This week, IEN reposts a blog from Larry Cuban that captures the challenges of clearly articulating the difficulty of reforming schools on a large scale while still fostering hope for the future. Cuban is a Professor Emeritus of Education at Stanford University, a former high school social studies teacher and district superintendent, and one of the foremost authorities on educational reform in the US. Previous IEN posts from Cuban or focused on Cuban’s work include Schooling around the World; The arc of Progressivism and “Grammar of Schooling”; and (Not) Reforming again and again and againThe original post appeared on Larry Cuban’s Blog onJuly 9th.
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Many years ago, I had met with a group of Stanford University graduate students then working on their joint Masters in Business Administration (MBA) and education. Some had taught for a few years through Teach for America and were eager to graduate and then apply their knowledge and skills learned in their MBA program tolargely minority, low-performing schools.
Here is the post I wrote about that discussion I had with these wannabe reformers eager to engage in changing schools.
Many of the 18 MBA students sitting around a seminar table had taught a few years in urban schools through Teach for America (TFA). Those who had no direct experience in schools had worked for consulting firms with contracts in major urban districts. Smart, savvy about organizations and passionate about reforming schools, the students wanted to hear my thoughts about reform that I had extracted from nearly a half-century of experience as teacher, superintendent, and researcher.
I offered four lessons. Since I have written about each of these lessons in earlier posts I will compress the lessons and cite the earlier posts for those readers who want more information.
* Reform talk and policy action in the purposes of tax-supported schooling, curriculum, instruction and organization of schools often occur in cycles but putting reforms into practice is slow, requires steady work, incremental, and often zig-zag. (See https://larrycuban.wordpress.com/2011/01/18/the-inexorable-cycles-of-school-reform/)
I spent about 30 minutes going over these lessons and then I opened the floor to students’ questions.
After a few questions asking me to clarify the lessons I had learned, a visibly agitated young woman recounted her experience as a TFAer in an urban district and her journey to Stanford for conceptual and organizational skills (and credentials). She wanted to return to a similar system to make organizational and instructional changes.
Then she asked her question: “Larry, look around this room. It is filled with people who want to reform failing schools. We will have the knowledge and skills and we will work hard. But your message to us is that reform talk occurs in cycles, adopted reforms come back again and again, reformers stumble a lot and when changes do occur they are small ones. Well, how can I put it: you don’t give me and my colleagues here too much hope. I am depressed from the lessons you have learned over so many decades. What advice would you give to all of us?”
I was neither surprised nor put off by the question. David Tyack and I had taught a course on the history of school reform for over a decade from which we wrote our book, Tinkering toward Utopia. Moreover, I had heard variations of this question often as a conference keynoter and in many prior discussions with students, colleagues, and conferees.
The upside of the student’s comment is recognizing that emotions and passions buried in heart-felt values of equity and helping urban low-income and minority students drive much school reform. That is a plus often overlooked by policymakers who too often prize values of effectiveness and efficiency and cite cost-benefit trade-offs and return on investment (ROI) rather than openly acknowledging the emotions involved in reform.
Emotions fuel practitioners, policymakers, and parents to move past the inevitable potholes on the road to reform success. Whether a reform is scientifically proven, logical, or even efficient surely matters but high-octane self-confidence and righteous belief in doing something worthwhile count also.
Unfortunately, emotions too often skip over inspection of assumptions. And there is one quiet assumption hidden in that student’s question.
Wanting to do good for urban youth, willing to put in hard work, and having a Stanford degree were somehow enough to turn around a failing classroom and an under-performing school. And here in this seminar I was claiming that any wannabe reformer needed knowledge of previous well-intentioned designs and prior reformers who had also worked hard but experienced a few small victories while often tasted the salt of many failures. That I may have triggered the blues in some of these wannabe reformers seemed both unfair and unrealistic to my questioner.
Even though nearly all these students accepted the accuracy of what I said-–many had read similar accounts of previous reforms–- I sensed that the questioner wanted reassurance that her time, energy, and commitment would pay off later in successful reforms.
Since I could neither reassure her nor give her unvarnished hope, what advice did I give this room filled with Reformers-R-Us?
What I did was talk about the importance of knowing realistically what faces anyone undertaking an adventure that contains the possibility, nay, probability of failure. I compared the launching of a reform in a school or district to climbing a difficult mountain. Responsible people want a guide. Someone who can tell the adventurers where the crevices are, what false turns to avoid, where the icy spots are and to be honest about the possibility that they may have to turn back before reaching the summit.
Accurate knowledge of forthcoming difficulties, honesty, and humility are crucial to reaching the summit of a mountain or implementing a school reform. Hope for success rests in expertise, problem solving, and courage but–and this is an especially important “but”–climbing that mountain (implementing that reform in an actual classroom or school) is still worth the effort even if success (however defined) is not achieved.
Although most schools take a break for the summer, there has been no letup in articles discussing AI and K-12 education. To take stock of the latest developments, this week’s IEN post shares headlines and links to over 20 articles on AI and education published in major sources of US education news since the middle of June. Among other issues, the articles highlight the rapidity of AI-related developments, the need for guidelines, the challenges for productive learning that created by AI, and AI’s potential to support teachers, teaching and learning in different subjects and domains. (Note: Although we attempted to use AI to help augment and format this list, it generated incorrect links, links to articles from previous years, and misidentified sources and authors.)
Where Chatbots Fit in the Curriculum Conversation: Use of the AI-powered tools to boost students’ writing and studying skills comes with advantages and disadvantages, Ed Finkel, K-12 Dive (July 1, 2026)
Fueled by AI and new technologies, innovations in assessment are emerging and quickly finding their way into classrooms, educational platforms, and large-scale tests. These include a wide range of digital tools that purport to help educators improve assessments across subjects and levels (see, for example, NWEA’s 75 digital learning tools and apps that teachers can use to support formative assessment and instruction in the classroom). Beyond these generic tools, however, a number of “micro-innovations” are demonstrating how new assessments can support the development of specific skills and knowledge in different subjects and at different levels. The effectiveness of most of these new assessment tools and approaches has not yet been established, but a review of recent articles from major education news outlets provides a sense of what’s already out there. The book Artificial Intelligence and Education in the Global South also provides a glimpse of AI’s role in assessments across different subjects and contexts in developing countries.
A game-based approach for assessing linguistic skills among students with dyslexia
Dysolve is an AI-based educational platform developed to support learners with dyslexia and related language-processing differences through adaptive, game-based activities rather than traditional static assessments or interventions. The platform provides users with customized interactive verbal games; as students play, the program analyzes responses in real time and generates new games that focus on specific cognitive and linguistic skills that need further development. To increase novelty, games are only used once and then disappear. Preliminary findings indicate potential improvements in reading outcomes for some elementary-aged learners,
Read-alouds and speech recognition for assessing reading abilities
Conventional early-grade reading assessments have relied on training educators to administer one-on-one tests, but this individualized approach makes large-scale testing expensive and demanding. Newer AI-based approaches, combined with developments in speech recognition technologies, however, can be administered to many students at once while still gathering detailed information about phonemic awareness, decoding ability, and reading fluency. For example, SoapBox Labs has developed speech-recognition technology designed to interpret children’s voices and convert oral reading or spoken responses into data that can inform assessment. This approach seeks to embed assessment within routine classroom activities, such as having early elementary students read aloud while automated systems transcribe speech, analyze fluency or comprehension indicators, and generate information that may guide instructional decisions. Following its acquisition by Curriculum Associates, this technology has been incorporated into existing educational programs, including i-Ready, reflecting broader efforts to integrate voice-based analytics into literacy instruction.
Among a slew of related platforms and tools, Amira fuses voice-based AI into reading activities with a chatbot or “reading assistant.” Amira’s reading assistant begins by observing a student read for six to ten minutes and gauges the child’s ability to name letters, sound out words and combine them into phrases and sentences. From that initial screening, Amira can gather information to spot signs of dyslexia, assess phonics mastery, estimate a student’s vocabulary size, and get a handle on decoding skills and comprehension levels. Then, the program reports findings to a teacher to support differentiated instruction, estimating the literacy levels and needs of individual students.
Amira’s “reading assistant” “observes” a student read to gauge key elements of reading ability, The74
Along with the Rapid Online Assessment of Reading (ROAR) and several other edtech-enabled approaches, Amira has been approved by states such as California and New Jersey to facilitate early screening of students for difficulties in learning to read. Some initial evidence suggests these digital tools can improve reading outcomes for some students, but with some limits. According to Ran Liu, chief AI scientist at Amira, “We’ve learned that around 25-30-minute sessions are where we see a ceiling effect.” Although Amira can also be used with Spanish-speaking students, all of these tools need to be adapted for other languages, and critical concerns include how well they will work for students with accents or speech-related challenges.
“[T]hese digital tools can improve reading outcomes for some students, but with some limits. According to Ran Liu, chief AI scientist at Amira, ‘We’ve learned that around 25-30-minute sessions are where we see a ceiling effect.’”
Automated Early Literacy Assessment in Low-Resource Languages
Although many of the most well-known AI tools focus almost exclusively on English, training AI models on locally collected speech data also enables assessments in a wide range of languages, including those that are often underrepresented in educational technology systems. To that end, the EGRA-AI project in South Africa explores whether speech-recognition models can automatically assess children’s early reading abilities in African languages such as Sepedi and isiXhosa. The system records children reading letters or words aloud and uses machine learning models to determine whether their pronunciation is correct.
AI-Supported Feedback on Student Writing in contexts with limited internet access
In addition to AI-enabled platforms like Classtime and Brisk that provide automated feedback on student performance across many subjects and levels, some tools are being designed specifically to meet the needs of educators working in areas with limited digital infrastructure and large class sizes. For example, in the AIED Unplugged initiative in Brazil, teachers photograph students’ handwritten essays and upload the images to an AI system that evaluates them using a predefined rubric. The system converts handwriting using optical character recognition and provides rubric-aligned feedback on organization, grammar, and argumentation. The system is designed for teachers to review the feedback before returning it to students.
A game-based approach to assessment in physics
Although many digital tools focus on foundational skills like reading, NWEA (Northwest Evaluation Association) has been working with the game maker Filament Games to develop a digital assessment that examines middle school students’ understanding of Newton’s Second Law of Motion. The assessment uses a collaborative 3D simulation in which pairs of students adjust variables, such as mass and force, to synchronize virtual vehicles, enabling the system to capture evidence of scientific reasoning during problem-solving. The assessment – Distance Dash – is a game-based, digital assessment delivered through the Roblox platform. In the game, “students pick a skateboard, a bike, a grocery cart, or an automobile, load each with different items, then collaboratively fine-tune the forces placed on them. The whole time, the game covertly measures several objectives, including whether students understand the principles of acceleration and how to apply optimal force.” The project is part of broader efforts to explore game-based environments as potential spaces for classroom assessment, while also raising questions about how such platforms shape collaboration, engagement, and the measurement of student learning.
A still image from Distance Dash on Roblox. (NWEA), The74
AI-Supported Preparation for High-Stakes Examinations
In Liberia, AI-driven chatbots are being piloted to help secondary school students prepare specifically for the West African Examinations Council (WAEC) exams. These chatbots simulate exam-style questions, provide explanations of correct answers, and offer targeted practice in areas where students struggle. Although they are primarily designed as learning tools, such systems implicitly rely on continuous formative assessment: the chatbot must infer a student’s level of understanding in order to generate appropriate questions and feedback.
AI-Based Measurement of Collaborative Problem-Solving
AI is also being used to measure competencies that are difficult to assess through traditional tests. In the ACTNext “Crisis in Space” pilot, students work together in a multiplayer game environment to solve a simulated emergency scenario. AI systems analyze students’ dialogue and interactions—such as turn-taking, information sharing, and problem-solving strategies—to assess collaborative skills. Rather than evaluating a single correct answer, the system analyzes patterns in communication and teamwork. This approach reflects broader efforts in educational measurement to assess 21st-century competencies, including collaboration and collective problem-solving, using AI-driven analysis of behavioral data
Oral assessments in higher education.
With students’ use of AI tools raising concerns about cheating, many educators are looking for alternatives to essays, research reports, and other written assessments. Those concerns, in turn, have fueled a renewed interest in oral assessments. For instance, Panos Ipeirotis, a professor at New York University’s business school, noticed that many students in his data science class were unable to discuss or defend their own written work when called upon. As Ipeirotis put it, “If you cannot defend your own work live, then the written artifact is not measuring what you think it is measuring.”
“If you cannot defend your own work live, then the written artifact is not measuring what you think it is measuring.” – Panos Ipeirotis
In response, he and a colleague built an “AI examiner” using conversational speech technology that probed students’ thinking about their capstone projects and that could question students about one of the cases discussed in class. With a class of over 30 students, a single instructor could not conduct such individualized oral exams, but Ipeirotis’ AI agent assessed 36 students for about 25 minutes each over nine days. Ipeirotis even had ChatGPT, Claude, and Gemini score students’ responses and asked them to review the scores and generate a final grade, with Claude designated as the “chair” of the panel to synthesize the decisions. Student reactions were mixed — most found the format more stressful than traditional written tests, but many also acknowledged it was a more authentic measure of their understanding
Large-scale developments in assessment that might eventually be used at the classroom and school level
Efforts to develop digital and multimodal assessment tasks for large-scale assessments may also provide models for how educators might assess capacities not normally measured in conventional assessments. Notably, the Program for International Student Assessment (PISA) has introduced a Creative Thinking assessment to examine the creative capacities of 15-year-old students in more than 60 countries. This assessment differs from conventional standardized measures by incorporating interactive digital tasks, including opportunities for students to produce drawings and respond to open-ended prompts with multiple possible solutions rather than a single correct answer. In addition to documenting creative expression, the assessment reflects broader efforts to capture dimensions of student learning that extend beyond strictly cognitive outcomes, such as engagement, flexibility in problem solving, and responsiveness to novel tasks. These kinds of tasks provide a model for other multi-modal assessments of competencies that may eventually find their way into tools and technologies available to educators.
Similarly, with the concerns about the authorship of college applicants’ personal essays, tech-enabled video interviews may become a more common part of the college application process. Even before the AI boom, companies like InitialView were developing platforms that allowed students to record video interviews they could send with their applications to a number of US colleges. Particularly popular with international applicants, the platform had, by 2014, attracted over 17,000 applicants from China. In the last few years, the company has developed a related application, VIVA, in which students upload a research paper or project, and an AI agent then generates a series of questions about their project that students answer during a recorded video interview. Originally offered by Caltech to accompany research papers that some applicants submitted as application supplements, the same video-based approach could be used to support oral defenses and classroom presentations in both K-12 and higher education.
Caltech’s application instructions & a sample image from the VIVA video interview
Questions for the future
These examples illustrate some of the ways AI and other digital tools may help educators conduct assessments tailored to specific skills, competencies, and subjects at different levels and in more- and less-developed contexts. At the same time, these examples demonstrate how quickly things are changing and how difficult it is to obtain detailed information about the effectiveness and impact of most AI-related developments. In this context, many educators and students may find themselves using these AI and technology tools without really knowing:
Which of these tools is most likely to improve learning?
For which students?
Under what conditions?
At what cost to professional judgment, student agency, and curricular coherence?
Under these conditions, AI developers and researchers have a responsibility to work with educators to keep these critical questions at the forefront of their collective work.
What are the benefits and drawbacks in using different AI-powered tools for assessment? In part three of this four-part series, Philip Seyfried, Suet Cheah, Alok Sharma, and Dana Bassynbekova highlight the differences in the key features and level of teacher oversight and control that several prominent AI platforms, tools, and chatbots offer for assessment and development of student learning. Their analysis was produced as part of a project working with District 79 of the New York City Public Schools. Part one of this series provided an overview of some uses of AI in both large-scale standardized tests and classroom-based assessments. Part two described some of the new platforms, apps, and tools that teachers can use to create, analyze, and score assessments, particularly those that support more student-centered learning. Part three took a deeper look at and compared the strengths and weaknesses of the assessment capabilities of selected teacher-directed AI platforms, EdTech tools, and AI “assistants” with multimodal capabilities. In the final post in this three-part series, Adelaida Kim and Thomas Hatch provide examples of “micro-innovations” in assessment that leverage AI and new technologies to support the development of specific skills and abilities across subjects and levels. For related stories on AI and education, see: Can AI “ignite the mind and heart”? Stability & change in the education system in China (Part 3); Scanning the global headlines for recent news on AI, schools, and education; AI, Cellphones, Literacy, Students’ Mental Health, Political Turmoil and More: Scanning the Headlines for the Top Education Stories for 2025.
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Artificial intelligence (AI) is rapidly reshaping what is possible in educational settings. AI enables new pathways not only in how students learn, but in how their understanding can be demonstrated, assessed, and developed over time. But the benefits and drawbacks of AI for assessment differ substantially, depending on the affordances of different platforms and tools. Broadly, three categories of AI-powered tools differ in their key features and the degree of teacher oversight, which has important implications for assessment, particularly assessments that move beyond traditional text-based responses toward multimodal, creative, and conversational demonstrations of understanding.
Teacher-Directed AI Platforms: Purpose-built EdTech tools designed to put curriculum and guardrails in teachers’ hands, with visibility into student interactions
Creative AI Tools: Platforms that empower students to demonstrate learning through the creation of videos, presentations, podcasts, and images
Multimodal General AI: Large-scale AI assistants that can generate text, images, and interactive experiences, and which are increasingly finding educational applications
Comparison at a Glance
Tool
Teacher Setup
Student Creation
Quiz / Feedback
Multimodal Output
Transcript Access
Magic School AI
✓
✓
✓
✓
✓
School AI
✓
–
✓
✓
✓
Flint AI
✓
✓
✓
✓
✓
NotebookLM
✓
✓
✓
✓
–
Canva (AI)
✓
✓
✓
✓
–
Google Gemini
✓
✓
✓
✓
–
Google Gems
✓
✓
✓
✓
–
Note: Current capabilities as of July, 2026. “Teacher Setup” refers to the teacher’s ability to configure the AI experience before students use it. “Student Creation” refers to whether students can produce their own multimodal artifacts (images, video, slides, audio) within the tool. “Quiz / Feedback” refers to the ability to quiz or provide feedback on student work. “Transcript Access” refers specifically to the teacher’s ability to read the student’s conversation with the AI.
Teacher-Directed AI Platforms
The tools in this category have been built specifically for K–12 and higher education contexts. Their defining features are teacher control, transparency, and safety. Educators can design AI-powered activities and chatbot experiences, set parameters for student interaction, and critically review what students have said and done on the platform. These features help make these tools useful for formative assessment, differentiated practice, and the ethical deployment of AI in school settings.
Magic School AI
Magic School AI | Teacher-Directed AI Platform
Overview
A comprehensive AI platform for educators offering 60+ AI-powered tools, including a “Magic Student” suite that lets teachers build structured AI activities for their classrooms.
Key Features
Teacher-designed AI chatbots and activities; student guardrails; access to conversation transcripts; learning analytics dashboard; differentiation tools.
Assessment Use
Teachers can assign AI-facilitated activities and review student interactions to assess comprehension, reasoning, and writing development.
Access Model
Free tier available; paid plans for full feature access. Widely adopted in US K–12 schools.
School AI
School AI | Teacher-Directed AI Platform
Overview
A student-facing AI learning environment built around “Spaces,” which are teacher-configured AI experiences with defined purposes, personas, and guardrails.
Key Features
Custom AI Spaces for each assignment or learning context; teacher visibility into all student-AI conversations; real-time monitoring; safety filters.
Assessment Use
Teachers can use conversation data as evidence of student thinking; Spaces can be configured to ask Socratic questions rather than simply provide answers, generating richer assessment evidence.
Access Model
School and district licensing model. Designed to integrate into existing classroom workflows.
School AI’s “Spaces” architecture can support alternative assessment approaches. Because teachers define what the AI does and does not do within each Space, they can design experiences that elicit student thinking rather than simply complete tasks for students. The transcript visibility feature is central to its use as an assessment tool.
Flint AI
Flint AI | Teacher-Directed AI Platform
Overview
An AI tutoring and classroom engagement platform that enables teachers to create custom AI tutors with specific personalities, knowledge bases, and behavioral constraints.
Key Features
Custom AI tutor creation; teacher monitoring of all student interactions; analytics on student engagement and learning; content guardrails; assignment integration.
Assessment Use
AI tutors can be configured to probe student understanding through questioning. Teacher-facing analytics provide formative data. Conversation logs serve as qualitative assessment artifacts.
Access Model
School and district licensing. Offers LMS integrations.
Flint emphasizes the tutoring relationship and students receive personalized support while teachers maintain visibility and control. For assessment purposes, the combination of analytics and conversation transcripts offers a window into student thinking that traditional written assessments may not capture.
What Teacher-Directed Platforms Share
Across Magic School AI, School AI, and Flint AI, three features stand out as essential to their value for learning and assessment:
Teacher-designed activities and guardrails: the teacher shapes the learning experience before students ever interact with the AI
Conversation visibility: teachers can read what students said and how the AI responded, creating a rich record of student thinking
Learning analytics: aggregate and individual data surfaces patterns in student engagement and understanding
Together, these features make teacher-directed platforms particularly useful for formative and alternative assessment at this time.
Creative AI Tools
The tools in this category empower students to create multimodal products, such as videos, podcasts, slide presentations, images, and diagrams, to demonstrate their learning. Teachers can ask students to produce an explanation, a visual argument, or a narrated presentation. AI dramatically lowers the technical barrier to these forms of expression, making them accessible to more students.
NotebookLM
NotebookLM | Creative AI Tool (Google)
Overview
Google’s AI-powered research and synthesis tool that allows users to upload source documents and interact with an AI grounded in those sources. Increasingly capable of generating multimedia outputs.
Key Features
Source-grounded AI responses (reduce hallucination); podcast-style audio generation from documents; study guide and FAQ generation; mind map and visual summary creation; video overview generation.
Assessment Use
Students can upload a set of sources and ask NotebookLM to generate a podcast, video overview, or visual explanation of a concept, thereby creating a multimedia artifact that demonstrates synthesis and understanding. Teachers can assess the quality of the artifact as evidence of learning.
Teacher Oversight
No direct teacher oversight or transcript visibility built in. Teachers assess the final product rather than the process.
One way to use Notebook-LM for assessment is to ask students to upload primary or secondary sources and then produce a NotebookLM-generated podcast or video that explains a concept, event, or argument. The quality of the output reflects the quality of the sources students selected, and the prompts they used can reveal meaningful understanding. Students then can analyze the results, identifying what AI did well and what important information and perspectives it misses. Notably, however, selecting lower quality texts and prompts may make it harder for students to demonstrate more sophisticated analyses.
Canva (with AI Tools)
Canva | Creative AI Tool
Overview
A widely used design platform that has integrated a suite of AI tools for image generation, photo editing, presentation creation, video production, and more.
Key Features
AI image generation and editing; AI-assisted slide presentation design; video creation with AI voiceover; photo background removal and editing; “Magic Write” for text generation; diagram and infographic templates.
Assessment Use
Students can edit images for a visual argument, build an AI-assisted presentation to explain a concept, create an infographic to synthesize research, or produce a short video demonstrating the process they went through. These artifacts serve as alternative assessments of understanding.
Teacher Oversight
No built-in teacher monitoring of AI interaction. Assessment focuses on the finished product. Canva for Education offers classroom management features, including assignment sharing.
Canva’s value for alternative assessment lies in its accessibility and range. Students who might struggle with a traditional essay may demonstrate a more sophisticated understanding through a well-designed infographic or a narrated video. Photo-editing tasks, such as adjusting an image for a presentation, can also demonstrate visual literacy and design thinking alongside content knowledge.
Both NotebookLM and Canva shift assessment from the process of thinking to its product, which can have both benefits and drawbacks. For instance, these tools enable simultaneous assessment of content knowledge and creative and technical skills, and the reduced technical barrier means more students can demonstrate learning in ways that suit their strengths. However, teachers must develop criteria for assessing multimodal products, not just written responses. Furthermore, the artifact itself (the video, the podcast, the presentation) becomes both the assessment and the evidence of learning, but neither tool currently provides teachers with visibility into the AI interactions that produced the artifact.
Multimodal General AI
General-purpose AI assistants like Google Gemini are increasingly capable across modalities by generating text, producing images, creating video, and supporting interactive experiences. As these tools add educational features (like Google Gems), they occupy a middle ground between creative tools and teacher-directed platforms. They are powerful and flexible, but their oversight features are currently more limited than those of purpose-built EdTech platforms.
Google Gemini
Google Gemini | Multimodal General AI (Google)
Overview
Google’s flagship AI assistant, available across the Google ecosystem. Gemini is increasingly multimodal, capable of generating text, images, and video, and of reasoning across multiple formats.
Key Features
Text generation and conversation; image generation; video generation (Veo integration); code generation; document analysis; integration with Google Workspace tools.
Assessment Use
Gemini can quiz students on a topic, provide feedback on submitted writing or work, and help students explore ideas through conversation. Its multimodal output capabilities allow students to create a range of artifacts.
Limitation
At this time, Gemini does not provide teachers with access to transcripts of student conversations. Assessment of AI-assisted work must rely on final products or student self-reporting.
Access
Gemini Advanced is available through Google accounts with a Google One subscription. Integrated into Google Workspace for Education.
Gemini’s growing multimodal capabilities make it a versatile tool for student creation. A student might ask Gemini to generate an image illustrating a concept, then embed it in a presentation with an explanation they have written. Or they might submit a draft essay and receive detailed feedback, an experience that mirrors personalized writing conferences. However, the absence of teacher-visible transcripts is a key limitation for use in formal assessment. Teachers can assess what students produce with Gemini’s help, but not the quality of their reasoning within the conversation itself.
Google Gems
Google Gems | Configurable AI Agents within Gemini
Overview
Gems are customizable AI personas within Google Gemini. Teachers or institutions can create Gems with specific roles (a research assistant, a writing coach, a practice quiz partner) and share them with students.
Key Features
Custom AI persona creation with defined roles and instructions; ability to set a specific knowledge focus; shareable with student groups; supports Socratic questioning, practice environments, and research assistance.
Assessment Use
A teacher can create a Gem configured to quiz students on a specific topic, ask follow-up questions, or provide scaffolded feedback on submitted work. Students interact with a purpose-built AI experience within the broader Gemini environment.
Limitation
Like Gemini generally, Gems do not currently provide teachers with access to conversation transcripts. The teacher sees neither what the students asked nor how the Gem responded.
Comparison Note
Gems offer similar configurability to teacher-directed EdTech platforms (Magic School AI, School AI, Flint), but currently lack the teacher-visibility features that make those platforms most useful for assessment.
Google Gems represent an important development: a mainstream AI platform that adds teacher-configurable experiences. However, Gems’ usefulness for assessment depends on whether or not future versions add teacher visibility into student interactions.
Implications for Assessment Design
Each category of tool implies a different approach to assessment design. Understanding these distinctions helps educators choose the right tool for the right assessment purpose.
Process-Visible Assessment
When using teacher-directed platforms (Magic School AI, School AI, Flint AI), the conversation itself is an assessment artifact. Teachers can evaluate:
The depth and relevance of questions a student asks the AI
How a student responds when the AI pushes back or asks a clarifying question
The progression of a student’s thinking across a multi-turn conversation
Whether a student recognizes when the AI has made an error
This form of assessment is particularly valuable because it surfaces metacognitive processes that traditional written products often obscure.
Product-Based Assessment
When using creative tools (NotebookLM, Canva) or general AI (Gemini), assessment focuses on what the student creates. Rubrics for product-based assessment should address:
Accuracy and depth of content knowledge demonstrated
Quality of synthesis across multiple sources or ideas
Clarity and effectiveness of communication in the chosen medium
Evidence of original thinking beyond AI-generated content
Appropriate attribution of AI-assisted elements
Product-based AI assessment works best when teachers pair it with reflections or oral explanations, giving students the opportunity to articulate what they made and why, which provides additional assessment evidence and can help reveal when students have not thought through or critically analyzed their use of AI.
Feedback and Practice Environments
Both teacher-directed platforms and Google Gems can serve as low-stakes practice and feedback environments that provide students with iterative responses to their work without the pressure of a formal grade. These uses include:
Submitting a draft for AI feedback before a teacher conference
Practicing for a presentation by interacting with a Gem configured as an audience member
Working through a problem set with an AI tutor that provides hints rather than answers
In these contexts, the AI functions less as an assessment instrument and more as a rehearsal space that frees teacher time for higher-order feedback and conferring.
Looking Ahead
The landscape of AI tools in education is evolving rapidly. Several trends are worth watching:
Growing teacher oversight of general AI tools. Platforms like Google Gemini and its Gems feature may add transcript visibility and classroom management features as they develop education-specific versions. This would significantly expand their usefulness for assessment.
Richer multimodal assessment. As students gain facility with tools like NotebookLM and Canva, educators will have the opportunity to design assessments that require video explanations, well-designed presentations, or AI-assisted research products, pushing assessment beyond text-based demonstrations of knowledge.
The conversation as curriculum. In teacher-directed platforms, the transcript of a student’s conversation with AI is a new kind of learning record that documents not just what a student knows, but how they think. Assessment frameworks will need to evolve to make productive use of this data.
Questions of attribution and academic integrity. As AI becomes embedded in the creation process, assessment design must grapple with what it means to demonstrate learning when AI has contributed to the product. Clear expectations, reflection requirements, and process-visible assessment approaches all play a role.
Next week: “Micro-Innovations” in Assessment for Specific Subjects, Levels, and Contexts: AI, New Technologies and the Future of Assessment (Part 4)
The rush to incorporate AI into all manner of educational platforms and products has already equipped educators with new ways to assess their students. Many of those tools support conventional tests and quizzes, but some may offer educators opportunities to develop alternative assessments, including portfolios, performance tasks, evidence demonstrations, peer reviews, and self-assessments. In particular, emerging technologies, including AI, could assist teachers in generating more complex, real-world tasks, facilitate data collection, analysis, and feedback, and perhaps foster the development and assessment of a wider range of abilities and overall well-being. Although it is too early to tell how effective many of the new developments will turn out to be, an examination of some of the news and research on assessment over the past few years points to new developments in digital platforms, digital portfolios, learning management systems, and tools for adaptive learning that all bear watching.
New Platforms, Portfolios, Learning Management Systems, and Assessment Tools
Teachers and students in the US and around the world now have access to a host of different learning platforms. Some of those platforms include features that may help educators manage the complexity of competency-based and personalized assessment. Lift Learning, Foundry, Headrush Learning, Epiphany Learning, and Building 21 represent systems designed specifically around competencies rather than content sequences. These platforms provide structures for organizing student evidence, tracking mastery, supporting project-based learning, and facilitating personalized learning plans. These elements aim to make it easier for teachers to capture artifacts from daily classroom work, such as quick reflections, conference notes, or mini-tasks, and align them to clear performance indicators. The flexibility of these systems allows educators to support formative assessments, such as “micro-conferences,” that provide students with quick feedback and collect and analyze data teachers can use to inform instruction.
Online platforms
Online platforms may also provide an environment that makes it easier for teachers and students to develop digital portfolios (e-portfolios) that track the development of skills and competencies that extend far beyond those measured by conventional tests. Digital portfolios can capture multimedia materials documenting the processes, products, and performances that students complete. The hope is that by creating a living, accessible collection of work, students, parents, and future educators can all trace academic growth and evolving interests over time, making learning more transparent, equitable, and aligned with real-world competencies.
Traditional learning management systems have also evolved to support alternative assessment practices. Schoology and Canvas, for example, offer features for rubric-based assessment, multimedia submissions, peer review, and mastery tracking. Meanwhile, Canvas Credentials extends this functionality through digital badges and micro-credentials, intended to indicate when students have demonstrated specific competencies by completing specific activities or producing particular products. These environments aim to provide teachers with an easy way to access new assessment tools, allowing them to integrate tools such as exit tickets, short video explanations, iterative revisions, or authentic performance tasks into familiar LMS workflows.
Platforms for “real-world” skills
Another emerging category includes tools that help bridge classroom learning with real-world skills and career pathways. Territorium, LifeJourney, and Lightcast help schools align student assessments with employability skills and labor-market data. These platforms support a broader vision of alternative assessment: one that recognizes not only classroom competencies but also skills demonstrated in internships, co-ops, community experiences, or extracurricular learning. By mapping student evidence to industry-recognized competencies, these tools help teachers and schools emphasize authentic tasks and support the development of abilities that go beyond conventional academic tasks.
LifeJourney Homepage showcasing mentors from various industries
Adaptive learning environments
New developments are also supporting the kind of adaptive learning and personalized assessment environments that many hope will make it possible to individualize and differentiate instruction more effectively than in the past. Area9 Lyceum, for example, uses adaptive algorithms to provide continuous formative checks and individualized learning pathways. In these contexts, students can receive real-time feedback, progress through dynamic question pathways, and engage in small-scale, personalized tasks that adjust to their performance. Similarly, some programs, such as Learn Everywhere, expand the boundaries of where assessment can occur. Allowing students to earn competency-based credit for learning outside the traditional classroom encourages schools to adopt flexible, evidence-driven assessment models. In this approach, teachers use short reflections, artifact documentation, and performance checkpoints to verify learning in diverse settings.
Tools that support multilingual learning and multimodal assessment
To extend the power of this support for alternative assessments, other new tools like Flint AI and School AI can help educators to create assessments that support multilingual learners. These tools enable students to read and respond to prompts, activities, and feedback in different languages. These tools can be particularly useful in subjects that focus on knowledge acquisition, critical thinking, and deeper learning – rather than simply on learning English or another non-native language. In addition, platforms like Canva and Notebook LM increasingly offer opportunities to create and analyze assessments in multiple modalities. These platforms enable students to demonstrate their learning through video-based presentations, audio podcasts, and graphic descriptions, providing windows into their thinking that conventional written responses cannot offer. Again, these alternative formats can be especially useful when students are still developing their capacities to express themselves in writing or in a non-native language.
All these developments are creating a new ecosystem for learning and assessment. The hope is that these new tools and platforms will reduce the burden on teachers, increase transparency for students, and support richer, more authentic, and more personalized demonstrations of learning. However, if the past is any guide, these new developments may be more likely to reinforce conventional testing and instruction than to lead to an immediate revolution. An account of the remarks of Larry Cuban, author of books like Oversold and Underused: Computers in the Classroom, to Google engineers put it this way: “AI will not force educators to rethink how teachers teach, and students learn. Instead, teachers will simply adapt AI to fit the ‘contours’ of their classrooms, keeping it on the periphery of their teaching repertoire.”
“AI will not force educators to rethink how teachers teach and students learn. Instead, teachers will simply adapt AI to fit the ‘contours’ of their classrooms, keeping it on the periphery of their teaching repertoire.” – Larry Cuban
Platforms like Kahoot!, Wayground, Blooket, Gimkit, Quizlet, Formative, Mentimeter, and Plickers can make it easy for teachers to quickly generate formative assessments that students find engaging and that provide frequent information on what students are and are not learning. At the same time, those tools are much better for creating tests and quizzes that measure recall and basic skills than for assessing deeper learning. As with all new technologies, issues of implementation, bias, equity, safety, and effectiveness must be addressed. So far, surveys suggest that the use of AI is growing at a pace that outstrips evidence of its effectiveness and efforts to produce guidelines to support ethical, equitable, and safe use. As a report from Milken Institute published at the end of 2025 indicated, 60% of schools and districts in the US had no guidance on AI use at all, with decisions about how to use AI left largely up to individual teachers. Under these conditions, concerns about AI among educators, parents, and even students are growing, leaving open a critical question: Can concerns about the use of AI and other new technologies for assessment be addressed as they become ubiquitous?
Next week: The Emerging Affordances of Teacher-Directed Platforms, EdTech Tools, and Multimodal Assistants: AI, New Technologies and the Future of Assessment (Part 3)
What effect will AI and other new technologies have on testing and assessment? In the first part of this four-part series, Adelaida Kim and Thomas Hatch provide an overview of how both large-scale tests and classroom-based assessments are changing as AI and new technologies continue to develop. Part two will describe some of the new platforms, apps, and tools that teachers can use to create, analyze, and score assessments, particularly those that support more student-centered learning. Part three will provide a deeper look at and a comparison of the strengths and weaknesses of the assessment capabilities of selected AI platforms, EdTech tools, and AI “assistants”. Part 4 will share examples of “micro-innovations” that are already demonstrating how AI and new technologies can assess and support the development of specific skills and abilities across different subjects and at different levels. For related stories on AI and education, see: Can AI “ignite the mind and heart”? Stability & change in the education system in China (Part 3); Scanning the global headlines for recent news on AI, schools, and education; AI, Cellphones, Literacy, Students’ Mental Health, Political Turmoil and More: Scanning the Headlines for the Top Education Stories for 2025.
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Almost every aspect of assessment is already being affected by AI and new technologies. These new technological developments intersect with long-standing debates about the role that testing and assessment should play in improving learning, teaching, quality assurance, and accountability, contributing to both hopes and fears for the future. For some, the hopes revolve around making standardized tests more efficient, while others envision a future where conventional standardized testing is obsolete and gives way for the assessment and development of a much wider range of competencies. As Ulrich Boser, co-author of a series of articles about the future of testing, predicted in 2021: “AI is going to eat assessments for lunch.” Of course, those hopes come along with widespread concerns about excessive screen time, cheating, surveillance, privacy, safety, bias, and equity. Although it’s impossible to take stock of every possibility and concern, scanning the headlines for articles about AI and assessment over the past year provides a sense of some of the latest developments in the use of AI for both large-scale standardized testing and classroom assessments.
“AI is going to eat assessments for lunch.” – Ulrich Boser
How might AI affect large-scale testing?
Many policymakers and researchers argue that standardized testing is an essential tool for accountability and for promoting equity in consequential decisions like college admissions. But critics raise significant concerns, including delays in reporting, which make it difficult, if not impossible, to use the results of these tests to inform instruction and support learning. Chad Aldeman has done the math to show that in 2025, only 6 states released their annual test results by July, while 16 states reported theirs only after October. As he explained, “states have gone from paper-and-pencil tests to computers and somehow gotten slower.”
“[S]tates have gone from paper-and-pencil tests to computers and somehow gotten slower.” – Chad Aldeman
The extent of testing also interferes with the time students and teachers have to spend on teaching and learning. A 2015 study from the Council of Great City Schools showed that in large urban districts, U.S. public school students take an average of 112 standardized tests between pre-K and 12th grade. Annually, this testing can take up 20-25 hours of class time. In 2013, a study from the American Federation of Teachers reported that in heavily tested grades, testing might take about 50 hours a year, with over 100 hours of test prep, together consuming almost 15 percent of instructional time. Accountability measures in some states contribute to this problem by instituting year-round testing that requires administering multiple tests over the course of the year, in the hope that the resulting data will help teachers improve student performance.
Compounding these concerns, the pressure to perform well on all these tests can contribute to a narrowing of the curriculum and a hyper-focus on a limited set of academic skills, making it difficult to support the development of a wider range of abilities and student wellbeing. This disconnect between what’s tested and what’s valued creates considerable frustration among educators. According to a survey by the EdWeek Research Center, almost 60% of educators do not believe that current state standardized tests appropriately measure what students need to know and be able to do.
Adjust item “delivery” to accommodate learning differences
Analyze responses to suggest revisions to test items
With these new developments, AI is already being used to grade most writing on New Jersey’s standardized tests; platforms like Classtime give students and teachers almost instant feedback designed to make test-prep more efficient; and test-makers are struggling to keep up with the new developments that enable some students to game the system and cheat on the newest online tests. If the past is any indication, these new developments in testing are likely to both foster long-needed improvements at the same time that they exacerbate some of the most critical problems of over-testing, disengagement, and inequity that continue to plague education.
If the past is any indication, these new developments in testing are likely to both foster long-needed improvements at the same time that they exacerbate some of the most critical problems of over-testing, disengagement, and inequity that continue to plague education.
Can AI contribute to the development of more powerful classroom assessments?
AI and new technologies are already changing key aspects of the classroom assessments teachers use day to day. It is far from clear how effective some of these changes will be, but developments may help teachers to measure greater skills, provide more useful feedback, and make assessments more relevant, useful, and personalized.
Measuring deeper understanding and complex skills. AI technologies, such as natural language processing, can support the development and analysis of alternative assessments, such as performance tasks and portfolios. In particular, teachers may be able to take advantage of AI to help them create tasks such as interactive scenarios in which students interview virtual experts to decide whether a historical artifact belongs in a museum or use a chatbot to research a topic. These kinds of tasks can be difficult for teachers to design and grade, but they give students opportunities to develop and demonstrate skills such as critical thinking, creativity, communication, and problem-solving that are not easily measured by simpler conventional tests. As a UNESCO think piece on the future of assessment argues, AI’s challenge to traditional testing is also “an opportunity to fundamentally realign educational evaluation with more authentic demonstrations of human learning, thinking, and creation.”
AI’s challenge to traditional testing is also “an opportunity to fundamentally realign educational evaluation with more authentic demonstrations of human learning, thinking, and creation.” – UNESCO
Providing Actionable Feedback. Beyond providing final scores, AI can analyze student responses to identify patterns in individual, group, and whole-class answers. These analyses give teachers immediate, concrete data they can use to adjust their instruction and help students right away. As Lauren Katzman points out, providing feedback can be an “unmanageable” task, since spending just 10 minutes reading each student’s draft in a class of 20 can take almost 2 hours. For a high school teacher with 100 students in different classes, reading that one draft can take almost 16 hours. To relieve that workload, initiatives are underway to train AI to provide teachers with information on students’ errors when explaining their reasoning for math problems, enabling teachers to correct student misconceptions in real time.
Automated writing evaluation (AWE) systems also provide AI-powered scores and feedback on writing directly to students. One meta-analysis found that this automatic feedback had a “moderate” effect size with larger effects for multilingual learners. However, wide variation in results led the researchers to warn that “automated feedback should be combined with other forms of support, such as teacher feedback and individualized learning opportunities, to ensure its effectiveness.” Correspondingly, research reveals that students who write without AI assistance but then use AI to revise their writing show the strongest learning-related brain activity. In contrast, students who use AI to help them write from the beginning show lower brain activity and “lower satisfaction and ownership over their work.”
“Personalized” and adaptive assessment and instruction. Numerous educational programs, particularly tutoring programs, are already using AI to “personalize” or individualize assessment and instruction in various ways. Among recent developments, educators can use AI to adapt assignments and tests to student learning differences by translating assessments into different languages; taking advantage of chatbots designed to respond to the behavioral cues of students with autism; and employing computer-assisted environments designed specifically for voice and gesture recognition.
AI can also generate test items that measure core skills but are tailored to a student’s individual interests. At the simplest level, that might include testing fractions by providing a student who loves baking with questions based on a cookie recipe or a student who loves sports might get questions based on the dimensions of a football field. AI can also help educators to generate more complex questions that draw on students’ experiences and local knowledge. For example, questions about physical phenomena that students have observed can replace more generic physics problems. Conceivably, more personalized testing can be more engaging for students, potentially reducing test-taking anxiety and increasing motivation and providing a more accurate representation of their knowledge and abilities. For the most part, however, these claims still need to be tested and verified.
Beyond tailoring content to student interests, many educators and researchers are exploring adaptive assessment — a form of personalization in which AI analyzes each student’s responses in real time and adjusts subsequent questions and tasks. This is the underlying logic of AI-powered many tutoring tools like Khan Academy’s Khanmigo, which guides students through problems by responding to their specific answers rather than simply providing correct ones, and platforms like Squirrel AI, which has been named one of TIME’s Best Inventions of 2025 for its ability to break subjects down into granular knowledge points and continuously adjust a student’s learning path based on their interactions. A systematic review of AI-driven intelligent tutoring systems in K-12 education finds that these systems can “monitor student progress, identify difficulties and errors, navigate structured subject content to offer and tailor the difficulty level, thus developing an optimal path for learning.” Researchers at the University of Michigan are developing adaptive chatbots that go further still, carrying out dialogue with students and providing scaffolding based on both the accuracy and the sentiment of their responses, with teachers able to customize the question sequences to match their own instructional goals. With new AI-based adaptive approaches far outpacing research on their effectiveness, how quickly and equitably these approaches can be implemented across schools remains an open question.
The future for AI and assessment?
New possibilities and challenges for AI and assessment will continue to emerge as AI and other technologies develop, making it difficult to predict exactly what might happen next. Regardless, some of the benefits and challenges are already clear. With these challenges in mind, some experts believe that smaller shifts in assessments and instruction are more likely in the next few years rather than a dramatic revolution. As Matt Johnson, a principal research director at Educational Testing Service (ETS), puts it: “My opinion is that there will be a slow creep of new stuff.” So far, some of the developments most likely to be a part of that “slow creep” include the use of AI by test makers and teachers to generate test items and tests. But Janet Garcia, CEO of PSI and President of the ETS, sees even bigger changes ahead: “One of the clearest trends I see emerging is the movement away from single-point, multiple-choice exams toward more continuous, real-time demonstrations of competence.”
“One of the clearest trends I see emerging is the movement away from single-point, multiple-choice exams toward more continuous, real-time demonstrations of competence.” – Janet Garcia
It remains to be seen how quickly these kinds of developments in large-scale testing and the assessment of a wider range of competencies might take hold, but, more concerning, it’s far from clear whether changes like these will make things better or worse for students and teachers
Next week: Can Online Platforms and Digital Tools Support More Student-Centered Learning? AI, New Technologies and the Future of Assessment (Part 2)
In the fourth part of this month’s Lead the Change (LtC) interview, Daisy Salazar-Garza discusses her firsthand experience of the inequities in the public education system and the impact this has on students, families, and communities. Salazar-Garza is a Ph.D. student in the School of Educational Studies’ Urban Leadership Program at Claremont University. German is a recipient of the Student Travel Award from the Educational Change Special Interest Group (SIG) of the American Educational Research Association (AREA). The LtC series is produced by co-editors Dr. Soobin Choi and Dr. Jackie Pedota and their colleagues who lead the Ed Change SIG. A PDF of the fully formatted interview will be available on the LtC website.
Lead the Change (LtC): The 2026 AERA Annual Meeting theme is “Unforgetting Histories and Imagining Futures: Constructing a New Vision for Educational Research.” This theme calls us to consider how to leverage our diverse knowledge and experiences to engage in futuring for education and education research, involving looking back to remember our histories so that we can look forward to imagine better futures. What steps are you taking, or do you plan to take, to heed this call?
Daisy Salazar-Garza: The 2026 AERA theme, “Unforgetting Histories and Imagining Futures: Constructing a New Vision for Education Research,” calls us to draw upon our diverse knowledge and lived experiences to engage in meaningful “futuring” for education. For me, as a Chicana educator, scholar, and first-generation doctoral student, this theme feels deeply personal. It is a call that echoes the lessons my family instilled in me from an early age.
My family, especially my father, taught me about life’s harsh realities and the beauty of resilience through the power of storytelling. Around family meals, during long drives, or in quiet moments on the porch, I listened to stories of our history—stories of struggle, perseverance, and hope. These narratives shaped my understanding of who I am and filled me with a deep sense of pride. They taught me to honor the strength passed down from my ancestors and to recognize that storytelling is not only an act of remembrance but also a tool for transformation.
This foundation shapes how I approach educational research. To truly “unforget” our histories, we must center the voices and stories that have been pushed to the margins. Leveraging our collective knowledge requires valuing the lived experiences of those most impacted by educational inequities. By empowering communities with a vested interest in the future of education, we can imagine possibilities rooted in justice, equity, and collective empowerment.
As I continue to heed the 2026 AERA theme, I draw upon this legacy of storytelling and historical remembrance to inform my work. Understanding the social, economic, political, and racial contexts that have shaped communities is essential to serving them authentically—honoring both their strengths and the systemic injustice they have endured. Through remembering and honoring these histories, we can envision and build educational spaces that celebrate our roots and uplift our voices. In doing so, we can cultivate a just and hopeful future that directly confronts the inequities we must transform.
Source: Bank Street Graduate School of Education website
LtC: What are some key lessons that practitioners and scholars might take from your work to foster better educational systems for all students?
DSG: Recently, I had the privilege of working with Dr. Osworth to co-author “Outward Portrayals of Equity: An Examination of Diversity, Equity, and Inclusion in Los Angeles County School Districts.” In 2024, we collected data from 80 public school districts to assess the current state of DEI commitments in Los Angeles County districts.
From this work, several lessons emerge for practitioners and scholars in the field of Educational Change. First, our findings highlight the need to look beyond surface-level portrayals of equity and focus on how DEI policies are enacted in districts and schools. Value statements made toward DEI without creating infrastructure through policy to support the work does not address the racialized nature of the structures within school districts (Salazar-Garza & Osworth, 2026). Second, schools as organizational systems often reproduce existing inequities. Recognizing these structural patterns is the first step toward redesigning them. Ultimately, transformative change needs to occur at the systemic level to disrupt and dismantle entrenched systems of inequality (Salazar-Garza & Osworth, 2026). Finally, pairing enforcement mechanisms, such as culturally responsive teaching, with policy can contribute to conscious efforts to alter internal patterns of organizational inequity (Salazar-Garza & Osworth, 2026).
“Value statements made toward DEI without creating infrastructure through policy to support the work do not address the racialized nature of the structures within school districts.”
Together, these insights emphasize that fostering educational change requires both reflective practice and systemic change. Equity efforts translate into improved student experiences and outcomes when we can redesign structures enacting patterns of inequity.
LtC: What do you see the field of Educational Change heading, and where do you find hope for this field for the future?
DSG: As a scholar-practitioner, I believe the field of educational change is heading toward a deeper partnership with people who are the most affected by our current educational realities. By centering the voices of teachers, students, families, and communities, we can inspire real progress. Change comes when research and practice work go hand in hand to bridge the gap between theory and lived experience.
Given the current polycrisis world we’re navigating, where social, economic, and environmental challenges continually intersect, I find hope in collaboration within the field of education (Virella, 2025). Dr. Virella’s Crisis as Catalyst: Equity-Oriented School Leadership During Difficult Times reminds me that even in moments of uncertainty, there is great potential for transformation. As a school principal who was interviewed and whose narrative is present in this research alongside numerous other school leaders, it is a reminder that practitioners are engaging in powerful practices that are meeting the needs of our present moment. It is also a call to action that we can study practices from the field, derive key lessons, and create frameworks that empower and sustain more educators across the field.
What gives me hope is seeing more educators and researchers approach their work not just as inquiry, but as partnership with students, families, communities. When our research centers humanity and lived experience, educational change can lead us toward a more just and human-centered system for all students.
References
Salazar-Garza,D. and Osworth, D. (2026) Outward portrayals of equity: an examination of diversity, equity, and inclusion in Los Angeles County school districts. Leadership in Education Racial Equity and the Organization: An Educational Change Call to Action. Frontiers in Education. https://doi.org/10.3389/feduc.2026.1642675
Virella, P. M. (2025). Crisis as catalyst: Equity-oriented school leadership during difficult times. Harvard Education Press.
What does it take to create more sustainable school facilities? In the third part to this series, Carter Hyde and Hannah Nguyen discuss some of the new developments in facilities and facilities management that schools across the country have implemented to conserve energy, cut costs, and support students’ learning and wellbeing. The first post explored the negative impact that climate change and related disruptions have on students, and the second post focused on how schools are making busing and other aspects of school transportation more sustainable.
Environmental changes are contributing to disasters, crises, and day-to-day conditions that disrupt schooling, increase costs, and undermine students’ health and learning. Combatting these problems is profoundly complex, often requiring difficult trade-offs. Efforts to improve student health and learning environments may conflict with long-term sustainability goals and cost-effectiveness. These tradeoffs force school administrators to weigh the benefits of expensive structural upgrades against smaller, more affordable interventions. Despite the challenges, schools in the US and around the world are taking innovative steps that range from major infrastructure upgrades to homegrown, creative adjustments made by teachers in their classrooms.
A student from John McDonogh Senior High School’s first graduating class since Hurricane Katrina walks past a damaged wall on the way to commencement June 8, 2007, in New Orleans, LA, K12 Dive
Major Infrastructure Upgrades and Renewable Energy
After salaries, energy represents a critical area for both reducing costs and addressing sustainability. In the US, energy bills make up the second highest cost for school districts, amounting to roughly 8 billion dollars per year. To address these significant expenses, many institutions are moving beyond reactive budgeting and toward strategic roadmaps that help schools set sustainability goals that are aligned with national sustainability targets. Schools can use these roadmaps to help reduce the schools’ energy and water consumption, waste, and greenhouse gas emissions.
In the US, energy bills make up the second highest cost for school districts, amounting to roughly 8 billion dollars per year.
In addition to strategic budgeting, some schools are turning to high-impact technology to reduce energy costs and to promote sustainable practices. For instance, some schools are now putting in place geothermal wells because they offer a particularly sustainable way to heat and cool schools without burning fossil fuels. At the same time, some schools are turning to solar energy so that they can develop their own sources of energy. Though a costly up-front investment, solar panels can help reduce the electrification gap by providing a sustainable way to power schools that reduces costs over time and contributes to better air quality.
Countries with large with large school electrification gaps tend to have high potential for solar power generation, UNESCO via Gem Statlink
Improving HVAC Systems and the Building “Envelope”
Beyond energy sources, improvements to the school’s physical “envelope”—the walls, windows, and climate systems—can support student performance. Upgrading old HVAC systems, in particular, provides a way to cool classrooms and create better learning conditions at the some time. As one review of survey data from New York State schools showed, improving HVAC systems contributed to a 2% increase in attendance and a 3% increase in math scores over multiple years. Among other benefits, HVAC improvements can produce better air flow, which reduces the spread of disease and helps students focus. Improving air filtration through the use of air purifiers and portable air cleaners, can also help improve cognition and mitigate illness-related absences.
At the same time, air conditioning alone is not always a sustainable solution, as these systems can expel hot air outdoors and contribute to global warming. As architect Francis Kere explains, “energy-intensive air conditioning, which expels hot air outdoors, contribute to global warming, which then fuels demand for more air conditioning.” Instead, Kere recommends using passive cooling techniques, such as overhanging roofs to improve air circulation and generate cross-ventilation.
A student leaves the secondary school building built by Pritzker Prize-winning architect Francis Kere, in Kere’s home village of Gando, Burkina Faso, The Japan Times via Reuters
Schools can also make improvements in the outdoor environment to address sustainability. For instance, planting trees on asphalt playgrounds can reduce temperatures through shading, and painting roofs white, adding vegetation of false ceilings, and creating more green spaces can reduce the “heat island” effect.
Balancing Lighting and Temperature
Lighting represents another area where schools need to consider potentially conflicting benefits. In a 2020 review of 130 studies, lighting was found to be one of the environmental factors that had the biggest impact on students’ learning and wellbeing. Maximizing the amount of natural light in classrooms, in particular, has been shown to have a number of benefits including reducing eye strain, boosting mood, and improving cognition. Although artificial lighting may lead to lower motivation and eye strain, research reviews highlight that students in classrooms with more natural light showed higher productivity, engagement, and attention level. Despite these benefits, some classrooms may still suffer from poor lighting or rely too heavily on artificial sources. This problem is exacerbated by the fact that, in an effort to reduce energy consumption and costs, many schools have implemented LED lighting in classrooms.
Maximizing the amount of natural light in classrooms, in particular, has been shown to have a number of benefits, including reducing eye strain, boosting mood, and improving cognition.
In addition to finding a balance that maximizes the benefits of natural lighting with the costs, schools have to take into account the fact that both too much direct sunlight and too little light can negatively impact student engagement and impair test scores. Furthermore, schools have to take into account mitigating factors, including structural limitations that prevent some classrooms from relying on daylight, as well as the increases in classroom temperature and energy costs that come with larger windows. One way to deal with these challenges is to use temperature-treated or double-paned glass to provide light while keeping the heat out. The use of window shades may also be useful in eliminating glare.
Teachers’ Role in Sustainability
Whether or not schools have the resources for major structural changes or sustainability upgrades, teachers play a key role in striking the right balance between lighting and temperature and supporting both sustainability and an optimal learning environment. For instance, teachers have demonstrated a host of creative ways to combat heat and to improve the environment including using fans, creating window art to reduce glare, and turning off heat-generating electronics. In some cases, the simplest solutions may be the best solutions, as teachers in schools located in temperate regions with good air quality can open windows to allow for natural air flow.
Improving Facilities in “Old” Buildings
Along with so many natural disasters and rising temperatures, many communities face a long-standing demand to improve aging or inadequate school buildings. One of the most recent assessments of school infrastructure in the US shows that it would cost almost 200 billion dollars to bring all K-12 school buildings into good overall condition and the American Society of Civil Engineers gives the condition of America’s 100,000 public school buildings an overall grade of D+. Estimates suggest it would take as much as 85 billion dollars a year to make the needed improvements. On top of that, the costs of deferred maintenance continue to compound with every one million dollars worth of needed improvements deferred in one year leading to $1.08 – 1.12 million in costs the following year.
In the US, the burden and responsibility for addressing this problem falls on individual school districts and communities, but many lack the resources to pay for the significant upfront costs of building new facilities. Some districts have tried to mitigate these costs – and the sustainability problems that new construction often produces – by repurposing older buildings. For instance, struggling malls have opened the doors to charter schools as tenants to use the empty spaces. One charter school in South Carolina opened up in a former JC Penny Store. In Massachusetts, instead of building a new high school, one district opted to co-locate a school in the community’s senior center. center down the road.
Liberty STEAM Charter School in Sumter, S.C., is one of many schools that have opened up in malls across the nation, The New York Times
For more information regarding infrastructure and sustainability, see:
Can new developments in busing and transportation help schools to cut costs and become more sustainable? That’s the question that Carter Hyde and Hannah Nguyen tackle in the second part of this three-part review of recent news and research related to schools and sustainability. Part 1 explored how climate change and related disruptions can have a negative impact on student learning. Part 3 will explore what schools can do to make their facilities and other aspects of school operations more sustainable.
What kinds of innovations might enable schools to cut costs and become more sustainable? New developments in school transportation and busing may be at the top of the list. Swapping diesel-fueled buses for electric vehicles, using technology to create more efficient routes, and encouraging biking and other transportation alternatives are among the most notable innovations that can make school transportation more sustainable.
Electric buses
The development of electric school buses has been one of the most important innovations in sustainable schooling, helping both to save money and, in some cases, supporting student attendance and learning. Potential cost savings are one key factor that has encouraged a number of communities in Rhode Island, Southern California, and New York to make the switch to electric school buses. Although electric buses can cost between $150,000 to $300,000 more than a conventional diesel-powered bus initially, replacing a diesel bus can ultimately help reduce operational costs by 60%.
More school districts are beginning to switch to electric vehicles, Herald Net
The invention of the vehicle grid has helped to drive those cost savings because bus batteries can be plugged into the grid, where they can be charged or where they can send energy back to the grid if the electrical utility needs more power. In addition to the direct cost-savings, electric buses can help to reduce air pollution with related health benefits. As one report put it, for electric buses, “the up-front investment, along with delivering students to school and home again, is delivering greater value; in better health for students and neighborhood residents as well as climate-saving reductions in greenhouse gas emissions.” That’s because gas-powered vehicles significantly increase health risks and switching to electric buses can yield “up to $247,600 in health and climate benefits for each bus, including reduced rates of adult mortality and childhood asthma.”
“[T]he up-front investment, along with delivering students to school and home again, is delivering greater value; in better health for students and neighborhood residents as well as climate-saving reductions in greenhouse gas emissions.”
Route mapping
Securing funding for electric buses is only one step, but new technologies and AI are also creating opportunities to increase efficiency through innovations in route mapping. One district in Colorado Springs teamed up with HopSkipDrive to test the company’s “RouteWise AI” program which aims to address bus driver shortages and reduce student absenteeism. The program has cut the number of bus routes in half and increased on-time arrival rates to 99%, saving the district $8 million over a decade.
Even the most efficient bus routes cannot solve every logistical problem, particularly in areas where buses are inaccessible or unavailable due to proximity limitations or driver shortages. In response to these limitations, many districts are shifting their focus toward encouraging safe alternative modes of transport to school. For instance, Hawai’i schools received an $8 million boost for school travel through the Safe Routes to Schools fund. The goal of the fund is to “get more kids out of cars and onto safe and comfortable pedestrian and bike paths within walking distance of their schools.” A lack of funds and limited availability of buses also led to an initiative at Detroit’s Davis Aerospace Technical High School to give students free bicycles for their commute to school. Donations from the community helped pay for the bikes, which helped to reduce chronic absenteeism and reduced the amount of time students had to spend walking to school or waiting for buses.
Junior Elyazar Holiday says having a bike helps him catch the buses he needs to ride to get to Davis Aerospace Technical High School. Here, he is pictured with his peers riding bikes in front of the school, Chalkbeat
“Bike buses,” consisting of groups of people who ride to or from school together, serve as another transportation related micro-innovation that can have multiple benefits. Michael Cohen, in a Washington Post article suggested the popularity of bike buses spread virally on social media when people in Barcelona posted videos of a “bicibus.” According to Cohen, numerous other communities have developed their own form of bike buses, and a variety of websites including Montclair (NJ) Bike Bus and Bike Bus World provide information and news for those in their local communities and offer specific guidelines to help others start their own versions. In addition to safety, switching from buses to bikes can also help to build relationships and social connections among students and parents, eliminating congestion, and reducing pollution.
Policy “roadmaps”
Beyond the buses and related technologies, policymakers are creating new policy “roadmaps” and “guidebooks” that provide a broader strategic framework that helps schools, districts, and municipalities to deal with their transportation needs. In 2023, New York became the first state to pass a school bus electrification mandate. To make the transition more tangible for schools, the New York State Energy Research and Development Authority (NYSERDA) released a bus roadmap and guidebook that details the key challenges, costs, funding and policies involved in the switch to electric buses. According to New York Governor Hochul, “our roadmap and guidebook will provide school districts and bus operators with the latest information to enhance their fleets with zero-emission buses through proper planning, purchasing, and financing.”
New York State’s Electric School Bus Road Map, NYSERDA
“[O]ur roadmap and guidebook will provide school districts and bus operators with the latest information to enhance their fleets with zero-emission buses through proper planning, purchasing, and financing.”
New York’s roadmap provides a blueprint for reaching sustainability targets and is a part of a much larger ongoing movement. In 2024, the Environmental Protection Agency posted updated emission standards that include guidelines for school buses. Under the 2021 Bipartisan Infrastructure Law, the EPA launched the Clean School Bus Program, a $5 billion, five-year grand program, to give schools the funding to purchase low- and zero-emission school buses. Although the Trump Administration has not provided additional funding, during the Biden Administration, nearly $2.7 billion was distributed, with 90% of the funds going directly to electric school buses.
Next week — How innovations in school facilities can address climate change and support learning: Sustainability, students and schooling (Part 3)
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Educators and education programs around the world are both developing new ways to make schooling more sustainable and creating new educational opportunities for students to learn about the world around them. To help take stock of these developments, in the first part of this 3-part series, Carter Hyde and Hannah Nguyen review some of the latest news and research that discusses how climate change affects student learning. Future posts will outline some of the new developments – or “micro-innovations” – in transportation and facilities that educators around the world are pursuing to support a more sustainable planet, cut costs and foster student learning and wellbeing.
How climate change can undermine student’s health and learning
Each year, schools face a host of climate-related risks that can have a wide range of effects on the health and learning of students. As the authors of a UNICEF report put it, many “schools and education systems are ill-equipped to protect students from the impacts of climate change, particularly in fragile contexts, and climate finance investments in education remain strikingly low.” Just as one example, worsening pollution levels can impact respiratory and cardiovascular conditions, affecting children’s overall health and contributing to absences from school. Illustrating the significant impact that reducing could have on children’s health, in the US, estimates suggest that replacing old buses through a federal rebate program increased attendance between 2012-2017 by 350,000 days and that replacing all buses produced before 2000 would add another 1.3 million school days.
“Schools and education systems are ill-equipped to protect students from the impacts of climate change, particularly in fragile contexts, and climate finance investments in education remain strikingly low.”
The costs of school disruptions have sparked a movement toward making schools climate resilient, particularly by improving transportation and infrastructure. More sustainable approaches to schooling can benefit not only students’ health but also help reduce costs that free up funds for other educational purposes. An analysis from the Boston Consulting Group illustrated how government actions on climate can save considerable money over time. As the report put it, “By investing a relatively small portion of GDP—less than 1%—into climate adaptation measures, it is possible to avoid much larger economic losses of up to 4% of GDP. Then, the remaining economic impact in a less-than-2°C scenario ranges from 4% to 6% of GDP.” Economically, even modest investments in climate adaptation can prevent much larger long-term losses.
Climate change costs and investments as a share of cumulative GDP until 2100 (%), BCG Analysis
Despite the available evidence, a focus on sustainability remains controversial in some countries. Countries, like Iran, Libya, and Yemenhave also refused to sign onto global accords—such as the Paris Agreement or United Nations Framework Convention on Climate Change—designed to support sustainability expressing concerns about sustainable practices negatively affecting their economies. In the US, in particular, the current administration has explicitly worked to remove policies and limit initiatives that aim to combat climate change or support more sustainable practices. The U.S. Department of Education’s recent decision to terminate the Green Ribbon Schools program is a prime example of the reduced funding. The 15-year-old program honored schools across the country for their implementation of environmental practices. The program’s termination came soon after the DOE concluded the National Blue Ribbon Schools Program, in which schools were honored for academic excellence.
International Education News 