Academic journal article Academy of Educational Leadership Journal

The Importance of Cognitive Style in Information Retrieval Tasks

Academic journal article Academy of Educational Leadership Journal

The Importance of Cognitive Style in Information Retrieval Tasks

Article excerpt


Accounting and business decisions often require database applications to convert raw data into useful business information (Hayes and Hunton, 2000). Modern accounting information systems use relational databases (Hooper and Page, 1996). Accounting academicians and professionals generally agree that accountants and auditors must become proficient with information systems technology, such as database management systems (DBMS) and information retrieval techniques (Borthick, 1996), particularly so they will not need to rely as heavily on the expertise of computer professionals (Hooper and Page, 1996). The AICPA information technology section also has identified database technology as one of the top ten information technologies with which accountants must be familiar (Anonymous, 1994). In addition, the CPA exam recognizes the importance of Information Technology (IT) topics and focuses a large part of the Business Environment Concepts exam on IT subjects relating to business (AICPA, 2010).

Formerly, information systems (IS) professionals were responsible for query tasks on behalf of end-users (Borthick, 1992). Today, however, accounting system queries can be easily performed by end-users because current database technology is more user friendly (Hooper and Page, 1996). In order to perform these query tasks, these end-users (such as accountants, auditors, and managers) must understand both the database structure and the available query language (Leitheiser and March, 1996).

The availability of accounting data is communicated through the use of a database structure representation (Dunn and Grabski, 2002). This representation details the stored data items and their logical organization. Examples of such representations are the entity-relationship (ER) model and the relational model. Ability to access data of interest also requires knowledge of a database query language. Examples of such languages are query-by-example (QBE) and structured query language (SQL).

Prior research on end-user performance in query construction tasks has not resulted in clear conclusions about the effect of database representation type, query tool type, and user characteristics. According to Dunn and Grabski (2002), this is a relatively new research field and these factors should be studied further to determine their combined effects on query writing performance.

Users of accounting information are not homogeneous. Neither are the database technologies used in accounting information systems homogeneous. Different users possess particular user characteristics that can impact their performance in writing queries (e.g., age, gender, educational background, experience, and cognitive style).

Therefore, this study uses both accounting participants and MIS participants as a proxy for the groups of potential end-users. This is the first study to explicitly include user characteristics in the research model.

Only one study attempted to manipulate both the database structure representation and the query language (Chan et al., 1993). Similarly, the current study manipulates both the data model and the query language. No prior studies have investigated the interaction between the two factors or included user characteristics as part of the research model. The current study solves this problem by measuring user cognitive styles and analyzing the main effects as well as the interaction of the different factors affecting the end-user query performance.

By better understanding how the end-user's cognitive style affects performance organizations can improve the way in which they train their employees on database concepts. By implementing separate sessions based on user's cognitive styles organizations would be able to more efficiently and effectively train employees. This would enable end-users to perform query tasks at a higher level with a lower investment in training. Also by understanding what effect cognitive styles can have on query performance professionals can improve their abilities by understanding what best suits their own particular. …

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