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Hacker's Action Theory
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Hacker's Action Theory
Action theory is a theory initially developed by German scientists in the field of applied psychology (Winfried Hacker, 1994; Freese and Zapf, 1994; Frese and Sabini 1985 ). Today it is applied in various fields of industry and science involving human action, like human capital in business , human computer interaction [1,4,10,13], and artificial intelligence .
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:
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:
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.
Knowledge Based Level:
Planning the way to accomplish the goals, deciding on the means essential
for this accomplishment
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]
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.
- 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.
Figure-1. Taken from “Creating creativity: user interfaces for supporting innovation”, Ben Shneiderman
Applicability to HCI
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).
Hacker also asserts that action theory is just a step towards filling cognition-action gap and the gap between theoretical and applied approaches . 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:
 Mark Antonius Neerincx, Harmonizing tasks to human knowledge and capacities- (dissertation), Groningen , 1995
Rauterberg, Daniel Felix,Human
Errors: Disadvantages and Advantages, 4th Pan Pacific Conference on Occupational
Ergonomics 1996, Ergonomics Society Taiwan,
 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
Frese, M. and Sabini, J. (1985): Goal directed behaviour: The concept of Action in Psychology. London: Lawrence Erlbaum Associates.
 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
 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.
 Shneiderman, B. (2000) Creating creativity: user interfaces for supporting innovation. In ACM Transactions on Computer-Human Interaction (TOCHI) March 2000