# Extracting Searching as Learning Tasks Based on IBRT Approach
## 3 Data and Methods  
### The Definition of Tasks in SAL  
[PERSON] et al. [15] first figured out the importance of task extraction and proposed that a task is the atomic information requirement that results in one or more queries. On the basis of [PERSON]'s work, [PERSON] et al. [18] proposed a more general definition of the complex web search task that captures the hierarchical structure of tasks and their associated subtasks. They also proposed that each search task can be divided into one or more subtasks which can also be considered independent tasks of the search and can eventually be decomposed into simpler tasks until each task represents the atomic information needs of the user. In addition, [PERSON] et al. defined a complex web search as a multifaceted or multistep information requirement consisting of a set of related subtasks, each of which may recursively be considered a search task [18; 41]. This definition is more general because it captures all kinds of tasks, whether complex or noncomplex.  
Research by [PERSON] et al. [1] pointed out that it is very important to distinguish different types of learning structures in SAL. When the information is considered to be knowledge or belief from constructivist epistemology, searching will be conceptual as a learning process. Users develop learning tasks and measure search results according to the conceptual changes of knowledge structure and beliefs, and they gradually change their knowledge structure to complete search-based learning tasks.  
In addition, the authors of [2; 42; 43; 26] pointed out that learners show different learning styles, which lead to different search preferences. [PERSON] et al. [44] classified learning styles into four categories: diverger, assimilator, converger, and accomodator; and this theory has become one of the most widely used learning models for students [45]. Moreover, he also proposed that investigating learners' learning styles before a course can help teachers achieve better teaching effects [46]. On the basis of [PERSON]'s theory, [PERSON] et al. [47] proposed that learning styles affect the learning process (e.g., planning tasks) and further affect students' learning outcomes. [PERSON] et al. [48] pointed out that the understanding of learning styles helps to develop methods to improve students' performance.  
According to the above studies, we consider that the tasks in SAL cover the following characteristics:  
* Hierarchical: Each process of SAL may cover one or more tasks, and each task may be divided into subtasks. In addition, subtasks can also be independent tasks. Therefore, an effective task extraction method should be able to accurately identify and represent this hierarchy.
* Learning style: In the process of SAL, learners divide learning goals depending on their learning style. Therefore, it is also important to develop a learning style-oriented SAL task extraction method.  
On the basis of the definition of tasks in complex search ([PERSON] et al. [5]), in this paper, we propose the definition of SAL tasks from the perspective of the tasks in SAL below.  
Multifaceted or multistep learning activities are generated by learning needs; in the process of satisfying a learning goal, the learner may partition the learning goal into a set of tasks according to their own learning style, and each task may be recursive to be partitioned to a set of low-granularity tasks.