An analysis of student and instructor perceptions of students' writing skills at the university level

This study examined university students' writing skills as perceived by university students and their English instructors. The goal of the study was to provide English instructors with objective, quantified information about writing perceptions from both the students' and instructors' viewpoints. ^ A survey instrument was developed based on a survey instrument created by Newkirk, Cameron, and Selfe (1977) to identify instructors' perceived knowledge of student writing skills. The present study used a descriptive statistical design. It examined five writing skill areas: attitude, content, grammar and mechanics, literary considerations, and the writing process through a questionnaire completed by a convenience sample of summer and fall admitted freshmen who were enrolled in Essay Writing and Freshman Composition courses and English Department instructors at a large South Florida public university. ^ The study consisted of five phases. The first phase was modifying of the Newkirk, Cameron, and Selfe (1977) questionnaire. Two versions of the revised survey were developed - one for instructors and one for students. The second phase was pilot testing the questionnaire for evaluation of administration and scoring. The third phase was administering the questionnaire to 1,280 students and 48 instructors. The fourth phase was analyzing the data. The study found a significant difference in the perceptions of students and instructors in all areas of writing skills examined by the survey. Responses to 29 of 30 questions showed that students felt they had better attitudes toward writing and better writing skills than instructors thought. ^ The final phase was developing recommendations for practice. Based on findings and theory and empirical evidence drawn from the fields of adult education and composition research, learner-centered, self-directed curriculum guidelines are offered. ^ By objectively quantifying student and instructor perceptions of students' writing skills, this study contributes to a growing body of literature that: (a) encourages instructors to acknowledge the perception disparities between instructors and students; (b) gives instructors a better understanding of how to communicate with students; and (c) recommends the development of new curriculum, placement tests, and courses that meet the needs of students and enables English instructors to provide meaningful instruction. ^

Ensemble fuzzy belief intrusion detection design

With the rapid growth of the Internet, computer attacks are increasing at a fast pace and can easily cause millions of dollar in damage to an organization. Detecting these attacks is an important issue of computer security. There are many types of attacks and they fall into four main categories, Denial of Service (DoS) attacks, Probe, User to Root (U2R) attacks, and Remote to Local (R2L) attacks. Within these categories, DoS and Probe attacks continuously show up with greater frequency in a short period of time when they attack systems. They are different from the normal traffic data and can be easily separated from normal activities. On the contrary, U2R and R2L attacks are embedded in the data portions of the packets and normally involve only a single connection. It becomes difficult to achieve satisfactory detection accuracy for detecting these two attacks. Therefore, we focus on studying the ambiguity problem between normal activities and U2R/R2L attacks. The goal is to build a detection system that can accurately and quickly detect these two attacks. In this dissertation, we design a two-phase intrusion detection approach. In the first phase, a correlation-based feature selection algorithm is proposed to advance the speed of detection. Features with poor prediction ability for the signatures of attacks and features inter-correlated with one or more other features are considered redundant. Such features are removed and only indispensable information about the original feature space remains. In the second phase, we develop an ensemble intrusion detection system to achieve accurate detection performance. The proposed method includes multiple feature selecting intrusion detectors and a data mining intrusion detector. The former ones consist of a set of detectors, and each of them uses a fuzzy clustering technique and belief theory to solve the ambiguity problem. The latter one applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The final decision is a combination of the outputs of feature selecting and data mining detectors. The experimental results indicate that our ensemble approach not only significantly reduces the detection time but also effectively detect U2R and R2L attacks that contain degrees of ambiguous information.

GRE as a predictor of graduate student success at a Hispanic serving institution of higher education

Accurately predicting the success of graduate students is an important aspect of determining which students should be admitted into graduate programs. The GRE is a pivotal factor to examine since it is one of the most widely used criteria for graduate school admission. Even though the GRE is advertised as an accurate tool for predicting first year graduate GPA, there is a lack of research on long term success factors such as time to degree and graduate rate (Luthy, 1996; Powers, 2004). Furthermore, since most studies have low minority sample sizes, the validity of the GRE may not be the same across all groups (ETS, 2008b; Kuncel, Hezlett, & Ones, 2001). Another gap in GRE studies is that few researchers analyze student characteristics, which may alter or moderate the prediction validity of the GRE. Thus, student characteristics such as degree of academic involvement, mentorship interactions, and other academic and social experiences have not been widely examined in this context. These gaps in the analysis of GRE validity are especially relevant given the high attrition rates within of some graduate programs (e.g., an estimated 68% of doctoral student never complete their programs in urban universities; Lovitts, 2001). A sequential mixed methods design was used to answer the research questions in two phases. The quantitative phase used student data files to analyze the relationship of two success variables (graduation rate and graduate GPA) to the GRE scores as well as other academic and demographic graduate student characteristics. The qualitative phase served to complement the first phase by describing a wider range of characteristics from the 11 graduate students who were interviewed. Both proximal and distal moderators influence student behaviors and success in graduate school. In the first phase of the study, the GRE was the distal facilitator under analysis. Findings suggested that both the GRE Quantitative and the GRE Verbal were predictors of success for master’s students, but the GRE Quantitative was not predictive of success for doctoral students. Other student characteristics such as demographic variables and disciplinary area were also predictors of success for the population of students studied. In the second phase of the study, it was inconclusive whether the GRE was predictive of graduate student success; though it did influence access to graduate programs. Furthermore, proximal moderators such as student involvement, faculty/peer interactions, motivational factors, and program structure were perceived to be facilitators and/or detractors for success.

The order selection and lot sizing problem in the make-to-order environment

This research is motivated by the need for considering lot sizing while accepting customer orders in a make-to-order (MTO) environment, in which each customer order must be delivered by its due date. Job shop is the typical operation model used in an MTO operation, where the production planner must make three concurrent decisions; they are order selection, lot size, and job schedule. These decisions are usually treated separately in the literature and are mostly led to heuristic solutions. The first phase of the study is focused on a formal definition of the problem. Mathematical programming techniques are applied to modeling this problem in terms of its objective, decision variables, and constraints. A commercial solver, CPLEX is applied to solve the resulting mixed-integer linear programming model with small instances to validate the mathematical formulation. The computational result shows it is not practical for solving problems of industrial size, using a commercial solver. The second phase of this study is focused on development of an effective solution approach to this problem of large scale. The proposed solution approach is an iterative process involving three sequential decision steps of order selection, lot sizing, and lot scheduling. A range of simple sequencing rules are identified for each of the three subproblems. Using computer simulation as the tool, an experiment is designed to evaluate their performance against a set of system parameters. For order selection, the proposed weighted most profit rule performs the best. The shifting bottleneck and the earliest operation finish time both are the best scheduling rules. For lot sizing, the proposed minimum cost increase heuristic, based on the Dixon-Silver method performs the best, when the demand-to-capacity ratio at the bottleneck machine is high. The proposed minimum cost heuristic, based on the Wagner-Whitin algorithm is the best lot-sizing heuristic for shops of a low demand-to-capacity ratio. The proposed heuristic is applied to an industrial case to further evaluate its performance. The result shows it can improve an average of total profit by 16.62%. This research contributes to the production planning research community with a complete mathematical definition of the problem and an effective solution approach to solving the problem of industry scale.

The role of emotional intelligence in college students' success

The purpose of this study was to determine if higher academic performance was positively correlated to higher emotional intelligence among traditional age male and female college students enrolled in an Introduction to Business course at a large multi-campus state college in Florida. The Bar-On 2004 (Emotional Quotient Inventory) EQ-i 133-item inventory was used to assess students’ emotional intelligence. Within the scope of this ex-post facto study, a quasi-experimental design was included to further determine if emotional intelligence could be increased through the inclusion of a curricular component on emotional intelligence. Four groups of students (N=111) participated in the three-phase study over two semesters. The first phase (pre-intervention) was limited to students with an established GPA and an attempted-to-completed credit hour ratio within the institution (N=82). Results showed a slight positive correlation between the two factors and the students’ emotional intelligence pretest assessment scores. The second phase of the study involved establishing a control and an experimental group in each of two semesters to compare the attainment of overall emotional intelligence scores as measured by the EQ-i. The third phase of the study examined four measures of academic success (GPA, the attempted-to-completed credit hour ratio, grade in the business course, and persistence in college) to determine if these factors were positively correlated with the students’ posttest EQ-i scores. The study also included a research question to determine if significant differences in overall EQ-i scores existed between male and female students during the three phases. Findings from the study indicated that (a) there was a slight positive correlation in the pre-intervention stage between emotional intelligence and traditional measures of academic success specifically, GPA and the attempted-to-completed credit hour ratio; (b) curricular intervention made a significant difference at the p <.05 level, with an .5 effect size, in one semester but failed to meet that threshold in the following semester with the second pair of groups; (c) at the post-intervention phase, the four measures of traditional academic success yielded a low positive correlation with the students’ emotional intelligence assessment scores, and (d) female students showed significant gains in their overall EQ-i scores.

Early career special education teachers' perceptions of school site induction support

Research highlights teacher attrition as one of the biggest challenges facing public schools and their attempts to provide a quality teacher for every student (Ingersoll & Smith, 2003). The teacher shortage is particularly daunting in special education where teachers are over twice as likely to leave the field. The first few years of teaching are the most critical in determining whether or not a beginning teacher will stay in the teaching profession (Whitaker, 2000). ^ A mixed-methods sequential explanatory design was utilized to examine research questions focused on the components of induction support that early career teachers received at their school site, including what they considered most valuable to their long-term retention in the classroom and their development as a quality teacher. Eighty seven early career special education teachers were surveyed during the first phase of the study and six participants were interviewed during the second phase. ^ Data analysis of the Likert-scale survey used in the study revealed that the majority of the respondents received at least 21 of the 25 listed induction components. Moreover, early career special education teachers indicated that they valued all 25 induction components. In addition, findings revealed that over two thirds of the respondents indicated a desire to remain a special education teacher. Overall, early career special education teachers felt confident in their abilities to teach students with disabilities; however, nearly half of the respondents did not feel satisfied with the induction they received. Independent t-tests showed a statistically significant difference between teachers who indicated a desire to remain in special education and those that did not on the level of satisfaction with their induction experience. ^ The six interviews provided elaboration and clarification of the survey responses. The participants expressed their passion for the art of teaching, their dedication to students with disabilities, and their frustration with being a beginning teacher. Furthermore, it was reported that the overall school culture was not very supportive. Participants offered relevant ideas for additional or alternate induction components that would be more effective.^

Social and environmental regulation of signal plasticity and signal reliability in the electric fish Brachyhypopomus gauderio

The balance between the costs and benefits of conspicuous signals ensures that the expression of those signals is related to the quality of the bearer. Plastic signals could enable males to maximize conspicuous traits to impress mates and competitors, but reduce the expression of those traits to minimize signaling costs, potentially compromising the information conveyed by the signals. ^ I investigated the effect of signal enhancement on the information coded by the biphasic electric signal pulse of the gymnotiform fish Brachyhypopomus gauderio. Increases in population density drive males to enhance the amplitude of their signals. I found that signal amplitude enhancement improves the information about the signaler's size. Furthermore, I found that the elongation of the signal's second phase conveys information about androgen levels in both sexes, gonad size in males and estrogen levels in females. Androgens link the duration of the signal's second phase to other androgen-mediated traits making the signal an honest indicator of reproductive state and aggressive motivation. ^ Signal amplitude enhancement facilitates the assessment of the signaler's resource holding potential, important for male-male interactions, while signal duration provides information about aggressive motivation to same-sex competitors and reproductive state to the opposite sex. Moreover, I found that female signals also change in accordance to the social environment. Females also increase the amplitude of their signal when population density increases and elongate the duration of their signal's second phase when the sex ratio becomes female-biased. Indicating that some degree of sexual selection operates in females. ^ I studied whether male B. gauderio use signal plasticity to reduce the cost of reproductive signaling when energy is limited. Surprisingly, I found that food limitation promotes the investment in reproduction manifested as signal enhancement and elevated androgen levels. The short lifespan and single breeding season of B. gauderio diminishes the advantage of energy savings and gives priority to sustaining reproduction. I conclude that the electric signal of B. gauderio provides reliable information about the signaler, the quality of this information is reinforced rather than degraded with signal enhancement.^

Ensemble Fuzzy Belief Intrusion Detection Design

With the rapid growth of the Internet, computer attacks are increasing at a fast pace and can easily cause millions of dollar in damage to an organization. Detecting these attacks is an important issue of computer security. There are many types of attacks and they fall into four main categories, Denial of Service (DoS) attacks, Probe, User to Root (U2R) attacks, and Remote to Local (R2L) attacks. Within these categories, DoS and Probe attacks continuously show up with greater frequency in a short period of time when they attack systems. They are different from the normal traffic data and can be easily separated from normal activities. On the contrary, U2R and R2L attacks are embedded in the data portions of the packets and normally involve only a single connection. It becomes difficult to achieve satisfactory detection accuracy for detecting these two attacks. Therefore, we focus on studying the ambiguity problem between normal activities and U2R/R2L attacks. The goal is to build a detection system that can accurately and quickly detect these two attacks. In this dissertation, we design a two-phase intrusion detection approach. In the first phase, a correlation-based feature selection algorithm is proposed to advance the speed of detection. Features with poor prediction ability for the signatures of attacks and features inter-correlated with one or more other features are considered redundant. Such features are removed and only indispensable information about the original feature space remains. In the second phase, we develop an ensemble intrusion detection system to achieve accurate detection performance. The proposed method includes multiple feature selecting intrusion detectors and a data mining intrusion detector. The former ones consist of a set of detectors, and each of them uses a fuzzy clustering technique and belief theory to solve the ambiguity problem. The latter one applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The final decision is a combination of the outputs of feature selecting and data mining detectors. The experimental results indicate that our ensemble approach not only significantly reduces the detection time but also effectively detect U2R and R2L attacks that contain degrees of ambiguous information.

Exploring Perceptions of Middle Class Urban Indian Women Regarding Socio-Cultural Deterrents Influencing Participation in Adult and Continuing Educational Programs

Unlike its childhood counterpart, adult and continuing education is a voluntary activity, where adult learners partake in educational programs for the sake of realizing some explicit or implicit goal. The purpose of this study was to explore the association between socio-cultural influences and deterrents to participation of middle class urban Indian women in adult and continuing educational programs. Darkenwald and Merriam’s (1982) theory of non-participation was selected as the theoretical lens used to guide this study. This study involved collecting qualitative data to analyze participant views and was collected through 16 semi-structured interviews to explore participants’ individual perceptions concerning socio-cultural deterrents influencing participation of middle class urban Indian women in adult and continuing educational programs. Qualitative data were analyzed to discover emerging themes and sub-themes. In the second phase of the study, a modified Deterrent to Participation Scale – General (DPS-G) was used to measure data collected from the surveys completed by participants, that included specific demographic questions. Descriptive statistics were used to examine the relationships between the demographic questions and the deterrent identified on the DPS-G. The interview and survey data were used convergently to understand the relationship between socio-cultural influences and deterrents impacting participant participation in adult and continuing educational programs. The findings of the study indicated that the biggest socio-cultural influence deterring participation among middle class urban Indian women in adult and continuing educational programs is marriage. It is an Indian social norm that comes with a set of pre-defined roles and expectations, and married women find themselves consumed by fulfilling the marital and familial expectations and responsibilities and participation in adult and continuing educational program is furthest from their mind. Middle class urban Indian women do realize the importance of educational pursuits, but do not feel that they can, after marriage. They are open, however, to pursuing adult educational programs in the form of short-term skill development programs leading to income generation, although they would lead primarily to home-based work enterprises.

Effect of Pavement-Vehicle Interaction on Highway Fuel Consumption and Emission

Vehicle fuel consumption and emission are two important effectiveness measurements of sustainable transportation development. Pavement plays an essential role in goals of fuel economy improvement and greenhouse gas (GHG) emission reduction. The main objective of this dissertation study is to experimentally investigate the effect of pavement-vehicle interaction (PVI) on vehicle fuel consumption under highway driving conditions. The goal is to provide a better understanding on the role of pavement in the green transportation initiates. Four study phases are carried out. The first phase involves a preliminary field investigation to detect the fuel consumption differences between paired flexible-rigid pavement sections with repeat measurements. The second phase continues the field investigation by a more detailed and comprehensive experimental design and independently investigates the effect of pavement type on vehicle fuel consumption. The third study phase calibrates the HDM-IV fuel consumption model with data collected in the second field phase. The purpose is to understand how pavement deflection affects vehicle fuel consumption from a mechanistic approach. The last phase applies the calibrated HDM-IV model to Florida’s interstate network and estimates the total annual fuel consumption and CO2 emissions on different scenarios. The potential annual fuel savings and emission reductions are derived based on the estimation results. Statistical results from the two field studies both show fuel savings on rigid pavement compared to flexible pavement with the test conditions specified. The savings derived from the first phase are 2.50% for the passenger car at 112km/h, and 4.04% for 18-wheel tractor-trailer at 93km/h. The savings resulted from the second phase are 2.25% and 2.22% for passenger car at 93km/h and 112km/h, and 3.57% and 3.15% for the 6-wheel medium-duty truck at 89km/h and 105km/h. All savings are statistically significant at 95% Confidence Level (C.L.). From the calibrated HDM-IV model, one unit of pavement deflection (1mm) on flexible pavement can cause an excess fuel consumption by 0.234-0.311 L/100km for the passenger car and by 1.123-1.277 L/100km for the truck. The effect is more evident at lower highway speed than at higher highway speed. From the network level estimation, approximately 40 million gallons of fuel (combined gasoline and diesel) and 0.39 million tons of CO2 emission can be saved/reduced annually if all Florida’s interstate flexible pavement are converted to rigid pavement with the same roughness levels. Moreover, each 1-mile of flexible-rigid conversion can result in a reduction of 29 thousand gallons of fuel and 258 tons of CO2 emission yearly.