Assisting End-users in Filling Out Web Services

With the quick advance of web service technologies, end-users can conduct various on-line tasks, such as shopping on-line. Usually, end-users compose a set of services to accomplish a task, and need to enter values to services to invoke the composite services. Quite often, users re-visit websites and use services to perform re-occurring tasks. The users are required to enter the same information into various web services to accomplish such re-occurring tasks. However, repetitively typing the same information into services is a tedious job for end-users. It can negatively impact user experience when an end-user needs to type the re-occurring information repetitively into web services. Recent studies have proposed several approaches to help users fill in values to services automatically. However, prior studies mainly suffer the following drawbacks: (1) limited support of collecting and analyzing user inputs; (2) poor accuracy of filling values to services; (3) not designed for service composition. To overcome the aforementioned drawbacks, we need maximize the reuse of previous user inputs across services and end-users. In this thesis, we introduce our approaches that prevent end-users from entering the same information into repetitive on-line tasks. More specifically, we improve the process of filling out services in the following 4 aspects: First, we investigate the characteristics of input parameters. We propose an ontology-based approach to automatically categorize parameters and fill values to the categorized input parameters. Second, we propose a comprehensive framework that leverages user contexts and usage patterns into the process of filling values to services. Third, we propose an approach for maximizing the value propagation among services and end-users by linking a set of semantically related parameters together and similar end-users. Last, we propose a ranking-based framework that ranks a list of previous user inputs for an input parameter to save a user from unnecessary data entries. Our framework learns and analyzes interactions of user inputs and input parameters to rank user inputs for input parameters under different contexts.

The Psychometric Properties of the Developmental Reading Assessment

ABSTRACT The purpose of this study was to examine the technical adequacy of the Developmental Reading Assessment (Beaver & Carter, 2004). Internal consistency analysis, factor analysis, and linear regression analyses were used to test whether the DRA is a statistically reliable measuring of reading comprehension for Grades 7 and 8 students. Correlational analyses, decision consistency analyses, and a focus group of experienced Intermediate (Grades 7 and 8) teachers examined whether there is evidence that the results from the DRA provide valid interpretations regarding students’ reading skills and comprehension. Results indicated that, as currently scored, internal consistency is low and skewness of distribution is high. Factor analyses did not replicate those cited by the DRA developers to prove construct validity. Two-way contingency analyses determined that decision consistency did not vary greatly between the DRA, EQAO, scores and report card marks. Views expressed during the focus group echoed many of the challenges to validity found in the statistical analysis. The teachers found that the DRA was somewhat useful, as there were limited alternative reading assessments available for the classroom, but did not endorse it strongly. The study found little evidence that the DRA provides valid interpretations regarding Intermediate students’ reading skills. Indicated changes to the structure and administration procedures of the DRA may ameliorate some of these issues.