Abstract: This paper describes a case study of the Human Factors design, development, and testing of a computer-based financial analysis package. The project applied the “usability goals” method proposed by Bennett (1984) to structure the definition, design, and testing of the new system. Learnability was defined as a key attribute in the product concept because of its salience in users' perception of system quality. The learnability attribute was assigned an operational definition in terms of time to mastery and error avoidance/recovery. The “back-to-front” strategy of Didner & Butler (1982) was applied for designing the menus. Empirical testing of user performance on sample problems in the alpha stage indicated that the new system surpassed the learnability objective. Lessons learned from this case study concern leverage in getting better managerial attention for Human Factors considerations in development projects, and clearer structure to direct needed research.

Abstract: Two variables, perceived translucency and component complexity, were hypothesized to influence the learnability of Blissymbols. Translucency was posited to facilitate symbol learning while component complexity was posited to retard learning. Results indicated that both of these hypotheses were confirmed. Additionally, results indicated that, for Bliss naive learners, translucency may be a more potent learnability variable than component complexity. Finally, translucency was found to most greatly affect Blissymbol learning in early rather than late learning trials. Results are discussed in terms of teaching Blissymbols to handicapped learners.

Abstract: Blissymbols are currently being used by a variety of special education programs for children and adults with communication impairments. However, there is little available research on the learnability of such systems in general, and the Bliss system in particular. The present study was designed to answer some basic questions about the psycholinguistic and learning characteristics of blissymbols. Two hundred symbols (14% of all existing symbols) were rated by college students for their inherent guessability (transparency) and also for the amount of perceived relationship between the symbol (translucency) and the symbol's meaning (gloss). The results indicate that the blissymbols are low in iconicity but that they are relatively translucent, and that translucency is related to component complexity. These findings are related to the learnability of the symbols and represent the first steps toward the development of a primary lexicon based on learnability characteristics in conjunction with other features.

Abstract: This paper explores the relationships between a computational theory of temporal representation (as developed by James Allen) and a formal linguistic theory of tense (as developed by Norbert Hornstein) and aspect. It aims to provide explicit answers to four fundamental questions: (1) what is the computational justification for the primitives of a linguistic theory; (2) what is the computational explanation of the formal grammatical constraints: (3) what are the processing constraints imposed on the learnability and markedness of these theoretical constructs: and (4) what are the constraints that a linguistic theory imposes on. representations. We show that one can effectively exploit the interface between the language faculty and the cognitive faculties by using linguistic constraints to determine restructions on the cognitive representations and vice versa.Three main results are obtained: (1) We derive an explanation of an observed grammatical constraint on tense .. the Linear Order Constraint .. from the information monotonicity property of the constraint propagation algorithm of Allen's temporal system: (2) We formulate a principle of markedness for the basic tense structures based on the computational efficiency of the temporal representations: and (3) We show Allen's interval-based temporal system is not arbitrary. but it can be used to explair, independently motivated linguistic constraints on tense and aspect interpretations.We also claim that the methodology of research developed in this study .. "cross-level" investigation of independently motivated formal grammatical theory and computational models .. is a powerful paradigm with which to attack representational problems in basic cognitive domains, e.g., space. time, causality, etc.

Abstract: This chapter contains sections titled: 7.1 Formalizing the Marcus Parser, 7.2 Two-stack Deterministic Parsing, 7.3 Parsability and Learnability, 7.4 Learnability, Parsability, and Locality

Abstract: This paper explores the relationships between a computational theory of temporal representation (as developed by james Allen) and a formal lingustic theory of lense (as developed by Norbert Hornstein) and aspect. It aims to provide explicit answers to four fundamental questions (1) what is the computational justification for the permitives of a linguistic theory; (2) what is the computational explanation of the formal grammatical contraints. (3) what are the processing constraints imposed on the learnability and markedness of these theoretical constructs and (4) what are the constraints a linguistic theory imposes or representations. We show that one can effectively exploit the interface between the language faculty and the cognitive faculties by using lingustic constrants to determine restrictions on the cognitive representations and vice versa. Theree man results are obtained (1) We derive an explanation of an observed grammatical constraint on tense. the property of the constraint propagation algorithm of Allen's temporal system; (2) We formulate a principle of markedness for the basic tense structures based on the computation efficiency of the temporal representations, and (3) We show Allen's interval-based temporal system is not arbitrary, but it can be used to explain independently motivated linguistic contraints on tense and aspect interpretations. We also claim that the methodology of research developed in this study "cross-level" investigation of independently motivated formal grammatical theory and computational models is a powerful paradigm with which to attach representational problems in basic cognitive domains. e.g., space, time, causality, etc.