As GenAI tools increasingly shape the spaces where we teach and learn, it’s time to reimagine how we assess student writing. By embracing distributed assessment, we can harness the power of AI to foster growth, safeguard integrity, and center the student experience in a dynamic and exciting way. This shift aims to ensure students get the necessary support and guidance to thrive. Enter distributed assessment, a game-changing strategy that marries the strengths of AI with the irreplaceable insight of human teachers, nurturing student growth, fostering integrity, and sparking engagement in writing.
Unlocking the Potential of Distributed Assessment
Imagine breaking down the essay writing process into smaller, more manageable pieces. With each step, students receive specific feedback, guiding their journey. Picture the structure of a typical 5-paragraph essay. By harnessing AI tools in collaboration with educators, students are enveloped in a tailored support system, one that adjusts to their personal needs and aspirations through every phase of writing. From the initial AI starter that helps students generate a table of contents or starting sentence, to the multiple checkpoints where both AI and human teachers provide feedback and record grades, this distributed approach ensures that students receive timely and tailored support throughout the writing journey.
The Synergy of AI and Educators
What makes distributed assessment stand out is its inherent collaborative spirit. AI excels in offering immediate, precise feedback on the technicalities of writing, and identifying areas for enhancement such as clarity and coherence. Teachers, on the other hand, bring a human touch that AI cannot replicate. They provide in-depth, personalized advice, exploring the reasons behind writing decisions and fostering creativity and analytical thinking. This powerful combination ensures students receive well-rounded feedback throughout the writing journey.
Navigating Through Checkpoints
Gone are the days of assessing an essay only at its conclusion. Distributed assessment introduces a paradigm shift—feedback is integrated at pivotal moments throughout the writing journey. This approach allows students to refine their work continuously, ensuring a polished final piece. It empowers students, offering them the chance to improve with the guidance of both AI and their teachers at crucial intervals, like after drafting their first version or during peer reviews. This method not only bolsters learners but it ensures students receive well-rounded human and AI feedback throughout the writing journey.
Championing Academic Integrity
The rise of AI in writing education brings up valid concerns about academic honesty. Distributed assessment addresses these head-on. By engaging students in a process where drafts are reviewed, and feedback is given regularly, educators can closely follow each student’s writing evolution, identifying any discrepancies early. This ongoing dialogue between students, teachers, and AI tools creates a culture of transparency and accountability that is essential in an era where the lines between human and machine-generated writing are increasingly blurred.
Empowering Learners Every Step of the Way
Perhaps the most significant impact of distributed assessment lies in its ability to transform writing education into a student-centric experience. With ongoing support and feedback, students are better positioned to grasp new concepts, set achievable goals, and actively participate in their learning journey. This shift from focusing solely on grades to fostering growth and introspection encourages students to view writing as an evolving, continual process.
Looking Forward
As AI starts playing a bigger part in how we learn and teach, it’s clear that distributed assessment is becoming a game-changer. It’s all about using this tech to its fullest while keeping things personal and focused on the students. This means teachers can do more than just beef up writing skills; they can help students think more deeply and reflect on their learning, skills that are gold in today’s world. So, let’s dive in, eager to try new things, shift gears when needed, and put our hearts into guiding our students forward.
It is important to note that the U.S. Department of Education’s guidelines advocate for a human-centric, equitable, and transparent application of AI in classrooms where humans are in the loop. It is true that we should always remind ourselves as educators of the importance of keeping human relationships, reasoning skills, and ethics at the forefront of educational AI use. AI holds incredible potential to automate mundane tasks, enabling a deeper focus on fostering student relationships and growth. By moving forward with equity and collaboration at the core, we can collectively harness AI’s power to enrich education like never before.
About the Author
Micah Miner – District Administrator Instructional Technology & Social Studies at Maywood, Melrose Park, Broadview School District 89, American Consortium for Equity in Education Contributing Writer, Times 10 Publications Author
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In April 2023, our family – comprising two dynamic teenagers, a mom in education, and a tech-savvy husband – embarked on a quest fueled by a simple yet profound question: ‘What great things can we accomplish with AI today?’ This question ignited our passion project, Kids Think Wide.
‘Kids Think Wide’: Born from AI
Our initial challenge was finding a name that echoed our vision and passion, particularly for art. We sought guidance from ChatGPT, which suggested names like ‘kidsthinkingdiversely.com’. However, seeking a more kid-friendly name, we settled on ‘Kids Think Wide’. This title perfectly aligns with our goal of expanding young minds through AI-driven educational tools. AI’s role extended beyond naming; it was instrumental in designing our logo, creating web content, and assisting in coding. Admittedly, AI solutions aren’t flawless – we’ve encountered coding limitations and often diverged from AI suggestions. In this creative process, we learned to embrace the journey and be patient, open to change, and always learning.
Crafting a Universe of AI-Generated Content
‘Kids Think Wide’ is dedicated to fostering a more equitable educational landscape. We are committed to representing everyone, promoting gender equality, and amplifying historically overlooked or unheard voices in engaging and fun ways! We’ve created over 10,000 AI-generated images and published approximately 400 on Kids Think Wide. A writing prompt and discussion questions accompany each image to help prepare and inspire students to write. Our unique offerings include ‘choose your own adventure’ stories. In these, students collaboratively brainstorm and build ideas for their narratives before selecting from 3 to 5 adventure paths to personalize them, such as:
Additionally, we’ve leveraged the popularity of short-form videos, similar to reels and TikTok, using animated images, or ‘Sparks’, to captivate and spark enthusiasm for creative writing among students.
Our journey with AI also revealed the biases and limitations inherent in image generators. We’ve found it’s easier to create images that involve subjects that are very common online – celebrities, movie scenes, and well-photographed places but getting an accurate representation of a wheelchair can be more challenging.
AI has allowed us to create scenes that challenge reality:
Journey through time, space, and into other worlds:
Create the fun, wild and whimsical:
The Evolution and Magic of AI-Generated Images
The last nine months have seen dramatic advancement in AI-generated images. The improvement in image quality, accuracy in prompt interpretation, and the ability to adjust specific image elements has been remarkable. Our journey through this dynamic domain has been an exhilarating blend of discovery and creativity. While perfecting an image is usually challenging and time-consuming, the results are frequently astonishing and rewarding. We start simple and slowly build on prompts. The arrangement of phrases and the specific words chosen play crucial roles. However, you can unlock unexpected and extraordinary outcomes through iteration, experimentation, and patience. It helps to know tokens (short phrases that often produce excellent results), e.g., playful mood, cinematic, low Angle shot, bokeh, or Chiaroscuro to name a few! On other occasions, it might require 30, 50, or even more re-rolls and remixes to create an image that genuinely captivates and is worth sharing.
While free tools provide a starting point, they often have limitations; investment in paid resources is usually necessary for more advanced or specific requirements.
As AI image generation rapidly evolves, we find ourselves exploring various tools. Midjourney stands out with its detailed control and often superior imagery, while Adobe Firefly is notable for its dedication to diversity and inclusivity. On the other hand, Dall-E brings a sense of whimsy to its creations. Each platform offers a unique experience. It’s not uncommon to initially admire an image, only to later discover anomalies like an extra limb or oddly placed fingers – the quirks of AI can lead to both amusing distortions and unexpected additions.
Engage with the AI Community
Our journey has shown us how important connecting with the AI community is. There are many skilled and helpful creators out there. We often turn to Twitter to engage with this community. It’s an excellent place for learning, sharing experiences, and finding support.
‘Kids Think Wide’ has evolved from a simple ‘what if’ conversation into a reality, thanks to AI’s extraordinary capabilities. This concept, unimaginable even nine months ago, has come to life through our family’s collective imagination and AI’s power. We’re excited to unveil more awe-inspiring images, thought-provoking writing prompts, and enhanced interactivity, all while staying at the forefront of AI developments. As ‘Kids Think Wide’ continues to grow, one thing is sure: the best is yet to come, with AI playing a pivotal role in our journey.
Thanks to Megs for the guest post
Rachelle Dené is a Spanish and STEAM: What’s Next in Emerging Technology Teacher at Riverview High School in Oakmont, PA. Rachelle is also an attorney with a Juris Doctor degree from Duquesne University School of Law and a Master’s in Instructional Technology. Rachelle is an ISTE-certified educator and community leader and served as president of the ISTE Teacher Education Network. She was named one of 30 12 IT Influencers to follow in 2021 and one of 150 Women Global EdTech Thought Leaders in 2022.
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These apps and websites can help teachers boost their productivity, personalize learning, and create lesson content.
Over the past five years, I’ve explored ways to integrate AI into my teaching practice—even before ChatGPT and other generative AI became some of the most talked-about topics in education. Every educator needs to learn about AI and how we can leverage this technology to benefit our students and enhance our own work. To best provide for our students, we need to understand how this technology will impact them and us. What better way than to explore new tools via AI in our teaching practice?
Rachelle Dené is a Spanish and STEAM: What’s Next in Emerging Technology Teacher at Riverview High School in Oakmont, PA. Rachelle is also an attorney with a Juris Doctor degree from Duquesne University School of Law and a Master’s in Instructional Technology. Rachelle is an ISTE-certified educator and community leader and served as president of the ISTE Teacher Education Network. She was named one of 30 12 IT Influencers to follow in 2021 and one of 150 Women Global EdTech Thought Leaders in 2022.
**Interested in writing a guest blog for my site? Would love to share your ideas! Submit your post here. Looking for a new book to read? Find these available at bit.ly/Pothbooks
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Time and the capacity to use data and understand it are at the essence of making data-driven decisions in classrooms and schools (Rhoads, 2019; Mandinach 2012, U.S Department of Education, 2010). In my research focusing on data literacy for educators, time has always been the number one issue for educators to use data to make decisions as well as learn and practice data literacy skills. Yet, with what we are going to talk about today, I believe that this can change by leaps and bounds.
Ultimately, as the world of education becomes increasingly data-driven, teachers and school leaders face the daunting task of learning how to effectively analyze and apply this data. The role of technology software in gathering, transforming, and visualizing data is no longer optional—it’s a necessity as our classrooms and schools are collecting immense amounts of data that can be utilized to support student learning. But how can we bridge the gap between the data we have and the insights we need in a quick and efficient manner? Enter Code Interpreter, a revolutionary tool that’s changing the way we approach data in education. Let’s discuss how it can be utilized to support data-driven decision-making as I believe it can solve many of the time and capacity issues facing teachers and school leaders in using data to make important decisions for students and school systems.
Note: For information related to my research into data literacy, please check out my study and its summary found here.
Data is Everywhere in Classrooms and Schools
Data for teachers and school leaders can be drawn from various avenues such as the school’s Student Information System, Learning Management System, and EdTech tools. Many of these tools provide opportunities within themselves to review the data they collect in the form of visualizations and dashboards. Yet, these tools do not provide in-depth analysis that can help teachers and school leaders make data and evidence-informed decisions to the best of their abilities. As a result, the data will need to be extracted, and cleaned, and further analysis will need to take place to see deeper insights as to what the data is telling us as well as how it may relate to other strands of data we’ve collected. For example, take test scores, student SEL surveys, and attendance data from a period of time. What we can now do is easily place those data points onto a single Excel file to be analyzed by Code Interpreter to see if any relationships may exist. With this said the goal of this blog is to demonstrate how this can be done by teachers and school leaders as they begin harnessing this tool to support them in their data-driven decision-making.
Step-by-Step Process of Using Code Interpreter
Now, we will discuss its major features in supporting educators in making data-driven decisions. First, we will discuss the process of how it can be used. Secondly, we will outline how it can conduct important data preparation and analysis steps for us in order for the results to be computed in a way that is understandable during analysis as well as to stakeholders. Third, we will go into further applications of Code Interpreter that can be utilized by teachers and school leaders. Let’s get started!
Important Facets Code Interpreter Can Do Essential to the Data-Driven Process
Before discussing how to use Code Interpreter in a step-by-step process, we want to cover some important facets it can do in the data-driven process: Clean Data, Statistical Analysis, Visualizations, and Articulate Data Findings to Stakeholders. All of these facets are critical when utilizing Code Interpreter and conducting any form of data analysis.
Cleans Data
One of the major hurdles in data analysis is data cleaning, a time-consuming but critical process to ensure accurate results. Code Interpreter can automate this process, identifying errors, inconsistencies, and outliers in raw data. With its robust data cleansing capabilities, Code Interpreter can streamline this often laborious task, leaving more time for interpretation and decision-making.
Note: This video illustrates how Code Interpreter cleans data. Cleaning data is super important in order to have valid results from a data set you are working with.
Conducts Detailed Statistical Analysis with a High Degree of Accuracy
Beyond cleaning data, Code Interpreter shines in its ability to conduct detailed statistical analysis. It can handle a wide variety of statistical techniques and tests, delivering a high degree of accuracy. Even complex data practices, often daunting for non-expert users, become more accessible and understandable with GPT-4’s intelligent interpretation and simplification of statistical outputs.
Visualizes the Data Based On the Statistical Outputs You Desire
Visualizing data is a key element in understanding and communicating complex information. GPT-4 Code Interpreter can assist in creating visually engaging and informative graphs, charts, and dashboards based on the statistical outputs you need. This automated visual representation of data can support data-driven decision-making by making the findings more tangible and accessible.
Note: Below is an example of a visualization of data produced by Code Interpreter
Articulates the Data to be Presented to Stakeholders
Another challenge that Code Interpreter addresses is the communication of data insights. Often, complex statistical analyses can be difficult to convey to stakeholders in a clear, understandable manner. Code Interpreter can summarize complex findings, generate reports, and even make predictions based on the data, making it easier for stakeholders to understand and apply these insights in decision-making.
Example in Action – Using Code Interpreter for Educational Data Analysis
Let’s focus on the example we provided at the beginning of this blog post. It focuses on reviewing test scores, student SEL surveys, and attendance data. We will now walk you through the steps of how to use Code Interpreter to dive into this data and analyze it. This will be a four-step process, which can take between five and ten minutes to complete.
Step 1: Gathering the Data
Your first task involves gathering your data from various sources – this could be test scores, student Social-Emotional Learning (SEL) surveys, and attendance data. Let’s say for this example that the test scores, the SEL survey, and attendance data are for the entire 2022-2023 school year. The assessment scores for an elementary school are from the most recent state-wide summative assessment given. Data can be collected from the student information system, the state’s assessment database, and the survey provided to students on a local Google Form. This may be the most time-consuming step of the process as sometimes data extraction features are hard to find and selecting data to extract may also take time as well.
Note: Below is a video example demonstrating how to export data from I-Ready Onto an Excel File.
Once collected, arrange all these data points on a single Excel spreadsheet. You might have columns for the grade levels, test scores, survey responses, and attendance records. Make sure your data is clean, accurate, and organized coherently for the best results. What an educator can do is copy and paste the columns from each of the extracted data sources onto a single spreadsheet. Then, they can prompt after uploading the data to Code Interpreter to clean the data (more on that later).
Note: This video demonstrates how to combine data from multiple data sets in four ways using Excel.
Now it’s time to engage with the Code Interpreter. To do this, you’ll need to import your Excel file into the platform. In most cases, this is as simple as clicking the “Upload” button and selecting your file.
Step 4: Prompting the Code Interpreter to Conduct Descriptive Statistics
Start with some basic analysis. For descriptive statistics, you might instruct the Code Interpreter to compute measures such as the mean, median, or standard deviation for your various data columns.
Note: Before moving into statistical prompts to ask Code Interpreter, be sure to prompt Code Interpreter to Clean the Data. For example, prompt Code Interpreter to clean the data and organize it for analysis, which it will then conduct for you.
To do this, you could input something like:
“Compute the mean, median, and standard deviation for the ‘Test Scores’ column.”
The Code Interpreter will then return the requested statistical measures.
What’s great is that it can provide easy-to-understand results. You can further review and question the results as well. Additionally, in this same instance, prompting it to visualize these results into graphs is another important feature, which can help in the data articulation piece for when it’s presented formally to other educators and stakeholders.
Step 5: Conducting Multivariate Analysis
For a more in-depth understanding, you can instruct the Code Interpreter to conduct multivariate statistical analyses. For example, you might want to find out if there’s a correlation between attendance and test scores.
To do this, you could input something like:
“Calculate the correlation between ‘Attendance’ and ‘Test Scores’ columns.”
The Code Interpreter will return the correlation coefficient, providing insight into the relationship between these variables.
Step 6: Interpreting the Results
Code Interpreter not only conducts the analysis but also provides a simplified interpretation of the results. This is a vital step to help you understand and apply the insights from the data to your decision-making process. As with descriptive statistics, you can further prompt it to dive deeper into the analysis or ask it to provide graphs to visualize the data.
Note: Below is a video demoing Code Interpreter a wide variety of ways that follow this protocol.
Code Interpreter isn’t limited to basic data analysis—it’s a versatile tool with a multitude of applications that can revolutionize the way we engage with data in education. Let’s explore some of the ways in which this advanced tool can assist teachers and school leaders beyond basic statistical analysis:
Facilitating Data Dialogues: The Code Interpreter can serve as a valuable assistant in data dialogues, aiding in both data cleaning and providing alternate perspectives in analysis. It can efficiently present various statistical outputs, offering multiple ways to interpret the data and stimulate insightful conversations among educators.
Developing Action Plans: With its ability to produce comprehensive reports and detailed analyses, the Code Interpreter can facilitate the development of data-driven action plans. By linking analyzed data to practical steps, it can help formulate action plans tailored to improve student outcomes.
Improving Instruction: The Interpreter’s analysis can uncover patterns and trends that are invaluable for informing instructional strategies. By linking data findings with recommendations for instruction, it allows educators to make data-informed decisions that directly impact classroom practices.
Enhancing Processes: Beyond the classroom, the Code Interpreter can also support the optimization of broader school processes. For instance, patterns in attendance data can inform changes in scheduling or student support services.
Predictive Analysis: The Code Interpreter’s predictive analysis capabilities can help forecast future trends, enabling proactive planning. For instance, it could predict future test scores based on current student performance and engagement metrics.
Personalized Learning: The Code Interpreter can help tailor educational experiences to individual student needs. By analyzing data at the student level, it can inform personalized learning plans to cater to each student’s unique strengths and areas for improvement.
Conclusion and Data Literacy Skills Needed to Be Effective Using Code Interpreter
We’ve embarked on a journey today, exploring the potential of the Code Interpreter in transforming educational practices through effective data analysis within classrooms and schools. By harnessing the power of this tool, we can redefine how we approach data, decision-making, and action in our educational spaces to improve our instruction and school systems for our students, faculty, and community.
However, as we navigate this digital landscape, it’s important to remember that tools like the Code Interpreter are most effective when coupled with our own data literacy skills. As teachers and school leaders, enhancing our understanding of data management and analysis will be instrumental in maximizing the benefits of these technological advancements.
This includes the ability to merge and transform data on spreadsheets, and the knowledge of single and multivariate statistical analysis. A strong foundation in these areas not only amplifies our ability to use tools like the Code Interpreter but also empowers us to question, interpret, and apply data insights in meaningful and impactful ways.
While this may seem like a daunting task, take heart in the knowledge that the digital age brings with it a wealth of resources to help build these skills. Online courses, webinars, workshops, and even integrated tutorials within tools like the Code Interpreter are at your fingertips, ready to help you embark on this exciting learning journey. For those who want to practice, Kaggle provides datasets from many different industries. It’s a great way to practice as the datasets come pre-packaged and are easy to work with as you get started with using Code Interpreter.
So, let’s take this as a hopeful invitation to embrace the future of data in education. The road ahead is full of opportunities for growth, innovation, and enhanced understanding, all aimed at one noble goal – the betterment of our educational environments. Together, equipped with our growing data literacy skills and the powerful Code Interpreter, let’s step forward into this exciting future.
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Imagine a classroom where every essay, every homework assignment springs from the well of individual thought and effort. This is the academic ideal, but as AI technologies become ubiquitous classroom companions, the lines defining academic integrity are being redrawn. How do we uphold the honor of independent scholarship when students have access to tools that can generate a polished essay in seconds?
As we navigate the era of digital transformation, AI emerges as both a beacon of innovation and a test of our educational principles. The White House’s executive order recognizes AI’s “extraordinary potential for both promise and peril” (Executive Office of the President, 2023, p. 1), while the Department of Education’s report cautions us at this “inflection point” where we must choose to either diminish or bridge educational disparities (Department of Education, 2023, p. 6). In this climate, the academic integrity of our classrooms hangs in the balance, necessitating a nuanced approach to integrating AI in education.
The Call for Ethical AI:
In a unified call for ethical AI, both the executive order and the Department of Education’s report emphasize the necessity of human oversight and equitable use of AI technologies. These documents compel us to create AI policies that not only comply with ethical standards but also reflect a shared vision for high-quality, equitable education (Executive Office of the President, 2023, p. 2; Department of Education, 2023, p. 10). We must forge policies that are adaptable to the rapid advancements in AI, ensuring they remain relevant and effective.
To navigate this terrain, the following steps can serve as a compass for schools:
Assessment of Current GenAI Usage:
Begin by evaluating how students and teachers are currently engaging with generative AI tools. Understand the ethical, academic integrity, and privacy concerns that arise with their usage.
AI Literacy and Understanding:
Invest in building a comprehensive AI literacy program. Ensure that every member of the school community, from students to educators, understands the capabilities and limitations of GenAI.
Designing Clear Guidelines:
Devise clear, actionable guidelines for how students and teachers can use GenAI tools responsibly. These guidelines should encourage the ethical use of AI while also fostering academic integrity.
Stakeholder Partnerships:
Collaborate with a broad range of stakeholders—including students, parents, teachers, and tech experts—to create a policy that is inclusive and representative of the community’s values and needs.
Policy as a Living Document:
Recognize that an AI policy is not set in stone but is a living document that will evolve as new multimodal technologies come, and where insights and challenges emerge.
Stakeholder-Specific Examples:
Provide concrete examples that resonate with various stakeholders, illustrating the appropriate use of AI in a way that is relevant and understandable to each group.
The policy should explicitly address:
Appropriate Use Cases: Clearly define scenarios where generative AI can be used to assist with assignments, ensuring that the use enhances learning without compromising on integrity.
Citation and Tracking of Generative AI Use: Establish norms for how students should cite and track their use of GenAI, promoting transparency and accountability.
Data Privacy and Security: Set firm boundaries to safeguard the data privacy and security of students and teachers, aligning with the best practices in digital safety.
By considering common issues such as generative AI grading challenges, the proliferation of misinformation, and the risks of overreliance on AI, policies can be designed to preempt and address these concerns effectively.
Introducing the Policy:
Implementing the policy can be done through varied educational strategies. Engage the school community in faculty meetings, workshops, debates, and peer learning sessions to foster a deep understanding of the policy. Also, include student voice in the process and find ways to creatively communicate to parents and community members. This multi-faceted approach ensures that as AI tools become more integrated into the educational fabric, they are used in a manner that is safe, secure, and aligned with the ethos of academic excellence.
Drawing from the four foundations suggested by the Department of Education—centering people, advancing equity, ensuring safety and effectiveness, and promoting transparency—we can outline strategies that educators can implement to develop AI policies that foster integrity and inclusivity (Department of Education, 2023, p. 10).
The Double-Edged Sword of AI in Academic Honesty:
AI can be a powerful ally in education, offering personalized learning experiences and support. However, it can also inadvertently encourage shortcuts. AI-powered platforms that complete math problems or auto-generate essays can detract from the learning process. Conversely, AI that supports students in research, data analysis, and the exploration of multiple perspectives can enhance critical thinking and original work.
AI holds the power to both enhance personalized learning and inadvertently encourage academic shortcuts. The Department of Education underscores the need to ensure safety and effectiveness of AI tools (Department of Education, 2023, p. 10), aligning with the executive order’s directive for rigorous evaluations of AI systems (Executive Office of the President, 2023, p. 2).
Balancing Act: Case Studies and Hypothetical Scenarios:
Consider the use case of a school district that implemented an AI tool designed to help students learn how to structure essays. The tool was effective, but teachers noticed an uptick in nearly identical essay outlines. The district responded by updating their policy to specify that while AI can be used for learning and practice, all submitted work must be uniquely crafted by the student, ensuring the final product demonstrates individual learning and critical thinking. This approach aligns with the administration’s emphasis on equity, as articulated in the executive order: “My Administration cannot — and will not — tolerate the use of AI to disadvantage those who are already too often denied equal opportunity and justice.” (Executive Office of the President, p. 3)
A district’s use of AI for essays can help lead to policy updates ensuring student work remains original, mirroring the White House’s stand on equitable AI use (Executive Office of the President, p. 3). AI in assessments should aid educators, not supplant them, providing a detailed look at student performance across various tasks. Feedback on drafts and support for authentic, real-world tasks are where AI shines, but human judgment remains the most important aspect of assessment, and is crucial to the student-teacher relationship. This balanced approach to AI leverages its strengths while upholding academic integrity and educational values.
Conclusion:
As we stand at the intersection of innovation and tradition, the path forward requires a delicate balance. We must embrace the tools that propel our students toward a bright future while instilling the timeless values of honesty and effort. It is not just about teaching students how to use AI responsibly; it’s about nurturing a mindset that values the learning journey as much as the destination. Ensuring AI systems “function as intended, are resilient against misuse or dangerous modifications” (Executive Office of the President, p. 3) is paramount in this endeavor.
Engagement Poll:
What is your biggest concern regarding AI and academic integrity? Share your thoughts and let’s address these challenges together.
U.S. Department of Education, Office of Educational Technology. (2023). Artificial intelligence and the future of teaching and learning: Insights and recommendations. https://tech.ed.gov/ai-future-of-teaching-and-learning/
About Micah
District Administrator Instructional Technology & Social Studies at Maywood, Melrose Park, Broadview School District 89, American Consortium for Equity in Education Contributing Writer, Times 10 Publications Author
**Interested in writing a guest blog for my site? Would love to share your ideas! Submit your post here. Looking for a new book to read? Find these available at bit.ly/Pothbooks
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Learning as I go: Reflections & lessons learned 