Sentence examples for computers for learning from inspiring English sources

As computing technology has evolved, there has been significant research and a range of approaches exploring the use of computers for learning.

The achievements and promises of computers for learning go to the heart of the information revolution: Unlike the agrarian and industrial revolutions that helped learners indirectly by feeding them, transporting them to school and providing them with electricity, the information revolution helps much more directly because it deals with the principal currency of knowledge- information.

Right now, all thirty districts of the country have Internet centers with fifty computers for surfing the web at the low cost of fifty cents per hour, and several more computers for learning computer basics, like Microsoft Word.

It seems reasonable to revisit the question of how comfortable medical trainees are in using computers for learning (i.e., perceived ease of use), how they perceive their online learning experiences (i.e., perceived usefulness), and how these perceptions have changed over time.

Certainly the promises of computers for learning are impressive.

The use of computers for learning is often a complex issue which involves cognitive and metacognitive concerns.

The implementation of a computer game for learning about geography by primary school students is the focus of this article.

Employing a mixed-method explorative approach, this study examined the in situ use of and opinions about an educational computer game for learning English introduced in three schools offering different levels of freedom to choose school activities.

To tackle this challenge, Harvard researchers will record activity in the brain's visual cortex in unprecedented detail, map its connections at a scale never before attempted, and reverse engineer the data to inspire better computer algorithms for learning.

To tackle this, Harvard researchers will record activity in the brain's visual cortex in unprecedented detail, map its connections at a scale never before attempted, and reverse-engineer the data to inspire better computer algorithms for learning.

In subsequent phases of the project, researchers at Harvard and their collaborators will build computer algorithms for learning and pattern recognition that are inspired and constrained by the connectomics data.