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SENSEMAKING IN INFORMATION SYSTEMS: TOWARD A SENSEMAKING INQUIRING SYSTEM
Title
SENSEMAKING IN INFORMATION SYSTEMS: TOWARD A SENSEMAKING INQUIRING SYSTEM.
Creator
Parrish, James, Courtney, James, University of Central Florida
Abstract / Description
Complexity and uncertainty have long been problems for organizations of all types. Organizational members do not do a very good job of dealing with the complexity and uncertainty as research shows that when faced with complex situations humans often turn to the same sources of information repeatedly (a practice that will eventually betray them), and/or reduce the amount of scanning that they do (Weick 1995; Boyd and Fulk 1996). Organizations often turn to information systems to help them deal...
Show moreComplexity and uncertainty have long been problems for organizations of all types. Organizational members do not do a very good job of dealing with the complexity and uncertainty as research shows that when faced with complex situations humans often turn to the same sources of information repeatedly (a practice that will eventually betray them), and/or reduce the amount of scanning that they do (Weick 1995; Boyd and Fulk 1996). Organizations often turn to information systems to help them deal with the complexity, but they often take a techno-centric view of knowledge that does not incorporate the human qualities needed for unstructured decisions (Malhotra 1997; Courtney 2001; Malhotra 2001). Additionally, there are times when the information systems that we are using may hinder the processes of dealing with the complexity (Weick and Meader 1993). Weick's (1995) concept of sensemaking is believed to help us to deal with this complexity. In his work with Meader (1993) he wonders what the effects of a sensemaking support system would have, but he does not have the answer because they state that it has not been asked. This dissertation answers the call of Weick and Meader as well as other scholars that have called for sensemaking and human intuition to be included in our information systems. This is accomplished by viewing sensemaking from an inquiring systems perspective (Churchman 1971) to develop a kernel theory that will be used in the context of design science to develop design requirements and principles for a sensemaking system. These design principles are then used to build an instantiation of the system in the form of SenseMan, a system designed to help a local government agency deal with complexity in the context of software updates. Finally the design is evaluated for its effectiveness in dealing with the complexity of in this context using both quantitative and qualitative methods.
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Date Issued
2008
Identifier
CFE0002253, ucf:47834
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0002253
FLOCKS, SWARMS, CROWDS, AND SOCIETIES: ON THE SCOPE AND LIMITS OF COGNITION
Title
FLOCKS, SWARMS, CROWDS, AND SOCIETIES: ON THE SCOPE AND LIMITS OF COGNITION.
Creator
Neemeh, Zachariah A, Favela, Luis H., University of Central Florida
Abstract / Description
Traditionally, the concept of cognition has been tied to the brain or the nervous system. Recent work in various noncomputational cognitive sciences has enlarged the category of "cognitive phenomena" to include the organism and its environment, distributed cognition across networks of actors, and basic cellular functions. The meaning, scope, and limits of 'cognition' are no longer clear or well-defined. In order to properly delimit the purview of the cognitive sciences, there is a strong need...
Show moreTraditionally, the concept of cognition has been tied to the brain or the nervous system. Recent work in various noncomputational cognitive sciences has enlarged the category of "cognitive phenomena" to include the organism and its environment, distributed cognition across networks of actors, and basic cellular functions. The meaning, scope, and limits of 'cognition' are no longer clear or well-defined. In order to properly delimit the purview of the cognitive sciences, there is a strong need for a clarification of the definition of cognition. This paper will consider the outer bounds of that definition. Not all cognitive behaviors of a given organism are amenable to an analysis at the organismic or organism-environment level. In some cases, emergent cognition in collective biological and human social systems arises that is irreducible to the sum cognitions of their constituent entities. The group and social systems under consideration are more extensive and inclusive than those considered in studies of distributed cognition to date. The implications for this ultimately expand the purview of the cognitive sciences and bring back a renewed relevance for anthropology and introduce sociology on the traditional six-pronged interdisciplinary wheel of the cognitive sciences.
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Date Issued
2017
Identifier
CFH2000191, ucf:46026
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFH2000191
THE THERMODYNAMICS OF PLANETARY ENGINEERING ON THE PLANET MARS
Title
THE THERMODYNAMICS OF PLANETARY ENGINEERING ON THE PLANET MARS.
Creator
Barsoum, Christopher, Lin, Kuo-Chi, University of Central Florida
Abstract / Description
Mars is a potentially habitable planet given the appropriate planetary engineering efforts. In order to create a habitable environment, the planet must be terraformed, creating quasi-Earth conditions. Benchmarks for minimum acceptable survivable human conditions were set by observing atmospheric pressures and temperatures here on Earth that humans are known to exist in. By observing a positive feedback reaction, it is shown how the sublimation of the volatile southern polar ice cap on Mars...
Show moreMars is a potentially habitable planet given the appropriate planetary engineering efforts. In order to create a habitable environment, the planet must be terraformed, creating quasi-Earth conditions. Benchmarks for minimum acceptable survivable human conditions were set by observing atmospheric pressures and temperatures here on Earth that humans are known to exist in. By observing a positive feedback reaction, it is shown how the sublimation of the volatile southern polar ice cap on Mars can increase global temperatures and pressures to the benchmarks set for minimum acceptable survivable human conditions. Given the degree of uncertainty, utilization of pressure scale heights and the Martin extreme terrain were used to show how less than desirable conditions can still produce results where these benchmarks can be met. Methods for obtaining enough energy to sublimate the southern polar ice cap were reviewed in detail. A new method of using dark, carbonaceous Martian moon material to alter the overall average albedo of the polar ice cap is proposed. Such a method would increase Martian energy efficiency. It is shown that by covering roughly 10% of the Martian polar ice cap with dark carbonaceous material, this required energy can be obtained. Overall contributions include utilization of pressure scale heights at various suggested settlement sites, as well as polar albedo altering as a method of planetary engineering. This project serves as a foundational work for long term solar system exploration and settlement.
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Date Issued
2014
Identifier
CFH0004540, ucf:45225
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFH0004540
Team Interaction Dynamics during Collaborative Problem Solving
Title
Team Interaction Dynamics during Collaborative Problem Solving.
Creator
Wiltshire, Travis, Fiore, Stephen, Jentsch, Florian, Salas, Eduardo, Wiegand, Rudolf, University of Central Florida
Abstract / Description
This dissertation contributes an enhanced understanding of team cognition, in general, and collaborative problem solving (CPS), specifically, through an integration of methods that measure team interaction dynamics and knowledge building as it occurs during a complex CPS task. The need for better understanding CPS has risen in prominence as many organizations have increasingly worked to address complex problems requiring the combination of diverse sets of individual expertise to achieve...
Show moreThis dissertation contributes an enhanced understanding of team cognition, in general, and collaborative problem solving (CPS), specifically, through an integration of methods that measure team interaction dynamics and knowledge building as it occurs during a complex CPS task. The need for better understanding CPS has risen in prominence as many organizations have increasingly worked to address complex problems requiring the combination of diverse sets of individual expertise to achieve solutions for novel problems. Towards this end, the present research drew from theoretical and empirical work on Macrocognition in Teams that describes the knowledge coordination arising from team communications during CPS. It built from this by incorporating the study of team interaction during complex collaborative cognition. Interaction between team members in such contexts has proven to be inherently dynamic and exhibiting nonlinear patterns not accounted for by extant research methods. To redress this gap, the present research drew from work in cognitive science designed to study social and team interaction as a nonlinear dynamical system. CPS was examined by studying knowledge building and interaction processes of 43 dyads working on NASA's Moonbase Alpha simulation, a CPS task. Both non-verbal and verbal interaction dynamics were examined. Specifically, frame-differencing, an automated video analysis technique, was used to capture the bodily movements of participants and content coding was applied to the teams' communications to characterize their CPS processes. A combination of linear (i.e., multiple regression, t-test, and time-lagged cross-correlation analysis), as well as nonlinear analytic techniques (i.e., recurrence quantification analysis; RQA) were applied. In terms of the predicted interaction dynamics, it was hypothesized that teams would exhibit synchronization in their bodily movements and complementarity in their communications and further, that teams more strongly exhibiting these forms of coordination will produce better problem solving outcomes. Results showed that teams did exhibit a pattern of bodily movements that could be characterized as synchronized, but higher synchronization was not systematically related to performance. Further, results showed that teams did exhibit communicative interaction that was complementary, but this was not predictive of better problem solving performance. Several exploratory research questions were proposed as a way of refining the application of these techniques to the investigation of CPS. Results showed that semantic code-based communications time-series and %REC and ENTROPY recurrence-based measures were most sensitive to differences in performance. Overall, this dissertation adds to the scientific body of knowledge by advancing theory and empirical knowledge on the forms of verbal and non-verbal team interaction during CPS, but future work remains to be conducted to identify the relationship between interaction dynamics and CPS performance.
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Date Issued
2015
Identifier
CFE0005907, ucf:50867
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005907
EPISODIC MEMORY MODEL FOR EMBODIED CONVERSATIONAL AGENTS
Title
EPISODIC MEMORY MODEL FOR EMBODIED CONVERSATIONAL AGENTS.
Creator
Elvir, Miguel, Gonzalez, Avelino, University of Central Florida
Abstract / Description
Embodied Conversational Agents (ECA) form part of a range of virtual characters whose intended purpose include engaging in natural conversations with human users. While works in literature are ripe with descriptions of attempts at producing viable ECA architectures, few authors have addressed the role of episodic memory models in conversational agents. This form of memory, which provides a sense of autobiographic record-keeping in humans, has only recently been peripherally integrated into...
Show moreEmbodied Conversational Agents (ECA) form part of a range of virtual characters whose intended purpose include engaging in natural conversations with human users. While works in literature are ripe with descriptions of attempts at producing viable ECA architectures, few authors have addressed the role of episodic memory models in conversational agents. This form of memory, which provides a sense of autobiographic record-keeping in humans, has only recently been peripherally integrated into dialog management tools for ECAs. In our work, we propose to take a closer look at the shared characteristics of episodic memory models in recent examples from the field. Additionally, we propose several enhancements to these existing models through a unified episodic memory model for ECAÂÂ's. As part of our research into episodic memory models, we present a process for determining the prevalent contexts in the conversations obtained from the aforementioned interactions. The process presented demonstrates the use of statistical and machine learning services, as well as Natural Language Processing techniques to extract relevant snippets from conversations. Finally, mechanisms to store, retrieve, and recall episodes from previous conversations are discussed. A primary contribution of this research is in the context of contemporary memory models for conversational agents and cognitive architectures. To the best of our knowledge, this is the first attempt at providing a comparative summary of existing works. As implementations of ECAs become more complex and encompass more realistic conversation engines, we expect that episodic memory models will continue to evolve and further enhance the naturalness of conversations.
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Date Issued
2010
Identifier
CFE0003353, ucf:48443
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0003353
Data-Driven Modeling and Optimization of Building Energy Consumption
Title
Data-Driven Modeling and Optimization of Building Energy Consumption.
Creator
Grover, Divas, Pourmohammadi Fallah, Yaser, Vosoughi, Azadeh, Zhou, Qun, University of Central Florida
Abstract / Description
Sustainability and reducing energy consumption are targets for building operations. The installation of smart sensors and Building Automation Systems (BAS) makes it possible to study facility operations under different circumstances. These technologies generate large amounts of data. That data can be scrapped and used for the analysis. In this thesis, we focus on the process of data-driven modeling and decision making from scraping the data to simulate the building and optimizing the...
Show moreSustainability and reducing energy consumption are targets for building operations. The installation of smart sensors and Building Automation Systems (BAS) makes it possible to study facility operations under different circumstances. These technologies generate large amounts of data. That data can be scrapped and used for the analysis. In this thesis, we focus on the process of data-driven modeling and decision making from scraping the data to simulate the building and optimizing the operation. The City of Orlando has similar goals of sustainability and reduction of energy consumption so, they provided us access to their BAS for the data and study the operation of its facilities. The data scraped from the City's BAS serves can be used to develop statistical/machine learning methods for decision making. We selected a mid-size pilot building to apply these techniques. The process begins with the collection of data from BAS. An Application Programming Interface (API) is developed to login to the servers and scrape data for all data points and store it on the local machine. Then data is cleaned to analyze and model. The dataset contains various data points ranging from indoor and outdoor temperature to fan speed inside the Air Handling Unit (AHU) which are operated by Variable Frequency Drive (VFD). This whole dataset is a time series and is handled accordingly. The cleaned dataset is analyzed to find different patterns and investigate relations between different data points. The analysis helps us in choosing parameters for models that are developed in the next step. Different statistical models are developed to simulate building and equipment behavior. Finally, the models along with the data are used to optimize the building Operation with the equipment constraints to make decisions for building operation which leads to a reduction in energy consumption while maintaining temperature and pressure inside the building.
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Date Issued
2019
Identifier
CFE0007810, ucf:52335
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007810
Information Propagation Algorithms for Consensus Formation in Decentralized Multi-Agent Systems
Title
Information Propagation Algorithms for Consensus Formation in Decentralized Multi-Agent Systems.
Creator
Hollander, Christopher, Wu, Annie, Shumaker, Randall, Wiegand, Rudolf, Turgut, Damla, Song, Zixia, University of Central Florida
Abstract / Description
Consensus occurs within a multi-agent system when every agent is in agreement about the value of some particular state. For example, the color of an LED, the position or magnitude of a vector, a rendezvous location, the most recent state of data within a database, or the identity of a leader are all states that agents might need to agree on in order to execute their tasking.The task of the decentralized consensus problem for multi-agent systems is to design an algorithm that enables agents to...
Show moreConsensus occurs within a multi-agent system when every agent is in agreement about the value of some particular state. For example, the color of an LED, the position or magnitude of a vector, a rendezvous location, the most recent state of data within a database, or the identity of a leader are all states that agents might need to agree on in order to execute their tasking.The task of the decentralized consensus problem for multi-agent systems is to design an algorithm that enables agents to communicate and exchange information such that, in finite time, agents are able to form a consensus without the use of a centralized control mechanism. The primary goal of this research is to introduce and provide supporting evidence for Stochastic Local Observation/Gossip (SLOG) algorithms as a new class of solutions to the decentralized consensus problem for multi-agent systems that lack a centralized controller, with the additional constraints that agents act asynchronously, information is discrete, and all consensus options are equally preferable to all agents. Examples of where these constraints might apply include the spread of social norms and conventions in artificial populations, rendezvous among a set of specific locations, and task assignment.This goal is achieved through a combination of theory and experimentation. Information propagation process and an information propagation algorithm are derived by unifying the general structure of multiple existing solutions to the decentralized consensus problem. They are then used to define two classes of algorithms that spread information across a network and solve the decentralized consensus problem: buffered gossip algorithms and local observation algorithms. Buffered gossip algorithms generalize the behavior of many push-based solutions to the decentralized consensus problem. Local observation algorithms generalize the behavior of many pull-based solutions to the decentralized consensus problem. In the language of object oriented design, buffered gossip algorithms and local observation algorithms are abstract classes; information propagation processes are interfaces. SLOG algorithms combine the transmission mechanisms of buffered gossip algorithms and local observation algorithms into a single "hybrid" algorithm that is able to push and pull information within the local neighborhood. A common mathematical framework is constructed and used to determine the conditions under which each of these algorithms are guaranteed to produce a consensus, and thus solve the decentralized consensus problem. Finally, a series of simulation experiments are conducted to study the performance of SLOG algorithms. These experiments compare the average speed of consensus formation between buffered gossip algorithms, local observation algorithms, and SLOG algorithms over four distinct network topologies.Beyond the introduction of the SLOG algorithm, this research also contributes to the existing literature on the decentralized consensus problem by: specifying a theoretical framework that can be used to explore the consensus behavior of push-based and pull-based information propagation algorithms; using this framework to define buffered gossip algorithms and local observation algorithms as generalizations for existing solutions to the decentralized consensus problem; highlighting the similarities between consensus algorithms within control theory and opinion dynamics within computational sociology, and showing how these research areas can be successfully combined to create new and powerful algorithms; and providing an empirical comparison between multiple information propagation algorithms.
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Date Issued
2015
Identifier
CFE0005629, ucf:50229
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005629
Inquiry as Practice for Continuous Improvement: A Framework for the Curricular Redesign of the Education Doctorate in Curriculum and Instruction Research Continuum at the University of Central Florida.
Title
Inquiry as Practice for Continuous Improvement: A Framework for the Curricular Redesign of the Education Doctorate in Curriculum and Instruction Research Continuum at the University of Central Florida.
Creator
Clark, Paola, Boote, David, Vitale, Thomas, Hopp, Carolyn, Swan, Bonnie, University of Central Florida
Abstract / Description
This design-based research study was conducted at the University of Central Florida with the aim of informing the Education Doctorate in Curriculum and Instruction research course sequence within the College of Education and Human Performance. The main purpose of this dissertation was to enhance and enrich the Ed.D. in Curriculum and Instruction research continuum courses to ensure that they support the use of applied research and practical theory as central to the development of scholarly...
Show moreThis design-based research study was conducted at the University of Central Florida with the aim of informing the Education Doctorate in Curriculum and Instruction research course sequence within the College of Education and Human Performance. The main purpose of this dissertation was to enhance and enrich the Ed.D. in Curriculum and Instruction research continuum courses to ensure that they support the use of applied research and practical theory as central to the development of scholarly practitioners. In order to fulfill its purpose, this study addressed three main goals: clarifying the Ed.D. in Curriculum and Instruction program goals, objectives, and research continuum learning outcomes; developing research course sequence curriculum maps; and redesigning sample curriculum units for individual research courses.The curriculum mapping and redesign process was supported by research-based design choices in alignment with the practice-oriented nature of the program. These design choices included the Carnegie Project on the Education Doctorate Working Principles and Design Concepts, in particular the use of Inquiry as Practice as the main redesign framework in combination with improvement science principles. These frameworks were first used as foundations to clarify the Ed.D. in Curriculum and Instruction program goal and overall objectives. Later, user-centered design principles were applied to create faculty and student personas in order to inform the redefinition of individual research course learning outcomes. In addition, the frameworks were used to create alignment matrices and demonstrate where they supported each of the program objectives. This iterative process was carried out simultaneously with the course curriculum map redesign for each of the research continuum courses using backward design principles, the spiral curriculum model, and taking into consideration the most suitable instructional modality for learning outcomes, including the best suited education technology choices. Further, some proposed sample course units were developed in greater detail utilizing Universal Design for Learning principles and the prioritization of learning outcomes. Course contents were selected based on cognitive and reasoning learning theories pertaining to mixed method courses for professional practitioners.The developed prototypes support the continuous Ed.D. in Curriculum and Instruction curriculum redesign efforts of the program and College of Education and Human Performance at the University of Central Florida and clearly distinguish the Ed.D. in Curriculum and Instruction program from traditional, research-based doctorates. Similarly, at the national level, this study also sought to benefit other CPED-influenced professional practice programs, as they also consider the careful redesign of their research or inquiry sequences to define their programs as ones that fully address the needs of advanced professional educators. Acknowledging the limitations of this study, further studies should identifying the motivational, cognitive, and organizational causes affecting student learning outcomes. Implementing and evaluating the prototypes developed to ensure their effectiveness in preparing scholarly practitioners to act as agents of change in their professional practices.
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Date Issued
2016
Identifier
CFE0006285, ucf:51585
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006285