Category Archives: artificial intelligence

The Emerging Affordances of Teacher-Directed Platforms, EdTech Tools, and Multimodal Assistants: AI, New Technologies and the Future of Assessment (Part 3)

Posted on July 8, 2026 by T Hatch | Leave a comment

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.

+++++++++++++++

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)

Can Online Platforms and Digital Tools Support More Student-Centered Learning? AI, New Technologies and the Future of Assessment (Part 2)

Posted on July 1, 2026 by T Hatch | Leave a comment

Can new developments in assessment support more student-centered learning? In the second part of this three-part series, Adelaida Kim summarizes how AI and other technologies already offer educators new ways to generate, administer, and analyze assessments, including more student-centered and competency-based assessments. Part one provided an overview of some of the uses of AI in both large-scale tests and classroom-based assessments. Part three will compare the strengths and weaknesses of the assessment capabilities of selected teacher-directed AI platforms, EdTech tools, and AI “assistants.” Part four will provide examples of “micro-innovations” that already demonstrate how AI and new technologies can assess and 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.

++++++++

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.

How Digital Portfolios Help Students Showcase Skills and Growth, *Eduction Week*

Learning management systems

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.

Notebook LLM using multiple sources to create assessments such as flashcards, quizzes, and student patterns. Ditch That Textbook, 2026

Implications?

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)

Reimagining Coaching and Teachers’ Time: Scanning the News for Innovations in Teachers’ Professional Learning (Part 2)

Posted on July 31, 2024 by T Hatch | Leave a comment

This week, IEN’s managing editor Sarah Etzel continues a scan of recent news articles and research on post-pandemic developments in the teaching profession. In part two of the post, Etzel describes some of the initiatives to use technology to help to free-up time for teachers by reorganizing staffing and scheduling. Part one explored innovations in blended and remote teacher professional development models and the use of AI to provide feedback to teachers.

What’s happened to teachers in the wake of the COVID-19 pandemic? On the one hand, in the US teacher vacancies appear to have grown substantially. One report released in the fall of 2023 showed 55,000 vacant teaching positions, an increase from 36,000 the previous year. On top of that, the report found that 270,000 teachers – almost 9% of the entire teaching force – are “underqualified,” either lacking full certification or teaching in a subject in which they are not certified. The National Center for Education Statistics also revealed that 86% of K-12 schools reported problems hiring new teachers in advance of the 2023-24 school year, and almost half of all public schools describing themselves as “understaffed.” On the other hand, the pandemic helped to stimulate experiments with new models for staffing and with virtual teachers that might help to address teacher shortages.

Staffing Changes: Unconventional Teaching Roles

Whether in-person or virtual, a small set of schools and organizations around the US are exploring what alternative teaching and staffing models for schools could look like. A report from FutureEd focusing on pandemic-inspired staffing strategies, for example, highlights the benefits of some co-teaching, team teaching, and mentor teaching models. Public Impact, working with a network of over 300 schools, has pioneered models designed to use teacher teams to enable teachers who have shown their effectiveness to reach more students. These “multi-classroom” leaders teach part-time and also lead small, collaborative teams of other teachers, paraprofessionals, and intern teachers in the same grade or subject. Cadence extends the reach of effective teachers by developing a national team of mentor teachers who deliver online lessons for a group of partner schools across the US. The teachers in the partner schools both learn from the mentor models and they can incorporate the lessons into the work with their own students. As Steven Wilson, a co-founder of Cadence, puts it: “It’s like being able to sit in the back of the room of the best teacher in the building for weeks at a time and see his or her moves and adapt them and make them your own.”

The FutureED report also emphasizes the potential of flexible class sizes, time blocks, and instructional cycles that allow for teachers to work with smaller groups of students outside of traditional grade-level and schedule constraints. As an example, the report highlights a particularly unusual approach from Kairos Academies in St. Louis that developed a seven-week schedule in which students attend school for five weeks, followed by two weeks off; staff have one week off, but use the other week to review data and plan for the next cycle. The report quotes, Gavin Schiffres, Kairos founder and CEO, describing what he sees as the advantages of the cycles; “With the cycle model, we operate in sprints, much like the technology industry. In a traditional calendar, you have kids in the building for such long stretches that as soon as there’s a break, everyone just wants to crash.”

“We operate in sprints, much like the technology industry. In a traditional calendar, you have kids in the building for such long stretches that as soon as there’s a break, everyone just wants to crash.”

Drawing on interviews with a small group of leaders from six districts involved in staffing experiments, the Center on Reinventing Public Education issued a report on how unconventional teaching roles could help to make the profession more sustainable and increase teacher satisfaction in the process. Some of these roles include:

Lead teacher: An individual who mentors a team of teachers (across content areas or grade levels) by developing curricula and co-teaching as necessary
Empowered teacher: An individual who supports with school-level policies and sets learning targets
Team teacher: An individual who teaches a large group of students (50-80) in collaboration with two to four other teachers
Community learning guide: An individual who works with a group of educators and their students to create experiences grounded in students’ wider environment, community, or culture.
Solo learning guide: An individual who independently teaches a small group students (5-15) in school or home contexts
Technical guide: An individual who leverages subject area expertise (e.g. robotics, architecture) to provide curriculum support and work with small groups of students

According to the report, teachers in these roles shared that they experienced less stress and felt more motivated; working in diverse or team settings, teachers were able to share responsibilities, learn from each other, and feel connected to the purpose of teaching. Despite the potential, a review of the CRPE report from the National Education Policy Center cautions that it is too early to tell whether these kinds of staffing changes could be scaled effectively or whether they would have the desired impact.

In order to address the shortage of teachers and support those that are in place, some schools in the US have also introduced models to support paraprofessionals to gain teaching credentials and become licensed teachers, while others have created pipelines for substitute teachers to gain teacher certifications. Beyond the US, organizations such as GPE KIX and UNICEF have been pioneering child-to-child teaching models, in which older students support the education of pre-primary learners, in areas where there are not enough teachers available (for past IEN coverage of peer-to-peer tutoring approaches, see: Education reform in Mexico, An interview with Dr. Santiago Rincón-Gallardo, and Bringing Effective Instructional Innovation to Scale through Social Movement in Mexico and Colombia).

Virtual teachers for in-person students

Along with developing new virtual and hybrid approaches for students to learn, during and after the pandemic, reports also note that some districts are spending millions of dollars on virtual teachers to fill-in when they can’t find the personnel they need in their local area. Among these, districts in Little Rock, Arkansas, Charleston County, South Carolina, San Jose, California, and Milwaukee Wisconsin have contracted with companies such as Elevate K-12, Coursemojo, and Proximity Learning to address their teacher vacancies and to provide virtual instructors who zoom into their classes. These companies employ fully certified virtual teachers who provide “synchronized learning services” in a range of subjects. The virtual teachers interact with students completely through the online platforms, with, in some cases, in-person supervision provided by paraprofessionals or long-term substitute teachers.

Elevate-K12’s model of “live teaching”, The 74

The benefits and drawbacks of these approaches are also being debated in the press. For some, these virtual options provide an alternative to other “quick fix” solutions that have been used to fill empty classrooms in the past, including hiring uncertified teachers, incentivizing military veterans to join the teaching force, or removing some degree requirements. According to the CEO of a San Jose charter school network that contracts with Coursemojo, this situation is not ideal, “but until we really, radically change the education profession here in the United States, we’re going to be looking at solutions like this.” Catherine Schumacher, Executive Director of Public Education Partners stated the importance of not shaming “districts for doing the absolute best they can do to get qualified teachers,” especially in a climate where “we have systematically underpaid…educators for years.”

Other advocates argue that the subjects virtual teachers are teaching have historically been hard to fill, meaning many students did not have access to these educational opportunities, particularly in low-resource school districts. As the Milwaukee Public Schools talent management director put it: “when we talk equity and access, I want to ensure that if my students want to take pre-calc, if they want chemistry, if they want physics, that they have the opportunity to do so.”

The cost-effectiveness of the virtual models also remains in question. For one school district in Milwaukee, Wisconsin, a contract with Elevate-K12 helped them fill 55 open positions at a cost of about $3.9 million, a savings from the $5 million it would have cost to hire that many in-person teachers. A district representative reported that they were able to save the $1.1 million because they did not have to provide benefits for Elevate K-12 teachers. In contrast, a school district in Charleston County, South Carolina that has used the virtual learning platform, Proximity found that these models were more expensive, as the schools needed to hire paraprofessionals to watch the students during the virtual classes.

Critics point to the fact that there is not yet enough evidence to show that students are achieving positive learning outcomes under these models, but proponents such as Elevate K-12 founder Shaily Baranwal, argue that virtual teaching during Covid-19 took place under emergency circumstances and, with more time to prepare and focus on delivery methods, post-pandemic virtual teaching could be particularly effective. Critics also question whether students’ social experiences and sense of belonging will suffer when they have virtual teachers, and some wonder who will be held accountable for student learning under blended learning models (i.e. the paraprofessionals who are in class every day with the students, or the virtual teachers?). With all these uncertainties, many parents remain skeptical of this virtual solution and question whether virtual teaching will be the best fit for their children.

The bottom line? Freeing up time to teach?

At the end of the day, the success of any of these “innovations” in professional learning depends on whether they can be put in place without adding to teachers already overloaded schedules and extensive set of responsibilities. Post-pandemic articles continue to highlight challenges like a lack of planning time for teachers and excessive time spent in staff meetings as well as hopes that AI may help address these issues by freeing up teachers’ teachers time from administrative tasks and helping teachers create differentiated assignments. Through a survey of 368 school-based employees across the U.S., AI-Equity found that 84% of those who used AI in the Daily/Weekly category reported they were “more excited about continuing education sector work because of AI,” compared to 52% of all respondents, while 94% of Daily/Weekly AI users shared that it made them more productive. According to research from MIT, AI can improve the performance of skilled workers in fields such as consulting by approximately 40%. A report from McKinsey and Co. estimates that teachers could free up 20-30% of their time by using AI and other technologies to support activities such as preparation, conducting evaluations and giving feedback, administrative duties, and professional development. The Christensen Institute argues that teachers may not use their reallocated time for increased student engagement without proper incentives, but freeing up teachers’ time could help to alleviate burnout and increase the attractiveness of the profession.

How artificial intelligence will impact K-12 teachers, McKinsey

However, sources also caution that AI should not be viewed as a panacea for solving these issues, and in fact, may exacerbate some of the challenges that teachers face. As one teacher explained, the expectations developing lessons incorporating AI and other forms of technology “takes extreme planning, and that, we don’t have time for anymore.” Moreover, the increasing use of AI raises numerous questions about the potential impact on students’ learning and development. In particular, as Julia Freeland Fisher cautions, the education market doesn’t prioritize relationship building within its attainment metrics and so may fail to take into account AI’s impact on those relationships. Under those conditions, as Freeland Fisher put it, “the more commonplace that AI companions, coaches, and anthropomorphized bots in learning and support models are, the more fragile students’ social connectedness may become.”