is the primary contribution
  • AI is minor, optional, or incidental

Examples:

  • New course or program models
  • Innovative instructional designs
  • New approaches to digital delivery or engagement

Apply for Excellence in AI-Enabled Digital Education if:

  • AI is essential to your solution or outcomes
  • Educational impact depends on AI integration
  • Responsible and reflective AI use is addressed

Examples:

  • AI-supported feedback or assessment systems
  • AI-driven learner support models
  • Responsible institutional AI implementation
  • Research evaluating AI impact on digital learning

Final Self-Check

Ask yourself:

If AI were removed, would the innovation still stand on its own?

  • Yes → Digital Learning Innovation
  • No → AI-Enabled Digital Education

Award for Excellence in Digital Learning Innovation

Description: Outstanding achievements in developing and implementing creative, impactful, and inclusive digital learning solutions. 

 

Who can submit: Individuals or teams who leverage technology to enhance educational experiences, promote accessibility, and drive learner engagement, setting new benchmarks for innovation in the digital learning landscape. Self-nomination permissible

Evaluation Criteria

1. Problem/Opportunity & Design Rationale

  • Clear articulation of the educational challenge or opportunity addressed
  • Innovation is intentionally designed to improve learning, teaching, or institutional goals (not novelty-driven)
  • Grounded in learner needs and digital learning context

Evidence may include: design rationale, needs assessment, user research, alignment to outcomes, theory of change

2. Educational Impact & Outcomes

  • Demonstrated or well-supported impact on learners, educators, or institutional effectiveness
  • Evidence of improved outcomes such as engagement, access, persistence, learning effectiveness, or efficiency
  • Uses data/evaluation methods appropriate to the context

Evidence may include: assessment results, analytics, pre/post comparisons, evaluation reports, survey results, qualitative findings

3. Innovation & Distinctiveness

  • Clear explanation of what is new, improved, or distinctive compared to typical practice
  • Creative integration of pedagogy, technology, learning design, or support model
  • Demonstrates thoughtful risk-taking or boundary-pushing with purpose

Evidence may include: comparative narrative (before/after), prototypes, design artifacts, workflow/process changes, adoption story

4. Implementation Quality & Feasibility

  • Demonstrates strong execution and operational readiness (people/process/technology)
  • Addresses implementation supports (training, change management, communication)
  • Demonstrates usability and reliability in real conditions

Evidence may include: implementation plan, training materials, change management artifacts, usage/adoption data, support documentation

5. Equity, Accessibility & Inclusive Innovation

  • Innovation improves access or reduces barriers for diverse learners
  • Accessibility and inclusion are intentionally built-in (not an afterthought)

Evidence may include: accessibility conformance practices, inclusive design documentation, disaggregated impact data, UDL-informed approaches

6. Scalability, Sustainability & Transferability

  • Potential for scaling/adaptation to other contexts or audiences
  • Sustainability plan exists (resourcing, governance, maintenance)

Evidence may include: sustainability plan, cost/resource model, replication guide, partnership plans, future roadmap

Can’t decide between AI-Enabled Education and Innovation Award?

The Award for Excellence in Digital Learning Innovation and the Award for Excellence in AI-Enabled Education recognize different—but sometimes overlapping—approaches to advancing digital learning. This decision tree is designed to help you determine which award best aligns with the primary focus of your work.

Apply for Excellence in Digital Learning Innovation if:

  • Your work advances digital or online learning broadly
  • Innovation is the primary contribution
  • AI is minor, optional, or incidental

Examples:

  • New course or program models
  • Innovative instructional designs
  • New approaches to digital delivery or engagement

Apply for Excellence in AI-Enabled Digital Education if:

  • AI is essential to your solution or outcomes
  • Educational impact depends on AI integration
  • Responsible and reflective AI use is addressed

Examples:

  • AI-supported feedback or assessment systems
  • AI-driven learner support models
  • Responsible institutional AI implementation
  • Research evaluating AI impact on digital learning

Final Self-Check

Ask yourself:

If AI were removed, would the innovation still stand on its own?

  • Yes → Digital Learning Innovation
  • No → AI-Enabled Digital Education

Award for Excellence in Digital Learning Support

Description: Demonstrated excellence in digital learning support for instructors or learners.

 

Who can submit: Individuals, teams, or organizations that provide exceptional support to enhance digital learning experiences, including student services professionals, instructional technologists, CTLs, IT support staff, administrators, educational consultants, and other professionals who have significantly contributed to improving the infrastructure, tools, or services that enable effective digital education. Self-nomination permissible.

Evaluation Criteria

1. Support Strategy & Alignment

  • Clear articulation of the support need(s) being addressed (learner and/or instructor)
  • Support approach is intentionally designed and aligned with digital learning goals and context
  • Support scope and service model are well-defined (who it serves, how it works, how it’s delivered)

Evidence may include: service model diagrams, support workflows, intake/escalation processes, staffing model, training materials

2. Impact on Learner and/or Instructor Success

  • Demonstrated or well-supported impact on success indicators (e.g., access, persistence, satisfaction, performance, teaching effectiveness)
  • Uses appropriate data and/or evaluation methods to support impact claims
  • Shows how support addressed barriers and improved experience or outcomes

Evidence may include: retention/persistence metrics, help-desk analytics, satisfaction surveys, LMS/usage analytics, qualitative feedback, evaluation summaries

3. Quality, Responsiveness & Reliability

  • Timely, reliable, and user-centered support (including hours/coverage, responsiveness, service consistency)
  • Clear quality standards and continuous improvement practices
  • Effective communication and resolution processes

Evidence may include: response/resolution time reports, QA rubrics, SLAs, service audits, ticketing reports, documented improvements based on trends

4. Equity, Accessibility & Inclusion in Support Design

  • Support is accessible to diverse users (e.g., disability accommodations, multilingual needs, varied schedules/contexts)
  • Intentional efforts to reduce equity gaps or barriers to participation
  • Demonstrates inclusive design of services and communications

Evidence may include: accessibility checks, inclusive communication examples, multilingual resources, outreach plans, disaggregated usage/outcome data

5. Scalability & Sustainability

  • Support model can scale to demand and adapt to growth or changing needs
  • Sustainability is addressed (resourcing, documentation, staffing continuity, governance)

Evidence may include: capacity planning, staffing forecasts, budget/resource plans, documentation repositories, governance/ownership models

6. Reflection & Transferable Lessons

  • Thoughtful reflection on successes, challenges, and improvements
  • Clear guidance or insights others can apply in similar contexts

Evidence may include: lessons learned, improvement roadmap, implementation playbook, evaluation reflections, future enhancement plans

Gomory-Mayadas Award for Excellence in Digital Learning Leadership

Description: Evidence of outstanding transformative leadership in online, blended, and/or digital learning that advances equity

 

Who can submit: Educators, administrators, instructional designers, researchers, and professionals who have demonstrated exceptional leadership in the field of digital education. Self-nomination permissible

Evaluation Criteria

1. Leadership Vision & Strategic Alignment

  • Clear vision for digital learning that aligns to organizational mission and learner needs
  • Demonstrates strategic thinking and purposeful prioritization
  • Shows how leadership decisions guided direction and coherence

Evidence may include: strategic plans, program vision statements, initiative charters, alignment maps, leadership communications

2. Transformative Impact & Outcomes

  • Demonstrated organizational, programmatic, or community-level impact
  • Evidence of meaningful change in outcomes (access, quality, satisfaction, scale, effectiveness)
  • Uses data or evaluation to substantiate results

Evidence may include: key performance indicators, adoption trends, learner outcomes, policy changes, evaluation reports, stakeholder feedback

3. Equity-Advancing Leadership

  • Leadership actions intentionally advance equity, inclusion, and access in digital learning
  • Addresses structural barriers and supports underserved learners or contexts

Evidence may include: equity initiatives, disaggregated outcomes, accessibility improvements, targeted support programs, policy/practice changes

4. Collaboration & Influence

  • Builds cross-functional and/or cross-institution collaboration
  • Demonstrates influence beyond a single unit (community, system, field leadership)

Evidence may include: partnership MOUs, cross-unit governance structures, coalition outcomes, invited talks/recognition, dissemination artifacts

5. Capacity Building & Enablement

  • Strengthens people and systems: faculty/staff development, processes, infrastructure, governance
  • Creates conditions for sustained excellence (not dependent on one person)

Evidence may include: professional learning programs, staffing models, governance charters, playbooks, operational frameworks

6. Reflection, Learning & Future Direction

  • Demonstrates reflective leadership and continuous improvement
  • Clear future direction with lessons learned and next steps

Evidence may include: retrospectives, improvement roadmaps, evaluation reflections, future strategy updates

John R. Bourne Award for Excellence in Online and Digital Programming

Description: Effective practices in developing or expanding innovative and impactful online and digital programs, and the creation, delivery and management of digital tools, platforms, and content that enhance teaching, learning and administrative processes in educational institutions.

 

Who can submit: Individuals, teams, or organizations that have demonstrated outstanding achievement in designing, delivering, or managing online programs, including educators, instructional designers, program coordinators, developers, and institutions that have created innovative, impactful, and accessible online learning experiences. Self-nomination permissible

Evaluation Criteria

1. Program Purpose, Audience & Fit

  • Program purpose and target learners are clearly defined
  • Program design aligns with learner needs, workforce/discipline expectations, and institutional goals

Evidence may include: program overview, learner personas, market/needs analysis, program outcomes map, accreditation/program requirements alignment

2. Program Quality & Learning Effectiveness

  • Clear learning outcomes and coherent curriculum/learning pathway
  • Evidence of effective teaching/learning design and assessment practices

Evidence may include: curriculum map, assessment plan, sample course design artifacts, learning outcome evidence, quality review results

3. Student Experience, Support & Success

  • Demonstrates strong learner support and experience design (advising, tutoring, onboarding, accessibility, engagement)
  • Evidence of student success and satisfaction

Evidence may include: support model, success/retention data, student feedback, onboarding resources, engagement analytics

4. Program Operations & Management

  • Effective delivery and management of the program (governance, staffing, policies, scheduling, quality assurance)
  • Demonstrates operational maturity and reliability

Evidence may include: governance documentation, staffing roles, operational workflows, QA cycles, policy guides, service-level practices

5. Scale, Sustainability & Resource Stewardship

  • Program is sustainable financially and operationally
  • Demonstrates scalable processes and responsible resource planning

Evidence may include: enrollment trends, capacity plans, budget/resource model, staffing projections, sustainability strategy

6. Innovation, Continuous Improvement & Transferability

  • Program evolves based on evidence and emerging needs
  • Demonstrates replicable practices or contributions to the field

Evidence may include: improvement cycles, evaluation plans, innovation examples, dissemination artifacts, playbooks/guides

Karen J. Swan OLJ Outstanding Research Achievement Award in Digital Education

Description: Excellence in research, including scholarly research and writing, leadership and service in research, and contributions to advancing the field.

Who can submit: Internal nomination by OLC, no self or outside submission permissible

OLC Outstanding Volunteer Achievement Award

Description: Recognizing outstanding contributions to the OLC community through volunteerism that exemplifies leadership, innovation, adaptability, impact, and collaboration.

Who can submit: Internal nomination by OLC, no self or outside submission permissible

*With the exception of Karen Swan OLJ Outstanding Research Achievement in Digital Learning and OLC Outstanding Volunteer Achievement Awards which use different evaluation criteria.

We invite leaders, educators, researchers, and innovators to showcase their achievements and inspire the future of digital education. Submit your application and be recognized for your contributions to shaping the digital learning landscape!

Application Criteria

We ask that submitters take note of the following award submission requirements:

  • All nominees need to be professional members or affiliated with OLC institutional members.
  • Self-nominations are permissible for all awards with the exception of the OLJ Research Award and Volunteer awards. Self-nominations will still require three letters of support to be considered as a complete application.
  • An individual cannot submit for more than one award or scholarship per year. However, an institution can have more than one award submitted within the same year.
  • There may be more than one winner selected for each award category.
  • It is possible for no award to be given within an area should the submissions within that category not meet the minimum threshold score for awards.

Materials Required for Application

  • A detailed description of the area of excellence that summarizes the practice(s), providing evidence of how the award criteria are met.
  • Supporting documentation of the practice(s) alignment to the award criteria. Evidence may include (but are not limited to) websites (URLs), screenshots, videos, assessment data, reports, testimonials.
  • Three (3) letters of support addressing how the award submission aligns to the OLC Dimensions of Quality. It is recommended that submission packets include letters from a mix of both internal and external senior leaders who can speak to the impact of the practice(s) highlighted in the submission.

Scoring Criteria

The following criteria will be used to evaluate all OLC Awards of Excellence submissions:

OLC Dimensions of Quality
How well does this submission impact:

Dimension Description

Evidence
Submission includes evidence of excellence for this dimension

Learning Effectiveness

Learning Effectiveness is centered around creating educational experiences that are intentionally designed to support all learners in equitably meeting articulated outcomes, thereby gaining valuable competencies and skills. This involves aligning learning outcomes with the mission, values, and overall strategy of the organization to provide quality learning opportunities that prepare learners for future work and promote lifelong learning. Through the leverage of online, blended, and digital environments, Learning Effectiveness facilitates inclusive, academically rigorous experiences that prioritize learner engagement and community development among instructors, learners, designers, and leaders.

Strongly Agree
3 – Agree
2 – Disagree
1 – Strongly Disagree or N/A
Reviewer Comments:

Learner Experience

Learner Experience is centered around providing a holistic and enriching educational journey, emphasizing equitable access to support services, meaningful interactions, and alignment with personal and professional goals. This dimension ensures the education process is perceived as rigorous, valuable, and supportive, fostering a sense of belonging and achievement. A positive experience is crucial for nurturing engagement, persistence, and overall satisfaction.

Strongly Agree
3 – Agree
2 – Disagree
1 – Strongly Disagree or N/A
Reviewer Comments:

Instructor Experience

Instructor Experience focuses on creating a supportive and enriching environment for all educators, enabling them to effectively engage with learners and find personal and professional fulfillment in their teaching roles. This dimension underscores the importance of providing a comprehensive array of opportunities for professional development, involvement in decision-making processes, access to high-impact teaching resources, and recognition of instructional efforts and achievements. A positive and rewarding teaching experience is crucial for sustaining high-quality learning environments that benefit both instructors and learners.

Strongly Agree
3 – Agree
2 – Disagree
1 – Strongly Disagree or N/A
Reviewer Comments:

Scale

Scale embodies the commitment to sustain and grow academically rigorous, outcomes-aligned online, digital, and blended education for a wide array of learners. This dimension emphasizes the importance of balancing broad access with the maintenance of high educational standards. By strategically scaling offerings, organizations can enhance enrollments, retention, learner success, and career advancement, all while adhering to quality benchmarks. Effective scaling involves thoughtful planning, incremental growth, and the robust support of academic and technical infrastructure, ensuring that expansion efforts equally benefit all segments of the learner population.

Strongly Agree
3 – Agree
2 – Disagree
1 – Strongly Disagree or N/A
Reviewer Comments:

Access

Access is foundational to ensuring that all learners—especially those from marginalized or underserved communities—can engage with high-quality online and blended education. This dimension emphasizes the proactive removal of physical, sensory, cognitive, technological, and socio-economic barriers, fostering an environment where differentiated learner needs are met through universal design principles. Access also involves the active dismantling of systemic barriers that limit educational success, ensuring pathways to academic achievement are clear and comprehensive, from admission to graduation.

Strongly Agree
3 – Agree
2 – Disagree
1 – Strongly Disagree or N/A
Reviewer Comments:

Awards of Excellence Winners

Please view the page below to see a list of Award of Excellence Winners.

List of Awards of Excellence Winners

Questions & Support

For additional information about the OLC Awards and Recognition programs, please email us at awards@onlinelearning-c.org.

Status: Closed

Important Dates

OLC Awards 2026

March 2, 2026

Award Portal Opens

June 15, 2026

Award Portal Closes

November 2026
Award Winners recognized at OLC Accelerate 2026 onsite in Orlando.

For additional information, please contact The Online Learning Consortium Awards Program awards@onlinelearning-c.org

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