The Effect of Active Student Responding in Computer-Assisted Instruction on Social-Studies Learning by Students with Learning Disabilities: A Brief Report

An alternating treatment design was used to compare the effects of three student response conditions (Clicking, Repeating, and Listening) during computer-assisted instruction on social-studies facts learning and maintenance. Results showed that all students learned and maintained more social-studies facts taught in the Repeating condition followed by the Clicking condition.

The effect of active student responding in computer -assisted instruction on social -studies learning by students with learning disabilities

The purpose of this study was to compare the effects of three student response conditions during computer-assisted instruction on the acquisition and maintenance of social-studies facts. Two of the conditions required active student responding (ASR), whereas the other required an on-task (OT) response. Participants were five fifth-grade students, with learning disabilities enrolled in a private school. An alternating treatments design with a best treatments phase was used to compare the effects of the response procedures on three major dependent measures: same-day tests, next-day tests, and maintenance tests. ^ Each week for six weeks, participants were provided daily one-to-one instruction on sets of 21 unknown social-studies facts using a hypermedia computer program, with a new set of facts being practiced each week. Each set of 21 facts was divided randomly into three conditions: Clicking-ASR, Repeating-ASR, and Listening-OT. Hypermedia lesson began weekly with the concept introduction lesson, followed by practice and testing. Practice and testing occurred four days per week, per set. During Clicking-ASR, student practice involved the selection of a social-studies response by clicking on an item with the mouse on the hypermedia card. Repeating-ASR instruction required students to orally repeat the social-studies facts when prompted by the computer. During Listening-OT, students listened to the social-studies facts being read by the computer. During weeks seven and eight, instruction occurred with seven unknown facts using only the best treatment. ^ Test results show that all for all 5 students, the Repeating-ASR practice procedure resulted in more social-studies facts stated correctly on same-day tests, next-day tests, and one-and two-week maintenance tests. Clicking-ASR was the next most effective procedure. During the seventh and eighth week of instruction when only the best practice condition was implemented, Repeating-ASR produced higher scores than all conditions (including Repeating-ASR) during the first six weeks of the study. ^ The results lend further support to the growing body of literature that demonstrates the positive relation between ASR and student achievement. Much of the ASR literature has focused on the effects of increased ASR during teacher-led or peer-mediated instruction. This study adds a dimension to that research in that it demonstrated the importance of ASR during computer-assisted instruction and further suggests that the type of ASR used during computer-assisted instruction may influence learning. Future research is needed to investigate the effectiveness of other types of ASR during computer-assisted instruction and to identify other fundamental characteristics of an effective computer-assisted instruction. ^

Three essays on entrepreneurial entry, serial entrepreneurship, and labor turnover

This study explores two important aspects of entrepreneurship — liquidity constraints and serial entrepreneurs, with an additional analysis of occupational choice among wage workers. In the first essay, I revisit the question of whether entrepreneurs face liquidity constraints in business formation. The principle challenge is that wealth is correlated with unobserved ability, and adequate instruments are often difficult to identify. This paper uses the son's birth order as an instrument for household wealth. I exploit the data available in the Korean Labor and Income Panel Study, and find evidence of liquidity constraints associated with self-employment in South Korea. The second essay develops and tests a model that explains entry into serial entrepreneurship and the performance of serial entrepreneurs as the result of selection on innate ability. The model supposes that agents establish businesses with imperfect information about their entrepreneurial ability and the profitability of business ideas. Agents continually observe signals with which they update their beliefs, and this process eventually determines their next business choice. Selection on ability induces a positive correlation between entrepreneurial experience (measured by previous business earnings and founding experience) and serial business formation, as well as its subsequent performance. The predictions in the model are tested using panel data from the NLSY79. The analysis permits a distinction to be made between selection on innate ability and learning by doing. Motivated by previous empirical findings that white-collar workers had higher turnover rates than blue-collar workers during firm expansion, the third essay further examines job turnover among workers with or without specific skills. I present a search-matching model, which predicts that when firm growth is driven by technological advance, workers whose skills are specific to the obsolete technology show a higher tendency to separate from their jobs. This hypothesis is tested with data from the PSID. I find supportive evidence that in the context of technological change, having an occupation requiring specific skills, such as computer specialists or engineers, increases the odds of job separation by nearly eight percent. ^

Metacognitive Strategies and Learning

During the past decade, metacognition has been identified not only as a component of cognition but also as an important factor in learning. This practitioner proposes that educators and educational researchers should focus on the development and implementation of metacognitive learning strategies. The existing metacognitive studies have concentrated on several areas. One area centers on the continuing efforts to identify all the elements of metacognition. Another area concentrates on the roles that metacognition plays in specific learning behaviors that occur at various ages and levels of complexity. The third area investigates the relationships of metacognition to specific content areas of learning by focusing on the effects of metacognitive learning strategies. The most common areas of study have been reading comprehension, math skills, writing skills, and applying metacognitive strategies to learn various subjects using the computer. Directly or indirectly, the existing studies relate to the expanding applications of the relationships and relevancies of metacognition to learning. Considerable evidence confirms that when students use metacognitive strategies they often experience a higher level of learning. This practitioner believes that experiencing higher levels of learning gives students the confidence they need to construct knowledge which promotes lifelong learning.

Inquiring Minds Want to Know: Inquiry-Based Learning in the General Education and Inclusion Science Classroom

This study sought to apply the concepts of inquiry-based learning by increasing the number of laboratory experiments conducted in two science classes, and to identify the challenges of this instruction for students with special needs. Results showed that the grades achieved through lab write-ups greatly improved grades overall.

Ensemble Stream Model for Data-Cleaning in Sensor Networks

Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as f-test is performed during each node’s split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

Ficcion de racionalidad: La memoria como operador mitico en las esteticas polares de Jorge Luis Borges y Jose Lezama Lima

The aesthetic placement and period designation of Jorge Luis Borges (1899–1986) and José Lezama Lima (1910–1976) are complicated issues among critics. Borges is considered a predecessor of the Latin American literary “boom,” but despite that taxonomy his work transcends that definition and provides a foundation for new trends, such as the “neobarroco” cultivated by Severo Sarduy. Lezama is considered part of the second wave of the “boom,” but his work feeds, stylistically, from the Spanish baroque. At the same time, Lezama's daring treatment of homoeroticism and his system of images place him after the “boom” in a narrative style that is postmodern. This study undertakes a revision of external and internal issues, revealing the key fictive elements that characterize both writers. Through discourse analysis, a poetic system is formulated, which incorporates features of the “neobarroco,” and postmodern narrative styles. ^ This dissertation uses a polar structure to analyze both poetic visions and finds that they are symmetrical. From this perspective, Borges and Lezama belong to the “core” of literature that centers its emphasis in the creation of a system versus other modes of writing in which mimetic function prevails. By doing this and by recycling world culture, they create postmodern myth: the new building material for Hispanic American literature. ^ There are a few studies that explore the works of Borges and Lezama within the context of Baroque aesthetics. This dissertation offers a comprehensive analysis that considers their poetic visions at large. Besides the difference in perspective, defined as macro-spatial in Borges and micro-spatial in Lezama, there are many similarities. Both writers question the cause and effect relationship and the use of metaphor. They share a redefinition of genre as well as a hedonistic approach to literature. This kinship in poetic vision is revealed through the polar method used for this study, which proposes a new form of aesthetic placement and period designation. ^

Trust based security mechanisms for wireless sensor networks

Wireless sensor networks are emerging as effective tools in the gathering and dissemination of data. They can be applied in many fields including health, environmental monitoring, home automation and the military. Like all other computing systems it is necessary to include security features, so that security sensitive data traversing the network is protected. However, traditional security techniques cannot be applied to wireless sensor networks. This is due to the constraints of battery power, memory, and the computational capacities of the miniature wireless sensor nodes. Therefore, to address this need, it becomes necessary to develop new lightweight security protocols. This dissertation focuses on designing a suite of lightweight trust-based security mechanisms and a cooperation enforcement protocol for wireless sensor networks. This dissertation presents a trust-based cluster head election mechanism used to elect new cluster heads. This solution prevents a major security breach against the routing protocol, namely, the election of malicious or compromised cluster heads. This dissertation also describes a location-aware, trust-based, compromise node detection, and isolation mechanism. Both of these mechanisms rely on the ability of a node to monitor its neighbors. Using neighbor monitoring techniques, the nodes are able to determine their neighbors’ reputation and trust level through probabilistic modeling. The mechanisms were designed to mitigate internal attacks within wireless sensor networks. The feasibility of the approach is demonstrated through extensive simulations. The dissertation also addresses non-cooperation problems in multi-user wireless sensor networks. A scalable lightweight enforcement algorithm using evolutionary game theory is also designed. The effectiveness of this cooperation enforcement algorithm is validated through mathematical analysis and simulation. This research has advanced the knowledge of wireless sensor network security and cooperation by developing new techniques based on mathematical models. By doing this, we have enabled others to build on our work towards the creation of highly trusted wireless sensor networks. This would facilitate its full utilization in many fields ranging from civilian to military applications.

Development and validation of an instrument to predict online student success using faculty perceptions

Distance learning is growing and transforming educational institutions. The increasing use of distance learning by higher education institutions and particularly community colleges coupled with the higher level of student attrition in online courses than in traditional classrooms suggests that increased attention should be paid to factors that affect online student course completion. The purpose of the study was to develop and validate an instrument to predict community college online student course completion based on faculty perceptions, yielding a prediction model of online course completion rates. Social Presence and Media Richness theories were used to develop a theoretically-driven measure of online course completion. This research study involved surveying 311 community college faculty who taught at least one online course in the past 2 years. Email addresses of participating faculty were provided by two south Florida community colleges. Each participant was contacted through email, and a link to an Internet survey was given. The survey response rate was 63% (192 out of 303 available questionnaires). Data were analyzed through factor analysis, alpha reliability, and multiple regression. The exploratory factor analysis using principal component analysis with varimax rotation yielded a four-factor solution that accounted for 48.8% of the variance. Consistent with Social Presence theory, the factors with their percent of variance in parentheses were: immediacy (21.2%), technological immediacy (11.0%), online communication and interactivity (10.3%), and intimacy (6.3%). Internal consistency of the four factors was calculated using Cronbach's alpha (1951) with reliability coefficients ranging between .680 and .828. Multiple regression analysis yielded a model that significantly predicted 11% of the variance of the dependent variable, the percentage of student who completed the online course. As indicated in the literature (Johnson & Keil, 2002; Newberry, 2002), Media Richness theory appears to be closely related to Social Presence theory. However, elements from this theory did not emerge in the factor analysis.

On Optimizing Compatible Security Policies in Wireless Networks

This paper deals with finding the maximum number of security policies without conflicts. By doing so we can remove security loophole that causes security violation. We present the problem of maximum compatible security policy and its relationship to the problem of maximum acyclic subgraph, which is proved to be NP-hard. Then we present a polynomial-time approximation algorithm and show that our result has approximation ratio for any integer with complexity .

Ensemble Stream Model for Data-Cleaning in Sensor Networks

Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as ƒ-test is performed during each node's split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

Identity, Ideology, and Cinema: Making Sense of Japan's Foreign and Security Policies in the 1950s and 2000s

Japan is an important ally of the United States–the world’s third biggest economy, and one of the regional great powers in Asia. Making sense of Japan’s foreign and security policies is crucial for the future of peace and stability in Northeast Asia, where the possible sources of conflict such as territorial disputes or the disputes over Japan’s war legacy issues are observed. This dissertation explored Japan’s foreign and security policies based on Japan’s identities and unconscious ideologies. It employed an analysis of selected Japanese films from the late 1940s to the late 1950s, as well as from the late 1990s to the mid-2000s. The analysis demonstrated that Japan’s foreign and security policies could be understood in terms of a broader social narrative that was visible in Japanese popular cultural products, including films and literatures. Narratives of Japanese families from the patriarch’s point of view, for example, had constantly shaped Japan’s foreign and security policies. As a result, the world was ordered hierarchically in the eyes of the Japan Self. In the 1950s, Japan tenaciously constructed close but asymmetrical security relations with the U.S. in which Japan willingly subjugated itself to the U.S. In the 2000s, Japan again constructed close relations with the U.S. by doing its best to support American responses to the 9/11 terrorist attacks by mobilizing Japan’s SDFs in the way Japan had never done in the past. The concepts of identity and unconscious ideology are helpful in understanding how Japan’s own understanding of self, of others, and of the world have shaped its own behaviors. These concepts also enable Japan to reevaluate its own behaviors reflexively, which departs from existing alternative approaches. This study provided a critical analytical explanation of the dynamics at work in Japan’s sense of identity, particularly with regard to its foreign and security policies.

Trust Based Security Mechanisms for Wireless Sensor Networks

Wireless sensor networks are emerging as effective tools in the gathering and dissemination of data. They can be applied in many fields including health, environmental monitoring, home automation and the military. Like all other computing systems it is necessary to include security features, so that security sensitive data traversing the network is protected. However, traditional security techniques cannot be applied to wireless sensor networks. This is due to the constraints of battery power, memory, and the computational capacities of the miniature wireless sensor nodes. Therefore, to address this need, it becomes necessary to develop new lightweight security protocols. This dissertation focuses on designing a suite of lightweight trust-based security mechanisms and a cooperation enforcement protocol for wireless sensor networks. This dissertation presents a trust-based cluster head election mechanism used to elect new cluster heads. This solution prevents a major security breach against the routing protocol, namely, the election of malicious or compromised cluster heads. This dissertation also describes a location-aware, trust-based, compromise node detection, and isolation mechanism. Both of these mechanisms rely on the ability of a node to monitor its neighbors. Using neighbor monitoring techniques, the nodes are able to determine their neighbors’ reputation and trust level through probabilistic modeling. The mechanisms were designed to mitigate internal attacks within wireless sensor networks. The feasibility of the approach is demonstrated through extensive simulations. The dissertation also addresses non-cooperation problems in multi-user wireless sensor networks. A scalable lightweight enforcement algorithm using evolutionary game theory is also designed. The effectiveness of this cooperation enforcement algorithm is validated through mathematical analysis and simulation. This research has advanced the knowledge of wireless sensor network security and cooperation by developing new techniques based on mathematical models. By doing this, we have enabled others to build on our work towards the creation of highly trusted wireless sensor networks. This would facilitate its full utilization in many fields ranging from civilian to military applications.

Ficción de Racionalidad: La memoria como operador mítico en las estéticas polares de Jorge Luis Borges y José Lezama Lima

The aesthetic placement and period designation of Jorge Luis Borges (1899-1986) and José Lezama Lima (1910-1976) are complicated issues among critics. Borges is obviously considered a predecessor of the Latin American literary “boom,” but despite that taxonomy his work transcends that definition and provides a foundation for new trends and styles, such as the “neobarroco” cultivated by Severo Sarduy. Lezama is considered part of the second wave of the “boom,” but his work feeds, stylistically, from the Spanish baroque. At the same time, Lezama’s daring treatment of homoeroticism and his revolutionary system of images place him after the “boom” in a narrative style that is postmodern. This study undertakes a thorough revision of external and internal issues, revealing the key linguistic and fictive elements that characterize both writers. Through discourse analysis and close reading, a poetic system is formulated, which incorporate features of the “neobarroco,” “boom” and postmodern narrative styles. This dissertation uses a polar structure to analyze both poetic visions and concludes that they are compatible and symmetrical. From this perspective, Borges and Lezama belong to the “core” of literature that centers its emphasis in the creation of a system versus other modes of writing in which mimetic function prevails. By doing this and by recycling world culture, they create postmodern myth: the new building material for Hispanic American literature. There are only a few studies that explore the works of Borges and Lezama within the context of Baroque aesthetics. For the first time, this dissertation offers a comprehensive analysis that considers their poetic visions at large. Besides the difference in perspective, defined as macro-spatial in Borges and micro-spatial in Lezama, there are many similarities in content and form. Both writers question the cause and effect relationship and the modern use of metaphor. They also share a redefinition of genre as well as a hedonistic approach to literature and culture. This kinship in poetic vision is revealed through the polar method used for this study, which proposes a new form of aesthetic placement and period designation.

Gender Benders: Shakespeare's Rosalind and Woolf's Orlando

English Renaissance playwright, William Shakespeare and twentieth century modernist author, Virginia Woolf’s works, “As You Like It” (1599) and “Orlando” (1928), respectively posit a vision of gender that transcends the physical sex of the body. The play’s heroine, Rosalind, and the novel’s protagonist, Orlando, each challenge the stability of the binary categories of male and female, demonstrating how gender is not absolute but rather a constantly adapting and evolving construct. This thesis traces the development of Rosalind and Orlando by analyzing and comparing both protagonists’ journeys towards concordia discors, considering how gender transformation plays a pivotal role in helping both figures transcend prescribed gender roles and restraints placed upon them by family and society. Both Rosalind and Orlando mount challenges to prescribed gender norms during periods when conservative gender roles were strictly enforced. By doing so, each character positions themselves as pivotal and progressive representations of gender performance for their time.