Filtering by
- All Subjects: Education
- All Subjects: Computer Science
- All Subjects: Evaluation
- Member of: ASU Electronic Theses and Dissertations
- Status: Published
Choropleth maps are a common form of online cartographic visualization. They reveal patterns in spatial distributions of a variable by associating colors with data values measured at areal units. Although this capability of pattern revelation has popularized the use of choropleth maps, existing methods for their online delivery are limited in supporting dynamic map generation from large areal data. This limitation has become increasingly problematic in online choropleth mapping as access to small area statistics, such as high-resolution census data and real-time aggregates of geospatial data streams, has never been easier due to advances in geospatial web technologies. The current literature shows that the challenge of large areal data can be mitigated through tiled maps where pre-processed map data are hierarchically partitioned into tiny rectangular images or map chunks for efficient data transmission. Various approaches have emerged lately to enable this tile-based choropleth mapping, yet little empirical evidence exists on their ability to handle spatial data with large numbers of areal units, thus complicating technical decision making in the development of online choropleth mapping applications. To fill this knowledge gap, this dissertation study conducts a scalability evaluation of three tile-based methods discussed in the literature: raster, scalable vector graphics (SVG), and HTML5 Canvas. For the evaluation, the study develops two test applications, generates map tiles from five different boundaries of the United States, and measures the response times of the applications under multiple test operations. While specific to the experimental setups of the study, the evaluation results show that the raster method scales better across various types of user interaction than the other methods. Empirical evidence also points to the superior scalability of Canvas to SVG in dynamic rendering of vector tiles, but not necessarily for partial updates of the tiles. These findings indicate that the raster method is better suited for dynamic choropleth rendering from large areal data, while Canvas would be more suitable than SVG when such rendering frequently involves complete updates of vector shapes.
This study sought to reveal how students’ perceptions of the policy and schooling in general affect their understanding of the concept of college readiness and the college readiness binary and to identify factors that help formulate those perceptions. This interpretivist, qualitative study relied on analysis of multiple face-to-face interviews with students to better understand how they think and act within the context of Move On When Ready, paying particular attention to students from historically vulnerable minority subgroups (e.g., the Latina (a)/Hispanic sub-population) enrolled in two schools deploying the MOWR strategy.
Findings suggest that interviewed students understand little about MOWR's design, intent or implications for their future educational trajectories. Moreover, what they believe is generally misinformed, regardless of aspiration, socio-cultural background, or academic standing. School-based sources of messaging (e.g., teachers and administrators) supply the bulk of information to students about MOWR. However, in these two schools, the flow of information is constricted. In addition, the information conveyed is either distorted by message mediators or misinterpreted by the students. The data reveal that formal and informal mediators of policy messages influence students’ engagement with the policy and affect students’ capacity to play an active role in determining the policy’s effect on their educational outcomes.