TiChi Introduction

Fitt's Law
Object-Action Interface
Prescriptive Theories
Fisheye strategy
Conceptual, semantic,
    syntactic, & lexical

Direct Manipulation

Information Processing
Hacker's Action Theory
Attention & Memory
Andersen's ACT-R
Knowledge & Mental
Social & Cultural

Theories in Computer human interaction
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Hacker's Action Theory
Umut Akdemir
October 2002


Action theory is a theory initially developed by German scientists in the field of applied psychology (Winfried Hacker, 1994[5]; Freese and Zapf, 1994[7]; Frese and Sabini 1985 [8]). Today it is applied in various fields of industry and science involving human action, like human capital in business [9], human computer interaction [1,4,10,13], and artificial intelligence [3].

Action theory defines a task-oriented view of human behaviors. The main purpose is to describe how a person completes a task. There are certain repeated patterns during completion of each task.


 Leontyev defines 3 levels of patterns throughout the completion of a task:

i)                    Motive-activity

ii)                   Goal-action

iii)                 Instrumental conditions-operations.

 In this approach, accomplishment of a top-level activity depends on accomplishment of lower level actions followed by operations. Motives are inspirations causing a set of goals, and actions for these goals consist of various operations. Operations can be directly and subjectively observed and recorded, however for the observation of higher-level tasks (goal setting, motivational level) indirect ways like interviewing or questionnaires may be needed.


Action theory distinguishes three levels of task completion, categorizing task completion mechanisms as skill-based, rule-based and knowledge-based.

 Different Levels of Action:

 1. Skill Based Level:
These actions are smooth, highly integrated actions, which are done in a nearly unconscious fashion by the users. The behaviors of the users are totally automated for a long time and users do not do any serious mental work during the realization of the task. A few good examples for this level are typing process of a secretary, save of a goalkeeper or password entry for software users.
 2. Rule Based Level:

 Here actions are defined and users apply the actions consciously going through a predefined procedure. These procedures can be given to users by proper training, or they can also be learned by experience. Different states in the system may cause different procedures to be applied (For instance if water levels fall abruptly in a dam, the workers should follow a set of procedures to store water). Many of the daily tasks fall into this category. e.g. browsing through various websites using hyperlinks.

 3. Knowledge Based Level:
 This is the level in which users use their mental capacity to solve a problem, which is not predefined. In order to accomplish the task, they need to set the goals and organize their movements for the solution. In this level we can define four stages in a complete cycle for goal realization.

 Stages of Actions:
 (i) Setting the goals and sub goals

 (ii) Planning the way to accomplish the goals, deciding on the means essential for this accomplishment
 (iii) Physical execution of the plan
 (iv) Evaluation and control of the results with feedback on the work done, application of the feedback in future goal setting and problem solving procedures.

 In the first two levels of action the control is feed-forward type, hence accomplishment of a task is predefined. Therefore it does not provide new information for the following tasks other than practice. However in knowledge based model there is feedback control, and after accomplishment of a task users gain information about their performance with feedback. Hence they recognize their mistakes and this improves their performance for future tasks. A good example for this may be unexpected errors met during development of a software by the creator. [1,2]


Scope, Application

Design of software interface for programming language development (e.g. Microsoft Visual C++, J Builder) is an application area for action theory. Any systematic approach to problem solving in these languages requires a decomposition of motives into sub-goals and smaller operations. Visual programming language software should encourage users in systematic approaches by providing top down design schemes. They should provide flexibility in switching between top-level activity design, and bottom level operation design. In Visual J++ while components can be added from the template in a top down style, at the same time actions on some smaller components can be edited synchronously without disturbing the top down design.
Moreover in Visual J++ code debugging is done while programmers type in the code; this feature provides users immediate feedback on their implementations. By this way they can improve their programming skills with debugging during typing process, learning to correct errors at their creation moments. Use of feedback is vital for allowing users to specialize in various environments.

 Design Principles:

            - Encourage transition to skill-based level

After typists are given the methodology for typing, improvement is based on practice; similarly pianists practice for training. For regular users of a program, skill based task completion takes much less time compared to rule based, and rule based completion takes much less time compared to knowledge based. Hence a computer program can be much more efficient if it lets users learn procedural ways to complete a task fast. Teaching skill-based knowledge to a novice user should be one of the main goals of a software application. For this purpose interactive tutorials can be helpful to let users automate procedures essential for them. These tutorials may require the users to do the same task for a certain number of times or let them build macros, which will do the task in an automated fashion.

-         Encourage exploration for improvement in knowledge-based and rule-based level

It is possible to improve user performance throughout software interaction. In order to let the user get feedback, software should have an undo and redo feature, which will encourage them to explore a wide variety of choices. During this phase a history-keeping feature can be helpful. Moreover for an application, in which tasks consist of discrete usage of sequential tasks, there can be an optional log analyzer, which may give feedback to the users about efficiency of their moves. For instance the analyzer may be able to grasp a task, which was done in “n” steps in the log file. If this task can be done in “k” steps (k<n), the analyzer can inform the users about this sequence of steps they may not be aware of.

-         Do not allow user to be stuck at a certain task, provide variety for accomplishing these tasks

Users should also have a variety of choices in order to accomplish certain tasks in the knowledge-base level. If the software provides only one way to accomplish any task, then in the situations that users are stuck, it becomes harder for them to mentally develop the exact response needed by the software.



Design of simulation software for students and employees is a good example for providing practice area for knowledge-base level. It gives users opportunity to explore, and provides procedural knowledge stimulating rule-based level in different situations. Figure-1 is taken from a simulation tool (SimPLE), an instance of dialysis simulation [11]. As it can be seen from the figure, users have control over the process, decomposing dialysis into subtasks. They can build macros from their subtask sequences; they can review how well they did with the help of feedback in the history window. 


Figure-1. Taken from “Creating creativity: user interfaces for supporting innovation”, Ben Shneiderman

Applicability to HCI

 Theory classification:

 Action theory can be thought of as explanatory and generative. It explains the systematic ways a person works in order to realize certain goals. Yet it is not predictive, it has no guidance on how different designs can improve the performance directly. Still it is generative as it gives models to software designers about principle patterns in user actions. It may give the designer extra insight about general organization of the interface (variety in procedures for knowledge level usage, practice facility for skill-level usage... as explained in scope/application).

 Limitations and impact on other people:


 Hacker also asserts that action theory is just a step towards filling cognition-action gap and the gap between theoretical and applied approaches [5]. It can be seen as a transition between theory and action. However it needs to be complemented by other theories in order to be used in HCI more efficiently. It distinguishes different types of user behaviors and determines the way users use their information to solve specific questions. Yet it is still far from being a prescriptive theory, which will guide software designers through use of different components.


Books and papers:

[1] Mark Antonius Neerincx, Harmonizing tasks to human knowledge and capacities- (dissertation), Groningen , 1995

[2] Matthias Rauterberg, Daniel Felix,Human Errors: Disadvantages and Advantages, 4th Pan Pacific Conference on Occupational Ergonomics 1996, Ergonomics Society Taiwan,
Erlbaum Associates, 1996.
[3]Rauterberg, M. (1996). Why and what can we learn from human errors. In: A. Özok & G. Salvendy (eds.), Advances in Applied Ergonomics (pp. 827-830). West Lafayette: USA Publishing.
[4]ARNOLD, B. & ROE, R. (1987) User errors in Human-Computer Interaction. In: M. Frese, E. Ulich & W. Dzida (Eds.) Human Computer Interaction in the Work Place. Amsterdam: Elsevier, pp. 203-220.
[5]Hacker, W. (1994): Action theory and occupational psychology. Review of German empirical research since 1987. The German Journal of Psychology, vol. 18, no 2, pp. 91-120.
[6] Leontyev, A. N. (1978). Activity, consciousness, and personality. Prentice Hall.

[7] Frese, M. and Zapf, D. (1994): Action as the core of work psychology: A German approach. In H.C. Triandis, M. D. Dunnette, L. M. Hough (eds.) Handbook of Industrial and Organisational Psychology, vol. 4. Palo Alto, CA: Consulting Psychologists Press

[8]Frese, M. and Sabini, J. (1985): Goal directed behaviour: The concept of Action in Psychology. London: Lawrence Erlbaum Associates.

[9] Rauch, A. & Frese, M. (2000). Human capital of small-scale business owners and business success: A longitudinal study on moderators and mediators. Presented at the ICSB World Conference 2000, Brisbane, June 16–18

[10] Higgins, P. (1998). Extending Cognitive Work Analysis to Manufacturing Scheduling. In P. Calder and B. Thomas (Eds.) Proceedings 1998 Australian Computer Human Interaction Conference, OzCHI’98, November 30–December 4, Adelaide, IEEE, pp. 236-243.

 [11] Shneiderman, B. (2000) Creating creativity: user interfaces for supporting innovation. In ACM Transactions on Computer-Human Interaction (TOCHI) March 2000

Online Resources

 [12]Further reading in action theory with good examples

[13]Task analysis in HCI, simulation of mental problem solving models

[14]Insight to learning process in various environments