Toward an understanding of how individuals overcome challenges to development: A phenomenological study of an inner -city student's attitude toward academic orientation and life

The purpose of this qualitative case study was to gain an understanding of the phenomenon of academic orientation by seeking the insights into an inner-city Haitian-American middle school student's attitudes and world view toward education and life. A phenomenological approach was used in order to explore the way in which Cindy, a minority student, gives meaning to her lived-experiences in terms of her desire to meet academic expectations and her ability to overcome social adversity and/or other risk factors.^ The study attempted to answer the following two research questions: (1) What provides the focus for Cindy's (the subject's) approach to her school work and/or life? (2) What are the processes that give meaning and direction to academic orientation and life for Cindy? In-depth interviewing was the primary method of data collection. In addition, journal and sketchbook entries and school district records were used and classroom observations made.^ The nature of the study to understand lived-experience facilitated the use of the case study method and a phenomenological method of description. Data analysis was conducted by means of an adapted form of the constant comparative approach. Patterns in the data which emerged were coded and categorized according to underlying generative themes. Phenomenological reflection and analysis were used to grasp the experiential structures of Cindy's experience. The following textural themes were identified and confirmed to be essential themes to Cindy's experience: personal challenge to do her best, personal challenge to want to learn, having a sense of determination, being able to think for self, having a disposition to like self, achieving self-respect through performance, seeing a need to help others, being intrinsically motivated, being an independent learner, attending more to academic pressure and less to peer pressure, having motivational catalysts in her life, learning and support opportunities, and having a self-culture. Using Mahrer's humanistic theory of experiencing, Cindy's development was interpreted in terms of her progression through a sequence of developmental plateaus: externalized self, internalized self, and integrating and actualizing self.^ The findings of this study were that Cindy's desire to meet academic expectations is guided by a meaning construction internal frame of reference. High expectations of self in conjunction with other protective factors found in Cindy's home and school environments were also found to be linked to her educational resilience and success. Cindy's lived-experiences were also found to be related to Mahrer's theory of human development. In addition, it was concluded that "minority" students do not all fit into social categories and labels. ^

Utilizing Real Objects to Increase Reading Comprehension in Students with Significant Cognitive Disabilities

This poster presents the results of a study conducted to evaluate the effects of pairing read-alouds with real objects related to stories read to students with significant cognitive disabilities to increase reading comprehension skills. The participants are four elementary students. The target audience is special education teachers.

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Characterizing Internet worm spatial-temporal infection structures

Since the Morris worm was released in 1988, Internet worms continue to be one of top security threats. For example, the Conficker worm infected 9 to 15 million machines in early 2009 and shut down the service of some critical government and medical networks. Moreover, it constructed a massive peer-to-peer (P2P) botnet. Botnets are zombie networks controlled by attackers setting out coordinated attacks. In recent years, botnets have become the number one threat to the Internet. The objective of this research is to characterize spatial-temporal infection structures of Internet worms, and apply the observations to study P2P-based botnets formed by worm infection. First, we infer temporal characteristics of the Internet worm infection structure, i.e., the host infection time and the worm infection sequence, and thus pinpoint patient zero or initially infected hosts. Specifically, we apply statistical estimation techniques on Darknet observations. We show analytically and empirically that our proposed estimators can significantly improve the inference accuracy. Second, we reveal two key spatial characteristics of the Internet worm infection structure, i.e., the number of children and the generation of the underlying tree topology formed by worm infection. Specifically, we apply probabilistic modeling methods and a sequential growth model. We show analytically and empirically that the number of children has asymptotically a geometric distribution with parameter 0.5, and the generation follows closely a Poisson distribution. Finally, we evaluate bot detection strategies and effects of user defenses in P2P-based botnets formed by worm infection. Specifically, we apply the observations of the number of children and demonstrate analytically and empirically that targeted detection that focuses on the nodes with the largest number of children is an efficient way to expose bots. However, we also point out that future botnets may self-stop scanning to weaken targeted detection, without greatly slowing down the speed of worm infection. We then extend the worm spatial infection structure and show empirically that user defenses, e.g. , patching or cleaning, can significantly mitigate the robustness and the effectiveness of P2P-based botnets. To counterattack, we evaluate a simple measure by future botnets that enhances topology robustness through worm re-infection.

An examination of the effects of a summer book-reading program on the language and early literacy outcomes of toddlers from high risk environments

The current study examined the impact of an early summer literacy program and the mediating effects of the home literacy environment on the language and literacy outcomes of a group of children at-risk for long-term developmental and academic delays. Participating children (n=54) were exposed to an intensive book-reading intervention each summer (June through mid August) over a 3-year period. The current study implemented an ex post facto, quasi-experimental design. This nonequivalent group design involved a pretest and posttest over three time points for a non-randomized treatment group and a matched non-treatment comparison group. Results indicated that literacy scores did improve for the children over the 3-year period; however, language scores did not experience the same rate of change over time. Receptive language was significantly impacted by attendance, and race/ethnicity. Expressive language was impacted significantly by gestational age and attendance. Results also indicated that language outcomes for young children who are exposed to a literacy program were higher than those who did not participate; however, only receptive language yielded significance at the p<.05 level. These study results also found that activities in the home that support literacy and learning do indeed impact language and literacy outcomes for these children, specifically, the age at which a child is read to, the number of books in the home, a child’s enjoyment of reading, and whether a child looks at books on his or her own impact language scores. This study concluded that at-risk young children do benefit from center-based literacy intervention. This literacy experience, however, is also driven by the children's home environment, their attendance to the program, whether they were premature or not and the type of caregiver.

Foundational Forensic Techniques for Cellular and Ad Hoc Multi-hop Networks

The Internet has become an integral part of our nation's critical socio-economic infrastructure. With its heightened use and growing complexity however, organizations are at greater risk of cyber crimes. To aid in the investigation of crimes committed on or via the Internet, a network forensics analysis tool pulls together needed digital evidence. It provides a platform for performing deep network analysis by capturing, recording and analyzing network events to find out the source of a security attack or other information security incidents. Existing network forensics work has been mostly focused on the Internet and fixed networks. But the exponential growth and use of wireless technologies, coupled with their unprecedented characteristics, necessitates the development of new network forensic analysis tools. This dissertation fostered the emergence of a new research field in cellular and ad-hoc network forensics. It was one of the first works to identify this problem and offer fundamental techniques and tools that laid the groundwork for future research. In particular, it introduced novel methods to record network incidents and report logged incidents. For recording incidents, location is considered essential to documenting network incidents. However, in network topology spaces, location cannot be measured due to absence of a 'distance metric'. Therefore, a novel solution was proposed to label locations of nodes within network topology spaces, and then to authenticate the identity of nodes in ad hoc environments. For reporting logged incidents, a novel technique based on Distributed Hash Tables (DHT) was adopted. Although the direct use of DHTs for reporting logged incidents would result in an uncontrollably recursive traffic, a new mechanism was introduced that overcome this recursive process. These logging and reporting techniques aided forensics over cellular and ad-hoc networks, which in turn increased their ability to track and trace attacks to their source. These techniques were a starting point for further research and development that would result in equipping future ad hoc networks with forensic components to complement existing security mechanisms.

Mitigating Inconsistencies by Coupling Data Cleaning, Filtering, and Contextual Data Validation in Wireless Sensor Networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Rap to Read: Employing a Culturally Relevant Curriculum with African American Students

This study examined the effects of using rap music on the reading skills of 2nd Grade African American students. The sample consisted of 105 students within eight classrooms in two Miami-Dade County public schools. Results revealed that rap was helpful for both fluency and comprehension instruction.

The use of visualization, onset-and-rime, story read-alouds, and discussion to improve diverse first graders' vocabulary and comprehension

It has long been known that vocabulary is essential in the development of reading. Because vocabulary leading to increased comprehension is important, it necessary to determine strategies for ensuring that the best methods of teaching vocabulary are used to help students make gains in vocabulary leading to reading comprehension. According to the National Reading Panel, multiple strategies that involve active engagement on the part of the student are more effective than the use of just one strategy. The purpose of this study was to determine if students' use of visualization, student-generated pictures of onset-and-rime-patterned vocabulary, and story read-alouds with discussion, would enable diverse first-grade students to increase their vocabulary and comprehension. In addition, this study examined the effect of the multimodal framework of strategies on English learners (ELs). This quasi-experimental study (N=69) was conducted in four first-grade classrooms in a low socio-economic school. Two treatment classes used a multimodal framework of strategies to learn weekly vocabulary words and comprehension. Two comparison classrooms used the traditional method of teaching weekly vocabulary and comprehension. Data sources included Florida Assessments for Instruction in Reading (FAIR), comprehension and vocabulary scores, and weekly MacMillan/McGraw Hill Treasures basal comprehension questions and onset-and-rime vocabulary questions. This research determined that the treatment had an effect in adjusted FAIR comprehension means by group, with the treatment group (adj M = 5.14) significantly higher than the comparison group ( adj M = -8.26) on post scores. However, the treatment means did not increase from pre to post, but the comparison means significantly decreased from pre to post as the materials became more challenging. For the FAIR vocabulary, there was a significant difference by group with the comparison adjusted post mean higher than the treatment's, although both groups significantly increased from pre to post. However, the FAIR vocabulary posttest was not part of the Treasures vocabulary, which was taught using the multimodal framework of strategies. The Treasures vocabulary scores were not significantly different by group on the assessment across the weeks, although the treatment means were higher than those of the comparison group. Continued research is needed in the area of vocabulary and comprehension instructional methods in order to determine strategies to increase diverse, urban students' performance.

Peer Support: An Intervention To Facilitate Second Language Acquisition In Students With Asperger Syndrome And Primary Language Deficits

This is a study of a peer support program to aid students in secondary school struggling to learn a second language (for college entrance requirements) who have Asperger Syndrone and primary language deficits.