Abstract
Sixty-six studies were reviewed that met several a priori criteria. Specifically, the studies had to be empirical investigations that related to a particular academic domain and that involved connected discourse presented either in traditional written form or on computer. In addition, the studies had to incorporate some measure of both knowledge and interest. The resulting body of literature was first summarized and analyzed in terms of the domains chosen, the subjects selected, the nature of the texts used, the manner in which knowledge and interest were assessed, and the principal outcomes reported. Next, from this analysis, six premises were proposed as guides for future research and practice. Finally, concluding remarks were advanced that address the overall significance of text-processing research that interactively considers the domain of knowledge and the interest of the reader.
Keywords
Affiliated Institutions
Related Publications
The Role of Subject-Matter Knowledge and Interest in the Processing of Linear and Nonlinear Texts
Sixty-six studies were reviewed that met several a priori criteria. Specifically, the studies had to be empirical investigations that related to a particular academic domain and...
Machine learning in automated text categorization
The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years, due to the increased availability of ...
ANALYSIS OF MULTITRAIT-MULTIMETHOD MATRICES: A TWO STEP PRINCIPAL COMPONENTS PROCEDURE
A relatively simple technique for .assessing the convergence of sets of variables across method domains is presented. The technique, two-step principal components analysis, empi...
Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
Preface 1 Overview of Learning Systems 1.1 What is a Learning System? 1.2 Motivation for Building Learning Systems 1.3 Types of Practical Empirical Learning Systems 1.3.1 Common...
LEARNING TO LAUGH (AUTOMATICALLY): COMPUTATIONAL MODELS FOR HUMOR RECOGNITION
Humor is one of the most interesting and puzzling aspects of human behavior. Despite the attention it has received in fields such as philosophy, linguistics, and psychology, the...
Publication Info
- Year
- 1994
- Type
- article
- Volume
- 64
- Issue
- 2
- Pages
- 201-252
- Citations
- 294
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.3102/00346543064002201