Task analysis basically is a process to identify human capabilities that supports the performance of a task under analysis. Therefore, it usually involves breaking down a task performance into smaller steps, and identifying different human capabilities that support the task performance. Within the structural framework of the IT field, task analysis is one segment of instructional design process. It is also the foundation for instructional design. Jonassen, Tessmer, and Hannum (1999) stated the purposes of task analysis as follows:

The shift of paradigm from behaviorism to cognitivism has changed the focus of task analysis on behaviors to the internal mental representations and processes. From the perspectives of behaviorism and cognitivism, learning is an outcome, either behavioral change as a result of shaping by a series of reinforcements or a reconstruction of knowledge representation as a result of mental process. Under these circumstances, if learning focuses on behaviors, then the target of task analysis should focus on the desired behaviors. Job task analysis, procedural analysis and functional job analysis (Jonassen, Tessmer, & Hannum, 1999) seem to serve the purpose. If learning focuses on transmission of "knowledge" as mental representation, then the target of task analysis should focus on the required "knowledge" entailed in the task. Methods, such as learning hierarchy, information processing, the methods that Jonassen, Tessmer, and Hannum (1999) classify as cognitive task analysis methods, meet the ends.

Chipman, Schrragen, and Shalin (2000) classified task analysis into two major categories, traditional task analysis, and cognitive task analysis, when they gave an overview of each chapter in their edited book Cognitive Task Analysis. Traditional task analysis refers to a breakdown of observable task performance into a series of overt observable behaviors that support the performance; cognitive analysis is "the extension of traditional task analysis techniques to yield information about the knowledge, thought processes, and goal structures that underlie observable task performance." (Chipman, Schrragen, & Shalin, 2000). The distinction mainly lies in overt physical actions and covert cognitive process. The development of cognitive task analysis was initiated because of the evolution from industrial age to information age, which was explained by Reigeluth (1999) as changes in instruction's supersystems that have impacts on the paradigm of education and training. The needs for standardization and efficiency gave more weight to the mechanistic analysis of the job performance; the demands for customization and effectiveness call for understanding of complex thinking and of process of problem-solving underlying the task performance. In fact, a lot of cognitive task analysis methods arise from analyses of human-computer interaction, which tackle the mental activities distributing and interacting between human and machines in decision-making, critical diagnostic and control tasks.

Jonassen, Tessmer, and Hannum (1999) described task analysis as a breakdown of performance into detailed levels of specificity", and as a front-end analysis, which consists of description of mastery performance and criteria, breakdown of job tasks into steps, and the consideration of the potential worth of solving performance problems. They also classified types of task analysis:

  1. Job/performance analysis: focusing on the behaviors engaged in by the performer
  1. Leaning analysis: focusing on the cognitive activities required to efficiently learn
  1. Cognitive task analysis: focusing on the performances and their associated knowledge states
  1. Content and subject matter analysis: examining the concepts and relationships of the subject matter
  1. Activity-based method: examining human activity and understanding in context

Such classifications recognize the differences in the functional purposes of task analysis and the types of human knowledge and capabilities to be analyzed. For example, learning hierarchical analysis, decomposing human cognitive skills into the rules and concepts in a hierarchical structure, could be used to identify topics that need to be taught and the sequence of teaching those topics. Activity theory, exploring the interaction between the individual in the society and the environment in terms of tools, rules and division of labors, could help identify what types of support need to be provided in the learning environment.

How do we describe tasks? Scholars developed different taxonomies of learning to help classify the tasks in order to identify the mental behavior, physical performance and affective state required by the task. There are three general domains: cognitive domain, i.e. knowledge and abilities requiring memory, thinking, and reasoning processes; affective domain, i.e. attitudes, dispositions, and emotions states; psychomotor domain, i.e. motor skills and perceptual processes.

Bloom's Taxonomy of Cognitive Domain

Recall previous learned information: specific, universals, and abstraction
Grasp the understanding of precious learned information
Break down informational materials into their component parts to develop divergent conclusions by identifying motives or causes, making inferences, and/or finding evidence to support generalizations
Creatively or divergently apply prior knowledge and skills to produce a new or original whole
Judge the value of material based on personal values/opinions, resulting in an end product, with a given purpose, without real right or wrong answers.


Robert Gagné's five learned capabilities

Intellectual Skills

Mental operations that permit individuals to respond to conceptualizations of the environment

  • Discrimination
  • Concrete concept/Defined concept
  • Rule using
  • Problem solving
Cognitive Strategy
An internal process by which the learner controls his/her own ways of thinking and learning
Verbal Information
Retrieve stored information
An internal state that affects an individual choice of action
Motor Skills
Capability to perform a sequence of physical movement

Ausubel's rote vs. meaningful learning

Ausubel (1968) described learning in terms of the relationship between learned materials and prior knowledge in the cognitive structure.

Rote Learning
Meaningful Learning
"learned materials are discrete and relative isolated entities which are only related to cognitive structure in an arbitrary, verbatim fashion, not permitting the establishment of significant relationships"
learning "take place if the learning task can be related in a nonarbitrary, substantive fashion to what the learner already knows, and if the learning adopts a corresponding learning set to do so"


Anderson's two types of knowledge

Anderson (1983) proposed two long-term memory stores: a declarative and a procedural memory. The knowledge in the declarative memory, i.e. facts and goals, is represented in terms of chunks. At the symbolic level, chunks are structured as a semantic network. On the other hand, the knowledge in the procedural memory is represented as production rules in forms of condition-action pairs, in which the flow of control passes from one production to another when the actions of one production create the conditions needed for another production to take place.

Declarative Knowledge
Procedural Knowledge
Knowledge about what it is
Knowledge about how to do things



Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.

Ausubel, D. P. (1968). Educational psychology: a cogntive view. New York: Holt, Rinehart and Winston.

Jonassen, D. H., Tessmer, M., & Hannum, W. H. (1999). Task analysis methods for instructional design.

In J. M. Schraggen, S. F. Chipman, & V. L. Shalin (2000), (Eds). Cognitive Task Analysis, p.p 365-383.Mahwah, Nj: Lawrence Erlbaum Association.