With the SAMR model, developed by R R. Puentedura (2006), teachers’ adoption and integration of educational technology works through stages. The teachers' skills and confidence develops in the usage and integration of technology into their teaching and learning experiences.
“SAMR” is an acronym for four levels of technology integration:
“S” for Substitution, “A” for Augmentation, “M” for Modification, and “R” for Redefinition.
Considering the inclusion of AI tools in relation to the SAMR model, teachers explore the transformative potential of AI to create more engaging, effective, and equitable learning experiences for all learners.
Substitution:
AI-powered worksheet generators: Teachers use AI to create differentiated worksheets, replacing manually created ones. This saves time and allows for easy customization based on Learner needs.
AI-powered marking assistants: AI assists in marking assessments like multiple-choice quizzes, freeing up teacher time for more complex tasks like providing feedback on essays.
AI-powered presentation creators: Learners use AI tools to generate presentations from their notes or outlines, replacing traditional slide creation. This allows them to focus on content instead of design.
AI-powered flashcard creation: Learners use AI to generate revision or flashcards from their learning material, replacing handwritten cards. This allows for quick and efficient study material creation. Teachers could also use this idea.
AI-powered speech-to-text: Learners use AI to recognise audio-to-text recognition, replacing traditional reading aloud. This helps develop learners' reading skills as they read aloud and the AI assists them.
AI-powered dictation: Instead of writing by hand, learners dictate their ideas to an AI tool that converts speech to text. This can be helpful for learners with dysgraphia or those who are busy using their hands for an experiment or learning activity, and can speak and record their notes at the same time.
AI-powered language translation: Learners use AI to translate texts from one language to another, replacing traditional dictionaries or translation websites. This can help learners learn new languages or access information in different languages.
AI-powered image recognition: Learners use AI to identify objects or landmarks in images, replacing traditional image searches or visual dictionaries. This can be helpful for learners learning about art, history, or science.
Augmentation:
AI-powered grammar and writing style checkers: Learners use AI to improve the grammar, clarity, and style of their writing, going beyond basic spell check. This can help learners develop their writing skills and produce higher-quality work.
AI-powered personalised reading recommendations: AI analyses learner reading level and interests to recommend relevant books and articles, enhancing independent reading time.
AI-powered writing feedback tools: Learners receive detailed feedback on their writing beyond grammar and spelling, including suggestions for improving clarity, organisation, and style.
AI-powered research summarisation tools: Learners use AI to summarise lengthy research articles or complex texts, helping them grasp key concepts quickly.
AI-powered study guides: AI analyses learning materials and generates customised study guides, highlighting key concepts and areas where learners need to focus.
AI-powered research assistants: Learners use AI to find relevant information and sources for their research, refining search queries and filtering results based on their needs. This can help learners save time and access more comprehensive information.
AI-powered personalised learning platforms: Learners use AI-powered platforms that adapt to their individual learning styles and pace, providing customised content and exercises. This can help learners learn more effectively and efficiently.
AI-powered feedback tools: Learners receive immediate feedback on their work from AI-powered tools, identifying areas for improvement and providing specific suggestions. This can help learners learn from their mistakes and improve their understanding.
Modification:
AI-powered personalised learning pathways: AI creates individualised learning paths for each learner, adapting to their pace, interests, and goals.
AI-powered global problem-solving simulations: Learners collaborate with peers worldwide in AI-powered simulations to address real-world challenges like climate change or poverty.
AI-powered learner portfolio creators: Learners use AI to curate and showcase their best work in dynamic, multimedia portfolios that demonstrate their learning and growth over time.
AI-powered interactive simulations: Learners engage with AI-powered simulations that allow them to manipulate variables and observe the outcomes, exploring complex concepts in a dynamic way. This can help learners develop a deeper understanding of scientific or mathematical principles.
AI-powered virtual field trips: Learners experience immersive virtual field trips powered by AI, exploring historical sites, museums, or natural environments from anywhere in the world. This can provide access to experiences that might not be otherwise available.
AI-powered creative writing tools: Learners use AI to generate different story ideas, create unique characters, or explore alternative plot lines, fostering creativity and expanding narrative possibilities. This can help Learners develop their storytelling skills and explore new genres.
AI-powered music composition tools: Learners use AI to create original music compositions, experimenting with different melodies, harmonies, and rhythms. This can help learners explore their musical creativity and learn about music theory.
Redefinition:
AI-powered virtual labs: Learners conduct experiments in AI-powered virtual labs, manipulating variables and observing results in a safe and controlled environment.
AI-powered debate partners: Learners engage in debates with AI-powered bots, practising argumentation skills and exploring different perspectives.
AI-powered historical character interviews: Learners interview AI-powered historical figures, asking questions and learning about their experiences in an interactive way.
AI-powered learner portfolio creators: Learners use AI to curate and showcase their best work in dynamic, multimedia portfolios that demonstrate their learning and growth over time.
AI-powered interactive timelines: Learners create dynamic timelines with AI, adding multimedia elements and exploring historical events in a non-linear way.
AI-powered collaborative design projects: Learners collaborate with peers from around the world on AI-powered design projects, using virtual reality and AI tools to create and test solutions to real-world problems. This can foster global collaboration and problem-solving skills.
AI-powered personalised learning companions: Learners interact with AI-powered learning companions that provide personalised support and guidance throughout their learning journey, adapting to their individual needs.
Exploring the transformative impact of Large Language Models (LLMs) and Gen AI models on learners' learning and the way teachers' teach is impacting on learning and teaching pedagogies.
LLMs are reshaping pedagogical approaches, such as
Personalised Learning: LLMs can analyse learner data and tailor learning experiences to individual needs, pace, and learning styles.
Inquiry-Based Learning: LLMs can facilitate inquiry-based learning by acting as more-knowledgeable assistants that can answer learner questions, provide relevant information, and guide research.
Collaborative Learning: LLMs can support collaborative learning by facilitating communication and knowledge sharing among learners.
Formative Assessment: LLMs can provide real-time feedback on learner work, allowing for immediate adjustments to instruction.
AI models are creating new opportunities and challenges for educators and learners.
AI may assist us, as teachers, and our learners in these many ways.
However, more than ever it is imperative that we, as teachers, focus on fostering critical thinking among all our learners.
Teach learners how to ask questions.
Encourage curiosity!
Expect analysis and examination of consent and not just accepting the AI response.
Create an awareness of ethics and being responsible AI users.
Empower learners to be conscious of AI bias, and to fight against perpetuating the biases further.
Think about assessments: What questions we are asking? Which home tasks may be used towards a term mark?
Ensuring access and equity to all learners in diverse learning environments.
More than ever we need to know the ability level of our learners.
Promoting the importance of self, and the value of being lifelong learners for ourselves, as teachers, and for our learners going into the future with AI.
Reference
Anderson, L. W., Krathwohl, D. R., Airasian, P. W., Cruikshank, K. A., Mayer, R. E., Pintrich, P. R., Raths, J. & Wittrock, M. C. (Eds.). (2001). Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives. New York: Longman.
Puentedura, Ruben. (2006) SAMR model http://hippasus.com/blog/archives/227 and http://www.hippasus.com/
Dr. Karen Walstra conducts professional teacher development workshops about technology integration.
Contact Karen was workshops and presentations for your staff development, at info@karenwastraconsulting.co.za
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