Technologies That Learn and Adapt to Users

Adaptability is one of the most important benefits of learning enhanced by computer technologies because it allows for adjusting the learning materials, instructions, feedback, and learning strategies based on learners’ needs and ability. The programmability and high-speed computation features of computers enable developed learning systems to take learners’ personal factors, such as their knowledge levels, preferences, and learning styles, into consideration while interacting with them. Moreover, during the learning process, the learning system can even analyze system logs to evaluate the learning status of individual users so that personalized guidance or feedback can be provided to them readily. The ultimate goal of such systems and features is a personalized learning environment. This entry discusses the strategies for developing adaptive learning mechanisms and potential research questions on adaptive learning.

There are several strategies for developing adaptive learning mechanisms.

The advancements in computer and communication technologies in the past decades have significantly influenced the studies of adaptive learning. In particular, the growth and popularity of the Internet have encouraged the development of Web-based adaptive learning systems in which webpages are treated as the basic units for presenting learning contents, and the way of linking pages provides a new form of adaptability. In such webpage-oriented adaptive learning, content adaptation is accomplished by generating personalized webpages based on learners’ knowledge levels and learning status (e.g., browsed pages and average browsing time), while interface adaptation is achieved by modifying the layout of the learning content on each webpage. Among various adaptation strategies for Web-based learning, adaptive navigation could be the most commonly adopted. There are several ways of supporting adaptive navigation on the Web, including personalized navigation path recommendation, the provision of personalized link annotations, and personalized link hiding.

The recent popularity of mobile, wireless communication and sensing technologies has further enabled a new opportunity for conducting adaptive learning; that is, the learning system is able to adapt the learning content and learning tasks and provide instant guidance and feedback based on real-world environments in which the learners are located. For example, in a mobile learning activity, the students were guided by the learning system via a mobile device with wireless communication and sensing facilities to observe butterfly ecology. Once the students approached a learning target (e.g., an area where a particular species of butterfly or a specified butterfly food plant is found), the learning system showed the corresponding learning tasks and hints to them. In another study, the learning system could even recommend personalized learning paths in the real world.

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