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Different learners have different characteristics, needs, and preferences. They differ, for example, in their learning goals, their knowledge about the domain, their cognitive traits, and their learning styles. Furthermore, learning takes place in different situations and contexts. For example, a learner might learn at home in a quiet environment or on the bus while going to school or university. Individual differences as well as differences in the situation and context of learning can affect the learning process and can make learning either easy or difficult for a particular person in a particular situation.

As David Jonassen and Barbara Grabowski pointed out, many studies showed that considering individual differences can help students to learn more effectively. Furthermore, the consideration of context and situation has shown to lead to many benefits for learners such as more hands-on and authentic learning experiences. Adaptive learning systems focus on exactly this issue by aiming at considering individual differences and providing learners with courses, materials, recommendations, and feedback that fit their individual characteristics and situations. However, in order to do so, such systems need to have information about a learner’s individual characteristics and situation. The process of getting this information is called student profiling.

In this process, different types of data, such as student behavior data, student performance data, or survey data, are utilized and information such as students’ knowledge, learning styles, or cognitive traits is inferred. The identified information is then typically stored in a student profile. As such, the student profile is a crucial component of every adaptive learning system, enabling the system to access information about the learner and his situation, as well as provide a learner with suitable adaptivity based on this information. A student profile that is updated frequently is called a dynamic student profile. This entry discusses terminology used when discussing student profiles and explains the types of student profiles. It then details the information used in dynamic student profiles and describes how they are updated.

Terminology

There are a few terms that are very similar to the term student profile. For example, the term learner profile is typically used interchangeably with the term student profile. Another similar term is student model. While there exist a few works in literature that distinguish between student model and student profile, in most works, these two terms are also used in identical context. Another term to mention is the term user profile or user model. While there are many similarities between a user profile and a student profile, there are also some significant differences. Most importantly, whereas a student profile is used in the educational domain by learning systems, a user profile is typically used in the non-educational domain (e.g., business). While it appears that a student could also be seen as a user, and therefore, a student profile could also be seen as a user profile, there are several techniques and approaches that are specific for student profiling and not useful for building and updating a user profile. For example, research on student profiling of learning styles only makes sense in the educational domain. On the other hand, not every technique and approach for user profiling is useful for building and updating a student profile.

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