The Importance of AI in Education Use: Enhancing Education Across All Levels

AI in Education: Transforming Learning from Kindergarten to Vocational Training

In an era where technology permeates every aspect of life, artificial intelligence stands out as a transformative force in education. Its integration promises to address longstanding challenges like personalized learning, teacher workload, and equitable access to quality education. Empirical studies highlight AI’s potential to enhance student outcomes significantly. For instance, adaptive learning systems powered by AI have been shown to improve test scores by up to 62 percent, as demonstrated in research on platforms that tailor content to individual needs. This capability extends across all educational levels, from the foundational years in kindergarten to advanced vocational training, fostering an environment where learning is more engaging and effective.

The journey begins early, even in kindergarten, where AI tools introduce young learners to interactive and personalized experiences. In settings like early childhood education, AI-driven apps and games adapt to a child’s pace, helping with basic skills such as letter recognition and simple math. Programs like Osmo use physical pieces combined with iPad technology to teach interactively, while Khan Academy Kids provides adaptive activities that respond to a child’s progress. These tools not only make learning fun but also allow educators to track development in real time, identifying areas needing extra support. Research indicates that such early exposure to AI-enhanced learning can boost self-efficacy and positive attitudes toward education, setting a strong foundation for lifelong learning.

Moving to primary and secondary schools, AI’s role becomes even more pronounced in aiding teachers and enhancing classroom dynamics. Teachers often face overwhelming administrative burdens, but AI assistants can automate routine tasks like lesson planning and grading, freeing up time for more meaningful interactions with students. A study found that AI reduces grading time by 70 percent, allowing educators to focus on pedagogy. For example, platforms like Gradescope streamline assessment processes, providing consistent feedback. In classrooms, AI facilitates personalized learning paths; intelligent tutoring systems analyze student data to offer tailored guidance, improving performance by 30 percent and reducing anxiety by 20 percent, according to empirical data. This personalization is crucial in diverse classrooms, where students have varying needs. Moreover, AI tools like Classcraft gamify behavior management, tracking engagement and promoting positive interactions.

Universities leverage AI to handle complex academic demands, from research assistance to adaptive coursework. In higher education, AI-powered platforms like Carnegie Learning’s Mika provide personalized tutoring for subjects like math, helping bridge gaps for incoming freshmen. Studies show that such systems enhance learning outcomes by offering real-time feedback and customized pathways. AI also supports educators in curriculum design; tools like ChatGPT assist in generating teaching plans and rubrics, as explored in case studies where professors used generative AI to refine assessments. A systematic review of 48 empirical studies on generative AI in education underscores its role as an assistant in learning support and instructional design, improving efficiency and fostering creativity when integrated thoughtfully. However, the review cautions against over-reliance, emphasizing the need to maintain critical thinking skills.

Vocational training and professional courses benefit immensely from AI’s practical applications. In fields like healthcare, automotive repair, and manufacturing, AI simulates real-world scenarios through virtual reality and augmented tools, allowing hands-on practice without risks. For instance, AI-driven platforms in vocational schools analyze performance in simulations, providing instant feedback to refine skills. Empirical evidence from studies on AI in vocational education shows improved skill acquisition and job readiness. In countries like Germany, AI is integrated into apprenticeship programs to predict learning behaviors and adapt training modules. This approach not only accelerates skill development but also aligns education with industry needs, as seen in programs where AI optimizes resources and enhances outcomes in technical training.

Homeschooling, often a flexible alternative to traditional schooling, finds AI to be a game-changer for parents and students alike. Without the structure of a formal classroom, AI tools offer personalized curricula and tutoring. Platforms like Power Homeschool use AI to adapt lessons, providing reports on progress and identifying challenges. Surveys indicate that 44 percent of homeschool educators use tools like ChatGPT for planning, compared to lower rates in traditional settings. AI enables exploration of advanced topics; gifted homeschoolers use chatbots to delve into quantum mechanics or ethics, fostering unstructured learning. Case studies show AI reducing preparation time from hours to minutes, making homeschooling more accessible for busy parents while maintaining educational quality.

Public, private, and homeschooling sectors all reap benefits from AI, though implementation varies. In public schools, AI addresses equity by providing resources to underserved areas; adaptive systems help close achievement gaps. Private institutions often pioneer AI integration, using premium tools for enhanced personalization. Homeschooling benefits from AI’s flexibility, allowing tailored education without institutional constraints. Across these, AI supports educators universally. Teachers report significant time savings—up to 55 minutes per hour in creating materials—enabling focus on student engagement. Pedagogues use AI for data analysis, predicting performance and intervening early. In special education, AI tools like speech recognition assist hearing-impaired students, promoting inclusivity.

Real-world examples illustrate AI’s impact. In Texas, a school uses AI exclusively for core subjects, allowing students to learn in two hours daily with personalized tutoring, freeing time for projects. Duolingo’s AI chatbot aids language learning through interactive conversations. Khanmigo, powered by GPT-4, serves as a tutor and assistant, available to public users after pilots in U.S. schools. Carnegie Learning provides AI-based curriculum for K-12, emphasizing adaptive math instruction. These cases demonstrate improved engagement and performance, with AI handling routine tasks while humans focus on emotional support.

Globally, countries are advancing AI in education. Singapore’s Smart Nation strategy aims for AI leadership by 2030, using companions for feedback and automated grading. South Korea deploys AI digital textbooks and personalized tutors, shifting from memorization to deeper learning. China’s national curriculum includes AI from primary levels, focusing on ethics and applications. Australia adopted a framework for generative AI in schools, emphasizing responsible use. Finland integrates AI literacy into curricula, preparing students for digital society. India uses AI for performance prediction and complex concept visualization via apps like Embibe. The UAE and Hong Kong follow suit, with policies supporting AI in education. These implementations, backed by empirical reviews, show AI enhancing outcomes while addressing challenges like digital divides.

Despite benefits, challenges persist. Over-reliance on AI may diminish critical thinking, as noted in meta-analyses where effect sizes on higher-order skills are moderate. Ethical concerns include data privacy and algorithmic bias; the EU’s AI Act classifies education as high-risk, mandating transparency. Teacher training is crucial—71 percent of U.S. K-12 teachers lack formal AI education. Balanced integration, combining AI’s efficiency with human insight, is key. Future directions include AI literacy curricula and metacognitive focus to prevent laziness.

AI’s empirical-backed importance in education spans all levels, aiding teachers through automation and personalization while boosting student outcomes. As global adoption grows, thoughtful implementation ensures equitable, effective learning.

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References:

Adaptive Learning and Test Score Improvements

• A study by Knewton found that students using AI-powered adaptive learning improved test scores by 62% compared to those who did not. This demonstrates the impact of personalization in platforms like those mentioned for early education.
• Adaptive AI platforms show test score gains of up to 62% across diverse student populations. This supports claims on foundational benefits in kindergarten and schools.

AI Reducing Grading Time

• AI-assisted grading reduces time by 70%, allowing educators to focus on student support. Relevant to teacher workload in primary/secondary schools.
• Platforms like Gradescope reduce grading time by 70%. This backs automation benefits for educators.

Intelligent Tutoring Systems’ Impact

• Intelligent tutoring systems improve grades by 30% and reduce anxiety by 20%. From Pai et al. (2020), supporting university and school personalization.
• AI in education enhances performance by 30% and reduces anxiety by 20%. Empirical data from systematic reviews.

Systematic Reviews on Generative AI

• A review of 48 empirical studies on generative AI in education highlights its role in learning support and design. Details promises and concerns in higher education contexts.

Homeschooling and AI Usage

• 44% of homeschool educators use ChatGPT for planning. From Age of Learning survey, compared to lower rates in traditional settings.

Teacher Time Savings

• Teachers save up to 55 minutes per hour using AI for materials creation. From PowerSchool’s PowerBuddy case study.

Lack of Teacher AI Training

• 71% of U.S. K-12 teachers lack formal AI education. Highlights challenges in implementation.

Global Implementations

• Singapore’s Smart Nation strategy integrates AI for personalized learning and feedback. Aims for AI leadership by 2030.
• South Korea deploys AI digital textbooks for personalized learning. Focuses on shifting from memorization.
• China includes AI in national curriculum from primary levels. Emphasizes ethics and applications.
• Australia adopted a framework for generative AI in schools. Guides responsible use.
• Finland integrates AI literacy into curricula. Starts from young ages to spot deepfakes.
• India uses AI apps like Embibe for performance prediction. Visualizes complex concepts.
• UAE and Hong Kong support AI policies in education. Mandates AI curriculum.

Ethical and Regulatory Concerns

• EU AI Act classifies education as high-risk, mandating transparency. Addresses bias and privacy.

🍎 Classroom revolution! 81% of teachers are now embracing AI tools, transforming digital learning landscapes. Discover how educators are leveraging cutting-edge technology to enhance student experiences and revolutionize teaching methods. The future of education is here, and it's powered by intelligent innovation! #EducationalTechnology #ArtificialIntelligence #ClassroomTech #MachineLearning

🔗 https://aidailypost.com/news/teachers-leap-ahead-ai-adoption-81-actively-using-tools

#sicilia #sicily #happyisland #isolafelice #italy
#IntelligenzaArtificiale #ScuolaSiciliana #ModelloIA #Innovazione #EducazioneInItalia #TecnologiaEducativa #odino #DidatticaAvanzata
#ArtificialIntelligence #SicilianSchool #AIModel #EducationalTechnology #AdvancedTeaching
https://www.sicilianpost.it/un-aiuto-daodino-e-siciliano-il-primo-modello-ia-in-italia-dedicato-alla-scuola/

To every #parent, #educator, #techintegrator, and #schooladministrator of #primaryschools and #secondaryschools : I highly recommend the book “The Digital Delusion” by Jared Cooney Horvath. He takes off the rose tinted glasses on our views and hype of #educationaltechnology —how it has affected our children’s #cognitivedevelopment from #literacy to #CriticalThinking and what we can do about it moving forward https://www.linkedin.com/posts/jared-cooney-horvath_%F0%9D%97%A7%F0%9D%97%B5%F0%9D%97%B2-%F0%9D%97%97%F0%9D%97%B6%F0%9D%97%B4%F0%9D%97%B6%F0%9D%98%81%F0%9D%97%AE%F0%9D%97%B9-%F0%9D%97%97%F0%9D%97%B2%F0%9D%97%B9%F0%9D%98%82%F0%9D%98%80%F0%9D%97%B6%F0%9D%97%BC%F0%9D%97%BB-is-activity-7403636159559434241-64JK

Quality in humanitarian education

Humanitarian education is a huge undertaking. Each year, for example, 17 million trainees learn first-aid skills through face-to-face (FTF) training programmes run by the 189 National Red Cross and Red Crescent Societies worldwide. People of varied educational backgrounds join their local Red Cross or Red Crescent branch because they want to learn how to do first aid, how to prepare for or recover from disaster, or how to make their community more resilient. They also join to meet other like-minded people, building social ties and using the power of peer education to learn by doing.

FTF training has been efficient in terms of preparing volunteers to perform the tasks assigned to them, and social, peer-education training has also been an important component of the identity of volunteers and their sense of belonging to the organization. However, this formal way of teaching reproduces a one-way, didactic transmission of information, in which volunteers are given the knowledge they need to perform pecific tasks. Recent progress in massive open online courses challenge this model, although ques- tions remain about how effective and sustainable such learning approaches are (Daniel, 2012). This trend generates important questions for the IFRC concerning the use of educational technology while maintaining the purpose and quality of humanitarian education (Stracke, 2012).

In 2009, the IFRC published its first online course – World of the Red Cross and Red Crescent – to support the training of its international personnel. Experts developed courses on global health, security and other thematic areas. These courses were delivered through a single ‘Learning Platform’ which became part of the Red Cross and Red Crescent Learning and Knowledge Sharing Network in 2010. The network initially emphasized accredited learning, thus acknowledging that such learning remains the only valid currency in the professional world, even though Red Cross Red Crescent workers have acquired skills and knowledge in the field that deserve recognition.

By May 2013, less than 1 per cent of the world’s 13 million Red Cross Red Crescent volunteers had accessed the Learning Platform. The cost of internet access and the digital divide remain major obstacles. But the number of learners on the Learning Platform doubled in 2012 and its growth rate is accelerating. Users have completed nearly 60,000 online courses since the platform’s launch in October 2009, with more than 5,000 course registrations every month. At almost 50 per cent, the completion rate is a major success compared to the 20 per cent that is considered an acceptable rate in e-learning. Eleven National Societies already have more than 1,000 learners on the platform, with the Canadian, French and Swedish Red Cross among the early adopters. In November 2012, the Australian Red Cross, which had never used online learning in training, became the first National Society to adopt the Learning Platform for training all of its 3,300 staff members. It organized a nationwide roll-out and integrated online education into its workforce development strategy, with research already scheduled to document impact on performance.

For the first time, the Learning Platform enables volunteers to tap into a global knowledge community with no intermediaries prescribing or circumscribing what they should learn. By connecting to the platform, volunteers discover learning opportunities that relate to an essential aspect of their engage- ment: their thirst for learning as the means to changing their reality.

In 2012, following the Learning Platform’s success, the IFRC offered a ‘new learning’ programme using dialogue between learners and peer review to promote open, active learning. In its pilot phase at the Global Youth Conference, 775 people from more than 70 National Societies – four times more than the number of conference attendees – participated in learning ‘missions’ and ‘live learning moments’. Fifty-eight per cent of participants worked consistently on the learning activities, producing more than 140 pages of content. The same percentage said the programme improved their ability to think critically, analyse, evaluate and apply what they had learned about youth issues.

Questions arose about the learning effectiveness and impact of the IFRC’s online courses. Perhaps prompted by the legitimate demand that a new medium demonstrate its value, these questions also reveal an attachment to and assumptions about the comparative advantage of traditional learning modalities. However, researchers completed two comprehensive comparative meta-analyses in 2010. Their conclusions were definitive: since 1991, distance learning has delivered equal or better learning outcomes than traditional FTF programmes (Shachar and Neumann, 2010), while ‘blended learning’ (supplementing FTF instruction with online instruction) has not enhanced learning results (US Department of Education, 2010).

These studies demonstrated that quality is not determined by the means of delivery; however, they did not determine or assess the quality of the pedagogies used, whatever medium or technology. Many online learning technologies of the recent past, including the IFRC’s first online courses, were modelled on top- down, legacy training systems – somewhat like early film-making, which started by recording live theatre. As Bill Cope at the University of Illinois explains: “In their basic approach and use in practice, these are heavily weighted to the transmission of centralized knowledge from the center to the periphery.” They are “frequently not effective” as the transmitted knowledge is “often abstract and de-contextualized”, while “the value of existing local knowledge, practices and understanding” is “not recognized or incorporated into the learning experience” (Cope and Keitges, 2013).

The IFRC is exploring how innovation in learning connects back to National Societies’ rich history and culture, how technology might support learning from the local knowledge of National Society volunteers to strengthen cross-cutting knowledge, skill and competency development, and how collaborative learning communities might be developed across language and other barriers for National Society volunteers. More than 50 online courses destined for the Learning Platform are now in the pipeline, with clearly established, open standards for technology, content and pedagogy, aligned to the ISO 19796-1 quality standard for learning, education and training. Every course is now required to have an evaluation framework in place, to collect data that will be used in an annual review process.

But for humanitarian education to truly be transformed, further pedagogical innovation is needed. For example, online educational resources should also be accessible from mobile devices, notes IFRC’s new guidelines. This opens up new pedagogical possibilities: non-traditional contexts for learning, reaching remote constituencies and allowing interaction both between teacher and learner, and between learners. New courses, like the public health in emergencies modules, use mobile-first responsive technology to deliver an immersive learning experience to any device (mobile, tablet or desktop) with a modern browser. These courses are grounded in the field experience of IFRC experts and the evidence base. The peda- gogical patterns emphasize application of knowledge, analytical skills and the ability to discover, analyse and interpret from a multiplicity of data sources through teamwork.

The ability to recollect information still matters, but developing the skills and competencies that will enable the learner to perform in the face of the unknown takes precedence.

Written by Reda Sadki. First published in the World Disasters Report 2013: Focus on technology and the future of humanitarian action.

#educationalTechnology #humanitarianEducation #pedagogy #worldDisastersReport2013

Institution, Technology, and the Reproduction of Society

https://social.trom.tf/display/dbc8dc44-1668-d936-143d-d6b115871445

My Ed(1) Toolbox

https://aartaka.me/my-ed.html

#HackerNews #MyEdToolbox #EdTech #Productivity #Tools #Learning #Resources #EducationalTechnology

Household- and school-level parental education and academic self-concept development in elementary school

UNICEF. An Unfair Start: Inequality in Children’s Education in Rich Countries. https://www.unicef.org/innocenti/reports/an-unfair-start (2019). OECD.…
#NewsBeep #News #Headlines #Education #EducationalTechnology #General #Latvia #LifeSciences #LV #MathematicalModelsofCognitiveProcessesandNeuralNetworks #Neurobiology #Neuropsychology #Neurosciences #psychology
https://www.newsbeep.com/83689/

https://www.businessinsider.com/ai-in-school-south-korea-textbook-rollback-jobs-education-2025-8

South Koreans are neither alarmist technophobes nor unthinking technophiles -- all of us in education at whatever level or capacity should take note!

#AI #ArtificialIntelligence #Education #SouthKorea #EducationalTechnology #EdTech

Rewriting the Imaginary: Educators as Moral Agents of Reinstitution

https://social.trom.tf/display/dbc8dc44-2068-9c6a-7f97-79c133838630

A relational sociology of large language models in education

This paper with Morten Hansen is out now in the British Journal of Sociology of Education:

Generative artificial intelligence products are often heralded as a solution to the problems of education bureaucracies by providing individualised learning opportunities in a cost-effective way. We posit that this claim has not been critically examined from a relational and material sociological perspective. In this conceptual paper we therefore mobilise a relational and material sociology to query the relational potentials of large language models (LLMs) as compared to more traditional education tools. We conclude that the appeal of LLM tools like ChatGPT resides in their seemingly endless mutability, i.e. the tools appear to change to respond to their users’ needs. The relational challenge is to ensure that this apparent movement on the part of the tool does not lead to stasis on the part of the learner. Our discussion brings to the fore the often forgotten cognitive and pedagogical functions of seemingly ‘dumb’ and static learning tools.

#education #educationalTechnology #generativeAI #LLMs #MortenHansen #relationalSociology #tools

Strong Evaluation in a Flat World: Resisting the Neutrality of Platforms

https://social.trom.tf/display/dbc8dc44-2068-8d0d-266c-7e1280384879

For lower division or survey courses, a return to pen and paper and in class writing might be the answer, but I am not sure what to about those courses that require research papers.

https://undark.org/2025/07/01/california-colleges-ai-detectors/?utm_source=firefox-newtab-en-us

#AI #ArtificialIntelligence #TurnItIn #EducationalTechnology #Education #HigherEducatiion

What if critique in edtech was not resistance, but creation? My latest blog post argues for critique as a generative act - not just pushing back on solutionism, but reimagining what learning could be.

Critique as Creation - From Technological Solutionism to Political Pedagogy:
https://www.e-learning-rules.com/blog/0037_critique_as_creation.html

#eLearning #EdTech #CriticalPedagogy #DigitalEducation #EducationalTechnology #LearningDesign

Technology corporations open a second front in the campaign to destroy US higher education. Note that the aggressors are getting help from campus collaborationists.

https://www.nytimes.com/2025/06/07/technology/chatgpt-openai-colleges.html?unlocked_article_code=1.NE8.hOlu.KkxMdqtOBI-P&smid=url-share

#HigherEducation #Universities #AI #ArtificialIntelligence #EducationalTechnology #EdTech

Shenandoah Students Creating VR Experience Following the Lewis and Clark Trail

https://www.su.edu/blog/2025/05/21/shenandoah-students-creating-vr-experience-that-follows-the-lewis-and-clark-trail/

#HackerNews #ShenandoahStudents #VRExperience #LewisAndClark #TrailInnovation #EducationalTechnology

A 19-year-old managed to infiltrate one of the largest student data systems in the U.S., exposing millions of private records. How did a single breach shake up educational tech and leave us all questioning our digital defenses?

https://thedefendopsdiaries.com/the-powerschool-data-breach-a-cautionary-tale-for-educational-technology/

#powerschoolbreach
#cybersecurity
#dataprotection
#educationaltechnology
#infosec

Cornell Chronicle: Developers, educators view AI harms differently, research finds. “Teachers are increasingly using educational tools that leverage large language models (LLMs) like ChatGPT for lesson planning, personalized tutoring and more in K-12 classrooms around the world. Cornell researchers have found the developers of such tools and the educators who use them have different ideas […]

https://rbfirehose.com/2025/05/17/cornell-chronicle-developers-educators-view-ai-harms-differently-research-finds/

Manchester/Salford Critical Ed Tech Network Event, February 19th 12pm-2pm

Dear colleagues,

I hope this finds you well. I’m reaching out to invite you to an informal lunchtime gathering where we can share our thoughts and concerns about educational technology and its impacts.

This is part of an exciting international initiative happening that week, with similar discussions taking place in cities around the world: https://criticaledtech.com/2024/07/26/cset-2025-critical-studies-of-education-and-technology-an-invitation-to-connect/ [criticaledtech.com]

We’ll be hosting Manchester’s contribution:

Date: Wednesday, February 19th, 2025 Time: 12:00 – 14:00 Venue: Humanities Bridgeford Street Building, University of Manchester

The format is deliberately informal – we’re inviting colleagues to give brief 5-minute contributions on any of these themes:

• What concerns you about EdTech in our current context?
• What social harms are you observing?
• How do you see the political economy of EdTech playing out locally?
• Where do you see hope for positive change?

No slides needed – just come ready to share your thoughts and meet others interested in these issues. This is very much about building connections across Manchester and Salford institutions and finding potential collaborators.

Your insights will contribute to an international open-access report, and there’s potential for involvement in a UK-wide meeting planned for June in Oxford/London.

If you’d like to contribute a 5-minute talk, just let me know which theme you’d like to address. You’re also very welcome to come and join the discussion even if you don’t want to speak. Lunch will be provided. 

Please get in touch by January 31st to confirm your talk or just register to attend on the day.

Look forward to seeing some of you in February.

Mark Carrigan (UoM) and Mar Borràs (MMU)

#CriticalEducationalTechnology #edtech #educationalTechnology #manchester #salford

On being realistic with students about platformisation

I’ve increasingly come to believe that studying educational technology without experiencing its constraints, workarounds and breakdowns is like trying to learn to swim by reading books about water. The lived reality of platforms is filled with minor breakdowns, awkward compromises and institutional constraints which shape how they’re used in practice. Pretending otherwise just perpetuates the fantasy of seamless platformisation which tech firms cynically sell to educational leaders who ought to know better.

Rather than hide these challenges, we should embrace them as learning opportunities which illuminate how technology actually gets used in educational institutions. This means being open with students about our rationales and constraints, explaining why things don’t work as planned and helping them understand the complex reality of implementing digital education. Otherwise we risk producing graduates who understand the theory but lack the practical wisdom needed to navigate the messy reality of educational technology. The alternative is to perpetuate unrealistic expectations which set people up to fail when they encounter the reality of working with technology in educational institutions.

#digitalisation #educationalTechnology #pedagogy #platformUniversity #platformisation #platforms #teaching