Many different data modelling or representation schemes have been used or proposed. One important use of such data representations is to communicate the data content of a proposed system design to users: the user validation task. The effects of the characteristics of four such data models on user comprehension were investigated in a controlled laboratory experiment. The results showed that the two primarily graphical representations were more understandable than two alternatives for most of a set of tasks designed to simulate user validation. There were some preliminary indications that the graphical or semantic data models led to more systematic data modelling behavior. Relational models did out-perform graphical models with respect to...
Conceptual data models are used for discovery and validation communication between analysts and user...
Although there has been a great deal of research on why individuals adopt and use information system...
The research examined naive user analysts\u27 learning of data analysis skills; namely. (1) the diff...
Many different data modelling or representation schemes have been used or proposed. One important us...
This paper describes a laboratory experiment which evaluates the effectiveness of different represen...
[[abstract]]The purpose of this study was to investigate similarities and differences in the quality...
This paper describes a laboratory experiment which evaluates the effectiveness of different represen...
The choice of an appropriate representation of data is one of the most crucial tasks in the entire s...
Models are created by people and people make mistakes. For this reason it is necessary to validate b...
Studying the acceptance of Information Systems (IS) artifacts is classic to the IS research discipli...
Representation theory proposes that the basic purpose of an information system (IS) is to faithfully...
Data models are important in information system (IS) development, particularly as tools for expressi...
The purpose of this study was to investigate similarities and differences in the quality of data rep...
An experimental case study on how task characteristics affect student performance was conducted with...
Over recent years, many scholars have studied the conceptual modeling of information systems based o...
Conceptual data models are used for discovery and validation communication between analysts and user...
Although there has been a great deal of research on why individuals adopt and use information system...
The research examined naive user analysts\u27 learning of data analysis skills; namely. (1) the diff...
Many different data modelling or representation schemes have been used or proposed. One important us...
This paper describes a laboratory experiment which evaluates the effectiveness of different represen...
[[abstract]]The purpose of this study was to investigate similarities and differences in the quality...
This paper describes a laboratory experiment which evaluates the effectiveness of different represen...
The choice of an appropriate representation of data is one of the most crucial tasks in the entire s...
Models are created by people and people make mistakes. For this reason it is necessary to validate b...
Studying the acceptance of Information Systems (IS) artifacts is classic to the IS research discipli...
Representation theory proposes that the basic purpose of an information system (IS) is to faithfully...
Data models are important in information system (IS) development, particularly as tools for expressi...
The purpose of this study was to investigate similarities and differences in the quality of data rep...
An experimental case study on how task characteristics affect student performance was conducted with...
Over recent years, many scholars have studied the conceptual modeling of information systems based o...
Conceptual data models are used for discovery and validation communication between analysts and user...
Although there has been a great deal of research on why individuals adopt and use information system...
The research examined naive user analysts\u27 learning of data analysis skills; namely. (1) the diff...