A comparison of content-based and context-based teaching on ninth-grade mathematics achievement

The purpose of this study was to determine if an experimental context-based delivery format for mathematics would be more effective than a traditional model for increasing the performance in mathematics of at-risk students in a public high school of choice, as evidenced by significant gains in achievement on the standards-based Mathematics subtest of the FCAT and final academic grades in Algebra I. The guiding rationale for this approach is captured in the Secretary's Commission on Achieving Necessary Skills (SCANS) report of 1992 that resulted in school-to-work initiatives (United States Department of Labor). Also, the charge for educational reform has been codified at the state level as Educational Accountability Act of 1971 (Florida Statutes, 1995) and at the national level as embodied in the No Child Left Behind Act of 2001. A particular focus of educational reform is low performing, at-risk students. ^ This dissertation explored the effects of a context-based curricular reform designed to enhance the content of Algebra I content utilizing a research design consisting of two delivery models: a traditional content-based course; and, a thematically structured, content-based course. In this case, the thematic element was business education as there are many advocates in career education who assert that this format engages students who are often otherwise disinterested in mathematics in a relevant, SCANS skills setting. The subjects in each supplementary course were ninth grade students who were both low performers in eighth grade mathematics and who had not passed the eighth grade administration of the standards-based FCAT Mathematics subtest. The sample size was limited to two groups of 25 students and two teachers. The site for this study was a public charter school. Student-generated performance data were analyzed using descriptive statistics. ^ Results indicated that contrary to the beliefs held by many, contextual presentation of content did not cause significant gains in either academic performance or test performance for those in the experimental treatment group. Further, results indicated that there was no meaningful difference in performance between the two groups. ^

A generalized multidimensional index structure for multimedia data to support content-based similarity searches in a collaborative search environment

Since multimedia data, such as images and videos, are way more expressive and informative than ordinary text-based data, people find it more attractive to communicate and express with them. Additionally, with the rising popularity of social networking tools such as Facebook and Twitter, multimedia information retrieval can no longer be considered a solitary task. Rather, people constantly collaborate with one another while searching and retrieving information. But the very cause of the popularity of multimedia data, the huge and different types of information a single data object can carry, makes their management a challenging task. Multimedia data is commonly represented as multidimensional feature vectors and carry high-level semantic information. These two characteristics make them very different from traditional alpha-numeric data. Thus, to try to manage them with frameworks and rationales designed for primitive alpha-numeric data, will be inefficient. An index structure is the backbone of any database management system. It has been seen that index structures present in existing relational database management frameworks cannot handle multimedia data effectively. Thus, in this dissertation, a generalized multidimensional index structure is proposed which accommodates the atypical multidimensional representation and the semantic information carried by different multimedia data seamlessly from within one single framework. Additionally, the dissertation investigates the evolving relationships among multimedia data in a collaborative environment and how such information can help to customize the design of the proposed index structure, when it is used to manage multimedia data in a shared environment. Extensive experiments were conducted to present the usability and better performance of the proposed framework over current state-of-art approaches.

The effects of content-based ESOL instruction on the overall English proficiency of foreign -born college students

This study investigates the effects of content-based ESOL instruction on the overall English proficiency of foreign-born college students. Based on various psychological and social factors which affect second language acquisition, it is suggested that the techniques of content-based instruction, while focusing on subject matter, allow the learners to overcome the language barrier by neutralizing their subconscious defense mechanism, thus attaining greater proficiency.^ Two groups of Miami-Dade Community College ESOL students were chosen as subjects for this study: a control group composed of students from the North and Wolfson campuses, where the ESOL program is based predominantly on structural or structural-functional approach, and an experimental group of Medical Center campus students, where content-based instruction is incorporated into curriculum. Ethnicity, gender, age, and other differences in the population are discussed in the study.^ The students' English Placement Test (EPT) scores were used as covariate, and the scores on Multiple Assessment Programs and Services (MAPS) test as dependent variables. Multivariate analysis of variance (MANOVA) was applied to test significant difference between the means. The results of the analysis of data indicate that there is a consistent difference in the mean performance of the Medical Center campus ESOL students demonstrated by their scores on MAPS. Although neither ethnicity, nor gender of the subjects has affected the outcome, age had a contributing effect. The implications of these findings suggest that content-based instruction facilitates greater overall English proficiency in foreign-born college students. ^

Art teachers' attitudes toward the Florida Sunshine State Standards for the Visual Arts

The State of Florida developed the Sunshine State Standards For the Arts Curriculum Framework as part of an initiative to raise student achievement in response to national calls for educational reform. The content-based art education approach used in the Sunshine State Standards reflects a viewpoint advocated by prominent art educators and professional art education organizations for more than two decades. Successful implementation of the Sunshine State Standards curriculum approach requires that art teachers be acquainted with and knowledgeable in the four foundational content areas of the arts: studio art, art history, art criticism, and aesthetics. ^ The purpose of this study was to examine art teachers' viewpoints and attitudes toward the content-based art education approach contained in the Florida Curriculum Framework Sunshine State Standards for the Visual Arts. A survey was conducted in order to obtain these viewpoints. Surveys were sent to 440 Miami-Dade County Public School art teachers. A total of 138 elementary, middle and senior high school level art teachers participated in the study. ^ Factors and variables explored in this study included teachers' level of education, type of community, and grade levels taught. The principal methods of analyses employed in the study were descriptive statistics used to display frequencies and percentages. In addition, cross tabulations with Chi-square tests, and Mann-Whitney U tests were used to examine responses to the survey items. ^ The results of the study revealed that the majority of art teachers supported the content-based art education approach used in the Sunshine State Standards for the Arts. However significant differences appeared in the responses to survey items as a result of art teachers' level of education, type of community, and grade levels. The results of this study indicate a need for further examination of teacher training and professional development programs. ^

A multimedia indexing and retrieval framework for multimedia database systems

The main challenges of multimedia data retrieval lie in the effective mapping between low-level features and high-level concepts, and in the individual users' subjective perceptions of multimedia content. ^ The objectives of this dissertation are to develop an integrated multimedia indexing and retrieval framework with the aim to bridge the gap between semantic concepts and low-level features. To achieve this goal, a set of core techniques have been developed, including image segmentation, content-based image retrieval, object tracking, video indexing, and video event detection. These core techniques are integrated in a systematic way to enable the semantic search for images/videos, and can be tailored to solve the problems in other multimedia related domains. In image retrieval, two new methods of bridging the semantic gap are proposed: (1) for general content-based image retrieval, a stochastic mechanism is utilized to enable the long-term learning of high-level concepts from a set of training data, such as user access frequencies and access patterns of images. (2) In addition to whole-image retrieval, a novel multiple instance learning framework is proposed for object-based image retrieval, by which a user is allowed to more effectively search for images that contain multiple objects of interest. An enhanced image segmentation algorithm is developed to extract the object information from images. This segmentation algorithm is further used in video indexing and retrieval, by which a robust video shot/scene segmentation method is developed based on low-level visual feature comparison, object tracking, and audio analysis. Based on shot boundaries, a novel data mining framework is further proposed to detect events in soccer videos, while fully utilizing the multi-modality features and object information obtained through video shot/scene detection. ^ Another contribution of this dissertation is the potential of the above techniques to be tailored and applied to other multimedia applications. This is demonstrated by their utilization in traffic video surveillance applications. The enhanced image segmentation algorithm, coupled with an adaptive background learning algorithm, improves the performance of vehicle identification. A sophisticated object tracking algorithm is proposed to track individual vehicles, while the spatial and temporal relationships of vehicle objects are modeled by an abstract semantic model. ^