MagicSchool.ai is an AI-powered tool designed specifically for teachers to enhance their classroom experience. It offers a range of features that help educators save time and improve instruction quality.
With MagicSchool, teachers can efficiently plan lessons, differentiate instruction, write assessments, and create Individualized Education Programs (IEPs).
Additionally, the platform facilitates clear communication between teachers, students, and parents.One of the standout features of MagicSchool is its ability to generate original educational content aligned with standards and tailored to individual student needs.
This empowers teachers to provide a personalized learning experience. The tool also enables teachers to give timely and meaningful feedback to students, promoting faster improvement.MagicSchool prioritizes safety and privacy by adhering to FERPA and COPPA regulations.
It does not collect or store any personally identifiable student information. Moreover, the platform supports multiple languages, breaking down language barriers and allowing educators to write creatively and clearly.Teachers using MagicSchool testify to its efficiency and effectiveness.
They appreciate tools like the text leveler, which quickly adapts content to different reading levels, and the Multiple Explanations for Complex Concepts feature, which supports student learning across various subjects.
MagicSchool also offers convenient features like class newsletters and quiz generation, saving valuable preparation time.In summary, MagicSchool.ai is an invaluable AI tool that empowers teachers with time-saving capabilities and helps them deliver tailored instruction, provide feedback, and effectively communicate with students and parents.
In this EdWeek blog, an experiment in knowledge-gathering, Ferlazzo will address readers’ questions on classroom management, ELL instruction, lesson planning, and other issues facing teachers. Send your questions to lferlazzo@epe.org. Read more from this blog.
What advice would you give to new (or veteran!) middle school teachers?
I spent my first year teaching in a middle school and I quickly made the move to high school. I should have gotten a lot more advice—like what contributors in this series have to offer—than I did that first year.
Today, Jeremy Hyler, Serena Pariser, Sarah Cooper, and Keturah Proctor share their experiences. Jeremy and Serena were also guests on my 10-minute BAM! Radio Show. You can also find a list of, and links to, previous shows here.
Jeremy Hyler is a middle school English and science teacher in Michigan. He has co-authored Create, Compose, Connect! Reading, Writing, and Learning with Digital Tools (Routledge/Eye on Education) and From Texting to Teaching: Grammar Instruction in a Digital Age, as well as Ask, Explore, Write. Jeremy blogs at MiddleWeb. He can be found on Twitter @jeremybballer and at his website jeremyhyler40.com:
I almost feel there should be a brochure or a handbook given to new middle school teachers before they even think about starting their first day. Needless to say, I was only ever given one piece of advice, and that was to keep them busy, or they would eat me alive. The teacher that gave me that advice meant well as a great mentor, but as I look back, it probably wasn’t the best advice.
For me, one of the first pieces of advice I can give to a new middle school teacher would be to build relationships with students. Take interest in them as a person. Don’t just focus on their academic strengths but take time and go to their sporting events. Ask them about what they like to do outside of school, too. If they like to fish or hunt, ask them to show you pictures of their fish or deer. Be involved with them more than just being their teacher.
Also, something that goes along with building relationships is being open and honest with your students. If you make a mistake, tell them. They will respect you more if you just admit you make mistakes like everyone else does. Furthermore, I would recommend telling your students when you have a bad day. It is amazing how many times my students lift me up and help me when I am not having the greatest day. It’s about showing them you are human and real, not a person that always has a great day.
Finally, take time for yourself. Don’t be afraid to leave work on time Friday or leave that stack of papers at school. It is important to take care of yourself and to just forget about your job for some time. If you don’t take time for yourself, burnout is inevitable. Take a walk, go to the movies, or go for a drive. Whatever you decide to do, you need to make time for yourself to stay energized.
Middle schoolers are so much fun to teach. They are curious, excited about life, bright-eyed and bushy-tailed. They are going through so much in their personal and social lives that one day can be so different from the next.
They also have a lot going on. They are learning to regulate their emotions, understand deep friendships, trying to figure out the world, and are attempting to be more independent in life. They are in this short-lived place where they are older than children but younger than what most consider a teenager. Sometimes, that can lead to a bit of a teeter-tottering of emotions that may follow them to class as they strive to be understood. As teachers of middle school students, you can find yourself making fun and engaging lessons where students are collaborating, competing, experimenting, and often creating. You’ll get to use your skill, pizazz, and energy. The advice I’d give to new or veteran middle school teachers is start the school year off with a self-care plan.
When we take care of ourselves, it shows up in our work and vice versa. Our students notice and need to be the best version of themselves. We give so much to middle schoolers that we have to remember to also give to ourselves. Middle schoolers, especially, deserve a teacher that is well-balanced and rested.
This could look like having a set of workout clothes on our bed (if we are teaching virtually) so we know to change directly in them after class. Or, if we are in a classroom, this could be as simple as bringing a set of workout clothes to class and changing before we leave school so we don’t go home and melt into the couch. That can too easily happen. Self-care could look like always keeping our water on our desks so we stay fully hydrated. It could also look like scheduling an at-home yoga video into our calendars just as you would a parent meeting. Or this could simply look like asking a colleague to be a workout buddy to hold each other accountable. Here’s a self-care inventory I created that you can use weekly, monthly, or whenever you feel the need to take a read on your self care.
When I was a first-year 6th grade teacher, I stayed late one night to grade a pile of papers that were on my desk. At 9 p.m., my principal walked by my class and saw my light on. He said just two words to me, “Go home.” He knew this is how teachers lose steam and eventually could burn out. My self-care was completely out of whack that year, and if I could get a time machine and travel back to my first year, I would have done much better if I took time to take care of myself. We can’t pour from empty cups. The thing about self-care is we should do it before we need it and keep our cups full. My advice would be to simply make self-care a proactive practice, not a reactive fix.
‘Love Them’
Sarah Cooper teaches 8th grade U.S. history and is the dean of studies at Flintridge Preparatory School in La Canada, Calif. Sarah is the author of Making History Mine: Meaningful Connections for Grades 5-9 (Stenhouse, 2009) and Creating Citizens: Teaching Civics and Current Events in the History Classroom, Grades 6-9 (Routledge, 2017). All of her recent writing can be found at sarahjcooper.com:
After more than two decades of teaching middle school, my answer has simplified over time.
Twenty years ago, I would have said that you need to keep students busy, change up activities multiple times a period, make sure they’re doingsomething. Ten years ago, I would have said that you need to see the infinite potential of middle schoolers and treat them as the fledgling young adults they are, complete with profoundly felt opinions and a desire to improve the world.
And I would still agree with both of these points.
But now, maybe because I realized anew during our recent period of online learning how meaningful it is for us to be in community together, the most important advice I would give any middle school teacher is this:
Find a way to love them.
For new teachers with shaky lesson plans, for veteran teachers with fatigue behind their eyes, this is the first and most important step. If your students feel that you’d rather be teaching high school and are just marking time with them, they’ll resent you. If they sense that their craziness drives you crazy, and not in a joking kind of way, they’ll slog into their seats.
But if you can laser through their messiness, floppiness, awkwardness, perfectionism, socializing, and so much else to understand that they are figuring themselves out, that’s your toehold in. For one colleague, this means accepting that her classes are just going to be loud, and she’s OK with that. For another, it’s creating a massive simulation that harnesses everyone’s talents and skills. For me, it’s coming into class, taking a breath and riding the wave of energy like a surfer—then grappling with hard current and historical issues, listening to my students’ opinions as they inform each other’s and my own.
If you can discover this toehold, you’ll secure a front-row seat to these young adolescents’ identity development and might even be able to help some of them in their journey. Many or all of them will probably accept you back. And, by the end of the year, some of them might even love you back—if you’re lucky!
‘Don’t Believe the Myths’
Keturah Proctor has had over 20 years of experience in education advocating for students through an anti-bias, anti-racist lens:
Don’t believe the myths about middle school students. From grades 5-8, students experience tremendous growth and change. Physically, they are changing. Socially, they are having to put themselves out there in a way they’ve never had to before. Academically, school is becoming more difficult, so students now have to manage their time and their study habits and their schedules. Emotionally, they are experiencing new feelings and may not have the words to communicate them. These years are full of tremendous highs and good feelings and tremendous lows when students are developing their resilience in order to navigate.
Middle school teachers, show your humanity, your personality, your individuality—middle school students want to know that you are a person, too. Their need for connection and validation is reinforced when they know that you, too, are being vulnerable.
As a middle school teacher, you should remove yourself from the center as the “all-knowing teacher” and position yourself as someone who is guiding young people. You have to learn to share the space with young people. Middle school students want independence. They want the room to discover, wonder, and to express themselves. As the teacher, you must be able to cultivate the environment where discovery is welcomed and celebrated.
Young people want to know that you believe in them and are rooting for them. Even when they make mistakes, that should be welcomed, because making mistakes is part of growing. Middle school students need to understand that they are safe to express who they are and encouraged to find out who they want to be. Individuality is a big part of middle school. Student expression and identity are a big part of the middle school years, and as a middle school teacher, you have to be prepared for that. You have to honor that students are coming in with their own lived experiences and are questioning, exploring, and affirming who they are and who they are becoming. As a middle school teacher, you have to be committed to learning, not just the content, but committed to learning and understanding young people, their perspectives, and their realities.
Learning to not only welcome student voice but provide space to cultivate it and for students to recognize their own brilliance and power. Provide a learning environment where each student feels like it was created for them. This means that you are going to find points of connection, authentic points of connection. It means immersing yourself in everything that young people are immersed in. Middle school teachers should develop an understanding of what students are experiencing, not only while at school but outside of school. It means knowing what’s happening on social media and learning about the dances, the styles, the music of young people. It means understanding what young people care about and what is important to them.
Being a middle school teacher means unlearning what it means to be “the teacher” and to develop an understanding that you are there to guide young people on their journey, by validating and affirming their discovery of self. Being a middle school teacher is about conveying academic content in a dynamic manner and being authentically engaged with students as they are walking through their journey of self-discovery.
I’ve taught 6th grade for over 20 years. In that time, I realized that my success had nothing to do with the instructional content, but it had everything to do with developing relationships with students where they saw that I was genuinely connected to them as people, not just my students. It meant including my students and valuing their input rather than just seeing them as passive receptors of information. We focused on community building and honoring the gifts and individuality of one another. That understanding was the north star for students to be able to realize that their actions and behavior have not just an impact on them personally, but that they are part of something bigger, allowing for reflection as to how everyone in the learning community is responsible for one another.
Thanks to Jeremy, Serena, Sarah, and Keturah for contributing their thoughts.
Consider contributing a question to be answered in a future post. You can send one to me at lferlazzo@epe.org. When you send it in, let me know if I can use your real name if it’s selected or if you’d prefer remaining anonymous and have a pseudonym in mind.
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AI can be a tool to create meaningful connections and learning experiences for children—and may help foster more equitable outcomes.
SOON AFTER ChatGPT broke the internet, it sparked an all-too-familiar question for new technologies: What can it do for education? Many feared it would worsen plagiarism and further damage an already decaying humanism in the academy, while others lauded its potential to spark creativity and handle mundane educational tasks.
Of course, ChatGPT is just one of many advances in artificial intelligence that have the capacity to alter pedagogical practices. The allure of AI-powered tools to help individuals maximize their understanding of academic subjects (or more effectively prepare for exams) by offering them the right content, in the right way, at the right time for them has spurred new investments from governments and private philanthropies.
There is reason to be excited about such tools, especially if they can mitigate barriers to a higher quality or life—like reading proficiency disparities by race, which the NAACP has highlighted as a civil rights issue. Yet underlying this excitement is a narrow view of the goals of education. In this framework, learners are individual actors who might acquire new knowledge and skills with the help of technology. The purpose of learning, then, is to master content—often measured through grades and performance on standardized tests.
But is content mastery really the purpose of learning? Naming reading proficiency as a civil rights issue likely has less to do with the value of mastering reading itself, and more to do with the fact that mastery of reading (or math, or other subjects) can help lay a foundation for what learning can unlock: breaking the intergenerational cycle of poverty, promoting greater self-awareness and self-confidence, and cultivating a stronger sense of agency over one’s destiny and the destinies of one’s communities. Content mastery is part of this equation, but making it the primary focus of education misses the fact that so much of a child’s future is shaped by factors beyond the classroom. Critically, networks, or who children and their families are connected to, and how, matter for helping children prepare to live fulfilling lives. This is especially true for networks that cut across socioeconomic, demographic, and other lines. Indeed, a large recent study highlighted how social capital, defined as friendships across socioeconomic divides, can play a larger role in fostering intergenerational economic mobility than school quality (often measured by the test scores of students who go there).
Networks that connect parents to coaches to help them navigate their children’s schooling can forge new support structures and trusting relationships between families and educators. Networks that connect students to role models and mentors can change the course of their academic and professional lives. A child’s broader social context, in addition to the knowledge and skills they gain through school, matters deeply for their future outcomes. Left without intervention, however, real-world networks often form and evolve in inherently unequal ways. For example, patterns of preferential attachment can lead “the rich to get richer,” excluding many from accessing connections that might improve their lives in important ways.
In practice, each AI needs an objective function that represents what it is optimizing for. Applications of AI for pedagogy and content mastery might optimize for “helping students get the highest possible score on a test.” Fostering more inclusive network connections, however, is a more deeply rooted and structural type of change than improving test scores. Using AI to help cultivate these networks might do more for children’s life outcomes than focusing on pedagogy and content mastery alone.
But some may argue that optimizing network connections is a more nebulous task than optimizing test scores. What, precisely, should the objective function(s) be?
One framework for exploring this may involve focusing on how the networks that children and families are enmeshed in form and evolve in the first place. In the context of schooling, this involves the wide range of policies that school districts design to determine which schools students can attend (“school assignment policies”), along with the practices families adopt when picking schools for their children under these policies. Such policies and practices have historically perpetuated harmful features like school segregation by race and socioeconomic status—which, despite nearly 70 years since its formal outlawing, continues to define public education in the US. Many scholars argue that demographic integration has historically been one of the most effective methods not only for enhancing the academic preparation of historically disadvantaged groups, but also for fostering greater compassion and understanding—say, an ethic of pluralism—across people from different backgrounds.
AI can help support the design of more equitable school assignment policies that foster diverse and integrated schools, for example, by supporting district-level planning efforts to redraw “school attendance zones”—i.e., catchment areas that determine which neighborhoods feed to which schools—in ways that seek to mitigate underlying patterns of residential segregation without imposing large travel burdens and other inconveniences upon families.
Existing researcher-practitioner partnerships—and some of my own research with collaborators Doug Beeferman, Christine Vega-Pourheydarian, Cassandra Overney, Pascal Van Hentenryck, Kumar Chandra, and Deb Roy—are leveraging tools from the operations research community and rule-based AI like constraint programming to explore alternative assignment policies that could optimize racial and socioeconomic integration in schools.
These algorithms can help simplify an otherwise cumbersome process of exploring a seemingly infinite number of possible boundary changes to identify potential pathways to more integrated schools that balance a number of competing objectives (like family travel times and school switching). They can also be combined with machine-learning systems—for example, those that try to predict family choice in the face of boundary changes—to more realistically estimate how changing policies might affect school demographics.
Of course, none of these applications of AI come without risks. School switching can be disruptive for students, and even with school-level integration, segregation can persist at smaller scales like classrooms and cafeterias due to curricular tracking, a lack of culturally responsive teaching practices, and other factors. Furthermore, applications must be couched in an appropriate sociotechnical infrastructure that incorporates community voices into the policymaking process. Still, using AI to help inform which students and families attend school with one other may spark deeper structural changes that alter the networks students connect to, and by extension, the life outcomes they ultimately achieve.
Changes in school assignment policies without changes in school selection behaviors amongst families, however, are unlikely to lead to sustainable transformations in the networks that students are tapped into. Here, too, AI may have a role to play. For example, digital school-rating platforms like GreatSchools.org are increasingly shaping how families evaluate and select schools for their children—especially since their ratings are often embedded across housing sites like Redfin, which can influence where families choose to live.
Some have argued that school-rating platforms, where ratings largely reflect test scores—measures notoriously reflective of race and income and not as indicative of how much schools actually help students learn—might have historically led white and affluent families to self-segregate into neighborhoods zoned for highly rated schools, creating a vicious cycle of residential segregation that reinforces patterns of school segregation and ensuing achievement gaps. A recent research project I did in collaboration with Eric Chu, Doug Beeferman, Rebecca Eynon, and Deb Roy fine-tuned large language models to explore how parents’ open-ended reviews on GreatSchools might contribute to such trends. Our results showed that parents’ reviews are strongly associated with school-level test scores and demographics, and not associated with measures of student progress, suggesting that parents who consult reviews to make schooling choices may be factoring demographics more than actual school effectiveness into their decisions.
GreatSchools continues to invest in new ratings schemes that seek to break these feedback loops and offer a more complete view of school quality—as Sisyphean a task as it may seem. What if platforms like GreatSchools also trained and deployed school recommender systems that simultaneously try to expose families to schools that satisfy their desires for their children (for example, rigorous course offerings, language immersion programs, compassionate and nurturing teachers) while also exposing them to schools “outside of their bubbles”—that is, quality schools they might not otherwise consider, perhaps because they have lower test scores, are in neighborhoods they wrote off before ever exploring, or something else? This multi-objective AI would not come without challenges of transparency and agency that accompany recommender systems deployed in other settings, but it could help spark new network connections that may not form otherwise.
These are just some examples, and they are not mutually exclusive with pedagogically focused applications. For example, while we likely lack the data to do this today, looking ahead, AI might help determine which students would benefit the most from which tutors—those who can not only help bridge learning gaps but also serve as relevant sources of mentorship, guidance, and inspiration. And expanding our focus in AI for education to include networks will not absolve us of the fairness concerns and other risks that existing deployments of AI continue to pose. Designing new applications of AI calls for careful and thoughtful exploration, especially as we as a society continue to respond to our rapidly changing AI landscape with a dynamic blend of fear, hope, concern, awe, and wonder. Of course, as in life itself, all of these emotions are important. Harnessing them to foster more inclusive network connections for the next generation of learners may be our most meaningful response of all.
Bernard Marr is a world-renowned futurist, influencer and thought leader in the fields of business and technology, with a passion for using technology for the good of humanity. He is a best-selling author of 20 books, writes a regular column for Forbes and advises and coaches many of the world’s best-known organisations. He has over 2 million social media followers, 1 million newsletter subscribers and was ranked by LinkedIn as one of the top 5 business influencers in the world and the No 1 influencer in the UK.
Bernard’s latest book is ‘Business Trends in Practice: The 25+ Trends That Are Redefining Organisations’
How Is AI Used In Education — Real World Examples Of Today And A Peek Into The Future
While the debate regarding how much screen time is appropriate for children rages on among educators, psychologists, and parents, it’s another emerging technology in the form of artificial intelligence and machine learning that is beginning to alter education tools and institutions and changing what the future might look like in education. It is expected that artificial intelligence in U.S. Education will grow by 47.5% from 2017-2021 according to the Artificial Intelligence Market in the US Education Sector report. Even though most experts believe the critical presence of teachers is irreplaceable, there will be many changes to a teacher’s job and to educational best practices.
Teacher and AI collaboration
AI has already been applied to education primarily in some tools that help develop skills and testing systems. As AI educational solutions continue to mature, the hope is that AI can help fill needs gaps in learning and teaching and allow schools and teachers to do more than ever before. AI can drive efficiency, personalization and streamline admin tasks to allow teachers the time and freedom to provide understanding and adaptability—uniquely human capabilities where machines would struggle. By leveraging the best attributes of machines and teachers, the vision for AI in education is one where they work together for the best outcome for students. Since the students of today will need to work in a future where AI is the reality, it’s important that our educational institutions expose students to and use the technology.
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Differentiated and individualized learning
Adjusting learning based on an individual student’s particular needs has been a priority for educators for years, but AI will allow a level of differentiation that’s impossible for teachers who have to manage 30 students in each class. There are several companies such as Content Technologies and Carnegie Learning currently developing intelligent instruction design and digital platforms that use AI to provide learning, testing and feedback to students from pre-K to college level that gives them the challenges they are ready for, identifies gaps in knowledge and redirects to new topics when appropriate. As AI gets more sophisticated, it might be possible for a machine to read the expression that passes on a student’s face that indicates they are struggling to grasp a subject and will modify a lesson to respond to that. The idea of customizing curriculum for every student’s needs is not viable today, but it will be for AI-powered machines.
Universal access for all students
Artificial intelligence tools can help make global classrooms available to all including those who speak different languages or who might have visual or hearing impairments. Presentation Translator is a free plug-in for PowerPoint that creates subtitles in real time for what the teacher is saying. This also opens up possibilities for students who might not be able to attend school due to illness or who require learning at a different level or on a particular subject that isn’t available in their own school. AI can help break down silos between schools and between traditional grade levels.
Automate admin tasks
An educator spends a tremendous amount of time grading homework and tests. AI can step in and make quick work out of these tasks while at the same time offering recommendations for how to close the gaps in learning. Although machines can already grade multiple-choice tests, they are very close to being able to assess written responses as well. As AI steps in to automate admin tasks, it opens up more time for teachers to spend with each student. There is much potential for AI to create more efficient enrollment and admissions processes.
Tutoring and support outside the classroom
Ask any parent who has struggled to help their teenager with algebra, and they will be very excited about the potential of AI to support their children when they are struggling at home with homework or test preparations. Tutoring and studying programs are becoming more advanced thanks to artificial intelligence, and soon they will be more available and able to respond to a range of learning styles.
There are many more AI applications for education that are being developed including AI mentors for learners, further development of smart content and a new method of personal development for educators through virtual global conferences. Education might be a bit slower to the adoption of artificial intelligence and machine learning, but the changes are beginning and will continue.
The benefits of AI are undeniable — but so are the risks of getting it wrong.
In this post, you’ll learn the 12 biggest AI mistakes organizations make and get practical ways to avoid these common missteps so you can effectively harness the power of AI.
1. Not Going “All In” on AI
AI is the most powerful technology humans have ever had access to — and now, every organization can put it to good use and create value for customers.
To fully realize the potential of AI, though, organizations must commit to its implementation and integration. It’s crucial to invest in the right infrastructure, personnel, and training to ensure successful AI adoption and avoid half-hearted attempts that can lead to wasted resources and suboptimal results.
2. Lack of Clear Business Goals
One of the biggest mistakes companies make is trying to implement AI solutions without having clear business goals in mind. This can result in a lot of wasted time and resources, with little or no return on investment (ROI).
If you’re going to launch AI initiatives in your business, make sure to establish specific, measurable objectives before you begin. By aligning AI projects with clear business goals, you can evaluate their impact and ROI, ensuring your efforts drive meaningful value for your organization.
3. Insufficient Expertise
Having the right expertise is critical for navigating the complexities of AI — but many companies underestimate the level of expertise needed and end up with poorly designed or inefficient systems.
Invest in hiring skilled professionals with expertise in machine learning, data science, and engineering, or focus on upskilling existing employees through training and education. Partnering with experienced consultants or vendors can also help you bridge knowledge gaps.
4. Ignoring Change Management
The successful integration of AI often involves significant changes to organizational processes, workflows, and employee roles. Neglecting the human aspect of AI adoption can lead to internal resistance, confusion, and reduced productivity.
Develop a robust change management strategy that includes clear communication, employee training, and support systems to help workers adapt to the new technology.
By addressing the cultural and behavioral aspects of AI adoption, you can facilitate a smoother transition and ensure your workforce is well-equipped to leverage the potential of AI with minimal disruption.
5. Poor Data Quality
AI models are only as good as the data they’re trained on. If the data used to train an AI model is incomplete, inconsistent, or biased, the model’s predictions may be inaccurate or unreliable.
In your organization, prioritize data quality by collecting, cleaning, and maintaining accurate, up-to-date datasets. Invest in proper data management practices to help you avoid skewed or biased AI models.
6. Neglecting to Involve the Right Stakeholders
Successful AI implementation requires collaboration across different teams, including IT, data science, business strategy, and legal. If a company neglects to involve the right stakeholders, they risk siloed decision-making, suboptimal results, and missed opportunities.
Make sure you’re engaging with all relevant parties early in the process, so you can identify requirements, manage expectations, and encourage collaboration, ensuring smoother AI adoption.
7. Over-Reliance on Black Box Models
Many AI models are complex, and their inner workings can be difficult to understand.
Companies that rely too heavily on “black box” models — complex machine learning algorithms and systems that don’t offer clear explanations for how they produce results — can run into problems with accountability and transparency.
These models are often characterized by their opacity, making it difficult for users, developers, or stakeholders to interpret underlying logic or decision-making processes.
Prioritize transparency in your organization’s AI models. This reduces the risks of unforeseen biases and errors and fosters trust. Consider providing clear explanations of how your AI systems work.
8. Inadequate Testing and Validation
Thorough testing and validation are essential for ensuring the reliability and accuracy of AI models. Plan to invest time and resources into rigorous testing processes, and be prepared to iteratively refine your models so you’re not making decisions based on faulty data.
9. Lack of Long-Term Planning
AI adoption requires long-term planning for ongoing maintenance, updates, and scalability. Companies that don’t plan for the future are at risk of becoming stuck with outdated AI models that don’t deliver expected outcomes.
When planning your AI initiatives, establish a comprehensive roadmap and allocate resources for the future, so your projects remain effective and aligned with evolving business needs.
10. Ignoring Ethical and Legal Considerations
AI models can raise a host of ethical and legal considerations, from data privacy and bias to accountability and transparency. Companies that don’t take these considerations seriously risk damaging their reputation, alienating customers, and even facing legal action.
Be proactive in addressing these types of issues, so your organization can build trust and avoid potential legal and reputational risks.
11. Misaligned Expectations
One common mistake is having unrealistic expectations about what AI can achieve.
While AI has transformative potential, it’s not a magic bullet. When making plans for artificial intelligence adoption, be realistic about AI’s capabilities and limitations. Manage stakeholder expectations throughout the implementation process, so you can avoid disappointment and ensure realistic assessments of potential project outcomes.
12. Failing to Monitor and Maintain AI Models
AI models require ongoing monitoring and maintenance to remain effective. Organizations must be prepared to regularly assess the performance of their AI systems. This will include updating and retraining models as necessary to account for changes in data or shifting business needs.
Neglecting this aspect of AI management can lead to outdated models that produce inaccurate or biased results. Establishing a robust monitoring and maintenance plan is essential for ensuring the long-term success of your AI projects.
Bernard Marr is a world-renowned futurist, influencer and thought leader in the fields of business and technology, with a passion for using technology for the good of humanity. He is a best-selling author of 20 books, writes a regular column for Forbes and advises and coaches many of the world’s best-known organisations. He has over 2 million social media followers, 1 million newsletter subscribers and was ranked by LinkedIn as one of the top 5 business influencers in the world and the No 1 influencer in the UK.
Bernard’s latest book is ‘Business Trends in Practice: The 25+ Trends That Are Redefining Organisations’
“In God we trust, all others bring data.” — W. Edwards Deming
“Without big data, you are blind and deaf and in the middle of a freeway.” — Geoffrey Moore
“If we have data, let’s look at data. If all we have are opinions, let’s go with mine.” — Jim Barksdale
“Without data you’re just another person with an opinion. -”Edwards Deming, Statistician
“Errors using inadequate data are much less than those using no data at all.”Charles Babbage, inventor and mathematician.
“If the statistics are boring, you’ve got the wrong numbers.” Edward Tufte, Professor emeritus of political science, statistics, and computer science at Yale University
“The ability to take data – to be able to understand it, to process it, to extract value from it, to visualise it, to communicate it – is going to be a hugely important skill in the next decades.” Hal Varian, Chief Economist, Google.
“I have no data yet. It is a capital mistake to theorise before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.” Sir Arthur Conan Doyle, Writer and Physician
In 1972, Mary Budd Rowe, University of Florida, coined the phrase “wait time” to describe the period of time between a teacher’s question and a student’s response. Rowe found that teachers typically wait between .7 seconds and 1.5 seconds before speaking after they have asked a question. However, when teachers utilize wait times of 3 seconds or more, Rowe found that there were demonstrated increases in student creativity and learning. Robert Stahl further expanded on Mary Budd Rowe’s concept in 1994 by coining the term “think time”—the period of uninterrupted silence for both teachers and students to reflect on and process their thoughts, feelings, and reactions. Stahl’s definition, although similar to “wait time,” more specifically labeled the action that teachers and students undergo during the period of silence as thinking.
Wait time 1 refers to the amount of time a teacher will wait for a student’s response to them asking a question before they will speak again.
Wait time 2 refers to the time a teacher waits following a student’s response before speaking.
Use Wait Time 1 to support learning
Mary Budd Rowe defined wait time as the time between when the teacher asks a question and the student responds. This is also called Wait Time 1.
She found that, traditionally, wait time has been less that 1.5 seconds. However, by doubling wait time to 3 seconds, several positive effects were experienced:
the length of responses increased
the correctness of responses increased
more students volunteered answers
“I don’t know” responses decreased
student confidence increased
Even teacher behaviors benefit from extended wait time. The quality of teachers’ questions increases while the number of questions asked decreases. Quality over quantity!
Now add Wait Time 2 to support learning
Wait Time 2 is the time after the student responds and the teacher replies.
Waiting an additional few seconds here can elicit an extended response from students. In some cases, the teacher may nod or give an “umm.”
A nonverbal signal that the teacher is considering allows students an opportunity to continue responding.
Students may not always be able to add any additional information, but Wait Time 2 is an opportunity for extra output and elaboration.
Oak Hill Middle School Teams 