e-Learning Ecologies MOOC’s Updates

differentiated instruction

Differentiated instruction is an approach whereby teachers adjust their curriculum and instruction to maximize the learning of all students: average learners, English language learners, struggling students, students with learning disabilities, and gifted and talented students. Differentiated instruction is not a single strategy but rather a framework that teachers can use to implement a variety of strategies, many of which are evidence-based. These evidence-based strategies include:

Employing effective classroom management procedures

Grouping students for instruction (especially students with significant learning problems)

Assessing readiness

Teaching to the student’s zone of proximal development

Adaptive learning tools enable differentiated instruction. Early attempts at adaptive learning worked only for very specific content and curricula. With recent AI advances in language models and video understanding, we can now apply adaptive learning technology to almost any type of class assignment or lesson at an unprecedented scale. When students receive individualized, in-the-moment support, the results can be magical.

Google classroom is testing something new with practice sets. The feature allows teachers to create interactive assignments and provides students with real-time feedback. The instant feedback that kids receive is described to be like having a teaching assistant in the classroom at all times. The technology helped give students 1:1 attention and validation — so they knew right away whether they got a problem correct or incorrect — and drove students’ intrinsic motivation and engagement through the roof.

This elevates a forgotten fundamental part of the learning process - it is personal, and therefore, with adaptive learning technologies, educators can receive data that Students get real-time feedback as they complete practice sets, so they know whether they’re on the right track.

Adaptive learning technology saves teachers time and provides data to help them understand students’ learning processes and patterns. For example, with practice sets, teachers can quickly see a student’s attempts at a given problem, so they know where a student got stuck and can identify areas for improvement. Since assignments are auto-graded, teachers can devote more time to making sure that each student gets the instruction and practice they need to succeed.

 

References

https://iris.peabody.vanderbilt.edu/module/di/cresource/q1/p01/

https://blog.google/outreach-initiatives/education/adaptive-learning-technology/#:~:text=What%20exactly%20is%20adaptive%20learning,address%20their%20unique%20learning%20needs.

https://inspiredelearning.com/blog/what-is-adaptive-learning/