#Practical AI Tools

[thisisgraeme]

Taking Action with AI in Education: Practical AI Applications for Educators (Volume 2)

Kia ora! Volume 2 of our AI in Education guide is out now! This hands-on guide gives educators practical strategies to use AI tools like ChatGPT, personalise learning, and create culturally responsive lessons. Download your copy and start exploring today!

Kia ora anō, koutou! After the release of Volume 1: AI Insights for Educators, I’m excited to share Volume 2: Practical AI Applications for Educators, co-authored with Michael Grawe. While the first volume laid a foundation of understanding around AI in education, this next guide is all about getting your hands dirty — exploring practical, hands-on ways to integrate AI tools into your teaching…

[whentherewerebicycles]

ok just going to think aloud through this two-part AI workshop... i will need to spend more time actually mapping it out but i want to do some big picture brainstorming about purpose/outcomes. here are some of the messy ideas i have:

i like workshops where our activities and discussions are geared towards developing or creating something students can take with them at the end - ideally something they will find useful beyond just the class or workshop. so my idea was that maybe we think about these workshops as an opportunity to develop our own personal codes of conduct around using AI tools in research. the phrase "code of conduct" feels a little too "here are the RULES" to me so i want to think of a different thing to call it... but basically i want to frame our work together as: I'm not going to tell you what to think about AI or how to use it - I'm going to guide us through a series of activities, discussions, and reflections where you are going to wrestle with your own feelings/thoughts/assumptions about AI tools and decide what feels right for you, in your own context, given your own values and priorities. what i want them to produce is basically an articulation of those personal values and priorities, plus some guidelines or guiding ideas they can use as they make decisions about the use of AI in their research projects.

i'm not sure how this will fit in yet but i know i want us to also think about the underlying emotions that lead us to use AI in situations where we would maybe rather not use it, or where we feel sort of torn or guilty about using it. like idk this is probably a cliche in conversations around AI and pedagogy at this point, but i think a lot of students use it because they feel immense pressure to produce at a certain level and they doubt their ability to produce at that level, whether because of skill or confidence or just like, the deadline is imminent and they didn't manage their time well enough to produce good work. i think in mentored research projects, students would probably also be tempted to use it because they would feel unsure about how to ask their mentor questions... faculty are not always like, sooo good at giving clear instructions or maintaining open channels of communication or encouraging students to ask questions, esp when students are doing independent/self-directed projects, and so i can see lots of situations where students might be like i don't want to seem dumb or behind so it's easier to just ask the machine than to ask the expert i'm working with. our students in particular also have tons of demands on their time (they're usually taking way too many classes so they can graduate early to save $$ and they're almost always working off-campus jobs and commuting long distances) so i think they often feel pressured to prioritize efficiency, and see the slow slog of learning as really inefficient. which it kind of is! it's iterative, it takes a long time, you have to mess up a bunch and figure out how to fix it, you go down rabbitholes that just lead to dead ends and then have to retrace your steps to figure out where you're supposed to be, etc etc. even well-structured classroom learning can feel that way, and students doing research are often working in unstructured, self-directed learning environments where they are having to both learn complex new skills AND learn to handle the project management aspects in a setting where they don't have a syllabus and a rubric to tell them what to do when. ANYWAY I gotta think about how to structure this part (small group discussion plus some kind of mindmapping board activity maybe?) but i think it will be useful for us to dig into the emotions that maybe influence our decision-making around using AI as a learning shortcut.

but then also SIGH i think i have to actually help them think about the less horrible ways to use AI. i had a meeting with our instructional coach yesterday and while she politely heard me out on my own fears/hesitations i think she is like, pretty pro-AI as a learning tool and was pushing me to actually think about how to teach students to use it responsibly. like instead of using it to generate content (ie cheat/take a shortcut to avoid the messy hard work of learning), we should be teaching students to use it to do things like generate practice problems or essay prompts to help them study, or to get feedback on a piece of writing without rewriting the essay, or to generate possible research questions so that students can evaluate and synthesize different options and make decisions about what to pursue... idk she was saying all this and i think my face was visibly like I Really, Genuinely Hate This lol but i'm sorry i can't control my own reactions!!! but it WAS kind of helpful to get the framing of like... we can't just tell kids to avoid it because it is about to be integrated into absolutely every aspect of their academic and professional lives whether they/we want it to be or not, so we HAVE to give them tools for using it responsibly and making critical judgments about it blah blah blah. and i GUESS i can see that!! these are probably the same decisions i will have to make about phone/technology/social media use as a parent... like i can forbid him to use screens (honestly i wish someone would forbid ME from using screens) but if he's going to be in all these settings where its use is expected and normalized, i have to give him tools for figuring out how he feels about these tools and making reasoned, value-based decisions about how he wants to use them.

i guess it's also helpful to notice like... thinking about this is helping ME clarify my own ethical framework for making these decisions. if i want to, i can say that i do not want to outsource any of my thinking to generative AI because it is morally and ideologically important to me to continue doing the slow slog of thinking and working and researching and learning and brainstorming with other actual human people, even if that working style is less "efficient." i can say that and i can then proceed to make decisions around using AI that are guided by that commitment. but even saying that lights up a fear pathway for me where i'm afraid that if i continue to work slowly while everyone around me speeds up, i will fall behind professionally, or i won't be able to produce work at the intellectual level of people who are relying on these technological enhancements, or whatever. so i have to think about that and then decide like, am i okay with that as a possible outcome, how will i manage those fears, are there situations where the work i am doing can be automated without loss or do i really want to have a blanket No for myself, etc etc. and that is useful thinking to do, like to sift through the fears and worries and what-ifs, and ALSO in doing so to realize that my personal framework does not have to be everybody's framework. but we should all HAVE a framework, and we should be able to talk about it openly and explain why we are making the choices we are making. and that is what i think i want the students to do... like i want our activities/discussions/etc to move them towards that space of being able to say, this is what i think and feel and believe, this is how i want to make decisions and this is how i want to justify the decisions i make.

anyway much 2 think about... gotta sift through some of the AI literacy resources she shared with me and work on articulating some learning outcomes... and then i think i can dive into actually building out some in-class activities and prompts.

[littlemeanings]

I really do not blame students for using AI within a capitalist education system that prioritizes efficiency, productivity, and short term memorization of profitable skills over genuine critical engagement. some skills are obviously crucial (i.e., writing for building critical thinking) but can and are still being built with minor adjustments like proctoring. the research shows cheating rates have not changed and have remained high since AI has become available. with the students that do cheat, it's due to deeper systemic issues. many high school and college students are working multiple jobs, caretaking for family members, have health issues, etc. and they will use whatever is available to give themselves some relief.

I get complaining about AI in passing. like I love to hate on it. but most people aren't really offering real ways to protest it other than just telling individuals they are evil for using it... which in any other area of politics we would think flawed and inadequate (re veganism, eco friendly lifestyle changes, etc).

sooo many AI-critical takes are liberal/idealist/individualist and not materialist. once again, we see individuals blamed for the profit-maximizing decisions of corporations (who are the ones responsible for the most harmful aspects of Al). instead of viewing the problems of AI as a symptom of structural issues requiring collective action, they would rather frame it as a personal character flaw of workers and students. and this individualizing of political issues closes off potential for a deeper critique, coalition building, and more opportunities for action. it's a way to both feel superior to other people and subscribe to inaction.

AI does not defy the capitalist historical pattern of labor-saving technology creation, monopolization, dependency enforcement, and exploitation. new technology increases productivity/profit expectations. these increased productivity expectations translate into pedagogy that also expects increased productivity. medical schools actively encourage regular AI use because they know doctors will now be expected to be faster and see more patients because of it - despite the fact most AI tools are not accurate enough to trust for medical information. however, this does not matter in the real capitalist world. what matters is how many patients you can see and how much money you can make for the shareholders and insurance companies.

just like all new labor-saving technology, AI decreases the bargaining power of workers and heightens capitalist contradictions: if you cant stay competitive and keep up with the pace as a worker you risk your job and livelihood.

I am not advocating for doctors, students, and other workers to continue uncritically using AI, but to understand their part in the class war and act accordingly. under capitalism, all productivity gains from new technology will always go straight to the company owners, who would rather expect double/triple the productivity of workers rather than give the time saved back to workers or god forbid give the workers ownership over the new technology.

AI will not save us from capitalism - capitalism develops the productive forces for its replacement. we must radically organize and self-educate. activism isn't about being perfect but doing the best you can consistently without burning yourself out and this will look different for everyone.

[ravkyu]

9.03.25

[lobotomysauce]

Are you pro-ai?

im mostly just mad about hbomerguy's awful plagarism video that was 4 hours of an overly extensively researched callout video for one cartoonishly evil guy that he decides to wrap up by being like "and to show how this applies on a broader societal level, AI is just The heckin' Plagarisms machine and its gonna be used to steal Copywrighted Disney Characters Small Artists Works!!!!!!"

[digitaldeeptech]

Must-Have Programmatic SEO Tools for Superior Rankings

Understanding Programmatic SEO

What is programmatic SEO?

Programmatic SEO uses automated tools and scripts to scale SEO efforts. In contrast to traditional SEO, where huge manual efforts were taken, programmatic SEO extracts data and uses automation for content development, on-page SEO element optimization, and large-scale link building. This is especially effective on large websites with thousands of pages, like e-commerce platforms, travel sites, and news portals.

The Power of SEO Automation

The automation within SEO tends to consume less time, with large content levels needing optimization. Using programmatic tools, therefore, makes it easier to analyze vast volumes of data, identify opportunities, and even make changes within the least period of time available. This thus keeps you ahead in the competitive SEO game and helps drive more organic traffic to your site.

Top Programmatic SEO Tools

1. Screaming Frog SEO Spider

The Screaming Frog is a multipurpose tool that crawls websites to identify SEO issues. Amongst the things it does are everything, from broken links to duplication of content and missing metadata to other on-page SEO problems within your website. Screaming Frog shortens a procedure from thousands of hours of manual work to hours of automated work.

Example: It helped an e-commerce giant fix over 10,000 broken links and increase their organic traffic by as much as 20%.

2. Ahrefs

Ahrefs is an all-in-one SEO tool that helps you understand your website performance, backlinks, and keyword research. The site audit shows technical SEO issues, whereas its keyword research and content explorer tools help one locate new content opportunities.

Example: A travel blog that used Ahrefs for sniffing out high-potential keywords and updating its existing content for those keywords grew search visibility by 30%.

3. SEMrush

SEMrush is the next well-known, full-featured SEO tool with a lot of features related to keyword research, site audit, backlink analysis, and competitor analysis. Its position tracking and content optimization tools are very helpful in programmatic SEO.

Example: A news portal leveraged SEMrush to analyze competitor strategies, thus improving their content and hoisting themselves to the first page of rankings significantly.

4. Google Data Studio

Google Data Studio allows users to build interactive dashboards from a professional and visualized perspective regarding SEO data. It is possible to integrate data from different sources like Google Analytics, Google Search Console, and third-party tools while tracking SEO performance in real-time.

Example: Google Data Studio helped a retailer stay up-to-date on all of their SEO KPIs to drive data-driven decisions that led to a 25% organic traffic improvement.

5. Python

Python, in general, is a very powerful programming language with the ability to program almost all SEO work. You can write a script in Python to scrape data, analyze huge datasets, automate content optimization, and much more.

Example: A marketing agency used Python for thousands of product meta-description automations. This saved the manual time of resources and improved search rank.

The How for Programmatic SEO

Step 1: In-Depth Site Analysis

Before diving into programmatic SEO, one has to conduct a full site audit. Such technical SEO issues, together with on-page optimization gaps and opportunities to earn backlinks, can be found with tools like Screaming Frog, Ahrefs, and SEMrush.

Step 2: Identify High-Impact Opportunities

Use the data collected to figure out the biggest bang-for-buck opportunities. Look at those pages with the potential for quite a high volume of traffic, but which are underperforming regarding the keywords focused on and content gaps that can be filled with new or updated content.

Step 3: Content Automation

This is one of the most vital parts of programmatic SEO. Scripts and tools such as the ones programmed in Python for the generation of content come quite in handy for producing significant, plentiful, and high-quality content in a short amount of time. Ensure no duplication of content, relevance, and optimization for all your target keywords.

Example: An e-commerce website generated unique product descriptions for thousands of its products with a Python script, gaining 15% more organic traffic.

Step 4: Optimize on-page elements

Tools like Screaming Frog and Ahrefs can also be leveraged to find loopholes for optimizing the on-page SEO elements. This includes meta titles, meta descriptions, headings, or even adding alt text for images. Make these changes in as effective a manner as possible.

Step 5: Build High-Quality Backlinks

Link building is one of the most vital components of SEO. Tools to be used in this regard include Ahrefs and SEMrush, which help identify opportunities for backlinks and automate outreach campaigns. Begin to acquire high-quality links from authoritative websites.

Example: A SaaS company automated its link-building outreach using SEMrush, landed some wonderful backlinks from industry-leading blogs, and considerably improved its domain authority. ### Step 6: Monitor and Analyze Performance

Regularly track your SEO performance on Google Data Studio. Analyze your data concerning your programmatic efforts and make data-driven decisions on the refinement of your strategy.

See Programmatic SEO in Action

50% Win in Organic Traffic for an E-Commerce Site

Remarkably, an e-commerce electronics website was undergoing an exercise in setting up programmatic SEO for its product pages with Python scripting to enable unique meta descriptions while fixing technical issues with the help of Screaming Frog. Within just six months, the experience had already driven a 50% rise in organic traffic.

A Travel Blog Boosts Search Visibility by 40%

Ahrefs and SEMrush were used to recognize high-potential keywords and optimize the content on their travel blog. By automating updates in content and link-building activities, it was able to set itself up to achieve 40% increased search visibility and more organic visitors.

User Engagement Improvement on a News Portal

A news portal had the option to use Google Data Studio to make some real-time dashboards to monitor their performance in SEO. Backed by insights from real-time dashboards, this helped them optimize the content strategy, leading to increased user engagement and organic traffic.

Challenges and Solutions in Programmatic SEO

Ensuring Content Quality

Quality may take a hit in the automated process of creating content. Therefore, ensure that your automated scripts can produce unique, high-quality, and relevant content. Make sure to review and fine-tune the content generation process periodically.

Handling Huge Amounts of Data

Dealing with huge amounts of data can become overwhelming. Use data visualization tools such as Google Data Studio to create dashboards that are interactive, easy to make sense of, and result in effective decision-making.

Keeping Current With Algorithm Changes

Search engine algorithms are always in a state of flux. Keep current on all the recent updates and calibrate your programmatic SEO strategies accordingly. Get ahead of the learning curve by following industry blogs, attending webinars, and taking part in SEO forums.

Future of Programmatic SEO

The future of programmatic SEO seems promising, as developing sectors in artificial intelligence and machine learning are taking this space to new heights. Developing AI-driven tools would allow much more sophisticated automation of tasks, thus making things easier and faster for marketers to optimize sites as well.

There are already AI-driven content creation tools that can make the content to be written highly relevant and engaging at scale, multiplying the potential of programmatic SEO.

Conclusion

Programmatic SEO is the next step for any digital marketer willing to scale up efforts in the competitive online landscape. The right tools and techniques put you in a position to automate key SEO tasks, thus optimizing your website for more organic traffic. The same goals can be reached more effectively and efficiently if one applies programmatic SEO to an e-commerce site, a travel blog, or even a news portal.

[mybreadsmybutters]

this site makes me feel like a liberal cuck for occasionally using AI to complete assignments like oh my GOD you dweebs dont even fuck with cheating in school!!!

[uitzinnigmp3]

YOUR SCHOOL IS FORCING YOU TO USE CHATGPT ??? thats crazy all my professors are telling us NOT to use it

lmao well it's like... they're telling us how to use it in the way THEY want us to so for example to reframe a research question, or to check if your text is written in the right style but they were very careful to not tell us too much useful stuff lmaooo and we're definitely not allowed to copy any ai text into assignments, but i guess they were like, well they're gonna use it anyway, better make sure they don't just write whole papers with it

[silverstrike]

You know... As someone who's spent almost 20 years of my life drawing, learning to improve, constantly trying out new techniques, learning new media, figuring out how lighting, coloring and anatomy works, yearning to become more skilled...

... it feels super disheartening that something a lazy tech bro farted out via MidJourney is gonna be deemed more impressive and more attention-grabbing, than someone who has put honest effort and hard work into making it.

[i-am-pinkie]

Writers are magic word people and do not need to use AI 😊

So it looks like NaNoWriMo are happy to have AI as part of their community. Miss me with that bullshit. Generative artificial intelligence is an active threat to creativity and the livelihoods of hundreds of thousands of people in creative fields.

Please signal boost this so writers can make an informed choice about whether to continue to take part in such a community.

[ravkyu]

1.03.25

i haven't been using tumblr for years now

[thisisgraeme]

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[richardtheteacher]

Discover how generative AI like ChatGPT is transforming the classroom. Learn practical ways teachers can use AI to plan lessons, differentiate instruction, give feedback, and boost student outcomes—all while saving time and energy.

[homeostasister]

*sigh* the website my physics class assigns problems on has this AI study tool to walk you through the steps of a problem if you don’t understand it, and it can honestly be pretty helpful sometimes, but it can also be completely, bafflingly wrong. What do you MEAN 1100/30 simplifies to 2200/30???

[local-magpie]

the reason they are likely against using those terms is because a decrease in learning skills isn't a permanent or necessarily serious thing - exclusively copying answers instead of trying to think things through also can cause a decrease in learning skills, as can relying too much on ANY tool that circumvents having to learn to do the thing. in all other cases this is perfectly reversable by just practicing learning, there's no reason to think this is any different. those three words are also especially prone to adding spin, something i dont think scientific reporting needs any more of.

[farmerstrend]

Safaricom & NGO Launch FarmerAI Solutions to Revolutionize Kenyan Agriculture

Safaricom PLC and Opportunity International, a global non-governmental organization, have developed FarmerAI in Kenya, an innovative AI chatbot that will provide smallholder farmers in underserved communities with real-time, relevant farming best practices. As per a 2022 report from the Kenya National Bureau of Statistics (KNBS), the agricultural sector contributes roughly 22.4% to the country’s…