Data Security & Privacy in AI Grading Tools: The 2026 Compliance Guide Every K-12 District Leader and IT Administrator Needs

In 2026, data security and privacy have emerged as the single biggest barrier to AI adoption in K-12 education.

While AI grading tools promise to save teachers hours every week and deliver more consistent, personalized feedback, many districts are hitting the brakes. Not because the technology doesn’t work - but because leaders are asking a much harder question: Can we trust these tools with our students’ most sensitive information?

The numbers paint a sobering picture. According to the Center for Internet Security’s 2025 K-12 Cybersecurity Report, 82% of schools experienced at least one cyber threat impact during an 18-month period. The Clever 2026 Cybersecure report revealed that 52% of U.S. school districts suffered a cybersecurity incident in 2025 - a sharp 16-percentage-point increase from the previous year. Even more alarming is the rise in third-party vendor breaches, which now account for 32% of all reported incidents, up dramatically from just 4% in 2023.

This surge in vendor-related risks has fundamentally changed how districts evaluate new technology. Superintendents, Chief Technology Officers, Privacy Officers, and procurement teams are no longer just asking about features or pricing. They’re asking the same critical question:

“Can we trust an AI tool with our students’ data?”

This guide was written to answer that question with clarity and confidence. It is a very comprehensive resource on data security and privacy for AI grading tools in K-12 education. Whether you’re a superintendent preparing for a board presentation, a CTO building a vendor evaluation framework, or a Privacy Officer reviewing contracts, this guide gives you everything you need - from a clear breakdown of FERPA, COPPA, NY Ed Law 2-d, and GDPR requirements to technical safeguards, contract language, real-world risk scenarios, and a practical 8-step vendor evaluation checklist.

Why Data Security Is Now the #1 Blocker in EdTech Procurement

Five years ago, the conversation around edtech in K-12 was dominated by questions of pedagogy, user experience, and instructional impact. Today, that conversation has shifted dramatically. Data security and privacy have become the single most important factor in whether a new AI tool gets adopted - or even makes it past the initial screening process.

The New Reality in 2026

The education technology landscape has changed in profound ways:

• Exploding number of vendors: The average school district now manages hundreds of third-party applications, each with access to sensitive student information. This creates an enormous attack surface that didn’t exist a decade ago.
• Student data is more valuable than ever: Attackers are no longer just after credit card numbers. Names, grades, behavioral notes, learning analytics, attendance records, and even biometric data (in some districts) are now highly sought-after on the dark web. This data can be used for identity theft, social engineering, or sold to data brokers.
• High-profile breaches have changed everything: The December 2024 PowerSchool breach exposed the personal information of more than 60 million students across hundreds of districts. Multiple incidents involving Illuminate Education and other major platforms have made school boards and parents extremely wary. These events are no longer seen as isolated incidents - they are now viewed as systemic risks.
• Regulatory pressure is intensifying: State attorneys general, the U.S. Department of Education, and parent advocacy groups are increasing enforcement. Investigations, fines, and public scrutiny are becoming more common. Districts that fail to properly vet vendors are increasingly being held accountable.

The Real Cost of Getting It Wrong

The financial and operational impact of a data breach in K-12 education is severe:

• A single incident can cost a mid-sized district between $500,000 and $2 million in direct expenses, including legal fees, breach notification, credit monitoring for affected families, system restoration, and enhanced security measures.
• Recovery time often ranges from 2 to 9 months, during which instructional time is lost, staff productivity drops, and trust erodes.
• Reputational damage can last for years. Parents lose confidence, board members face pressure, and media coverage can damage the district’s standing in the community.

Beyond the immediate costs, there is also the hidden price of opportunity cost. When districts spend months or years recovering from a breach, they fall behind in innovation and student support.

This is why the procurement process has fundamentally changed.

Today, procurement teams, IT leaders, and privacy officers will not even consider piloting a new AI grading tool until the vendor can demonstrate:

• A signed Student Data Privacy Addendum (DPA)
• Completed security questionnaires
• Proof of compliance with FERPA, COPPA, NY Ed Law 2-d, and other applicable laws
• Clear technical safeguards and contractual protections

In short, data security and privacy are no longer just compliance checkboxes - they are now the primary gatekeepers of AI adoption in K-12 education.

The 2026 Regulatory Landscape for AI Grading Tools

Understanding the legal requirements is no longer optional - it is a fundamental part of responsible AI adoption in K-12 education. In 2026, the regulatory environment has become more complex, more enforcement-focused, and more demanding than ever before, especially as AI tools process increasing volumes of sensitive student data.

Below is a clear breakdown of the key federal and state frameworks every district leader and IT administrator must understand when evaluating AI grading platforms.

1. FERPA (Family Educational Rights and Privacy Act)

FERPA remains the foundational federal law protecting student education records. When a district uses an AI grading tool, the vendor is generally considered a “school official” with a legitimate educational interest - but only if strict conditions are met.

Key Requirements:

• Student data may only be used for the specific educational purpose described in the contract (e.g., generating grades and feedback).
• The district must maintain direct control over how the data is used and disclosed.
• Parents and eligible students have the right to inspect, review, and request corrections to their education records.

The Biggest Red Flag in 2026:

Any vendor that claims it can use student data to “improve its AI models,” “train future versions of the platform,” or “enhance its algorithms” without explicit, written district authorization is almost certainly violating FERPA. This has become one of the most common points of failure during procurement reviews.

Practical Implication: Districts must ensure the contract explicitly prohibits any secondary use of student data beyond the immediate grading and feedback service.

2. COPPA (Children’s Online Privacy Protection Act) – 2025 Amendments

The January 2025 updates to COPPA significantly strengthened protections for children under 13. The most important change is the shift toward explicit parental consent for any non-educational use of student data, including AI model training, behavioral profiling, or targeted advertising.

Key Changes in 2025:

• Schools may still provide consent under the “school operator exception,” but they must properly document this authorization.
• Vendors must obtain verifiable parental consent before using student data for any purpose outside of direct educational services.

Why This Matters for AI Grading Tools:

Many AI platforms are designed to continuously learn and improve. Under the updated COPPA rules, this type of model training on student data from children under 13 is now heavily restricted unless proper consent is obtained and documented.

Practical Implication: Elementary and middle school districts must pay special attention to COPPA compliance when selecting AI tools. A strong vendor will clearly explain how they handle consent and data usage for younger students.

3. New York Education Law §2-d (and Part 121 Regulations)

New York’s Education Law §2-d is widely regarded as one of the strictest student data privacy laws in the United States. It applies to all public schools and charter schools in New York and sets a very high bar for vendors.

Key Requirements:

• Vendors must align with the NIST Cybersecurity Framework
• Districts must appoint a Data Protection Officer
• Contracts must include specific required clauses
• Districts must provide annual notification to parents about which vendors have access to student data
• Strict limitations on any secondary or commercial use of student data

Vendor Certification Requirement:

Vendors must provide a formal certification (often included as Exhibit A in the Student Data Privacy Addendum) confirming they will not sell student data, use it for marketing, or engage in prohibited profiling.

Practical Implication: Even districts outside New York often use NY Ed Law 2-d as a benchmark because it represents best-in-class protection. Choosing a vendor that meets these standards provides strong protection across most states.

4. SOPIPA (Student Online Personal Information Protection Act – California)

California’s SOPIPA law prohibits operators of online services from:

• Using student data for targeted advertising
• Creating profiles of students for non-educational purposes
• Selling student data to third parties

Practical Implication: This law is particularly relevant for AI tools that might use learning analytics or behavioral data. Any platform that attempts to monetize student data through advertising or profiling is non-compliant with SOPIPA.

5. GDPR & UK GDPR (for Districts with International Connections)

For districts that serve international students, have EU or UK staff, or operate programs with cross-border data flows, GDPR and UK GDPR compliance becomes essential.

Key Requirements:

• Data transfers outside the European Economic Area (EEA) or UK must be protected by Standard Contractual Clauses (SCCs) or participation in the EU-US Data Privacy Framework
• Vendors must appoint an EU/UK representative to handle data protection matters
• Individuals have strong rights to access, correct, and delete their data

Practical Implication: Even if your district is based in the U.S., using a globally compliant vendor (like GradingPal) simplifies operations if you ever serve international families or participate in exchange programs.

6. Other State Laws

In addition to the major federal and New York/California laws, many states have enacted their own student data privacy legislation, including:

• California AB 1584
• Texas Student Data Privacy laws
• Illinois Student Online Personal Protection Act
• And similar laws in Colorado, Connecticut, and others

The Safest Strategy in 2026:

Rather than trying to comply with dozens of different state laws individually, the most effective approach is to choose a vendor that meets the highest common denominator - typically a combination of FERPA + NY Ed Law 2-d + COPPA (2025) + GDPR.

This “highest bar” approach gives districts strong protection no matter where they are located and significantly reduces legal risk.

What “Good” Looks Like: 10 Must-Have Technical + Contractual Controls

When evaluating any AI grading platform in 2026, demand the following:

Any vendor that cannot clearly demonstrate all 10 of these should be treated with extreme caution.

GradingPal’s Complete Security & Privacy Stack

GradingPal was purpose-built from the ground up to meet the rigorous demands of K-12 institutions. Unlike many general-purpose AI tools that were later adapted for education, we designed our entire platform with student data protection as a foundational principle - not an afterthought.

Here is exactly how we protect student data at every level:

Encryption & Infrastructure

Every piece of student work is protected by industry-leading encryption standards:

• All student submissions are encrypted at rest using AES-256, the gold standard for data encryption.
• Data in transit is protected by TLS 1.2+, ensuring secure transmission between users and our systems.
• We host our platform on enterprise-grade cloud infrastructure through AWS and Supabase, which includes automatic backups, geographic redundancy, and 24/7 monitoring.
• Critically, no student data is ever stored on personal devices, laptops, or unencrypted systems - eliminating one of the most common points of vulnerability in education technology.

These measures ensure that even in the unlikely event of a physical server compromise, student data remains protected.

Access Controls

We enforce strict, role-based access controls to ensure the principle of least privilege:

• Teachers can only access data for their own classes.
• District and school administrators can only view information within their authorized scope.
• GradingPal staff access is extremely limited, fully logged, and requires formal authorization for every instance.
• Multi-factor authentication (MFA) is enforced for all user accounts, significantly reducing the risk of unauthorized access through compromised credentials.

This layered approach prevents both external breaches and internal misuse of student data.

AI Provider Contracts

One of GradingPal’s most important differentiators is how we handle third-party AI providers.

We partner with leading AI models from Anthropic, OpenAI, Google, Microsoft, and Mistral. However, every contract with these providers contains explicit, legally binding prohibitions against using student data to train or improve their underlying models.

This protection is one of the strongest in the industry. While many AI tools quietly use student work to enhance their algorithms, GradingPal contractually and technically prevents this. For districts concerned about FERPA violations or long-term data misuse, this represents a critical safeguard.

Data Handling Philosophy

Our approach to student data is guided by strict principles of minimization and purpose limitation:

• Data Minimization: We only collect the minimum information necessary to deliver accurate grading and meaningful feedback.
• Student work is processed solely for the purpose of generating scores, personalized comments, and analytics - nothing more.
• We never sell student data to third parties.
• We never use student data for targeted advertising, behavioral profiling, or any commercial purpose.
• In limited cases, we may use de-identified data for research and product improvement - but only under strict safeguards and never in a way that could re-identify individual students.

This philosophy ensures that student data serves education, not corporate interests.

Breach Response

We maintain a comprehensive, documented incident response plan that is regularly tested and updated.

In the event of a security incident, we commit to notifying affected districts without undue delay. Notifications include clear details about the nature of the incident, the data potentially affected, and the steps being taken to mitigate harm - all in accordance with FERPA, New York Education Law 2-d, and other applicable regulations.

Our goal is full transparency and rapid action to protect both students and districts.

Audit & Logging

Complete visibility is essential for compliance and trust.

Every data access and processing event within the GradingPal platform is logged in detail. Districts can request activity reports for any time period, allowing IT teams and privacy officers to verify who accessed what data and when.

This level of auditability supports internal reviews, board reporting, and regulatory compliance audits.

The Student Data Privacy Addendum (DPA) – Explained in Plain Language

The Student Data Privacy Addendum (DPA) is the single most important legal document when adopting any AI grading tool in 2026. While privacy policies are often vague and marketing-oriented, a well-drafted DPA serves as a binding contract that clearly defines how student data will be handled, protected, and ultimately returned or destroyed.

GradingPal’s Student Data Privacy Addendum is publicly available at gradingpal.com/data-privacy-addendum. Below is a clear, plain-language explanation of what it includes and why each section matters for district leaders and IT teams.

Clear Roles and Responsibilities

The DPA explicitly defines the relationship between your district and GradingPal:

• Your district is the data controller - meaning you own the student data and decide how it is used.
• GradingPal acts as the data processor - we only process student data according to your instructions.
• Under FERPA, GradingPal is designated as a “school official” with a legitimate educational interest, which allows us to access education records while remaining fully compliant.

This clear separation of roles protects your district from liability and ensures you retain ultimate control.

Purpose Limitation

Student data may only be used for the specific purposes outlined in the agreement - namely, to provide AI-powered grading, generate personalized feedback, and deliver analytics.

We cannot use student data for any other reason without your explicit written permission. This prevents mission creep, where vendors gradually expand how they use student information over time.

Prohibited Uses (The Strongest Protections)

The DPA includes some of the strongest prohibitions in the industry:

• No use of student data for targeted advertising
• No creation of student profiles for non-educational purposes
• No sale of student data to third parties
• Most importantly - no training of AI models on student data

This last point is especially critical in 2026. Many AI platforms quietly use student work to improve their algorithms. GradingPal contractually and technically prohibits this practice.

COPPA Authorization for Students Under 13

For elementary and middle schools, the DPA includes specific provisions for COPPA compliance. Schools can authorize the collection of data from children under 13 under the “school operator exception,” provided they properly notify parents. GradingPal clearly outlines this process and supports districts in meeting their documentation requirements.

New York Education Law §2-d Compliance

The DPA includes full compliance with New York’s strict Education Law §2-d, including:

• The required vendor certification (Exhibit A)
• Alignment with the NIST Cybersecurity Framework
• Specific contract language required under Part 121 regulations

Even if your district is not in New York, this level of compliance provides strong protection and is increasingly viewed as a best-practice benchmark nationwide.

Data Return and Destruction

When your contract with GradingPal ends, the DPA guarantees that all student data will be securely returned or permanently destroyed within 30 days. This clean break is essential for districts that want to switch vendors or simply ensure student data does not linger after the relationship concludes.

Breach Notification

The DPA outlines clear timelines and procedures for breach notification. In the event of a security incident, we commit to notifying affected districts promptly and providing all required details in accordance with FERPA, NY Ed Law 2-d, and other applicable laws. Transparency and speed are non-negotiable.

Sub-Processor Oversight

GradingPal uses several subprocessors (including leading AI providers). The DPA includes:

• A full, up-to-date list of all subprocessors
• Contractual requirements that each subprocessor meets the same high security and privacy standards
• Advance notice (at least 14 days) before any new subprocessor is added, giving districts the opportunity to object if needed

Key Advantage: Publicly Available with No NDA Required

One of GradingPal’s biggest advantages is that our complete DPA is publicly available with no Non-Disclosure Agreement (NDA) required.

This dramatically accelerates the legal and procurement review process. Many vendors force districts to sign an NDA just to see their data processing agreement - a practice that slows everything down. GradingPal removes this barrier entirely, allowing your legal team, privacy officer, and IT department to review the document immediately and begin the approval process without unnecessary delays.

How Districts Can Quickly Complete Due Diligence and Sign a Custom DPA

Many districts assume that reviewing and signing a Data Privacy Addendum (DPA) is a long, complicated process that can drag on for weeks or even months. At GradingPal, we’ve intentionally designed the entire process to be fast, transparent, and low-friction - without sacrificing legal rigor or district control.

Here’s exactly how most districts complete due diligence and get started:

1. Download Our Public DPA and Student Data Privacy Addendum

All of our legal documents - including the full Student Data Privacy Addendum - are publicly available on our website with no NDA required. Your legal, privacy, and IT teams can immediately access and review the complete agreements without any barriers or delays.

2. Review with Your Legal and Privacy Team

Most districts complete their initial review in just 3 to 7 business days. Because our documents are written clearly and follow industry best practices (FERPA, COPPA, NY Ed Law 2-d, and GDPR), legal teams are usually able to move quickly. We’ve designed them to address the most common concerns districts raise during procurement.

3. Request Custom Language or District-Specific Addendums

Every district has slightly different requirements. If your legal team needs specific language, additional clauses, or a district-specific addendum, simply let us know. We’re happy to accommodate reasonable customizations and typically turn around revisions within a few business days.

4. Sign Electronically

Once the agreement is finalized, signing is done electronically through a secure platform. This eliminates paperwork and speeds up the final approval process.

5. Begin Using the Platform

As soon as the DPA is signed, you can immediately start using GradingPal with full compliance. There’s no waiting period or additional setup required from a legal standpoint.

Additional Support We Provide

To make the process even easier, we offer the following resources at no cost:

• Pre-filled Security Questionnaires - We provide completed versions of the most common security and compliance questionnaires used by districts, saving your IT team significant time.
• Custom Security Briefs for Procurement - We can prepare a tailored security and compliance summary specifically for your procurement team or board.

No credit card or financial commitment is required to begin the review process. You can download all documents, ask questions, and even start a free trial while your legal and procurement teams complete their due diligence.

We understand that district legal and IT teams are extremely busy. Our goal is to remove unnecessary obstacles so you can focus on what really matters - protecting student data while giving teachers powerful tools to improve outcomes.

Real-World Risk Scenarios and How GradingPal Mitigates Them

While no system can guarantee 100% protection against every possible threat, understanding real-world risks - and how a vendor actively mitigates them - is essential for making confident decisions. Below are four common risk scenarios that districts face when using AI tools, along with a detailed explanation of how GradingPal is designed to protect against each one.

Scenario 1: Vendor Breach

The Risk:

A major edtech company is hit by a sophisticated ransomware attack. Attackers gain access to the company’s systems and exfiltrate large volumes of student data, including names, grades, and personal information. This type of incident has become increasingly common, with third-party vendor breaches rising dramatically in recent years.

GradingPal Mitigation:

Even in the event of a breach, student data remains strongly protected through multiple layers of defense:

• All student submissions are encrypted at rest using AES-256, making the data unreadable even if attackers gain access to our systems.
• Strict role-based access controls and multi-factor authentication limit who can access data in the first place.
• We maintain a documented and regularly tested incident response plan. In the event of a breach, we notify affected districts without undue delay and provide full details as required by FERPA, NY Ed Law 2-d, and other applicable laws.

The combination of strong encryption and rapid response significantly reduces both the likelihood and impact of a data breach.

Scenario 2: AI Model Training on Student Work

The Risk:

A teacher uploads student essays into an AI grading tool. Without the district’s knowledge or consent, the AI company uses that student work to train and improve its underlying AI models. This practice not only raises serious FERPA concerns but can also lead to long-term data misuse.

GradingPal Mitigation:

We take a zero-tolerance approach to this risk:

• Our contracts contain explicit, legally binding prohibitions against using student data to train or improve AI models.
• We require the same strict prohibition from all our AI subprocessors (including Anthropic, OpenAI, Google, Microsoft, and Mistral).
• These protections are both contractual and technical. Student data is processed only for the immediate purpose of generating grades and feedback - nothing else.

This is one of the strongest protections available in the AI grading space and addresses one of the top concerns raised by district legal and privacy teams in 2026.

Scenario 3: Unauthorized Internal Access

The Risk:

A district employee (or even a teacher) attempts to view student data from another teacher’s class - whether out of curiosity, for improper reasons, or due to a misconfigured system. Without proper controls, this type of unauthorized internal access can go undetected and lead to privacy violations.

GradingPal Mitigation:

We enforce strict role-based access controls at the platform level:

• Teachers can only see data for their own classes.
• School and district administrators can only access information within their authorized scope.
• All access is logged and auditable.

This means that even if someone tries to access data they shouldn’t, the system prevents it before any data is viewed. This protection works automatically and does not rely on manual oversight.

Scenario 4: Contract Ends Abruptly

The Risk:

A district decides to switch vendors mid-year or at the end of a contract. Without clear data return and deletion policies, student data can remain on the old vendor’s systems indefinitely, creating ongoing compliance and security risks.

GradingPal Mitigation:

Our Student Data Privacy Addendum guarantees that:

• Upon termination of the agreement, all student data will be securely returned or permanently destroyed within 30 days.
• Districts receive a full export of all grades, feedback, and analytics before the relationship ends.
• We provide clear documentation confirming data deletion upon request.

This ensures a clean and compliant transition, giving districts full control and peace of mind when moving to a new platform.

Actionable 8-Step Vendor Evaluation Checklist for IT Leaders & Procurement Teams

Evaluating AI tools in 2026 requires more than checking features and pricing. With student data at stake and regulatory scrutiny increasing, districts need a structured, thorough approach to vendor assessment. Use this 8-step checklist for every AI grading or educational platform you evaluate this year.

1. Request the Full Student Data Privacy Addendum (Not Just a Privacy Policy)

Privacy policies are often marketing documents. A true Student Data Privacy Addendum (DPA) is a legally binding contract that defines exactly how student data will be used, protected, and deleted. Always ask for the full DPA early in the process.

2. Verify the “No AI Training on Student Data” Clause in the Contract

This is one of the most critical protections in 2026. Confirm that the vendor explicitly prohibits using student data to train or improve its AI models - and that this prohibition extends to all of their AI subprocessors. Without this clause, you risk serious FERPA violations.

3. Confirm Encryption Standards (AES-256 at Rest + TLS 1.2+)

Strong encryption is non-negotiable. Verify that the platform uses AES-256 encryption for data at rest and TLS 1.2 or higher for data in transit. These are the current industry standards for protecting sensitive student information.

4. Review the Sub-Processor List and Their Data Practices

Most AI tools rely on third-party AI providers (such as OpenAI, Anthropic, or Google). Ask for the complete list of subprocessors and review how each one handles student data. A reputable vendor will provide this list transparently and include contractual safeguards.

5. Check for Public Legal Documents (No NDA = Higher Transparency)

Vendors that make their full legal documents (including the DPA) publicly available without requiring an NDA demonstrate greater transparency and confidence in their practices. This also dramatically speeds up your legal and procurement review process.

6. Validate Breach Notification Timelines Against Your State Requirements

Different states have different breach notification laws (FERPA, NY Ed Law 2-d, etc.). Make sure the vendor’s breach notification timeline and procedures align with the strictest requirements that apply to your district. Ask for their documented incident response plan.

7. Test the 30-Day Data Deletion Commitment (Ask for Written Confirmation)

When a contract ends, student data should not linger indefinitely. Confirm that the vendor will securely return or destroy all student data within 30 days of termination. Request this commitment in writing as part of the contract.

8. Run a Pilot with a Small Group While Monitoring Data Flows

Before committing to a full rollout, conduct a limited pilot with a small number of classes or schools. During the pilot, closely monitor how data is collected, processed, stored, and accessed. This real-world test often reveals issues that don’t appear in documentation.

Pro Tip:

Any vendor that pushes back, delays, or provides vague answers to these questions should be treated with caution and, in most cases, removed from consideration. A trustworthy vendor will welcome these questions and respond clearly and promptly.

This checklist is designed to be practical, comprehensive, and easy for busy IT leaders and procurement teams to use. Following these eight steps will help you make confident, well-informed decisions while significantly reducing risk for your district.

Conclusion: Trust Must Be Earned - Not Assumed

In 2026, choosing an AI grading tool is no longer just a pedagogical decision. It has become a critical data governance and risk management decision - one that directly affects students, parents, staff, and your district’s reputation for years to come. With rising cyber threats, stricter regulations, and growing parental scrutiny, the stakes have never been higher.

The right platform will do more than simply “check the boxes.” It will:

• Meet or exceed the strictest regulatory requirements - including FERPA, COPPA (2025), NY Ed Law 2-d, SOPIPA, and GDPR - giving your district confidence no matter where you operate.
• Provide transparent, publicly available legal documentation - eliminating unnecessary delays caused by NDAs and allowing your legal and procurement teams to move quickly.
• Offer ironclad contractual protections against the misuse of student data, including explicit bans on AI model training, targeted advertising, and data sales.
• Make due diligence fast and straightforward for busy IT leaders, privacy officers, and legal teams - without compromising on security or compliance standards.

GradingPal was designed specifically for this new environment.

We didn’t build our security and privacy program around marketing claims or generic best practices. Instead, we built it around the real, daily needs of K-12 districts - the need for ironclad protection, radical transparency, and genuine partnership. Our entire platform reflects this philosophy: strong encryption, strict access controls, contractual prohibitions on AI training, and a commitment to making compliance as seamless as possible.

Our goal is simple: give district leaders and IT administrators complete peace of mind so they can stop worrying about data risks and focus on what truly matters - improving teaching and learning for every student.

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