A teacher for every learner: Rising to the challenge with computational intelligence

A few years ago, providing a teacher for every learner was proposed as one of five Grand Research Challenges in Computer Science and Engineering. Although current research interest with learning objects is on the decline, this paper argues that they can still play a major role in meeting the Grand Challenge. In particular, the paper discusses the granularity, sequencing, and context aspects of learning objects, showing how these aspects are at the heart of personalization in an e-learning system. However, catering for granularity, sequencing, and context in an instructionally principled fashion are difficult computational problems. The paper discusses and proposes a range of computational intelligence techniques that can address these problems and thus contribute to achieving the vision of a teacher for every learner.