Personalization
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Future classrooms are Personalized
In future classrooms, AI tutors will act as personal learning companions, adapting lessons to individual needs and paces. Micro-credentials earned through adaptive learning modules will showcase specific skills, empowering students to build personalized pathways, all guided by insightful learning analytics that illuminate strengths and areas for growth.
Read further for more information, media, real-life examples, and thought-provoking questions regarding this revolutionary future classroom trend.
Adaptive Learning
More advanced adaptive learning technologies will provide real-time feedback and dynamically adjust the learning path based on a student's progress. These systems might use artificial intelligence and machine learning to continuously adapt to individual learning styles, strengths, and weaknesses.
Discussion Question:
As learning becomes more personalized and individualized, how do you think educators will prevent a loss of collaboration and teamwork opportunities among students?
Present day example:
Mindspark by Educational Initiatives (created by the speaker in the above video) - An adaptive teaching software from India, focusing on Math, Science, and English. https://www.mindspark.org/
"Ei Mindspark adapts itself to every student’s learning level & progressively questions a student on a particular concept, providing feedback for their answers. If the student responds correctly, the next question presented is marginally more difficult than the previous one, which enables the student to self-learn the concept gradually and thoroughly."
AI-driven Personalized Tutoring
Personal AI tutors offer a world of possibilities for students. Imagine a tireless, patient companion who tailors lessons to your unique strengths and weaknesses, offering instant feedback and customized practice exercises. This personalized approach not only boosts understanding and confidence, but also cultivates a love for learning fueled by constant, encouraging support.
Discussion Question:
If you could choose one historical figure for your students to have a conversation with, who would you choose and why? What would you hope your students would learn from the experience?
Present day example:
As you may know, the current most popular chat-bot is the revolutionary ChatGPT. They have released "An AI tutor skilled in guiding students through their academic queries."
ChatGPT AI Tutor (requires subscription): https://chat.openai.com/g/g-QhTV4OrrZ-ai-tutor
Blockchain and Micro-Credentials
Micro-credentials combined with blockchain technology unlock a future where learning is bite-sized, relevant, and instantly verifiable. Learners will be acquiring specific, in-demand skills through flexible, short courses, then showcasing them on a secure, tamper-proof digital record. This combination empowers learners to build personalized skill portfolios, while employers gain transparency and trust in verifying qualifications.
Discussion Question:
How can educators ensure that the adoption of blockchain for microcredentials not only enhances the verifiability of skills but also promotes a culture of continuous learning and professional development?
Present day example:
"The European Blockchain Services Infrastructure (EBSI) was born in 2018 when 29 countries (all EU members states, Norway and Liechtenstein) and the EU Commission have joined forces to create the European Blockchain Partnership (EBP).
EBP’s vision is to leverage blockchain to create cross-border services for public administrations, businesses, citizens and their ecosystems to verify information and make services trustworthy."
ESBI - https://ec.europa.eu/digital-building-blocks/sites/display/EBSI/Home
Data Analytics for Intervention
Predictive analytics can help identify students at risk of falling behind and enable early intervention. By analyzing data on student performance and behavior, educators can provide targeted support to prevent academic challenges before they escalate.
Relevant article:
A review of learning analytics intervention in higher education (Wong, B. Tm., Li, K.C, 2020)
https://link.springer.com/article/10.1007/s40692-019-00143-7
Discussion Question:
What ethical considerations should educators take into account when using predictive analytics for early intervention, and how can they ensure that data-driven interventions are supportive rather than stigmatizing for students?
Present day example:
Schoolytics - student data platform https://www.schoolytics.com/
"Student progress is multi-dimensional, and therefore, your data should be too. The flexible nature of the platform means that you can track academic progress (assessment scores, grades, homework completion, etc.) as well as things like interventions and behavior/discipline."