Understanding conceptual schemas: exploring the role of application and IS domain knowledge

Although information systems (IS) problem solving involves knowledge of both the IS and application domains, little attention has been paid to the role of application domain knowledge. In this study, which is set in the context of conceptual modeling, we examine the effects of both IS and application domain knowledge on different types of schema understanding tasks: syntactic and semantic comprehension tasks and schema-based problem-solving tasks. Our thesis was that while IS domain knowledge is important in solving all such tasks, the role of application domain knowledge is contingent upon the type of understanding task under investigation. We use the theory of cognitive fit to establish theoretical differences in the role of application domain knowledge among the different types of schema understanding tasks. We hypothesize that application domain knowledge does not influence the solution of syntactic and semantic comprehension tasks for which cognitive fit exists, but does influence the solution of schema-based problem-solving tasks for which cognitive fit does not exist. To assess performance on different types of conceptual schema understanding tasks, we conducted a laboratory experiment in which participants with high- and low-IS domain knowledge responded to two equivalent conceptual schemas that represented high and low levels of application knowledge (familiar and unfamiliar application domains). As expected, we found that IS domain knowledge is important in the solution of all types of conceptual schema understanding tasks in both familiar and unfamiliar applications domains, and that the effect of application domain knowledge is contingent on task type. Our findings for the EER model were similar to those for the ER model. Given the differential effects of application domain knowledge on different types of tasks, this study highlights the importance of considering more than one application domain in designing future studies on conceptual modeling.

Syntactic complexity measures and their relation to oral proficiency in Japanese as a foreign language

The study reported in this article is a part of a large-scale study investigating syntactic complexity in second language (L2) oral data in commonly taught foreign languages (English, German, Japanese, and Spanish; Ortega, Iwashita, Rabie, & Norris, in preparation). In this article, preliminary findings of the analysis of the Japanese data are reported. Syntactic complexity, which is referred to as syntactic maturity or the use of a range of forms with degrees of sophistication (Ortega, 2003), has long been of interest to researchers in L2 writing. In L2 speaking, researchers have examined syntactic complexity in learner speech in the context of pedagogic intervention (e.g., task type, planning time) and the validation of rating scales. In these studies complexity is examined using measures commonly employed in L2 writing studies. It is assumed that these measures are valid and reliable, but few studies explain what syntactic complexity measures actually examine. The language studied is predominantly English, and little is known about whether the findings of such studies can be applied to languages that are typologically different from English. This study examines how syntactic complexity measures relate to oral proficiency in Japanese as a foreign language. An in-depth analysis of speech samples from 33 learners of Japanese is presented. The results of the analysis are compared across proficiency levels and cross-referenced with 3 other proficiency measures used in the study. As in past studies, the length of T-units and the number of clauses per T-unit is found to be the best way to predict learner proficiency; the measure also had a significant linear relation with independent oral proficiency measures. These results are discussed in light of the notion of syntactic complexity and the interfaces between second language acquisition and language testing. Adapted from the source document

Does the type of concurrent task affect preferred and cued gait in people with Parkinson's disease?

Difficulty performing more than one task at a time is common in people with Parkinson's disease, resulting in interference with one or both tasks. While studies have shown that greater interference in gait occurs with more complex concurrent tasks, the impact of the type of concurrent task is unclear in the Parkinson's population. Thus the first purpose of this study was to investigate the effect of the concurrent task (calculation, language, or motor) on gait in people with Parkinson's disease. As visual cues are commonly used to aid stride regulation in people with Parkinson's disease, the second purpose of this study was to determine whether this method of increasing stride length was still effective if other tasks were performed simultaneously. Sixteen patients with Parkinson's disease and 16 gender- and age-matched controls performed six cognitive and motor concurrent tasks when seated, walking 10 m, and walking over visual cues. Stride length decreased in people with Parkinson's disease when performing the concurrent calculation and language tasks, but not with the motor task. The language task was more complex than the calculation task, thus the effect was not due to task complexity alone. Visual cues were effective in improving stride length whist maintaining velocity in people with Parkinson's disease, even when performed under dual task conditions. These findings highlight the importance of the task when assessing and retraining dual tasking during gait, and suggest that retraining dual tasking can occur whilst simultaneously using visual aids to regulate stride length.

The relationship between diurnal type and time duration estimation at morning and evening times of day

This study investigates whether different diurnal types (morning versus evening) differ in their estimation of time duration at different times of the day. Given that the performance of morning and evening types is typically best at their preferred times of day, and assuming different diurnal trends in subjective alertness (arousal?) for morning and evening types, and adopting the attentional gate model of time duration estimation, it was predicted that morning types would tend to underestimate and be more accurate in the morning compared to evening types where the opposite pattern was expected. Nineteen morning types, 18 evening types and 18 intermediate types were drawn from a large sample (N=1175) of undergraduates administered the Early/Late Preference Scale. Groups performed a time duration estimation task using the production method for estimating 20-s unfilled intervals at two times of day: 0800/1830. The median absolute error, median directional error and frequency of under- and overestimation were analysed using repeated-measures ANOVA. While all differences were statistically non-significant, the following trends were observed: morning types performed better than evening types; participants overestimated in the morning and underestimated in the evening; and participants were more accurate later in the day. It was concluded that the trends are inconsistent with a relationship between subjective alertness and time duration estimation but consistent with a possible relationship between time duration estimation and diurnal body temperature fluctuations. (C) 2002 Elsevier Ltd. All rights reserved.