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Title: Learning Opportunities and Challenges of Sensor-enabled Intelligent Tutoring Systems on Mobile Platforms: Benchmarking the Reliability of Mobile Sensors to Track Human Physiological Signals and Behaviors to Enhance Tablet-Based Intelligent Tutoring Systems.
Creator: Vazquez, Luis, Proctor, Michael, Jentsch, Florian, Gonzalez, Avelino, Sottilare, Robert, University of Central Florida
Abstract / Description: Desktop-based intelligent tutoring systems have existed for many decades, but the advancement of mobile computing technologies has sparked interest in developing mobile intelligent tutoring systems (mITS). Personalized mITS are applicable to not only stand-alone and client-server systems but also cloud systems possibly leveraging big data. Device-based sensors enable even greater personalization through capture of physiological signals during periods of student study. However, personalizing...
Show moreDesktop-based intelligent tutoring systems have existed for many decades, but the advancement of mobile computing technologies has sparked interest in developing mobile intelligent tutoring systems (mITS). Personalized mITS are applicable to not only stand-alone and client-server systems but also cloud systems possibly leveraging big data. Device-based sensors enable even greater personalization through capture of physiological signals during periods of student study. However, personalizing mITS to individual students faces challenges. The Achilles heel of personalization is the feasibility and reliability of these sensors to accurately capture physiological signals and behavior measures.This research reviews feasibility and benchmarks reliability of basic mobile platform sensors in various student postures. The research software and methodology are generalizable to a range of platforms and sensors. Incorporating the tile-based puzzle game 2048 as a substitute for a knowledge domain also enables a broad spectrum of test populations. Baseline sensors include the on-board camera to detect eyes/faces and the Bluetooth Empatica E4 wristband to capture heart rate, electrodermal activity (EDA), and skin temperature. The test population involved 100 collegiate students randomly assigned to one of three different ergonomic positions in a classroom: sitting at a table, standing at a counter, or reclining on a sofa. Well received by the students, EDA proved to be more reliable than heart rate or face detection in the three different ergonomic positions. Additional insights are provided on advancing learning personalization through future sensor feasibility and reliability studies.
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Date Issued: 2018
Identifier: CFE0007260, ucf:52177
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007260

Title: Automated Synthesis of Memristor Crossbar Networks.
Creator: Chakraborty, Dwaipayan, Jha, Sumit Kumar, Leavens, Gary, Ewetz, Rickard, Valliyil Thankachan, Sharma, Xu, Mengyu, University of Central Florida
Abstract / Description: The advancement of semiconductor device technology over the past decades has enabled the design of increasingly complex electrical and computational machines. Electronic design automation (EDA) has played a significant role in the design and implementation of transistor-based machines. However, as transistors move closer toward their physical limits, the speed-up provided by Moore's law will grind to a halt. Once again, we find ourselves on the verge of a paradigm shift in the computational...
Show moreThe advancement of semiconductor device technology over the past decades has enabled the design of increasingly complex electrical and computational machines. Electronic design automation (EDA) has played a significant role in the design and implementation of transistor-based machines. However, as transistors move closer toward their physical limits, the speed-up provided by Moore's law will grind to a halt. Once again, we find ourselves on the verge of a paradigm shift in the computational sciences as newer devices pave the way for novel approaches to computing. One of such devices is the memristor -- a resistor with non-volatile memory.Memristors can be used as junctional switches in crossbar circuits, which comprise of intersecting sets of vertical and horizontal nanowires. The major contribution of this dissertation lies in automating the design of such crossbar circuits -- doing a new kind of EDA for a new kind of computational machinery. In general, this dissertation attempts to answer the following questions:a. How can we synthesize crossbars for computing large Boolean formulas, up to 128-bit?b. How can we synthesize more compact crossbars for small Boolean formulas, up to 8-bit?c. For a given loop-free C program doing integer arithmetic, is it possible to synthesize an equivalent crossbar circuit?We have presented novel solutions to each of the above problems. Our new, proposed solutions resolve a number of significant bottlenecks in existing research, via the usage of innovative logic representation and artificial intelligence techniques. For large Boolean formulas (up to 128-bit), we have utilized Reduced Ordered Binary Decision Diagrams (ROBDDs) to automatically synthesize linearly growing crossbar circuits that compute them. This cutting edge approach towards flow-based computing has yielded state-of-the-art results. It is worth noting that this approach is scalable to n-bit Boolean formulas. We have made significant original contributions by leveraging artificial intelligence for automatic synthesis of compact crossbar circuits. This inventive method has been expanded to encompass crossbar networks with 1D1M (1-diode-1-memristor) switches, as well. The resultant circuits satisfy the tight constraints of the Feynman Grand Prize challenge and are able to perform 8-bit binary addition. A leading edge development for end-to-end computation with flow-based crossbars has been implemented, which involves methodical translation of loop-free C programs into crossbar circuits via automated synthesis. The original contributions described in this dissertation reflect the substantial progress we have made in the area of electronic design automation for synthesis of memristor crossbar networks.
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Date Issued: 2019
Identifier: CFE0007609, ucf:52528
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007609

Title: Academic Engagement through Experiential Learning: Building Transferable Skills within Undergraduate Education.
Creator: Lee, Shara, Cintron Delgado, Rosa, Laureano Fuentes, Gloria, Boyd, Karen, Okumus, Fevzi, Dressler, Sheri, University of Central Florida
Abstract / Description: Presently, there is a national focus on the industry-benefitting skills developed through undergraduate education. The purpose of this study is to examine the effectiveness of an experiential learning course on building three ability-based transferable skills: communication, emotional intelligence, and professional qualities. These skills have been determined to be important components to the skill set of graduates intending to enter any career, including one within the hospitality industry....
Show morePresently, there is a national focus on the industry-benefitting skills developed through undergraduate education. The purpose of this study is to examine the effectiveness of an experiential learning course on building three ability-based transferable skills: communication, emotional intelligence, and professional qualities. These skills have been determined to be important components to the skill set of graduates intending to enter any career, including one within the hospitality industry. Results from an examination of three related instruments led to conclusions that an experiential learning course positively impacts self-perceived skill development among the three aforementioned skills as well as perception of overall performance. In addition, it was determined that experiential learning courses benefitted interns irrespective of self-reported learning style preference and that such courses may aid in narrowing the perceived gap between intern and employer perceptions of intern skill levels and thereby prepare graduates with increasing success for societal productivity.
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Date Issued: 2012
Identifier: CFE0004568, ucf:49189
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004568

Title: MOBILITY AND SAFETY EVALUATION OF INTEGRATED DYNAMIC MERGE AND SPEED CONTROL STRATEGIES IN WORK ZONES.
Creator: Zaidi, Syed, Radwan, Essam, University of Central Florida
Abstract / Description: There has been a considerable increase in the amount of construction work on the U.S. national highways. Due to the capacity drop, which is the result of lane closure in work zone area, congestion occurs with a high traffic demand. The congestion increases number and severity of traffic conflicts which raise the potential for accidents; furthermore traffic operational properties of roadway in work zone area become worse. Intelligent Transportation System technologies have been developed and...
Show moreThere has been a considerable increase in the amount of construction work on the U.S. national highways. Due to the capacity drop, which is the result of lane closure in work zone area, congestion occurs with a high traffic demand. The congestion increases number and severity of traffic conflicts which raise the potential for accidents; furthermore traffic operational properties of roadway in work zone area become worse. Intelligent Transportation System technologies have been developed and are being deployed to improve the safety and mobility of traffic in and around work zones. The use of Dynamic Merge Controls (dynamic early merge and dynamic late merge) have been initiated to enhance traffic safety and to smooth traffic operations in work zone areas. The use of variable speed limit (VSL) systems at work zones is also one of those measures. VSL systems improve safety by helping the driver in determining the maximum speed that drivers should travel. Besides adding improvement to safety, they are also expected to improve mobility at the work zones. The main goal of this study was to evaluate the safety and operational effectiveness of the dynamic merge systems in the presence of VSL controls. VISSIM model is utilized to simulate a two-to-one lane configuration when one out of the two lanes in the work zone is closed for traffic. Two scenarios each for early and late simplified dynamic lane merge system (SDLMS) with and without VSLs, whereas one scenario each for the current Motorist Awareness System (MAS) and VSL alone were adopted to assess the effectiveness of these scenarios under different traffic demand volumes and different driversÃƒÂƒÃ‚Â‚ÃƒÂ‚Ã‚Â' compliance rates to the messages displayed by the systems. Mean throughputs and travel time were operational measures of effectiveness whereas speed variance and deceleration means were taken as safety surrogate measures. Three different logics were coded each for VSL alone, early SDLMS+VSL and late SDLMS+VSL in calibrated and validated VISSIM model for SDLMS through Vehicle Actuated Programming (VAP) code. It is found that for low and medium volume levels (V0500, V1000 and V1500), there is no significant difference between the Maintenance of Traffic (MOT) plans for mean throughputs. For higher volume levels (V2000 and V2500), late SDLMS with and without VSL produced significantly higher mean throughputs for all compliance rates and truck percentages. This study revealed that VSL increases travel time through the work zone. It is also found out that VSL makes the system safer at higher volumes (2,000 vph and 2,500 vph). Another outcome of this study is that the addition of VSL to the dynamic merge systems helps in improving the overall safety of the system by lowering speed variances and deceleration means of the vehicles travelling through the work zone. The passage of traffic through the work zone is made safer when a speed control is integrated to a dynamic merge system.
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Date Issued: 2010
Identifier: CFE0003519, ucf:48974
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0003519

Title: An intelligent editor for natural language processing of unrestricted text.
Creator: Glinos, Demetrios George, Gomez, Fernando, Arts and Sciences
Abstract / Description: University of Central Florida College of Arts and Sciences Thesis; The understanding of natural language by computational methods has been a continuing and elusive problem in artificial intelligence. In recent years there has been a resurgence in natural language processing research. Much of this work has been on empirical or corpus-based methods which use a data-driven approach to train systems on large amounts of real language data. Using corpus-based methods, the performance of part-of...
Show moreUniversity of Central Florida College of Arts and Sciences Thesis; The understanding of natural language by computational methods has been a continuing and elusive problem in artificial intelligence. In recent years there has been a resurgence in natural language processing research. Much of this work has been on empirical or corpus-based methods which use a data-driven approach to train systems on large amounts of real language data. Using corpus-based methods, the performance of part-of-speech (POS) taggers, which assign to the individual words of a sentence their appropriate part of speech category (e.g., noun, verb, preposition), now rivals human performance levels, achieving accuracies exceeding 95%. Such taggers have proved useful as preprocessors for such tasks as parsing, speech synthesis, and information retrieval. Parsing remains, however, a difficult problem, even with the benefit of POS tagging. Moveover, as sentence length increases, there is a corresponding combinatorial explosing of alternative possible parses. Consider the following sentence from a New York Times online article: After Salinas was arrested for murder in 1995 and lawyers for the bank had begun monitoring his accounts, his personal banker in New York quietly advised Salinas' wife to move the money elsewhere, apparently without the consent of the legal department. To facilitate the parsing and other tasks, we would like to decompose this sentence into the following three shorter sentences which, taken together, convey the same meaning as the original: 1. Salinas was arrested for murder in 1995. 2. Lawyers for the bank had begun monitoring his accounts. 3. His personal banker in New York quietly advised Salinas' wife to move the money elsewhere, apparently without the consent of the legal department. This study investigates the development of heuristics for decomposing such long sentences into sets of shorter sentences without affecting the meaning of the original sentences. Without parsing or semantic analysis, heuristic rules were developed based on: (1) the output of a POS tagger (Brill's tagger); (2) the punctuation contained in the input sentences; and (3) the words themselves. The heuristic algorithms were implemented in an intelligent editor program which first augmented the POS tags and assigned tags to punctuation, and then tested the rules against a corpus of 25 New York Times online articles containing approximately 1,200 sentences and over 32,000 words, with good results. Recommendations are made for improving the algorithms and for continuing this line of research.
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Date Issued: 1999
Identifier: CFR0008181, ucf:53055
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFR0008181

Title: Analysis of Driver Behavior Modeling in Connected Vehicle Safety Systems Through High Fidelity Simulation.
Creator: Jamialahmadi, Ahmad, Pourmohammadi Fallah, Yaser, Rahnavard, Nazanin, Chatterjee, Mainak, University of Central Florida
Abstract / Description: A critical aspect of connected vehicle safety analysis is understanding the impact of human behavior on the overall performance of the safety system. Given the variation in human driving behavior and the expectancy for high levels of performance, it is crucial for these systems to be flexible to various driving characteristics. However, design, testing, and evaluation of these active safety systems remain a challenging task, exacerbated by the lack of behavioral data and practical test...
Show moreA critical aspect of connected vehicle safety analysis is understanding the impact of human behavior on the overall performance of the safety system. Given the variation in human driving behavior and the expectancy for high levels of performance, it is crucial for these systems to be flexible to various driving characteristics. However, design, testing, and evaluation of these active safety systems remain a challenging task, exacerbated by the lack of behavioral data and practical test platforms. Additionally, the need for the operation of these systems in critical and dangerous situations makes the burden of their evaluation very costly and time-consuming. As an alternative option, researchers attempt to use simulation platforms to study and evaluate their algorithms. In this work, we introduce a high fidelity simulation platform, designed for a hybrid transportation system involving both human-driven and automated vehicles. We decompose the human driving task and offer a modular approach in simulating a large-scale traffic scenario, making it feasible for extensive studying of automated and active safety systems. Furthermore, we propose a human-interpretable driver model represented as a closed-loop feedback controller. For this model, we analyze a large driving dataset to extract expressive parameters that would best describe different driving characteristics. Finally, we recreate a similarly dense traffic scenario within our simulator and conduct a thorough analysis of different human-specific and system-specific factors and study their effect on the performance and safety of the traffic network.
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Date Issued: 2018
Identifier: CFE0007573, ucf:52578
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007573

Title: Vicarious Trauma, Emotional Intelligence, and The Impact On Job Satisfaction In Residence Life Staff.
Creator: Hodge, Lynell, Owens, J. Thomas, Cintron Delgado, Rosa, Allen, Kay, Preston, Michael, Winton, Mark, University of Central Florida
Abstract / Description: (")There are wounds that never show on the body that are deeper and more hurtful than anything that bleeds.(") ? Laurell K. Hamilton,Due to the proximity of working with and engaging students, residence life staff members, have a unique work experience. This functional area of student affairs is responding to myriad student needs. Staff are responding to varying levels of campus emergencies, student illness, and assault (physical or sexual) on a given workday or workweek (Ojo (&) Thomas, 2012...
Show more(")There are wounds that never show on the body that are deeper and more hurtful than anything that bleeds.(") ? Laurell K. Hamilton,Due to the proximity of working with and engaging students, residence life staff members, have a unique work experience. This functional area of student affairs is responding to myriad student needs. Staff are responding to varying levels of campus emergencies, student illness, and assault (physical or sexual) on a given workday or workweek (Ojo (&) Thomas, 2012). One study found college students' on-campus lifestyle and routine activities can create opportunities for victimization (Fisher, Sloan, Cullen, Lu, (&) 1998). What cumulative impact does responding to these victimizations have on residence life staff members? This study will investigate the relationship between the exposures to vicarious trauma, considering emotional intelligence as a mitigating factor to explain job satisfaction of residence life staff members. Taking a closer look at how the continued exposure to victimization of others (in this case students), the individual's job satisfaction provides context to burnout and attrition, specifically in residence life professionals. Understanding how secondary exposure can impact a professional is a concern that has been studied in other professions such as nursing, social work, and mental health counseling. The findings have provided invaluable insight to the professional's experience. This study will attempt to do the same by exploring how these three variables interact with each other, through the use of three scales, Vicarious Trauma Scale (VTS), Genos-Emotional Intelligence Inventory (Genos-I), and Job Satisfaction Scale (JSS). ?
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Date Issued: 2016
Identifier: CFE0006325, ucf:51549
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006325

Title: Prototype Development in General Purpose Representation and Association Machine Using Communication Theory.
Creator: Li, Huihui, Wei, Lei, Rahnavard, Nazanin, Vosoughi, Azadeh, Da Vitoria Lobo, Niels, Wang, Wei, University of Central Florida
Abstract / Description: Biological system study has been an intense research area in neuroscience and cognitive science for decades of years. Biological human brain is created as an intelligent system that integrates various types of sensor information and processes them intelligently. Neurons, as activated brain cells help the brain to make instant and rough decisions. From the 1950s, researchers start attempting to understand the strategies the biological system employs, then eventually translate them into machine...
Show moreBiological system study has been an intense research area in neuroscience and cognitive science for decades of years. Biological human brain is created as an intelligent system that integrates various types of sensor information and processes them intelligently. Neurons, as activated brain cells help the brain to make instant and rough decisions. From the 1950s, researchers start attempting to understand the strategies the biological system employs, then eventually translate them into machine-based algorithms. Modern computers have been developed to meet our need to handle computational tasks which our brains are not capable of performing with precision and speed. While in these existing man-made intelligent systems, most of them are designed for specific purposes. The modern computers solve sophistic problems based on fixed representation and association formats, instead of employing versatile approaches to explore the unsolved problems.Because of the above limitations of the conventional machines, General Purpose Representation and Association Machine (GPRAM) System is proposed to focus on using a versatile approach with hierarchical representation and association structures to do a quick and rough assessment on multitasks. Through lessons learned from neuroscience, error control coding and digital communications, a prototype of GPRAM system by employing (7,4) Hamming codes and short Low-Density Parity Check (LDPC) codes is implemented. Types of learning processes are presented, which prove the capability of GPRAM for handling multitasks.Furthermore, a study of low resolution simple patterns and face images recognition using an Image Processing Unit (IPU) structure for GPRAM system is presented. IPU structure consists of a randomly constructed LDPC code, an iterative decoder, a switch and scaling, and decision devices. All the input images have been severely degraded to mimic human Visual Information Variability (VIV) experienced in human visual system. The numerical results show that 1) IPU can reliably recognize simple pattern images in different shapes and sizes; 2) IPU demonstrates an excellent multi-class recognition performance for the face images with high degradation. Our results are comparable to popular machine learning recognition methods towards images without any quality degradation; 3) A bunch of methods have been discussed for improving IPU recognition performance, e.g. designing various detection and power scaling methods, constructing specific LDPC codes with large minimum girth, etc.Finally, novel methods to optimize M-ary PSK, M-ary DPSK, and dual-ring QAM signaling with non-equal symbol probabilities over AWGN channels are presented. In digital communication systems, MPSK, MDPSK, and dual-ring QAM signaling with equiprobable symbols have been well analyzed and widely used in practice. Inspired by bio-systems, we suggest investigating signaling with non-equiprobable symbol probabilities, since in bio-systems it is highly-unlikely to follow the ideal setting and uniform construction of single type of system. The results show that the optimizing system has lower error probabilities than conventional systems and the improvements are dramatic. Even though the communication systems are used as the testing environment, clearly, our final goal is to extend current communication theory to accommodate or better understand bio-neural information processing systems.
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Date Issued: 2017
Identifier: CFE0006758, ucf:51846
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006758

Title: Modeling User Transportation Patterns Using Mobile Devices.
Creator: Davami, Erfan, Sukthankar, Gita, Gonzalez, Avelino, Foroosh, Hassan, Sukthankar, Rahul, University of Central Florida
Abstract / Description: Participatory sensing frameworks use humans and their computing devices as a large mobile sensing network. Dramatic accessibility and affordability have turned mobile devices (smartphone and tablet computers) into the most popular computational machines in the world, exceeding laptops. By the end of 2013, more than 1.5 billion people on earth will have a smartphone. Increased coverage and higher speeds of cellular networks have given these devices the power to constantly stream large amounts...
Show moreParticipatory sensing frameworks use humans and their computing devices as a large mobile sensing network. Dramatic accessibility and affordability have turned mobile devices (smartphone and tablet computers) into the most popular computational machines in the world, exceeding laptops. By the end of 2013, more than 1.5 billion people on earth will have a smartphone. Increased coverage and higher speeds of cellular networks have given these devices the power to constantly stream large amounts of data.Most mobile devices are equipped with advanced sensors such as GPS, cameras, and microphones. This expansion of smartphone numbers and power has created a sensing system capable of achieving tasks practically impossible for conventional sensing platforms. One of the advantages of participatory sensing platforms is their mobility, since human users are often in motion. This dissertation presents a set of techniques for modeling and predicting user transportation patterns from cell-phone and social media check-ins. To study large-scale transportation patterns, I created a mobile phone app, Kpark, for estimating parking lot occupancy on the UCF campus. Kpark aggregates individual user reports on parking space availability to produce a global picture across all the campus lots using crowdsourcing. An issue with crowdsourcing is the possibility of receiving inaccurate information from users, either through error or malicious motivations. One method of combating this problem is to model the trustworthiness of individual participants to use that information to selectively include or discard data.This dissertation presents a comprehensive study of the performance of different worker quality and data fusion models with plausible simulated user populations, as well as an evaluation of their performance on the real data obtained from a full release of the Kpark app on the UCF Orlando campus. To evaluate individual trust prediction methods, an algorithm selection portfolio was introduced to take advantage of the strengths of each method and maximize the overall prediction performance.Like many other crowdsourced applications, user incentivization is an important aspect of creating a successful crowdsourcing workflow. For this project a form of non-monetized incentivization called gamification was used in order to create competition among users with the aim of increasing the quantity and quality of data submitted to the project. This dissertation reports on the performance of Kpark at predicting parking occupancy, increasing user app usage, and predicting worker quality.
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Date Issued: 2015
Identifier: CFE0005597, ucf:50258
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005597

Title: Pen-based Methods For Recognition and Animation of Handwritten Physics Solutions.
Creator: Cheema, Salman, Laviola II, Joseph, Hughes, Charles, Sukthankar, Gita, Hammond, Tracy, University of Central Florida
Abstract / Description: There has been considerable interest in constructing pen-based intelligent tutoring systems due to the natural interaction metaphor and low cognitive load afforded by pen-based interaction. We believe that pen-based intelligent tutoring systems can be further enhanced by integrating animation techniques. In this work, we explore methods for recognizing and animating sketched physics diagrams. Our methodologies enable an Intelligent Tutoring System (ITS) to understand the scenario and...
Show moreThere has been considerable interest in constructing pen-based intelligent tutoring systems due to the natural interaction metaphor and low cognitive load afforded by pen-based interaction. We believe that pen-based intelligent tutoring systems can be further enhanced by integrating animation techniques. In this work, we explore methods for recognizing and animating sketched physics diagrams. Our methodologies enable an Intelligent Tutoring System (ITS) to understand the scenario and requirements posed by a given problem statement and to couple this knowledge with a computational model of the student's handwritten solution. These pieces of information are used to construct meaningful animations and feedback mechanisms that can highlight errors in student solutions. We have constructed a prototype ITS that can recognize mathematics and diagrams in a handwritten solution and infer implicit relationships among diagram elements, mathematics and annotations such as arrows and dotted lines. We use natural language processing to identify the domain of a given problem, and use this information to select one or more of four domain-specific physics simulators to animate the user's sketched diagram. We enable students to use their answers to guide animation behavior and also describe a novel algorithm for checking recognized student solutions. We provide examples of scenarios that can be modeled using our prototype system and discuss the strengths and weaknesses of our current prototype.Additionally, we present the findings of a user study that aimed to identify animation requirements for physics tutoring systems. We describe a taxonomy for categorizing different types of animations for physics problems and highlight how the taxonomy can be used to define requirements for 50 physics problems chosen from a university textbook. We also present a discussion of 56 handwritten solutions acquired from physics students and describe how suitable animations could be constructed for each of them.
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Date Issued: 2014
Identifier: CFE0005472, ucf:50380
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005472

Title: Real-time traffic safety evaluation models and their application for variable speed limits.
Creator: Yu, Rongjie, Abdel-Aty, Mohamed, Radwan, Ahmed, Madani Larijani, Kaveh, Ahmed, Mohamed, Wang, Xuesong, University of Central Florida
Abstract / Description: Traffic safety has become the first concern in the transportation area. Crashes have cause extensive human and economic losses. With the objective of reducing crash occurrence and alleviating crash injury severity, major efforts have been dedicated to reveal the hazardous factors that affect crash occurrence at both the aggregate (targeting crash frequency per segment, intersection, etc.,) and disaggregate levels (analyzing each crash event). The aggregate traffic safety studies, mainly...
Show moreTraffic safety has become the first concern in the transportation area. Crashes have cause extensive human and economic losses. With the objective of reducing crash occurrence and alleviating crash injury severity, major efforts have been dedicated to reveal the hazardous factors that affect crash occurrence at both the aggregate (targeting crash frequency per segment, intersection, etc.,) and disaggregate levels (analyzing each crash event). The aggregate traffic safety studies, mainly developing safety performance functions (SPFs), are being conducted for the purpose of unveiling crash contributing factors for the interest locations. Results of the aggregate traffic safety studies can be used to identify crash hot spots, calculate crash modification factors (CMF), and improve geometric characteristics. Aggregate analyses mainly focus on discovering the hazardous factors that are related to the frequency of total crashes, of specific crash type, or of each crash severity level. While disaggregate studies benefit from the reliable surveillance systems which provide detailed real-time traffic and weather data. This information could help in capturing microlevel influences of the hazardous factors which might lead to a crash. The disaggregate traffic safety models, also called real-time crash risk evaluation models, can be used in monitoring crash hazardousness with the real-time field data fed in. One potential use of real-time crash risk evaluation models is to develop Variable Speed Limits (VSL) as a part of a freeway management system. Models have been developed to predict crash occurrence to proactively improve traffic safety and prevent crash occurrence.In this study, first, aggregate safety performance functions were estimated to unveil the different risk factors affecting crash occurrence for a mountainous freeway section. Then disaggregate real-time crash risk evaluation models have been developed for the total crashes with both the machine learning and hierarchical Bayesian models. Considering the need for analyzing both aggregate and disaggregate aspects of traffic safety, systematic multi-level traffic safety studies have been conducted for single- and multi-vehicle crashes, and weekday and weekend crashes. Finally, the feasibility of utilizing a VSL system to improve traffic safety on freeways has been investigated. This research was conducted based on data obtained from a 15-mile mountainous freeway section on I-70 in Colorado. The data contain historical crash data, roadway geometric characteristics, real-time weather data, and real-time traffic data. Real-time weather data were recorded by 6 weather stations installed along the freeway section, while the real-time traffic data were obtained from the Remote Traffic Microwave Sensor (RTMS) radars and Automatic Vechicle Identification (AVI) systems. Different datasets have been formulated from various data sources, and prepared for the multi-level traffic safety studies. In the aggregate traffic safety investigation, safety performance functions were developed to identify crash occurrence hazardous factors. For the first time real-time weather and traffic data were used in SPFs. Ordinary Poisson model and random effects Poisson models with Bayesian inference approach were employed to reveal the effects of weather and traffic related variables on crash occurrence. Two scenarios were considered: one seasonal based case and one crash type based case. Deviance Information Criterion (DIC) was utilized as the comparison criterion; and the correlated random effects Poisson models outperform the others. Results indicate that weather condition variables, especially precipitation, play a key role in the safety performance functions. Moreover, in order to compare with the correlated random effects Poisson model, Multivariate Poisson model and Multivariate Poisson-lognormal model have been estimated. Conclusions indicate that, instead of assuming identical random effects for the homogenous segments, considering the correlation effects between two count variables would result in better model fit. Results from the aggregate analyses shed light on the policy implication to reduce crash frequencies. For the studied roadway segment, crash occurrence in the snow season have clear trends associated with adverse weather situations (bad visibility and large amount of precipitation); weather warning systems can be employed to improve road safety during the snow season. Furthermore, different traffic management strategies should be developed according to the distinct seasonal influence factors. In particular, sites with steep slopes need more attention from the traffic management center and operators especially during snow seasons to control the excess crash occurrence. Moreover, distinct strategy of freeway management should be designed to address the differences between single- and multi-vehicle crash characteristics.In addition to developing safety performance functions with various modeling techniques, this study also investigates four different approaches of developing informative priors for the independent variables. Bayesian inference framework provides a complete and coherent way to balance the empirical data and prior expectations; merits of these informative priors have been tested along with two types of Bayesian hierarchical models (Poisson-gamma and Poisson-lognormal models). Deviance Information Criterion, R-square values, and coefficients of variance for the estimations were utilized as evaluation measures to select the best model(s). Comparisons across the models indicate that the Poisson-gamma model is superior with a better model fit and it is much more robust with the informative priors. Moreover, the two-stage Bayesian updating informative priors provided the best goodness-of-fit and coefficient estimation accuracies.In addition to the aggregate analyses, real-time crash risk evaluation models have been developed to identify crash contributing factors at the disaggregate level. Support Vector Machine (SVM), a recently proposed statistical learning model and Hierarchical Bayesian logistic regression models were introduced to evaluate real-time crash risk. Classification and regression tree (CART) model has been developed to select the most important explanatory variables. Based on the variable selection results, Bayesian logistic regression models and SVM models with different kernel functions have been developed. Model comparisons based on receiver operating curves (ROC) demonstrate that the SVM model with Radial basis kernel function outperforms the others. Results from the models demonstrated that crashes are likely to happen during congestion periods (especially when the queuing area has propagated from the downstream segment); high variation of occupancy and/or volume would increase the probability of crash occurrence.Moreover, effects of microscopic traffic, weather, and roadway geometric factors on the occurrence of specific crash types have been investigated. Crashes have been categorized as rear-end, sideswipe, and single-vehicle crashes. AVI segment average speed, real-time weather data, and roadway geometric characteristics data were utilized as explanatory variables. Conclusions from this study imply that different active traffic management (ATM) strategies should be designed for three- and two-lane roadway sections and also considering the seasonal effects. Based on the abovementioned results, real-time crash risk evaluation models have been developed separately for multi-vehicle and single-vehicle crashes, and weekday and weekend crashes. Hierarchical Bayesian logistic regression models (random effects and random parameter logistic regression models) have been introduced to address the seasonal variations, crash unit level's diversities, and unobserved heterogeneity caused by geometric characteristics. For the multi-vehicle crashes: congested conditions at downstream would contribute to an increase in the likelihood of multi-vehicle crashes; multi-vehicle crashes are more likely to occur during poor visibility conditions and if there is a turbulent area that exists downstream. Drivers who are unable to reduce their speeds timely are prone to causing rear-end crashes. While for the single-vehicle crashes: slow moving traffic platoons at the downstream detector of the crash occurrence locations would increase the probability of single-vehicle crashes; large variations of occupancy downstream would also increase the likelihood of single-vehicle crash occurrence.Substantial efforts have been dedicated to revealing the hazardous factors that affect crash occurrence from both the aggregate and disaggregate level in this study, however, findings and conclusions from these research work need to be transferred into applications for roadway design and freeway management. This study further investigates the feasibility of utilizing Variable Speed Limits (VSL) system, one key part of ATM, to improve traffic safety on freeways. A proactive traffic safety improvement VSL control algorithm has been proposed. First, an extension of the traffic flow model METANET was employed to predict traffic flow while considering VSL's impacts on the flow-density diagram; a real-time crash risk evaluation model was then estimated for the purpose of quantifying crash risk; finally, the optimal VSL control strategies were achieved by employing an optimization technique of minimizing the total predicted crash risks along the VSL implementation area. Constraints were set up to limit the increase of the average travel time and differences between posted speed limits temporarily and spatially. The proposed VSL control strategy was tested for a mountainous freeway bottleneck area in the microscopic simulation software VISSIM. Safety impacts of the VSL system were quantified as crash risk improvements and speed homogeneity improvements. Moreover, three different driver compliance levels were modeled in VISSIM to monitor the sensitivity of VSL's safety impacts on driver compliance levels. Conclusions demonstrate that the proposed VSL system could effectively improve traffic safety by decreasing crash risk, enhancing speed homogeneity, and reducing travel time under both high and moderate driver compliance levels; while the VSL system does not have significant effects on traffic safety enhancement under the low compliance scenario. Future implementations of VSL control strategies and related research topics were also discussed.
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Date Issued: 2013
Identifier: CFE0005283, ucf:50556
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005283

Title: Explicit Feedback Within Game-Based Training: Examining the Influence of Source Modality Effects on Interaction.
Creator: Goldberg, Benjamin, Bowers, Clint, Cannon-Bowers, Janis, Kincaid, John, McDaniel, Thomas, Sottilare, Robert, University of Central Florida
Abstract / Description: This research aims to enhance Simulation-Based Training (SBT) applications to support training events in the absence of live instruction. The overarching purpose is to explore available tools for integrating intelligent tutoring communications in game-based learning platforms and to examine theory-based techniques for delivering explicit feedback in such environments. The primary tool influencing the design of this research was the Generalized Intelligent Framework for Tutoring (GIFT), a...
Show moreThis research aims to enhance Simulation-Based Training (SBT) applications to support training events in the absence of live instruction. The overarching purpose is to explore available tools for integrating intelligent tutoring communications in game-based learning platforms and to examine theory-based techniques for delivering explicit feedback in such environments. The primary tool influencing the design of this research was the Generalized Intelligent Framework for Tutoring (GIFT), a modular domain-independent architecture that provides the tools and methods to author, deliver, and evaluate intelligent tutoring technologies within any training platform. Influenced by research surrounding Social Cognitive Theory and Cognitive Load Theory, the resulting experiment tested varying approaches for utilizing an Embodied Pedagogical Agent (EPA) to function as a tutor during interaction in a game-based environment. Conditions were authored to assess the tradeoffs between embedding an EPA directly in a game, embedding an EPA in GIFT's browser-based Tutor-User Interface (TUI), or using audio prompts alone with no social grounding.The resulting data supports the application of using an EPA embedded in GIFT's TUI to provide explicit feedback during a game-based learning event. Analyses revealed conditions with an EPA situated in the TUI to be as effective as embedding the agent directly in the game environment. This inference is based on evidence showing reliable differences across conditions on the metrics of performance and self-reported mental demand and feedback usefulness items. This research provides source modality tradeoffs linked to tactics for relaying training relevant explicit information to a user based on real-time performance in a game.
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Date Issued: 2013
Identifier: CFE0004850, ucf:49696
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004850

Title: Implementation Strategies for Real-time Traffic Safety Improvements on Urban Freeways.
Creator: Dilmore, Jeremy, Abdel-Aty, Mohamed, University of Central Florida
Abstract / Description: This research evaluates Intelligent Transportation System (ITS) implementation strategies to improve the safety of a freeway once a potential of a crash is detected. Among these strategies are Variable Speed Limit (VSL) and ramp metering. VSL are ITS devices that are commonly used to calm traffic in an attempt to relieve congestion and enhance throughput. With proper use, VSL can be more cost effective than adding more lanes. In addition to maximizing the capacity of a roadway, a different...
Show moreThis research evaluates Intelligent Transportation System (ITS) implementation strategies to improve the safety of a freeway once a potential of a crash is detected. Among these strategies are Variable Speed Limit (VSL) and ramp metering. VSL are ITS devices that are commonly used to calm traffic in an attempt to relieve congestion and enhance throughput. With proper use, VSL can be more cost effective than adding more lanes. In addition to maximizing the capacity of a roadway, a different aspect of VSL can be realized by the potential of improving traffic safety. Through the use of multiple microscopic traffic simulations, best practices can be determined, and a final recommendation can be made. Ramp metering is a method to control the amount of traffic flow entering from on-ramps to achieve a better efficiency of the freeway. It can also have a potential benefit in improving the safety of the freeway. This thesis pursues the goal of a best-case implementation of VSL. Two loading scenarios, a fully loaded case (90% of ramp maximums) and an off-peak loading case (60% of ramp maximums), at multiple stations with multiple implementation methods are strategically attempted until a best-case implementation is found. The final recommendation for the off-peak loading is a 15 mph speed reduction for 2 miles upstream and a 15 mph increase in speed for the 2 miles downstream of the detector that shows a high crash potential. The speed change is to be implemented in 5 mph increments every 10 minutes. The recommended case is found to reduce relative crash potential from .065 to -.292, as measured by a high-speed crash prediction algorithm (Abdel-Aty et al. 2005). A possibility of crash migration to downstream and upstream locations was observed, however, the safety and efficiency benefits far outweigh the crash migration potential. No final recommendation is made for the use of VSL in the fully loaded case (low-speed case); however, ramp metering indicated a promising potential for safety improvement.
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Date Issued: 2005
Identifier: CFE0000339, ucf:46287
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0000339

Title: Context-Centric Affect Recognition From Paralinguistic Features of Speech.
Creator: Marpaung, Andreas, Gonzalez, Avelino, DeMara, Ronald, Sukthankar, Gita, Wu, Annie, Lisetti, Christine, University of Central Florida
Abstract / Description: As the field of affect recognition has progressed, many researchers have shifted from having unimodal approaches to multimodal ones. In particular, the trends in paralinguistic speech affect recognition domain have been to integrate other modalities such as facial expression, body posture, gait, and linguistic speech. Our work focuses on integrating contextual knowledge into paralinguistic speech affect recognition. We hypothesize that a framework to recognize affect through paralinguistic...
Show moreAs the field of affect recognition has progressed, many researchers have shifted from having unimodal approaches to multimodal ones. In particular, the trends in paralinguistic speech affect recognition domain have been to integrate other modalities such as facial expression, body posture, gait, and linguistic speech. Our work focuses on integrating contextual knowledge into paralinguistic speech affect recognition. We hypothesize that a framework to recognize affect through paralinguistic features of speech can improve its performance by integrating relevant contextual knowledge. This dissertation describes our research to integrate contextual knowledge into the paralinguistic affect recognition process from acoustic features of speech. We conceived, built, and tested a two-phased system called the Context-Based Paralinguistic Affect Recognition System (CxBPARS). The first phase of this system is context-free and uses the AdaBoost classifier that applies data on the acoustic pitch, jitter, shimmer, Harmonics-to-Noise Ratio (HNR), and the Noise-to-Harmonics Ratio (NHR) to make an initial judgment about the emotion most likely exhibited by the human elicitor. The second phase then adds context modeling to improve upon the context-free classifications from phase I. CxBPARS was inspired by a human subject study performed as part of this work where test subjects were asked to classify an elicitor's emotion strictly from paralinguistic sounds, and then subsequently provided with contextual information to improve their selections. CxBPARS was rigorously tested and found to, at the worst case, improve the success rate from the state-of-the-art's 42% to 53%.
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Date Issued: 2019
Identifier: CFE0007836, ucf:52831
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007836

Title: Sustainability Analysis of Intelligent Transportation Systems.
Creator: Ercan, Tolga, Tatari, Mehmet, Al-Deek, Haitham, Oloufa, Amr, University of Central Florida
Abstract / Description: Commuters in urban areas suffer from traffic congestion on a daily basis. The increasing number of vehicles and vehicle miles traveled (VMT) are exacerbating this congested roadway problem for society. Although literature contains numerous studies that strive to propose solutions to this congestion problem, the problem is still prevalent today. Traffic congestion problem affects society's quality of life socially, economically, and environmentally. In order to alleviate the unsustainable...
Show moreCommuters in urban areas suffer from traffic congestion on a daily basis. The increasing number of vehicles and vehicle miles traveled (VMT) are exacerbating this congested roadway problem for society. Although literature contains numerous studies that strive to propose solutions to this congestion problem, the problem is still prevalent today. Traffic congestion problem affects society's quality of life socially, economically, and environmentally. In order to alleviate the unsustainable impacts of the congested roadway problem, Intelligent Transportation Systems (ITS) has been utilized to improve sustainable transportation systems in the world. The purpose of this thesis is to analyze the sustainable impacts and performance of the utilization of ITS in the United States. This thesis advances the body of knowledge of sustainability impacts of ITS related congestion relief through a triple bottom line (TBL) evaluation in the United States. TBL impacts analyze from a holistic perspective, rather than considering only the direct economic benefits. A critical approach to this research was to include both the direct and the indirect environmental and socio-economic impacts associated with the chain of supply paths of traffic congestion relief. To accomplish this aim, net benefits of ITS implementations are analyzed in 101 cities in the United States. In addition to the state level results, seven metropolitan cities in Florida are investigated in detail among these 101 cities. For instance, the results of this study indicated that Florida saved 1.38 E+05 tons of greenhouse gas emissions (tons of carbon dioxide equivalent), $420 million of annual delay reduction costs, and $17.2 million of net fuel-based costs. Furthermore, to quantify the relative impact and sustainability performance of different ITS technologies, several ITS solutions are analyzed in terms of total costs (initial and operation (&) maintenance costs) and benefits (value of time, emissions, and safety). To account for the uncertainty in benefit and cost analyses, a fuzzy-data envelopment analysis (DEA) methodology is utilized instead of the traditional DEA approach for sustainability performance analysis. The results using the fuzzy-DEA approach indicate that some of the ITS investments are not efficient compared to other investments where as all of them are highly effective investments in terms of the cost/benefit ratios approach. The TBL results of this study provide more comprehensive picture of socio-economic benefits which include the negative and indirect indicators and environmental benefits for ITS related congestion relief. In addition, sustainability performance comparisons and TBL analysis of ITS investments contained encouraging results to support decision makers to pursue ITS projects in the future.
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Date Issued: 2013
Identifier: CFE0004994, ucf:49549
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004994

Title: EXPLOITING OPPONENT MODELING FOR LEARNING IN MULTI-AGENT ADVERSARIAL GAMES.
Creator: Laviers, Kennard, Sukthankar, Gita, University of Central Florida
Abstract / Description: An issue with learning effective policies in multi-agent adversarial games is that the size of the search space can be prohibitively large when the actions of both teammates and opponents are considered simultaneously. Opponent modeling, predicting an opponent's actions in advance of execution, is one approach for selecting actions in adversarial settings, but it is often performed in an ad hoc way. In this dissertation, we introduce several methods for using opponent modeling, in the form of...
Show moreAn issue with learning effective policies in multi-agent adversarial games is that the size of the search space can be prohibitively large when the actions of both teammates and opponents are considered simultaneously. Opponent modeling, predicting an opponent's actions in advance of execution, is one approach for selecting actions in adversarial settings, but it is often performed in an ad hoc way. In this dissertation, we introduce several methods for using opponent modeling, in the form of predictions about the players' physical movements, to learn team policies. To explore the problem of decision-making in multi-agent adversarial scenarios, we use our approach for both offline play generation and real-time team response in the Rush 2008 American football simulator. Simultaneously predicting the movement trajectories, future reward, and play strategies of multiple players in real-time is a daunting task but we illustrate how it is possible to divide and conquer this problem with an assortment of data-driven models. By leveraging spatio-temporal traces of player movements, we learn discriminative models of defensive play for opponent modeling. With the reward information from previous play matchups, we use a modified version of UCT (Upper Conference Bounds applied to Trees) to create new offensive plays and to learn play repairs to counter predicted opponent actions. In team games, players must coordinate effectively to accomplish tasks while foiling their opponents either in a preplanned or emergent manner. An effective team policy must generate the necessary coordination, yet considering all possibilities for creating coordinating subgroups is computationally infeasible. Automatically identifying and preserving the coordination between key subgroups of teammates can make search more productive by pruning policies that disrupt these relationships. We demonstrate that combining opponent modeling with automatic subgroup identification can be used to create team policies with a higher average yardage than either the baseline game or domain-specific heuristics.
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Date Issued: 2011
Identifier: CFE0003914, ucf:48720
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0003914

Title: An Exploratory Comparison of a Traditional and an Adaptive Instructional Approach for College Algebra.
Creator: Kasha, Ryan, Kincaid, John, Wiegand, Rudolf, Hartshorne, Richard, Morris, Cliff, University of Central Florida
Abstract / Description: This research effort compared student learning gains and attitudinal changes through the implementation of two varying instructional approaches on the topic of functions in College Algebra. Attitudinal changes were measured based on the Attitude Towards Mathematics Inventory (ATMI). The ATMI also provided four sub-scales scores for self-confidence, value of learning, enjoyment, and motivation. Furthermore, this research explored and compared relationships between students' level of mastery...
Show moreThis research effort compared student learning gains and attitudinal changes through the implementation of two varying instructional approaches on the topic of functions in College Algebra. Attitudinal changes were measured based on the Attitude Towards Mathematics Inventory (ATMI). The ATMI also provided four sub-scales scores for self-confidence, value of learning, enjoyment, and motivation. Furthermore, this research explored and compared relationships between students' level of mastery and their actual level of learning. This study implemented a quasi-experimental research design using a sample that consisted of 56 College Algebra students in a public, state college in Florida. The sample was enrolled in one of two College Algebra sections, in which one section followed a self-adaptive instructional approach using ALEKS (Assessment and Learning in Knowledge Space) and the other section followed a traditional approach using MyMathLab. Learning gains in each class were measured as the difference between the pre-test and post-test scores on the topic of functions in College Algebra. Attitude changes in each class were measured as the difference between the holistic scores on the ATMI, as well as each of the four sub-scale scores, which was administered once in the beginning of the semester and again after the unit of functions, approximately eight weeks into the course. Utilizing an independent t-test, results indicated that there was not a significant difference in actual learning gains for the compared instructional approaches. Additionally, independent t-test results indicated that there was not a statistical difference for attitude change holistically and on each of the four sub-scales for the compared instructional approaches. However, correlational analyses revealed a strong relationship between students' level of mastery learning and their actual learning level for each class with the self-adaptive instructional approach having a stronger correlation than the non-adaptive section, as measured by an r-to-z Fisher transformation test. The results of this study indicate that the self-adaptive instructional approach using ALEKS could more accurately report students' true level of learning compared to a non-adaptive instructional approach. Overall, this study found the compared instructional approaches to be equivalent in terms of learning and effect on students' attitude. While not statistically different, the results of this study have implications for math educators, instructional designers, and software developers. For example, a non-adaptive instructional approach can be equivalent to a self-adaptive instructional approach in terms of learning with appropriate planning and design. Future recommendations include further case studies of self-adaptive technology in developmental and college mathematics in other modalities such as hybrid or on-line courses. Also, this study should be replicated on a larger scale with other self-adaptive math software in addition to focusing on other student populations, such as K - 12. There is much potential for intelligent tutoring to supplement different instructional approaches, but should not be viewed as a replacement for teacher-to-student interactions.
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Date Issued: 2015
Identifier: CFE0005963, ucf:50821
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005963

Title: Designing a Virtual Embedded Scenario-Based Military Simulation Training Program using Educational and Design Instructional Strategies.
Creator: Cook, Christina, Hopp, Carolyn, Gunter, Glenda, Hewitt, Randall, Vitale, Thomas, University of Central Florida
Abstract / Description: The purpose of this dissertation in practice was to develop and implement a new training program for designers of military intelligence simulation scenarios used to train soldiers. The use of education and design instructional strategies assisted in the ability for designers to gain mastery skills in creating realistic, high-fidelity scenarios that are applied in the training process. The use of simulation scenarios to train adult learners has increased significantly with improvements in...
Show moreThe purpose of this dissertation in practice was to develop and implement a new training program for designers of military intelligence simulation scenarios used to train soldiers. The use of education and design instructional strategies assisted in the ability for designers to gain mastery skills in creating realistic, high-fidelity scenarios that are applied in the training process. The use of simulation scenarios to train adult learners has increased significantly with improvements in technology and its fidelity to engage learners in a realistic way. Despite these advances, the lack of effective design, implementation and analysis of military simulation training programs in the military intelligence community has led to a decrease in simulation utilization, as in the case of the organization examined in this problem of practice. The current training program's increasing difficulties with consistent use by military intelligence simulation scenario designers were discovered in the results of a gap analysis conducted in 2014, prompting this design. This simulation design aimed to examine: (1) a research-based design methodology to match training requirements for the designers, (2) formative assessment of performance and (3) a research-based evaluation framework to determine the effectiveness of the new training program. For the organization's training program, a Simulation-Based Embedded Training (SBET) solution using scenarios was conceived based on research grounded in cognitive theory and instructional design considerations for simulations. As a structured framework for how to design and implement an effective and sustained training program, the educational instructional design model, ADDIE, was used. This model allowed for continual flexibility in each phase to evaluate and implement changes iteratively. The instructional model and its techniques were used with fidelity, specifically for training the designers of the simulation system. Industries will continue to increase the use of simulation as advances in technologies offer more realistic, safe, and complex training environments.A detailed strategy was provided specific to the organization using a research-based instructional approach integrated into program requirements set forth by the government. This proposed solution, supported by research in the application of instructional strategies, is specific to this organization; however, the training program design differs from other high-fidelity military simulator training programs through its use of dispersed training to the simulation scenario designers using realistic scenarios to mimic the tasks that the designers themselves must create. The difference in the solution in this dissertation in practice is: 1) that the simulation scenarios are designed without the help of subject matter experts by using the embedded instructional strategies and 2) the design is to the fidelity of realism required for military intelligence training exercises.
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Date Issued: 2018
Identifier: CFE0006990, ucf:51617
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006990

Title: A COMPARATIVE REVIEW OF THE WORKS OF FELDMAN, STERNBERG, GARDNER AND EISNER AND THE RESULTING PRACTICAL APPLICATION FOR THE SECONDARY ART CLASSROOM.
Creator: Denmark, Heather, Kaplan, Jeffrey, University of Central Florida
Abstract / Description: Some fields come and go, but there will always be a need for older generations to teach the younger generations. For this reason, teachers will always be needed. The material that they choose to teach can sometimes determine the outcome of a nation. Take a look into German and Roman histories; they are littered with teachers convincing students that their way is right. I think that it is imperative that we research the full potential of what we are teaching our students. For that reason, my...
Show moreSome fields come and go, but there will always be a need for older generations to teach the younger generations. For this reason, teachers will always be needed. The material that they choose to teach can sometimes determine the outcome of a nation. Take a look into German and Roman histories; they are littered with teachers convincing students that their way is right. I think that it is imperative that we research the full potential of what we are teaching our students. For that reason, my thesis will consist of analyzing and synthesizing the research of Feldman, Sternberg, Gardner and Eisner, gathering information on their works and applying them to art education. I will apply my findings to the modern day secondary art classroom; whether it is classroom design or visual handouts, I will use the knowledge gathered to better equip the room to the advancement of multiple intelligences in hopes of inspiring my future students to be creative and lifetime learners.
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Date Issued: 2011
Identifier: CFH0003803, ucf:44741
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFH0003803

Title: INTELLIGENT DESIGN.
Creator: Dudziak, Jillian, Poindexter, Carla, University of Central Florida
Abstract / Description: As human beings we are designed and created in a fabric that is profound and complex. We are built with a framework where mind and body work in a concerted effort to maintain our lives automatically. A deep and defining part of our existence as humans is not just the innate desire to live but to live in consistent well-beingemotionally, physically, and mentally. I believe when we incorporate our knowledge of human physiology into our creative process then we allow ourselves a greater...
Show moreAs human beings we are designed and created in a fabric that is profound and complex. We are built with a framework where mind and body work in a concerted effort to maintain our lives automatically. A deep and defining part of our existence as humans is not just the innate desire to live but to live in consistent well-beingemotionally, physically, and mentally. I believe when we incorporate our knowledge of human physiology into our creative process then we allow ourselves a greater opportunity to create an authentic connection with our intended audience. My work during the past three years has been rooted in the study of these philosophical and scientific principles. I created a series of visual experimentations that aim to assist in my understanding of human beings at an emotional and biological level. Armed with a deep desire to understand humanity, my goal is to create work that fosters positive change and has significant impact in the world. My past and present research has been focused on human emotions, the intuitive creative process and the relationship between technology and establishing social identity.
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Date Issued: 2011
Identifier: CFE0003693, ucf:48844
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0003693

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