---
id: "workshop:writing-smarter-with-ai-digital-assistants-for-enhanced-reading-and-writing"
type: "InnovateUS workshop"
title: "Writing Smarter with AI: Digital Assistants for Enhanced Reading and Writing"
url: "https://innovate-us.org/writing-smarter-with-ai-digital-assistants-for-enhanced-reading-and-writing"
date: "2025-01-22"
duration: "60 minutes"
language: "English"
series: "AI for Literacy Achievement"
instructors: ["Perpetual Baffour"]
recording: "https://www.youtube.com/watch?v=LclJWgR8KZA"
transcript: "automatic, from the recording"
source: "InnovateUS (innovate-us.org)"
licence: "CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/), as stated on innovate-us.org"
---

# Writing Smarter with AI: Digital Assistants for Enhanced Reading and Writing

InnovateUS workshop · 22 January 2025 · 60 minutes

AI writing tools have advanced far beyond simple spelling and grammar correction, now offering personalized feedback, real-time insights, and curriculum-aligned resources. These digital assistants can provide dynamic, interactive support to strengthen reading and writing comprehension through adaptive learning experiences. In this workshop, participants will: 1) discover the evolution of AI writing assistants and the latest trends shaping the field, 2) explore key research questions and future directions for digital writing assistants, 3) dive deep into popular AI writing tools to analyze their potential for personalized feedback and student support, and 4) engage in a hands-on activity designed to demonstrate how AI tools can empower educators to assess writing skills, identify areas for growth, and foster stronger comprehension.

## Learning goals

- Discover the evolution of AI writing assistants and the latest trends shaping the field
- Explore key research questions and future directions for digital writing assistants
- Dive deep into popular AI writing tools to analyze their potential for personalized feedback and student support
- Engage in a hands-on activity designed to demonstrate how AI tools can empower educators to assess writing skills, identify areas for growth, and foster stronger comprehension.

## Speakers

- **Perpetual Baffour**, Research Director, The Learning Agency

Part of the series [AI for Literacy Achievement](https://innovate-us.org/workshop-series/ai-for-literacy-achievement).

Recording: https://www.youtube.com/watch?v=LclJWgR8KZA

## Transcript

Automatic transcript of the recording: names and terms can be misheard, and the times can be a few seconds off. Each time links to that moment of the video. The transcript alone: https://innovate-us.org/writing-smarter-with-ai-digital-assistants-for-enhanced-reading-and-writing.txt (plain text) and https://innovate-us.org/writing-smarter-with-ai-digital-assistants-for-enhanced-reading-and-writing.json (every segment with its start and end second).

**David Fields**

[0:02](https://youtu.be/LclJWgR8KZA?t=2) I'm sure people will continue to join, but I want to respect our time here and get us going. Thank you for joining us for the first workshop of Rethinking Reading, AI for Literacy Achievement. This is a new InnovateUS series sponsored by the Burns Center for Social Change's Equitable Literacy Initiative and led by our partners at the Learning Agency. In this series, we'll showcase how innovative leaders are using AI to make rapid gains in advancing literacy in today's classrooms. You can find the full schedule and register for all the upcoming workshops at innovate-us.org at literacy. We'll put that in the link for you. My name is David Fields, and I'm a senior fellow here at the Burns Center for Social Change at Northeastern University. And the Burns Center designs and implements practical solutions to society's hardest problems. We develop innovative, participatory, and equitable approaches to solve problems using new technologies.

[1:04](https://youtu.be/LclJWgR8KZA?t=64) For those of you not yet familiar with InnovateUS, this is a program out of the Burns Center. And I encourage you to visit innovate-us.org and check out hundreds of free 60-minute workshops that are at your own pace. We've got courses in AI and digital skills designed for public sector professionals. So now I'm thrilled to hand it over to Perpetual Baffour. She's research director at the Learning Agency. She's going to lead this first workshop on AI tools for enhanced reading and writing. Perpetual brings experience in machine learning, data analytics, and education research. And previously, she was data analyst for the Office of Evaluation, Research, and Accountability at the School District of Philadelphia. And she's served as research associate at the Center for American Progress. And she's an Emerson Fellow of National Policy for the University of Pennsylvania's Netter Center for Community Partnerships.

[2:05](https://youtu.be/LclJWgR8KZA?t=125) Perpetual was recently selected as one of Worth Magazine's Worthy 100, which is a distinction honoring 100 people making an impact across various industries and sectors. So without further ado, Perpetual, I turn it to you.

**Bonnie McGilpin**

[2:29](https://youtu.be/LclJWgR8KZA?t=149) You're on mute, Perpetual.

**Perpetual Baffour**

[2:46](https://youtu.be/LclJWgR8KZA?t=166) Thank you so much, David. I'm really excited to be connecting with you all in this workshop series. And hi, everyone. As David mentioned, we're excited to talk about the possibilities and opportunities for AI in promoting literacy outcomes. I'm going to share my screen because I do have a slide deck that I'm hoping will help facilitate this conversation. So I'm going to go ahead and share my screen. I hope you all can see my screen. I'll keep moving. It seems like we all can. And so, as David mentioned, this is a workshop series in which we'll be talking about the opportunities for AI in literacy tools and literacy intervention strategies. But we'll be approaching it from slightly different angles in each workshop. This first one we're using to kick off the series is going to hone in on the specific tool of writing assistance. So what are some ways in which AI-powered writing assistance can be used to help students improve their reading comprehension and their writing proficiency in tools and platforms that are using AI in a way that is rooted in evidence-based writing instruction and research-based practices?

[3:55](https://youtu.be/LclJWgR8KZA?t=235) And this is really important for us to emphasize because we're not promoting AI simply because it's the new brand new shiny toy in the room. We want to make sure that it's really being used in a way that's thoughtful, strategic, and coherent with current frameworks in place in classrooms that are driving evidence-based outcomes. So overall, I'm really excited to be working at the Learning Agency and in partnership with the Byrne Center and Innovate US in this workshop series. Our hope is that you'll take away actionable information on how to explore and implement AI literacy tools, how to create personalized reading intervention strategies, and design inclusive literacy programs. In this specific workshop, we're diving into AI writing tools because they've come a long way and we'll talk about that a little bit later. We're hoping over the course of this next hour, you'll be able to understand just a deep dive into what are the current trends, what are the current tools, who are the key players, what are the key research questions, what are future promising directions of AI writing tools.

[5:02](https://youtu.be/LclJWgR8KZA?t=302) And after having this sort of bird's eye view on the lay of the land, we're going to dive deeply and spotlight two specific tools so you get a little bit more of a practical understanding how AI powered writing assistance can be experienced by a student, by a teacher, and also by an education leader. I believe most of you are state or district education leaders or highly influential in your communities, and so we're hoping to also set aside some time for a hands-on interactive activity where we can get a little bit more precise and detailed and practical about how these platforms can improve your work and enhance the way you're able to not only understand AI, but leverage it for positive learning outcomes. So let's first take a step back to kind of set the tone for the conversation and let's consider the evolution of AI in writing assistance. Because we have come quite a long way, AI has really come a long way from being these simple rules-based systems and very basic computer algorithms.

[6:04](https://youtu.be/LclJWgR8KZA?t=364) When it comes to AI writing tools in particular, they have advanced from very simple spell checkers and grammar correction tools to now these highly sophisticated language generating models that can engage in naturalistic human-like conversation. And as you can imagine, that widens the possibilities and the opportunities for AI in writing assistant tools. So if you look at this timeline here and thinking about the history and how far we've come, in the 1950s and 70s, as modern computers were being invented, the idea of an AI writing assistant was very simple. Check grammar, check spelling, using simple rules, if then conditional statements, or a dictionary with the correct spellings of words. But then as personal computers became more modern, became more accessible to the everyday consumer in the 80s and the 90s, now you have these word processing packages, like WordPerfect, where now the everyday consumer has access to a tool that can improve spelling and improve grammar.

[7:09](https://youtu.be/LclJWgR8KZA?t=429) So accessibility increases, but not necessarily sophistication. That is until we get into the 2000s. And due to one of, I think, one of the groundbreaking advancements in AI, which is through this idea of deep learning. So here, due to advancements in software and in hardware, we're now able to take a computer and train it on vast amounts of data in a relatively quick amount of time to perform complex tasks. And we're able to do it by allowing the computer to process and learn information as if it had a human brain. And that's through the concept of neural networks. So deep learning and neural networks revolutionized machine learning in the 2000s. Due to advancements in the resources, the hardware, and the algorithms, now we can train computer machines to do more intelligent things. And as you can imagine, this paves the path for more advanced writing assistance.

[8:09](https://youtu.be/LclJWgR8KZA?t=489) For instance, in 2010, Grammarly emerges on the scene and launches its own AI-powered tool for advanced grammar and style suggestions. You also have other products like Hemingway Editor that emerges in 2015. Now we're in the 2020s, and the rate of growth or advancement in AI is increasing, some might argue, exponentially. Because, again, these advancements in large language models, these computers being able to hold a vast amount of information on human language, how they communicate, what are the relationships between these words, what are the patterns between these words, what is the context in this communication? That increases a lot of the capabilities of large language models to not only understand language, but also generate language as well. As you might know, AI has become more mainstream due to generative language models like a GPT or a Gemini.

[9:10](https://youtu.be/LclJWgR8KZA?t=550) And so these advancements have been trickled into the scope of writing assistance because now they can offer more comprehensive content generation and editing. So who are some of the key players in the field? Two of the big ones, I've mentioned one so far, Grammarly and OpenAI. So these two organizations or entities alone have about a 15% market share in AI writing assistance software. But if we're considering key trends when it comes to what these key players or developers are focusing on, they're leveraging these advancements in language generating models that now have a better contextual understanding of language and are now also able to generate language to be able to build writing assistance that can generate feedback. One of the key evidence-based practices in writing instruction is having timely, actionable, and specific feedback. And these key players are tapping into that by using these advanced machine learning algorithms to provide specifics to suggestions on grammar and style.

[10:17](https://youtu.be/LclJWgR8KZA?t=617) They're also tapping into other innovations in the AI scope. One of the biggest areas in AI research is this idea of summarization. How well can an AI algorithm summarize a text? And so they're leveraging that within AI writing assistance, using its ability to generate content and summarize text to provide more accurate and meaningful feedback to students on their literacy. They're also tapping into domain-specific writing as well. So how do you adapt feedback when a student is writing an essay in a social studies classroom as opposed to, let's say, a science classroom or the traditional English language arts classroom? So overall, what we're really seeing is that these key players are taking a strategic approach to stay competitive by tapping into the latest capabilities of generative language models. I put Khan Academy and CommonLit here because they are also two other popular platforms, specifically when it comes to high school ELA educators.

[11:21](https://youtu.be/LclJWgR8KZA?t=681) They are also looking into how can we use AI within our platforms. I'm going to talk about Khan Academy a little bit more later. But they're investigating, you know, we serve millions of students. How can we leverage AI? How can we leverage predictive AI? How can we leverage generative AI within this platform since we have a large student base and since we know we're already designing our curriculum and our instruction to be based in research? How can we thoughtfully integrate AI? So it's not just an add-on or a plug-in, but it's baked into their evidence-based approaches. Now, what are some of the key research questions? If we're thinking about using AI thoughtfully in literacy tools and literacy interventions, and we want to make sure that they're helping students and not harming students, we'll put on the slide here six key areas of research that will ensure we have future promising directions in AI-powered writing assistants. One of them is advancing this area of AI called natural language processing, or NLP for short.

[12:24](https://youtu.be/LclJWgR8KZA?t=744) That's the subdomain of AI that's specifically focused on how AI can process, reason, and generate human language, naturalistic language, right? And so if NLP is going to increasingly get more advanced, like we see in models like ChatGPT or Gemini, how do we make sure that those advancements can be applicable and useful in an education domain as well? Another key area is human-AI collaboration. Many of us, although there might be some difference of opinion, but many of us believe that AI cannot replace teachers, but it can support them. It can be a helper. It can complement them in their instructional practices. But what is the right form of collaboration? What is the appropriate dynamic between a human teacher and an AI agent when it comes to assessing students' reading comprehension and writing? Is it the teacher working with AI input, or is it the AI working with human input?

[13:28](https://youtu.be/LclJWgR8KZA?t=808) What is the order of operations there? There are a lot of research studies that are looking into that, trying to see what is the best ecosystem in which a human teacher can work in using AI so it's actually increasing efficiency and increasing productivity, rather than being something that's another task or another burden placed on teachers. Then we look into this research area of domain-specific assistance. There are a lot of large language models that are very generalized, but there's a risk they're also too generic, meaning while they can perform somewhat decent overall, they're not super great at any specific thing. So we want to look at domain-specific writing assistance that can tap into different subjects or can tap into different student populations. One of the key evidence-based practices in writing instruction is in integrating writing across the curriculum, across social studies, across history, across civics, across science.

[14:28](https://youtu.be/LclJWgR8KZA?t=868) So how do we, and researchers are looking into this, adapt AI and customize it for these different domains within writing? Design and personalization. So this is thinking about how can we create the user experience or how do we design the user experience or the user interface so that the user is placed at the center? It's a student-centered experience, it's a teacher-centered experience, and there's a lot more personalization happening. Another key evidence-based practice is personalization. Making sure that there is tailored instruction and tailored feedback. So, this is another key area of research. The last two I will mention. Multimodal capabilities. In my personal opinion, multimodal models, and so these are thinking about models that can work with multiple modes of data, text, images, audio, video, to me, this is the most exciting direction of AI, because it becomes a much more immersive experience for the user.

[15:30](https://youtu.be/LclJWgR8KZA?t=930) So what are some ways in which we can take these AI writing assistants, which primarily focus on dealing with text, which makes sense intuitively, right? With writing essays, they are text-based products, but what are some ways in which we can incorporate audio, video, maybe even images, so that these AI writing assistants can be an immersive experience for students and can also provide even more personalized or even equitable And then lastly, ethics and fairness. writing instruction? So this is looking at how do we ensure these AI systems are helping students and not harming them, particularly the ones who are the most vulnerable or marginalized. If we're thinking about achievement gaps, if we're thinking about specific populations like English language learners, there are research studies that are looking into issues of fairness and bias. Is this AI algorithm better with one student population than the other? If so, that's problematic, and we need to look into that.

[16:31](https://youtu.be/LclJWgR8KZA?t=991) So overall, these key questions are spanning a number of areas to make sure these writing assistants are inclusive and effective for teachers and students. I mentioned earlier, I work at the Learning Agency, and when it comes to our lens, our voice, or our approach to this issue of AI writing assistants, we are very much pro-AI, especially when it's used in a way to support teachers and improve the student learning And one of our strategic approaches to advancing the opportunities of AI in writing assistant experience. tools is through supporting the open data movement or an open access movement. What that means is we are very eager to release open datasets on student writing that can be used not only by researchers and technologists, but also be used to benchmark the performance of popular models when it comes to writing evaluation. So so far, we have released a number of student writing datasets, and we have run about eight specific competitions, and where based on this dataset, the challenge is for data scientists and machine learning experts to train the best AI algorithm on this dataset for specific aspects of writing evaluation.

[17:50](https://youtu.be/LclJWgR8KZA?t=1070) One of the key evidence-based practices we see in writing instruction, for example, is teaching writing as a process, right? And so one of our datasets is a dataset on the writing process. What key strokes were students making as they were constructing the essay? And training an AI algorithm that not only understands the final product, but also understands the writing process. We also have released other datasets in which the data, the student essay was labeled for different organizational elements, like the thesis or the supporting claim, which allows the AI algorithm to not just provide a generic score, but be able to have explicit instruction and explicit feedback on specific writing skills, like thesis development or evidence integration. So in releasing these benchmark datasets, these educational essay collections that allow AI algorithms to perform tasks that are aligned with research-based practices, we are excited to promote these algorithms and promote these datasets.

[18:51](https://youtu.be/LclJWgR8KZA?t=1131) So far, we have partnered with, collaborated, or attracted interest from over 10 vendors in using our dataset and algorithms. Google is one example. I'll mention this a little bit later, but Google is also looking into their own Gemini powered writing assistant tool. And we've been fortunate to work with them and share our data and algorithms for that purpose. We also want to make sure that as more folks are getting excited about these models, like a chat GPT or a Gemini, that they're actually doing well in the task we want them to do well in. And so we're going to be doing more benchmarking, which is basically just evaluating these models for how well it can actually provide quality feedback on essays. Really quickly, I want to do a quick overview on what Big Tech is doing. What are they saying about AI writing assistants, or what are they pursuing or exploring? At a high level, Big Tech companies are building these super large general foundation models that they're hoping can perform well at a number of tasks.

[19:57](https://youtu.be/LclJWgR8KZA?t=1197) Education isn't their number one priority, but we have noticed it is becoming an increasing investment for them. And so we have noticed there are some trends or some patterns in how these Big Tech companies are developing AI writing assistants for the education market. I mentioned earlier, Google is highly invested in building out more products and building out Gemini and using AI for classroom purposes and in writing assistant tools. Microsoft has the Teacher Copilot, also has 365 Education, and where they're leveraging AI-powered features for grammar and spelling checks, sentence suggestions, and even the ability to summarize text. Amazon is also looking to provide a range of AI and ML services that can be leveraged by educational institutions for developing custom AI writing assistants or integrating AI into existing learning platforms. So Big Tech companies are definitely trying to put their hat in the ring.

[21:00](https://youtu.be/LclJWgR8KZA?t=1260) But I will say that when it comes to AI tools that can provide very specific, thoughtfully designed, and intentioned feedback on student writing, we can't discount the value of Ed So now I'm going to spotlight two in particular. Tech products. The first is Conmigo Writing Coach. We thought it would be great to highlight Conmigo's Writing Coach as an example because it is affiliated with Khan Academy, one of the biggest platforms in the K-12 space. So Conmigo Writing Coach is a new tool that's being rolled out. The current Writing Coach is only available for the student experience, but there is a wait list for the teacher or the educator experience quite soon. And so I'm going to quickly describe what this Writing Coach will offer for teachers. So they're using AI, once again, to align with research on effective writing instruction. And some of the ways they're doing that real-time feedback, as we mentioned, is an advantage of AI, getting that immediate and precise feedback for students without having to wait too long for teacher evaluation or reporting.

[22:08](https://youtu.be/LclJWgR8KZA?t=1328) The coach will also provide suggestions on structure, clarity, and grammar. And they're also aiming to foster inclusivity by offering feedback that is encouraging and growth-oriented. So their aim is that the tool is responsive to diverse learning needs. Now, to talk a little bit more about what are the advantages, because I'm sure some of you might know, there are so many edtech tools on the market, so many edtech products. What is really different with AI now? As I mentioned before, real-time feedback is a huge one. But if we're also talking about teaching writing as a process, AI can be a key lever in this space. And so the Conmigo Writing Coach has their AI able to walk students through iterative revisions, from brainstorming to drafting to feedback phases and revisions. So rather than a teacher having to review 50 different draft histories from a student, the AI can do this in real-time, which saves the teacher a lot of time as well.

[23:15](https://youtu.be/LclJWgR8KZA?t=1395) Because the AI is already allowed to provide real-time feedback and data, that allows for Also, detailed reporting. more detailed reporting for the teacher. And so one of the evidence-based practices is having real-time progress and monitoring on student performance, right? And AI-powered tools can help in this respect as well. Next, I want to dive into Quill.org. And this will actually be the focus of our hands-on activity as well. But Quill.org is actually a pioneer in AI-powered writing assistance. So they were long in the AI game before it became mainstream, before it became like the hot new thing on the market. But they are still prioritizing AI and leveraging the latest advancements to continue to enhance I'm sure many of you are probably familiar with Quill. their technology. I'm sure many of you are probably familiar with Quill as they serve millions of students. But if not, I'll give a quick recap. This is a platform that uses AI to deliver tailored feedback to students.

[24:16](https://youtu.be/LclJWgR8KZA?t=1456) And it's this personalization that helps students with diverse learning needs progress at their own pace, which is a critical feature for making education accessible to students with varying skill levels. So if we're thinking about equity, if we're thinking about closing achievement gaps, AI-powered tools that are thoughtfully designed to respond to diverse learning needs or to target vulnerable populations can help achieve this goal. Quill offers six different learning tools that use AI to provide immediate and custom feedback to students. So Quill Connect is focused on the specific writing skill sentence construction, excuse me, so helping students to compose complex and well-structured sentences. Quill Lessons enables teachers to basically facilitate whole class and small group writing instruction, which aligns with the evidence-based practice of allowing students to engage, reflect on their writing, and collaborate with peers.

[25:16](https://youtu.be/LclJWgR8KZA?t=1516) Quill Diagnostic is really the first step. It is the tool that allows the platform to identify specific student needs, their learning areas, and then it personalized learning plans for that student. So Quill is an adaptive platform, which is also key when we're thinking about AI-powered tools. Quill Proofreader focuses on the specific writing skill of editing. So students edit passages and then receive personalized exercises based on their results. Quill Grammar, that's focusing on very basic grammar skills from comma placement to parallel structure. And then finally, Quill Reading for Evidence, this is their latest tool, which is leveraging generative AI, so the latest technology in generative feedback, to help students in the So if you read a text, are you able to then support a specific claim or write a specific skill of evidence integration.

[26:18](https://youtu.be/LclJWgR8KZA?t=1578) argument using evidence that's sourced from the text? Now, I'm going to move on to a hands-on activity. We will share the link in the chat. Quill offers a demo account with sample student data that allows an educator to get a feel, sort of a simulative experience of how it could be useful for them. So I'm going to quickly stop sharing my screen, just so I can open the other window. I'll also note, no worries. I might be moving rather quickly as we move through this demo. And I just want to, or maybe I can enter in the chat. It's quill.org slash demo. So I'm going to share my screen. And we can get started.

[27:21](https://youtu.be/LclJWgR8KZA?t=1641) I hope you all can see my screen. So when you click that link, you'll see here, this is the main view for a teacher. It's a real-time data dashboard on students' performance across different Quill activities. So Quill has over 900 activities. They're structured to take about 10 to 15 minutes each. And they're able to capture a lot of data for students at an individual level and also as a classroom level. I thought it might be helpful to spend a few minutes, maybe just running through a couple of sample activities, just so those who aren't familiar get a feel for the activity. Now, when I click on the link, it's going to open to a new tab. So I hope you will still be able to see my screen when I do so. Let's start with Quill Diagnostics. I'm going to go here. This is the first step to create that personalized learning plan. So here we see, this is a diagnostic that covers fundamental areas of sentence structure.

[28:26](https://youtu.be/LclJWgR8KZA?t=1706) So it's allowing the platform to understand a student's ability to create both basic and advanced sentences. So I'm going to click try a sample activity here. Can you all see the baseline diagnostic on the screen? Or do you? Okay, so it looks like it does work even when it opens a new tab. Okay, awesome. Now, we don't have enough time to complete the entire diagnostic, but I'm just going to click on a few questions just to give you a sense of the skills that they're covering. And so they're going to look at different things when it comes to sentence structure, both basic and advanced sentences. Some are going to look at subject verb agreement. Some are going to look at other issues when it comes to grammar and mechanics. But at a high level, this diagnostic sets the path for a personalized learning plan for a student. I also want to mention that Quill has developed a specific diagnostic for English language learners that they've aligned with the WIDA standards to make sure that the diagnostic is valid.

[29:32](https://youtu.be/LclJWgR8KZA?t=1772) I don't have enough time to kind of go over all of those details, but I'm going to quickly Can you all see me hovering over this menu option that says Teacher Center? toggle back here. So Teacher Center is their library. They have published so many resources, guides, videos, walkthroughs, video tutorials, and research reports showing how They've been able to increase learning outcomes for English language learners and how they've aligned their AI with evidence-based practices. So this demo is just to give you a slice. If you want more information, I highly recommend you check out the Teacher Center. So the Quill Diagnostic sets the path for the personalized learning plans. If we look at one of the other learning tools super quickly, let's try Quill Connect. You might remember this is the tool that focuses on combining sentences, composing complex and well-structured sentences.

[30:36](https://youtu.be/LclJWgR8KZA?t=1836) Let's try a sample activity. I'm going to click on Try a Sample Activity here. And here we'll be able to get a sense of the type of feedback a student would receive from the underlying AI model. So in this example, we have to combine these sentences into one sentence. I'm going to purposefully give an incorrect response. I do believe I have basic skills in sentence structure, but for demonstration purposes, I'm going to give an inaccurate response. I'm going to combine these sentences with commas, but without conjunctions. And let's see what we get. So if I click Get Feedback. Okay, we get one piece of feedback, which says, put powerful in front of the word it describes to make your sentence shorter and more concise, right?

[31:36](https://youtu.be/LclJWgR8KZA?t=1896) And so it's giving different suggestions or feedback recommendations to improve it, right? And so that's just one example. Now, there are many other tools as well, but we unfortunately don't have time to cover them all. But what I want to do next is talk a little bit more about the teacher perspective. So for the teacher, what is the advantage? So I mentioned before, real-time data and progress monitoring is really key when it comes to teachers being able to leverage AI for time savings and for detailed analytics to track individual and classroom-level progress. So if I go back to the main view of the demo account, and if I scroll down here, or actually, if I scroll up, I'm going to go to Activity Analysis. And this provides classroom-level reports on each activity.

[32:37](https://youtu.be/LclJWgR8KZA?t=1957) And so with each activity, you're able to see students' completion rates, the average scores, how much time they spent on average on each question. And so the data is aggregated to provide analytics and data points at a larger level. But if you want to get even more detailed reporting, for instance, let's say I take a look at this activity, capitalizing dates, holidays, and seasons. It will show individual performance on each activity. So you're able to move from the aggregate level to an individual level to see score, time spent, questions, and average score, which is important. So if I scroll down here, I'm going to scroll down here, I'm going to scroll down I will say, Quill does provide free access, but they also have a premium offering as well. They provide free access, but they also have a premium offering as well, which just has more expansive offerings in terms of detailed reporting and capabilities for the teacher.

[33:42](https://youtu.be/LclJWgR8KZA?t=2022) So just want to flag that as well. If I toggle back to the Activity Summary page, you'll see here, for each individual, they have a square in which the color represents the proficiency level, the icon represents the specific learning tool it's associated with, and then you're able to see what activities the student actually completed. So that's a quick overview of the teacher perspective. Now for the next part of the interactive activity, we're going to take it one level higher. We're going to think about, let's say you were a school leader or a district leader or state leader, and you're thinking about intervention plans and strategies that can incorporate more AI in the approach. What I'm going to do is I'm going to throw out a couple of hypothetical scenarios. And we're going to spend some time just kind of brainstorming what are some ways in which we could leverage a tool like Quill in that intervention plan or in the implementation.

[34:46](https://youtu.be/LclJWgR8KZA?t=2086) So I'm going to read the scenario. The question is, what is the AI-integrated approach we can consider? Based on what we've learned about Quill, how could Quill be useful in this respect? Just to give us some ideas or plant some seeds about integrating AI into intervention strategies. So here's the first scenario. So let's say a school district is piloting an afterschool intervention program for middle school students who are below grade level in writing. So I'll stop sharing my screen just so I can also have a chance to look at the chat. But let's say there are school districts that are piloting an afterschool intervention program for middle school students below grade level in writing. I'll also quickly mention Quill does serve grades 4 through 12. What are some ways in which an AI-integrated approach could be leveraged in this afterschool intervention program?

[35:48](https://youtu.be/LclJWgR8KZA?t=2148) And can we cite some specific examples from the Quill tool? So feel free to type into the chat your thoughts here. So there's an afterschool intervention program for middle school students who are below grade level in writing. Maybe for this first one, I can give a quick assist. So the first idea that comes to mind is to use the Quill Diagnostic as the first step. So using the Quill Diagnostic assessments to identify specific grammar or syntax weaknesses. And so for that afterschool intervention program, we're able to hone in on why these students are below grade level. And then Quill is able to provide explicit instruction on those specific writing skills, as well as provide personalized practice tasks.

[36:55](https://youtu.be/LclJWgR8KZA?t=2215) And then district leaders can track aggregate progress through the platform's analytics. I see here Jacqueline says, to help personalize writing instruction, exactly. Victoria says, specific practice opportunities, the data can be used to support preparing and also communication with the general teacher. And she meant, or Victoria also says, the example you provided would be a good example of why a roving teacher will be needed to help students use the feedback. Thank you so much, Victoria. And my apologies, I don't want to assume pronouns there. But yeah, so these are great examples and great input that you all have provided. So let's try another example. Let's say you wanted to promote teacher professional development. So you wanted to equip teachers with tools that enhance writing instruction while maintaining consistency across schools.

[37:58](https://youtu.be/LclJWgR8KZA?t=2278) What could we do with AI in that respect? And could Quill be integrated? So Jacqueline asks, who is our audience for these scenarios? So these scenarios would be, you are in the position of a state leader. So you are a state education leader, and you want to equip teachers with tools that enhance writing instruction while maintaining consistency across schools. If you want to be more specific, let's say high school English language arts teachers. We want to equip high school ELA teachers with better tools for enhancing writing instruction. Any thoughts coming to mind? I'll give folks a few seconds to type. Okay, Victoria asks, restate the scenario. So the scenario is state leaders want to equip teachers with tools Yep, absolutely.

[39:01](https://youtu.be/LclJWgR8KZA?t=2341) that enhance writing instruction while maintaining consistency across schools. So this is to promote teacher professional development. Jacqueline says, Quill diagnostic for teachers. Yes. So yes, I think that is one appropriate response. And so teachers may not be familiar with Quill, right? And so there would need to be a process to get them started or onboarded onto Quill to show them what Quill can offer and to provide time and space for teachers to learn how to use the platform like Quill diagnostic, right? And so totally fair point. I'm giving a quick appetizer of what Quill can offer, but I've checked out their website and Quill really offers a full buffet of resources and guides on how their platform is designed, as well as best practices for implementation.

[40:03](https://youtu.be/LclJWgR8KZA?t=2403) So again, I will say these are just exercises and scenarios to think about ways in which AI can be integrated into an intervention strategy. So what I'll do next, I'm going to go back to sharing my screen because I know we're running tight on time, but I do want to just summarize a few points before we open space for the Q&A. So I'm going to go back to sharing my screen. Okay, I hope you all can still see my screen. So in terms of key takeaways, to recap, one, AI writing assistants can do more than check spelling and grammar. They have progressed significantly due to these large language models that are very advanced, can offer contextual understanding of essays, can generate content, and can provide domain-specific support.

[41:04](https://youtu.be/LclJWgR8KZA?t=2464) When it comes to using educational data science and AI for innovation, at the Learning Agency, we've been really excited about driving advancements in AI writing assessment through these publicly available datasets and through these open source algorithms that can be able to evaluate writing at a specific level, detect plagiarism, and provide quality feedback at a human or teacher level. When it comes to AI-powered writing assistants, we believe this is a great strategic lever for personalized and accessible learning. So innovative tools like Quill and like Conmigo can provide personalized feedback, also align with educational standards. I forgot to mention, Quill is aligned with the Common Core. And so you can trust that what they're teaching can be linked to specific strands in these educational standards while also creating inclusive and supportive learning environments for students and educators.

[42:05](https://youtu.be/LclJWgR8KZA?t=2525) And we believe that because AI is able to provide immediate feedback, real-time data, and curriculum-aligned resources, it can become an excellent tool for educators to feel more empowered and equipped in their work without feeling replaced, but feeling supported. In terms of staying connected, feel free if you have any questions and want to reach out to me personally or in regards to our work at the Learning Agency, happy to connect and talk more about AI writing assistants or our work specifically. The workshop in this series will be taking place February 11th, but you'll be getting more information on that soon. That's more detailed than what I have here. But I also want to do a quick plug too if you're interested in learning more about AI-powered writing assistants, these data sets that I mentioned, these algorithms or advancements, feel free to sign up for our newsletter to stay up-to-date on the latest in edtech and what they can provide and what the opportunities are like here.

[43:14](https://youtu.be/LclJWgR8KZA?t=2594) On the screen is a QR code, so you can capture it. You can use your phone. If you turn on your camera, capture that QR code, it will take you to the necessary link to sign up for our newsletter. With that, I believe we wanted to move on to a Q&A session.

* * *

Original page: https://innovate-us.org/writing-smarter-with-ai-digital-assistants-for-enhanced-reading-and-writing · Licence: CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/), as stated on innovate-us.org