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This is just an idea I had that could be used in the math classroom. I think it could be very cost efficient if you have to buy the materials on your own but will also allow your students to be creative and experiment with a hands on activity.

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The two key takeaways I got from the COSN report is the integration of technology in instructional design, especially since I am in math and I feel that it is tough, and the application of Universal Design for Learning principles. The integration of technology in the classroom is crucial in todays education. It promotes student engagement, supports personalized learning, and enables access to many instructional resources. I am particularly interested in how digital tools and platforms can be aligned with state standards to improve learning outcomes and make instruction more interactive, especially in math. The concept of the Universal Design for Learning is important since it promotes accessibility and inclusion by encouraging educators to offer multiple ways for students to be engaged and to express themselves. I would like to learn more about practical ways to implement the Universal Design for Learning in an online course design and explore tools that support it, especially since our school is implementing more online software and learning each year. I feel that these two take aways stood out to me because of my struggle integrating technology into math efficiently.

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Integrating Technology And UDL In A Math Classroom

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Integrating Technology And UDL In A Math Classroom

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I found this resource helpful showing me how I could use UDL in my content field. It also breaks down what UDL is more, speaks on the classroom culture, and provides some ways to put it into action.

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Math Teaching Models: Universal Design For Learning

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Thought I would try a video for this one! I think AI can be great but can also see some concerns with it as well. Also, I am not sure why the video is showing like this, but on my end when I actually click on it the video will open up.

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This article talks about the different ways artificial intelligence is affecting our world. It explains how AI can be really helpful by making life easier, improving communication with technology, and being used in lots of different industries. AI can also have some bad to it though. AI can be biased if the data it's trained and created on is not complete and people might start depending on it too much which could hurt their ability to think and process on their own. Also there are concerns about how much energy AI uses and if it is always being used in ways that are beneficial. One of the scarier things is how AI might affect jobs, human relationships, and even be used to spread false information. Overall, the article says we need to be careful with how we use AI and make sure it's helping people in the right ways. I think that this helps back a little bit of my concerns in the video I made. There is good, but the quality of human interaction could decline due to AI if it relied on to much.

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There is no denying that Artificial Intelligence has changed our lives. However, some might argue if it’s for the better.

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This article explores AI in education and encourages educators to consider both its advantages and disadvantages sense it is being used more. The good thing about AI in the classroom is that AI can personalize learning by adapting content to individual students needs, it can provide immediate and detailed feedback depending on how it is used, and it can assist teachers in creating lessons and assessments efficiently saving a lot of time and planning. Also, it promotes inclusiveness by offering tools like text-to-speech and speech recognition, which support students with special needs or just students that have accommodations. It also gives teachers access to a lot of educational resources. With that being said, the article also addresses several concerns. These concerns include the potential for academic dishonesty, data privacy and security risks, biases embedded in AI algorithms, the possibility of reduced teacher-student interaction due to relying on technology, and the financial burden of implementing AI systems if you are not using free options. I think that this article still piggy backs a little bit off of what I said in my video. Can AI be beneficial? ABSOLUTELY! WIth that being said, it definetily requires us to be careful when deciding when and how we use it.

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Generative AI has opened up a whole new world to administrators, educators, and students. The power of AI is undeniable, and understanding the pros and cons of artificial intelligence in education is essential for making informed decisions. To best use AI in schools, teachers and administrators need to know AI’s advantages and challenges.

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I had some issues with my screen casting and had to go through some loops to make this happen! Because of this I started with a powerpoint and then went into the actual website itself. I am glad I was able to get the voice part and screen recording to work at least. Besides this website costing money ($69) a year for the best version, I think it can be very beneficial for student engagement and collaboration. The website itself also offers a lot of support videos and a certification course if you want to master it.

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I do not have a lot of experience at all with a makerspace. I have seen it but never really considered using it in my classroom. With that being said, I found this online makerspace, GeoGebra, that combines multiple maths like geometry, algebra, statistics, and calculus. GeoGebra allows you create and move graphs, shapes, and equations. This makes visualizing and understanding tougher math concepts easier. You can move things around and see how everything changes in real time, so it is very interactive. It is also good for collaboration and sharing projects, which makes it really good for not only students learning but for teachers teaching math. I already see a way that I can use this when introducing pythagorean Theorem and Trig Functions in my Geometry class.

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GeoGebra - the world's favorite, free math tools used by over 100 million students and teachers

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Free digital tools for class activities, graphing, geometry, collaborative whiteboard and more

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This article is a little lengthy, which is why I only chose one to go along with my video, but the article is very detailed and helpful in my opinion. The article touches on the major advancement of brain-computer interface(BCI) technology, more specifically the coming together of powerful artificial intelligence and machine learning. With the decoding of noisy and complex brain activity with success, the integration makes BCIs' practical use more viable while enabling the systems to accommodate individual users. This study does bring up the important ethical and security concerns that come with BCI.. Because BCIs provide direct access to neural data, there is a high risk of privacy violations, unwanted data being seen or taken, and the misuse of sensitive brain data. The writers in this article emphasize the importance of putting in place security measures and ethical frameworks to safeguard users as BCI technology develops and becomes more popular. With all of this being said, it aligns with how I felt in my video. Is there a lot of good that could come from it? No doubt. There are still way to many flaws for me to feel comfortable with it though.

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Adaptive learning can be beneficial for teachers in the classroom by providing personalized instruction tailored to each student’s needs. Adaptive learning can modify content in real time based on student performance, helping students that struggle to receive extra support while other students can move ahead. This helps with closing gaps and providing enrichment. Personally, I could use this in our P.A.W.S sessions at my school. We have two days a week where we allow in school remediation and enrichment and I think this would be a great way to help all students during that time. Sometimes I have students of all skill levels and this would help break down and manage it better for sure.

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This article shows five major ethical concerns related to AI. They emphasize the risks of bias that is in AI systems. Transparency is another major issue, as many AI models operate like “black boxes,” making it hard to understand how decisions are made. The article also stresses the need for accountability. This part emphasizes that humans, not the AI or machines, must be held responsible for the decisions AI makes. The other concerns are privacy and how data is collected and used. Also, how AI could possibly influence the choices humans make.

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1. AI and injustice

"How can we create AI systems that are just and equitable? Many AI systems are machine learning systems that are trained on data. If the data reflects historical biases or injustices, then the systems that are trained on these data will do the same. There are significant concerns about disparate impacts on historically marginalized groups by AI systems because of the data they're trained on.

"For example, Amazon developed, implemented, and subsequently abandoned a hiring algorithm because they found that it was biased against women. The data they used to train the algorithm consisted of resumes submitted to Amazon, which were disproportionately from men. The problem of biased training data leading to biased AI systems is one of the most pressing AI ethics concerns."

2. AI and human freedom and autonomy

"How can we develop and implement AI systems that promote human freedom and autonomy rather than impede it? AI can be used to influence human behavior, sometimes in ways that are imperceptible and ethically problematic.

"AI systems have been used to influence voter behavior, as we saw in the Cambridge Analytica scandal and in the proliferation of deep fakes in political campaigning. AI systems can be used to influence workers to work longer hours, for example by nudging rideshare drivers to drive longer. Additionally, the data used to train AI systems are sometimes collected without informed consent, raising concerns about privacy and data protection.

"AI systems should promote the freedom and autonomy of all human beings, not just those who have the power to develop and profit from AI. How to achieve this goal is a challenging problem."

3. AI and labor disruption

"How can we develop and deploy AI systems that create opportunities for meaningful work and well-paying jobs rather than contributing to technological unemployment? And how can we facilitate equitable access to those jobs?

"There is no question that AI is disrupting labor markets, impacting available jobs and required skills. It is also clear that AI is disrupting many different kinds of work - it is not just jobs involving routine skills that are being affected, but also creative work. What is less clear is what the nature of these disruptions will be, who will benefit, and who will be harmed.

"Given that so many workers will be affected - in many different sectors and at many different levels - it is crucial that processes for developing and deploying AI systems are inclusive and involve the participation of those likely to be affected. How this should be done remains an important and open question."

4. AI and explainability

"Given that many AI systems make decisions or recommendations that can be life-changing for those impacted, it is important that those decisions be explainable, interpretable, and easily communicated to those who are thus affected. There are challenging technical questions surrounding the creation of explainable AI - and there are also challenging societal questions surrounding the extent to which we should allow unexplainable AI systems to affect people's lives.

"The European Union's General Data Protection Regulation (GDPR) has attempted to curb the impacts of unexplainable AI. For example, if someone is denied a loan based on an AI recommendation, they should have recourse under this regulation to an explanation of why their application was rejected. Whether a regulation like this should be adopted in the United States is an important societal question, and addressing this question well requires expertise from relevant technical and social scientific fields, as well as from affected publics."

5. AI and existential risk

"The possibility of superintelligent AI is the subject of much discussion - in films, fiction, popular media, and academia. Some prominent AI developers have recently raised concerns about this, even suggesting that artificial general intelligence could lead to the extinction of humanity. Whether these fears are realistic - and whether we should be focusing on them over other concerns - is hotly debated.

"Many think that these fears are more science fiction than reality and that a focus on them will distract from the ways in which AI systems are actually putting people at risk today. In particular, a focus on such fears could distract from how AI systems are currently exacerbating existing inequalities.

"Others - perhaps impressed with the achievements of large language models such as ChatGPT - believe that artificial general intelligence is on the horizon and that existential risks need to be taken seriously now. For them, there are real and pressing concerns about superintelligence and AI becoming smarter and more powerful than we are."

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5 AI Ethics Concerns the Experts Are Debating

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Just as social media exploded on the scene in the 2010s, artificial intelligence (AI) is having its moment. This technology comes with many benefits but raises many ethical concerns as well.

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IXL is an Adaptive Learning tool I use because it gives students their own skill plans based on what they need and also shows them the mastery goal as they work on the assignments. Also, if they miss a question it will show them the correct steps. One of the main things I like about it that our district does is link IXL the the students NWEA MAP Assessment scores. Based on their scores, IXL gives them their own skill plan to target areas of concern and also provides enrichment opportunities.

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By selecting “remember” you will stay signed in on this computer until you click “sign out.” If this is a public computer please do not use this feature.

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Austin McIntyre Book Creator Presentation

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According to the article, one of the biggest benefits is that Adaptive Learning makes learning more personalized, which helps keep students more engaged and allows them to learn more efficiently. The systems are able to adjust in real-time, which makes it easier for students to focus on areas where they struggle. The article also explains that adaptive learning is not perfect by any means. It can be expensive and complicated to set up if your school is not paying for it. Also, it works best when it’s part of a blended learning strategy that still includes some human interaction so technology alone is not typically enough. Overall, adaptive learning has a lot of potential to improve education, but it needs to be used in the right way to really be effective. I see this when I use IXL at times because even though it explains the problems to students when they miss it, sometime the interaction and explanation from me is needed to help them understand

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Any e-learning software worth its salt in today's market will include at least some form of adaptive learning system. It's not hard to see why. Organisations the world over have turned to the technology to help improve their training programmes, as well as to save time and money. But do you know all of the pros and cons of adaptive learning?

In this guide, we'll break down the positive and negative aspects of adaptive learning, and provide you with more insight about if and when to incorporate it into your training courses.

What is adaptive learning?

The idea behind adaptive learning is simple: people learn best when training materials are adapted to meet their needs. Adaptive learning harnesses the power of technology to automatically offer personalised educational content to each learner.

In practice, adaptive learning works by collecting data through an LMS or LXP. This includes information that is manually input by users as well as statistics regarding their use of the platform. Using this data, artificial intelligence is then able to determine what to serve to the user. This makes it possible to offer content and training methods that are tailored to each user's preferences and requirements-even at scale.

With adaptive learning, training is centred around the learner themselves. Instead of offering the same content to everyone, each individual has their own unique training pathway, and is only shown modules and material that will truly be valuable to them. In short, adaptive learning makes training more effective.

Benefits of adaptive learning

There are plenty of advantages of adaptive learning-so it's no wonder that more and more businesses are turning to it. Let's take a look at each of them in greater detail.

Training courses adapted to each learner

The first benefit of adaptive learning won't come as a surprise: it makes it possible to personalise learners' training courses. It makes selections and refines its choices in real time, offering increasingly tailored content to each individual as it gains more data about them.

To give an example, this process may start by asking the learner to fill out a questionnaire via an LMS. The adaptive learning algorithm will then analyse their results and will map out a training course that fits their existing knowledge level and the pace at which they gain new skills.

Higher retention rates, better results

Another plus point for adaptive learning is its ability to increase retention rates. To put it another way, it makes employees more likely to retain what they learn during the course and, in turn, helps them to develop new skills more easily. As such, adaptive learning is effective in promoting knowledge consolidation.

To help achieve this, the learner's LXP or LMS will enable them to put their knowledge into practice-for example, via the use of virtual workshops. Adaptive learning platforms can also jog learners' memories by offering them online materials, such as quizzes, at the end of their training course.

An intelligent coaching system

Thanks to artificial intelligence, it's now possible to offer more comprehensive support to remote learners than ever before. That's because adaptive learning systems come complete with coaches, as well as other kinds of virtual tutors.

These 'coaches' are, more accurately, chatbots, which are fuelled by data provided by the user. The more a learner communicates with their virtual coach-for example, by asking them questions, or letting them know which skills they want to build-the better the coach will be at understanding them and at providing relevant answers and support. And since these coaches are virtual, there's no need to book in a specific time slot to speak to them: they're available 24/7.

Improved learner engagement

Adaptive learning puts a strong emphasis on providing an excellent user experience. This is what sets it apart from earlier types of e-learning systems-and it also makes the training process much more engaging for learners.

Training courses now evolve to fit the learner's strengths and weaknesses, as well as their existing range of skills and experience. Everyone is able to learn at their own pace, and no one needs to waste time on unnecessary activities. Instead, employees will only be offered content that either meets their interests or helps them build a required skill.

Another plus is that, in contrast to traditional e-learning modules, adaptive learning offers a truly engaging environment. With formats such as group activities, virtual classes, online discussions and serious games, there's plenty to keep learners motivated and stimulated.

Less admin work

Automation is at the heart of how adaptive learning works. This means it allows stakeholders to skip the tedious admin and save huge amounts of time, especially as creating an adaptive learning course is simpler than ever. Employees also benefit from this system, as they no longer need to sit through training sessions that aren't useful for them. Instead, they can focus their attention on gaining knowledge that they can actually use on the job-and, as a result, will gain new skills even more quickly.

Disadvantages of adaptive learning

It can be tricky to get the hang of

Though adaptive learning systems are powerful and rich in features, they aren't always easy to get the most out of. To maximise the potential of the platform, training managers and designers need to put a lot of effort into planning out courses. After all, it requires the creation of suitable, high-quality adaptive learning content in multiple formats, including video and audio, as well as interactive elements. This can certainly prove complex, and it requires a strong understanding of how to use a variety of software.

It needs to be integrated into your blended learning strategy

We may be living in a digital era, but moving the training process entirely online has drawbacks. Without contact with others, learners are likely to end up feeling cut off and unmotivated. Meanwhile, it's been proven time and again that human interaction helps us to retain knowledge much more easily.

A common mistake, therefore, is to assume that adaptive learning can take the place of all other forms of training. Instead, it should be just one of the many tools in our arsenal, and form part of a broader digital learning strategy. Ideally, it should be used within the context of blended learning, in combination with face-to-face sessions and other forms of online content.

Your team needs to be able to correctly interpret its results

Adaptive learning systems generate a lot of data. It's up to your team to sort through, interpret and analyse it all-and with so much to get through, it can leave you with more questions than answers. Say, for example, a group of learners performed poorly on a test, and you need to figure out why. Did the learners actually fail to master the material, or were there problems with the questions themselves?

Similarly, your adaptive learning platform might offer you a huge variety of graphs, statistics and figures. It can become a bit overwhelming if you're not sure what to look out for! That's why it's important to keep your focus on the data that will actually help you to reach your goals and execute your strategy.

LMS platforms aren't always optimised for adaptive learning

When investing in a learning management system, you need to choose your platform wisely. Be sure to check that the provider offers adequate support and the right set of features to enable you to roll out your adaptive learning strategy. Thankfully, this is one problem that you can easily avoid. To guarantee a smooth and successful transition to adaptive learning, all you need to do is choose a platform like Rise Up!

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Adaptive learning is changing the world of training. Visit us to see some of the benefits and disadvantages of this approach.

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This article talks about a really interesting and kind of scary idea. The question is: "What if AI becomes conscious someday?" The article explains that we do not fully understand the consciousness of AI yet, so it’s hard to say for sure if AI could ever actually feel things like pain, sadness, and feeling in general. For this lets say it could. Then we would have to really think about how we treat AI, what we have it do, and how often we have it work. The article brings up ethical questions about whether we should build an AI system that could suffer and whether it’s even right to make machines that might be aware of their own existence. It makes you realize that AI not just a decision based on technology but also a moral decision based on how it progresses.

The link would not load in so here it is: https://www.vox.com/future-perfect/414324/ai-consciousness-welfare-suffering-chatgpt-claude

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AI systems could become conscious. What if they hate their lives?

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How to not torture ChatGPT and Claude’s successors.