The effectiveness of an intelligent tutoring system on the attitude and achievement of developmental mathematics students in a community college

This study examined the effectiveness of intelligent tutoring system instruction, grounded in John Anderson's ACT theory of cognition, on the achievement and attitude of developmental mathematics students in the community college setting. The quasi-experimental research used a pretest-posttest control group design. The dependent variables were problem solving achievement, overall achievement, and attitude towards mathematics. The independent variable was instructional method.^ Four intact classes and two instructors participated in the study for one semester. Two classes (n = 35) served as experimental groups; they received six lessons with real-world problems using intelligent tutoring system instruction. The other two classes (n = 24) served as control groups; they received six lessons with real-world problems using traditional instruction including graphing calculator support. It was hypothesized that students taught problem solving using the intelligent tutoring system would achieve more on the dependent variables than students taught without the intelligent tutoring system.^ Posttest mean scores for one teacher produced a significant difference in overall achievement for the experimental group. The same teacher had higher means, not significantly, for the experimental group in problem solving achievement. The study did not indicate a significant difference in attitude mean scores.^ It was concluded that using an intelligent tutoring system in problem solving instruction may impact student's overall mathematics achievement and problem solving achievement. Other factors must be considered, such as the teacher's classroom experience, the teacher's experience with the intelligent tutoring system, trained technical support, and trained student support; as well as student learning styles, motivation, and overall mathematics ability. ^

The effectiveness of an intelligent tutoring system on the attitude and achievement of developmental mathematics students in a community college

This study examined the effectiveness of intelligent tutoring system instruction, grounded in John Anderson's ACT theory of cognition, on the achievement and attitude of developmental mathematics students in the community college setting. The quasi-experimental research used a pretest-posttest control group design. The dependent variables were problem solving achievement, overall achievement, and attitude towards mathematics. The independent variable was instructional method. Four intact classes and two instructors participated in the study for one semester. Two classes (n = 35) served as experimental groups; they received six lessons with real-world problems using intelligent tutoring system instruction. The other two classes (n = 24) served as control groups; they received six lessons with real-world problems using traditional instruction including graphing calculator support. It was hypothesized that students taught problem solving using the intelligent tutoring system would achieve more on the dependent variables than students taught without the intelligent tutoring system. Posttest mean scores for one teacher produced a significant difference in overall achievement for the experimental group. The same teacher had higher means, not significantly, for the experimental group in problem solving achievement. The study did not indicate a significant difference in attitude mean scores. It was concluded that using an intelligent tutoring system in problem solving instruction may impact student's overall mathematics achievement and problem solving achievement. Other factors must be considered, such as the teacher's classroom experience, the teacher's experience with the intelligent tutoring system, trained technical support, and trained student support; as well as student learning styles, motivation, and overall mathematics ability.

An investigation of computer anxiety among vocational -technical teachers in Dade County, Florida

The purpose of this research was to investigate the relationship of computer anxiety to selected demographic variables: learning styles, age, gender, ethnicity, teaching/professional areas, educational level, and school types among vocational-technical educators.^ The subjects (n = 202) were randomly selected vocational-technical educators from Dade County Public School System, Florida, stratified across teaching/professional areas. All subjects received the same survey package in the spring of 1996. Subjects self-reported their learning style and level of computer anxiety by completing Kolb's Learning Style Inventory (LSI) and Oetting's Computer Anxiety Scale (COMPAS, Short Form). Subjects' general demographic information and their experience with computers were collected through a self-reported Participant Inventory Form.^ The distribution of scores suggested that some educators (25%) experienced some overall computer anxiety. There were significant correlations between computer related experience as indicated by self-ranked computer competence and computer based training and computer anxiety. One-way analyses of variance (ANOVA) indicated no significant differences between computer anxiety and/or computer related experiences, and learning style, age, and ethnicity. There were significant differences between educational level, teaching area, school type, and computer anxiety and/or computer related experiences. T-tests indicated significant differences between gender and computer related experiences. However, there was no difference between gender and computer anxiety.^ Analyses of covariance (ANCOVA) were performed for each independent variable on computer anxiety, with computer related experiences (self-ranked computer competence and computer based training) as the respective covariates. There were significant main effects for the educational level and school type on computer anxiety. All other variables were insignificant on computer anxiety. ANCOVA also revealed an effect for learning style varied notably on computer anxiety. All analyses were conducted at the.05 level of significance. ^

An assessment of computer usage within the Bahamian public school system and recommended guidelines towards the development of a strategic national computer plan

Computers have dramatically changed the way we live, conduct business, and deliver education. They have infiltrated the Bahamian public school system to the extent that many educators now feel the need for a national plan. The development of such a plan is a challenging undertaking, especially in developing countries where physical, financial, and human resources are scarce. This study assessed the situation with regard to computers within the Bahamian public school system, and provided recommended guidelines to the Bahamian government based on the results of a survey, the body of knowledge about trends in computer usage in schools, and the country's needs. ^ This was a descriptive study for which an extensive review of literature in areas of computer hardware, software, teacher training, research, curriculum, support services and local context variables was undertaken. One objective of the study was to establish what should or could be relative to the state-of-the-art in educational computing. A survey was conducted involving 201 teachers and 51 school administrators from 60 randomly selected Bahamian public schools. A random stratified cluster sampling technique was used. ^ This study used both quantitative and qualitative research methodologies. Quantitative methods were used to summarize the data about numbers and types of computers, categories of software available, peripheral equipment, and related topics through the use of forced-choice questions in a survey instrument. Results of these were displayed in tables and charts. Qualitative methods, data synthesis and content analysis, were used to analyze the non-numeric data obtained from open-ended questions on teachers' and school administrators' questionnaires, such as those regarding teachers' perceptions and attitudes about computers and their use in classrooms. Also, interpretative methodologies were used to analyze the qualitative results of several interviews conducted with senior public school system's officials. Content analysis was used to gather data from the literature on topics pertaining to the study. ^ Based on the literature review and the data gathered for this study a number of recommendations are presented. These recommendations may be used by the government of the Commonwealth of The Bahamas to establish policies with regard to the use of computers within the public school system. ^

A computer based approach to improve the dietary and physical activity patterns of a diverse group of adolescents

Diet and physical activity patterns have been implicated as major factors in the increasing prevalence of childhood and adolescent obesity. It is estimated that between 16 and 33 percent of children and adolescents in the United States are overweight (CDC, 2000). Moreover, the CDC estimates that less than 50% of adolescents are physically active on a regular basis (CDC, 2003). Interventions must be focused to modify these behaviors. Facilitating the understanding of proper nutrition and need for physical activity among adolescents is the first step in preventing overweight and obesity and delaying the development of chronic diseases later in life (Dwyer, 2000). The purpose of this study was to compare the outcomes of students receiving one of two forms of education (both emphasizing diet and physical activity), to determine whether a computer based intervention (CBI) program using an interactive, animated CD-ROM would elicit a greater behavior change in comparison to a traditional didactic intervention (TDI) program. A convenience sample of 254 high school students aged 14-19 participated in the 6-month program. A pre-test post-test design was used, with follow-up measures taken at three months post-intervention. ^ No change was noted in total fat, saturated fat, fruit/vegetables, or fiber intake for any of the groups. There was also no change in perceived self-efficacy or perceived social support. Results did, however, indicate an increase in nutrition knowledge for both intervention groups (p<0.001). In addition, the CBI group demonstrated more positive and sustained behavior changes throughout the course of the study. These changes included a decrease in BMI (ppre/post<0.001, ppost/follow-up<0.001), number of meals skipped (ppre/post<0.001), and soda consumption (ppre/post=0.003, ppost/follow-up=0.03) and an increase in nutrition knowledge (ppre/post<0.001, ppre/follow-up <0.001), physical activity (ppre/post<0.05, p pre/follow-up<0.01), frequency of label reading (ppre/follow-up <0.0l) and in dairy consumption (ppre/post=0.03). The TDI group did show positive gains in some areas post intervention, however a return to baseline behavior was shown at follow-up. Findings of this study suggest that compared to traditional didactic teaching, computer-based nutrition and health education has greater potential to elicit change in knowledge and behavior as well as promote maintenance of the behavior change over time. ^

Signal processing of physiological signals for automated assessment of stress in computer users

The need to provide computers with the ability to distinguish the affective state of their users is a major requirement for the practical implementation of affective computing concepts. This dissertation proposes the application of signal processing methods on physiological signals to extract from them features that can be processed by learning pattern recognition systems to provide cues about a person's affective state. In particular, combining physiological information sensed from a user's left hand in a non-invasive way with the pupil diameter information from an eye-tracking system may provide a computer with an awareness of its user's affective responses in the course of human-computer interactions. In this study an integrated hardware-software setup was developed to achieve automatic assessment of the affective status of a computer user. A computer-based "Paced Stroop Test" was designed as a stimulus to elicit emotional stress in the subject during the experiment. Four signals: the Galvanic Skin Response (GSR), the Blood Volume Pulse (BVP), the Skin Temperature (ST) and the Pupil Diameter (PD), were monitored and analyzed to differentiate affective states in the user. Several signal processing techniques were applied on the collected signals to extract their most relevant features. These features were analyzed with learning classification systems, to accomplish the affective state identification. Three learning algorithms: Naïve Bayes, Decision Tree and Support Vector Machine were applied to this identification process and their levels of classification accuracy were compared. The results achieved indicate that the physiological signals monitored do, in fact, have a strong correlation with the changes in the emotional states of the experimental subjects. These results also revealed that the inclusion of pupil diameter information significantly improved the performance of the emotion recognition system. ^

A digital signal processing approach for affective sensing of a computer user through pupil diameter monitoring

Recent research has indicated that the pupil diameter (PD) in humans varies with their affective states. However, this signal has not been fully investigated for affective sensing purposes in human-computer interaction systems. This may be due to the dominant separate effect of the pupillary light reflex (PLR), which shrinks the pupil when light intensity increases. In this dissertation, an adaptive interference canceller (AIC) system using the H∞ time-varying (HITV) adaptive algorithm was developed to minimize the impact of the PLR on the measured pupil diameter signal. The modified pupil diameter (MPD) signal, obtained from the AIC was expected to reflect primarily the pupillary affective responses (PAR) of the subject. Additional manipulations of the AIC output resulted in a processed MPD (PMPD) signal, from which a classification feature, PMPDmean, was extracted. This feature was used to train and test a support vector machine (SVM), for the identification of stress states in the subject from whom the pupil diameter signal was recorded, achieving an accuracy rate of 77.78%. The advantages of affective recognition through the PD signal were verified by comparatively investigating the classification of stress and relaxation states through features derived from the simultaneously recorded galvanic skin response (GSR) and blood volume pulse (BVP) signals, with and without the PD feature. The discriminating potential of each individual feature extracted from GSR, BVP and PD was studied by analysis of its receiver operating characteristic (ROC) curve. The ROC curve found for the PMPDmean feature encompassed the largest area (0.8546) of all the single-feature ROCs investigated. The encouraging results seen in affective sensing based on pupil diameter monitoring were obtained in spite of intermittent illumination increases purposely introduced during the experiments. Therefore, these results confirmed the benefits of using the AIC implementation with the HITV adaptive algorithm to isolate the PAR and the potential of using PD monitoring to sense the evolving affective states of a computer user.

DIMUSE: An integrated framework for distributed multimedia system with database management and security support

With the recent explosion in the complexity and amount of digital multimedia data, there has been a huge impact on the operations of various organizations in distinct areas, such as government services, education, medical care, business, entertainment, etc. To satisfy the growing demand of multimedia data management systems, an integrated framework called DIMUSE is proposed and deployed for distributed multimedia applications to offer a full scope of multimedia related tools and provide appealing experiences for the users. This research mainly focuses on video database modeling and retrieval by addressing a set of core challenges. First, a comprehensive multimedia database modeling mechanism called Hierarchical Markov Model Mediator (HMMM) is proposed to model high dimensional media data including video objects, low-level visual/audio features, as well as historical access patterns and frequencies. The associated retrieval and ranking algorithms are designed to support not only the general queries, but also the complicated temporal event pattern queries. Second, system training and learning methodologies are incorporated such that user interests are mined efficiently to improve the retrieval performance. Third, video clustering techniques are proposed to continuously increase the searching speed and accuracy by architecting a more efficient multimedia database structure. A distributed video management and retrieval system is designed and implemented to demonstrate the overall performance. The proposed approach is further customized for a mobile-based video retrieval system to solve the perception subjectivity issue by considering individual user's profile. Moreover, to deal with security and privacy issues and concerns in distributed multimedia applications, DIMUSE also incorporates a practical framework called SMARXO, which supports multilevel multimedia security control. SMARXO efficiently combines role-based access control (RBAC), XML and object-relational database management system (ORDBMS) to achieve the target of proficient security control. A distributed multimedia management system named DMMManager (Distributed MultiMedia Manager) is developed with the proposed framework DEMUR; to support multimedia capturing, analysis, retrieval, authoring and presentation in one single framework.

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.

Abstractions to support dynamic adaptation of communication frameworks for user-centric communication

The convergence of data, audio and video on IP networks is changing the way individuals, groups and organizations communicate. This diversity of communication media presents opportunities for creating synergistic collaborative communications. This form of collaborative communication is however not without its challenges. The increasing number of communication service providers coupled with a combinatorial mix of offered services, varying Quality-of-Service and oscillating pricing of services increases the complexity for the user to manage and maintain ‘always best’ priced or performance services. Consumers have to manually manage and adapt their communication in line with differences in services across devices, networks and media while ensuring that the usage remain consistent with their intended goals. This dissertation proposes a novel user-centric approach to address this problem. The proposed approach aims to reduce the aforementioned complexity to the user by (1) providing high-level abstractions and a policy based methodology for automated selection of the communication services guided by high-level user policies and (2) providing services through the seamless integration of multiple communication service providers and providing an extensible framework to support the integration of multiple communication service providers. The approach was implemented in the Communication Virtual Machine (CVM), a model-driven technology for realizing communication applications. The CVM includes the Network Communication Broker, the layer responsible for providing a network-independent API to the upper layers of CVM. The initial prototype for the NCB supported only a single communication framework which limited the number, quality and types of services available. Experimental evaluation of the approach show the additional overhead of the approach is minimal compared to the individual communication services frameworks. Additionally the automated approach proposed out performed the individual communication services frameworks for cross framework switching.

Leveraging symbiotic relationships for emulation of computer networks

The lack of analytical models that can accurately describe large-scale networked systems makes empirical experimentation indispensable for understanding complex behaviors. Research on network testbeds for testing network protocols and distributed services, including physical, emulated, and federated testbeds, has made steady progress. Although the success of these testbeds is undeniable, they fail to provide: 1) scalability, for handling large-scale networks with hundreds or thousands of hosts and routers organized in different scenarios, 2) flexibility, for testing new protocols or applications in diverse settings, and 3) inter-operability, for combining simulated and real network entities in experiments. This dissertation tackles these issues in three different dimensions. First, we present SVEET, a system that enables inter-operability between real and simulated hosts. In order to increase the scalability of networks under study, SVEET enables time-dilated synchronization between real hosts and the discrete-event simulator. Realistic TCP congestion control algorithms are implemented in the simulator to allow seamless interactions between real and simulated hosts. SVEET is validated via extensive experiments and its capabilities are assessed through case studies involving real applications. Second, we present PrimoGENI, a system that allows a distributed discrete-event simulator, running in real-time, to interact with real network entities in a federated environment. PrimoGENI greatly enhances the flexibility of network experiments, through which a great variety of network conditions can be reproduced to examine what-if questions. Furthermore, PrimoGENI performs resource management functions, on behalf of the user, for instantiating network experiments on shared infrastructures. Finally, to further increase the scalability of network testbeds to handle large-scale high-capacity networks, we present a novel symbiotic simulation approach. We present SymbioSim, a testbed for large-scale network experimentation where a high-performance simulation system closely cooperates with an emulation system in a mutually beneficial way. On the one hand, the simulation system benefits from incorporating the traffic metadata from real applications in the emulation system to reproduce the realistic traffic conditions. On the other hand, the emulation system benefits from receiving the continuous updates from the simulation system to calibrate the traffic between real applications. Specific techniques that support the symbiotic approach include: 1) a model downscaling scheme that can significantly reduce the complexity of the large-scale simulation model, resulting in an efficient emulation system for modulating the high-capacity network traffic between real applications; 2) a queuing network model for the downscaled emulation system to accurately represent the network effects of the simulated traffic; and 3) techniques for reducing the synchronization overhead between the simulation and emulation systems.

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. ^

Information systems to support decision-making in *construction owner organizations: A data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, non-integrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. ^ A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. ^ One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects. ^

The relationship of instructor technical literacy to the academic performance of students in career academies

Career Academy instructors' technical literacy is vital to the academic success of students. This nonexperimental ex post facto study examined the relationships between the level of technical literacy of instructors in career academies and student academic performance. It was also undertaken to explore the relationship between the pedagogical training of instructors and the academic performance of students. ^ Out of a heterogeneous population of 564 teachers in six targeted schools, 136 teachers (26.0 %) responded to an online survey. The survey was designed to gather demographic and teaching experience data. Each demographic item was linked by researchers to teachers' technology use in the classroom. Student achievement was measured by student learning gains as assessed by the reading section of the FCAT from the previous to the present school year. ^ Linear and hierarchical regressions were conducted to examine the research questions. To clarify the possibility of teacher gender and teacher race/ethnic group differences by research variable, a series of one-way ANOVAs were conducted. As revealed by the ANOVA results, there were not statistically significant group differences in any of the research variables by teacher gender or teacher race/ethnicity. Greater student learning gains were associated with greater teacher technical expertise integrating computers and technology into the classroom, even after controlling for teacher attitude towards computers. Neither teacher attitude toward technology integration nor years of experience in integrating computers into the curriculum significantly predicted student learning gains in the regression models. ^ Implications for HRD theory, research, and practice suggest that identifying teacher levels of technical literacy may help improve student academic performance by facilitating professional development strategies and new parameters for defining highly qualified instructors with 21st century skills. District professional development programs can benefit by increasing their offerings to include more computer and information communication technology courses. Teacher preparation programs can benefit by including technical literacy as part of their curriculum. State certification requirements could be expanded to include formal surveys to assess teacher use of technology.^

A middleware to support services delivery in a domain-specific virtual machine

The increasing use of model-driven software development has renewed emphasis on using domain-specific models during application development. More specifically, there has been emphasis on using domain-specific modeling languages (DSMLs) to capture user-specified requirements when creating applications. The current approach to realizing these applications is to translate DSML models into source code using several model-to-model and model-to-code transformations. This approach is still dependent on the underlying source code representation and only raises the level of abstraction during development. Experience has shown that developers will many times be required to manually modify the generated source code, which can be error-prone and time consuming. ^ An alternative to the aforementioned approach involves using an interpreted domain-specific modeling language (i-DSML) whose models can be directly executed using a Domain Specific Virtual Machine (DSVM). Direct execution of i-DSML models require a semantically rich platform that reduces the gap between the application models and the underlying services required to realize the application. One layer in this platform is the domain-specific middleware that is responsible for the management and delivery of services in the specific domain. ^ In this dissertation, we investigated the problem of designing the domain-specific middleware of the DSVM to facilitate the bifurcation of the semantics of the domain and the model of execution (MoE) while supporting runtime adaptation and validation. We approached our investigation by seeking solutions to the following sub-problems: (1) How can the domain-specific knowledge (DSK) semantics be separated from the MoE for a given domain? (2) How do we define a generic model of execution (GMoE) of the middleware so that it is adaptable and realizes DSK operations to support delivery of services? (3) How do we validate the realization of DSK operations at runtime? ^ Our research into the domain-specific middleware was done using an i-DSML for the user-centric communication domain, Communication Modeling Language (CML), and for microgrid energy management domain, Microgrid Modeling Language (MGridML). We have successfully developed a methodology to separate the DSK and GMoE of the middleware of a DSVM that supports specialization for a given domain, and is able to perform adaptation and validation at runtime. ^