Digital technology has made learning more accessible, personalized, collaborative and data-driven. However, its benefits are uneven because outcomes depend on access, digital literacy, platform design and how teachers and learners use the systems.
This question belongs to the human knowledge context, specifically learning and education, and is shared by SL and HL students.
| Change | Mechanism and significance |
|---|---|
| Wider access | Networks and the internet allow learners to access courses, videos, digital libraries and teachers across geographical boundaries. This can reduce barriers created by location, but unequal connectivity and device access can deepen the digital divide. |
| Personalized learning | Algorithms can adjust content, difficulty and feedback using learner performance data. This may support individual progress, but profiling can reproduce bias or reduce learners to incomplete data patterns. |
| Collaboration | Shared documents, learning platforms and video conferencing create virtual learning spaces. Students can collaborate across locations, although participation may be limited by language, time zones or platform access. |
| Changing authority | Learners can obtain information without depending entirely on teachers or textbooks. This redistributes power, but misinformation means learners must evaluate sources and distinguish information from reliable knowledge. |
A common misconception is that digital technology automatically improves learning. Technology does not cause educational progress by itself; effects emerge from interactions among digital systems, teachers, institutions, learners and social conditions.
Real-world example: Khan Academy introduced Khanmigo in 2023, after the 2022 coursebook, as an AI-supported tutor and teaching assistant. The system uses generative AI to provide prompts and feedback rather than simply supplying answers. Its impacts include new forms of immediate support for some learners and planning assistance for teachers. Its implications include opportunities for personalized learning, alongside risks involving inaccurate output, data privacy, unequal access and over-reliance on automated feedback.
Exam technique: For an explain question, connect each change to a clear mechanism. For discuss or evaluate, balance opportunities and risks, compare at least two affected groups, and distinguish observed impacts from future implications.
