For a long time, experts and researchers have debated about the best way of education between phonics and whole-word recognition. Throughout the educational system, children as well as adults have been educated similarly following a “one-size-fits-all” approach regardless of individual differences. However, recently “personalized learning”, in which instruction is in accordance with a student’s individual needs, has gained a growing appreciation.
Why is personalized learning useful?
Learners can be divided into several categorizes. Some are highly self-motivated and learn best exploring a realm of knowledge. Some prefer a more structured approach. Another type is more motivated by external rewards and may learn best with step-by-step instruction. Others resist learning and do not have any motivation or interest in achieving goals.
The categorization of different learners is the base for developing personalized instruction. However, the truly personalized learning can be more individualized. According to their learning type, students prefer differently among learning examples, solving problems and so on. Under different conditions, people can also switch their preferences.
Many personalized learning approaches make use of computerized instruction. There are “intelligent” Web-based education systems, “recommender” systems that guide individual learner using Web-based resources, and algorithms that adjust recommendations to the abilities of the student.
What personalized learning systems are available now?
Web-based education systems are common. Systems that deliver and facilitate individual learning and multimedia modules that provide various forms of information have been designed. The delivery of instructional material is an important part of personalized learning. For instance, the instructional contents are delivered in different sequences in intelligent tutoring systems tailored for each individual. Many methods have been explored to optimize the order of presentation.
Recommender systems are widely encountered on the web also. These systems are more often designed for specific learning problem, such as mastering a second language. For example, some systems recommend books or reading lessons that most suited to an individual learner by tracking student’s errors and learning weaknesses.
What can engineering do to improve learning?
Ongoing research in neuroscience is providing clues to refine individualized instruction. A major challenge for the software engineers is to develop teaching methods that optimize learning, given the diversity of individual preferences and the complexity of each human brain. Engineers will play roles in most aspects of these complex problems. Mastery of these processes in advanced software could make learning more reliable.
Reference:
Advance personalized learning. (n.d.). Retrieved September 30, 2008 from http://www.engineeringchallenges.org/cms/8996/9127.aspx
2 comments:
The personalized learning is really a interesting topic.I agree with the opinion that the personalized learning will lead to better result of the learning, but what I wonder is that adjusting to the "fit for all teaching" is also a kind of learning.Facing with the same condition of teaching is very important, because as you mention the personalized learning is not conducted in large scale.
I agree that personalized learning will lead to better results though it makes teaching more complicated.
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