Learning is personal because brains are not all alike. Throughout the educational system, teaching has traditionally followed a one-size-fits-all approach to learning. However, in recent years, a growing appreciation of individual preferences and aptitudes has led toward more personalized learning.
The four types of students are those who are highly self-motivated, those who prefer some coaching, those who are motivated by external rewards and those who resist learning altogether. In fact, truly personalized learning could be even more subtly individualized. Currently, “intelligent” Web-based education systems, development of “recommender” systems and creation of algorithms that adjust recommendations to the abilities of the student are projects attempting to meet the personalized education challenge. Web-based education systems are already common. Multimedia modules of information can provide text, audio, video, animation, or static graphics in any order suitable for the student.
Many methods for optimizing the order of presentation have been explored, such as the genetic algorithm. It eliminates unsuccessful presentation sequences and modifies successful ones for a new round of tests. In addition, there are also personalized learning methods that are designed for specific learning problems, such as a recommender system for learning English as a second language. In this system, students’ errors and learning weaknesses are tracked, and the students can rate the lessons that they are given. Data on weaknesses and interest are then used to generate a lesson tailored to the individual. In fact, recommender systems are widely encountered on the Web — search engines that fail to find a particular term often recommend alternatives. However, such systems have not yet been developed extensively for education.
Given the diversity of individual preferences and the complexity of each human brain, developing teaching methods that optimize learning is a major challenge for the software engineers of the future.
Advance personalized learning. (n.d.). Retrieved October 13, 2008, from http://www.engineeringchallenges.org/cms/8996/9127.aspx
The four types of students are those who are highly self-motivated, those who prefer some coaching, those who are motivated by external rewards and those who resist learning altogether. In fact, truly personalized learning could be even more subtly individualized. Currently, “intelligent” Web-based education systems, development of “recommender” systems and creation of algorithms that adjust recommendations to the abilities of the student are projects attempting to meet the personalized education challenge. Web-based education systems are already common. Multimedia modules of information can provide text, audio, video, animation, or static graphics in any order suitable for the student.
Many methods for optimizing the order of presentation have been explored, such as the genetic algorithm. It eliminates unsuccessful presentation sequences and modifies successful ones for a new round of tests. In addition, there are also personalized learning methods that are designed for specific learning problems, such as a recommender system for learning English as a second language. In this system, students’ errors and learning weaknesses are tracked, and the students can rate the lessons that they are given. Data on weaknesses and interest are then used to generate a lesson tailored to the individual. In fact, recommender systems are widely encountered on the Web — search engines that fail to find a particular term often recommend alternatives. However, such systems have not yet been developed extensively for education.
Given the diversity of individual preferences and the complexity of each human brain, developing teaching methods that optimize learning is a major challenge for the software engineers of the future.
Advance personalized learning. (n.d.). Retrieved October 13, 2008, from http://www.engineeringchallenges.org/cms/8996/9127.aspx
1 comment:
I think personalised learning is a suitable way for younger generation to learn new things. I think this kind of learning should also be adopted by university.
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