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- Title
- CONSTRUCTING EDUCATIONAL CRITICISM OF ONLINE COURSES: A MODEL FOR IMPLEMENTATION BY PRACTITIONERS.
- Creator
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Thompson, Kelvin, Dziuban, Charles, University of Central Florida
- Abstract / Description
-
Online courses are complex, human-driven contexts for formal learning. Little has been said about the environment emerging from the interaction of instructor(s), learners, and other resources in such courses. Theories that focus on instructional settings and methods that are designed to accommodate inquiry into complex phenomena are essential to the systematic study of online courses. Such a line of research is necessary as the basis for a common language with which we can begin to speak...
Show moreOnline courses are complex, human-driven contexts for formal learning. Little has been said about the environment emerging from the interaction of instructor(s), learners, and other resources in such courses. Theories that focus on instructional settings and methods that are designed to accommodate inquiry into complex phenomena are essential to the systematic study of online courses. Such a line of research is necessary as the basis for a common language with which we can begin to speak holistically about online courses. In this dissertation, I attempt to generate better questions about the nature of online instructional environments. By combining prior works related to educational criticism and qualitative research case study with original innovations, I develop a model for studying the instructional experiences of online courses. I then apply this approach in the study of one specific online course at the University of Central Florida (UCF).
Show less - Date Issued
- 2005
- Identifier
- CFE0000657, ucf:46553
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000657
- Title
- A PROBE INTO LEARNING APPROACHES AND ATTITUDES TOWARDS TECHNOLOGY-ENHANCED LANGUAGE LEARNING (TELL) IN CHINESE INSTRUCTION.
- Creator
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Yuan, Rong, Orwig, Gary, University of Central Florida
- Abstract / Description
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This quantitative research, carried out at the military environment at the Defense Language Institute investigated whether learning approaches could predict learners' language proficiency and learners' attitude towards technology-enhanced language learning (TELL). In addition, it also examined whether learners' demographic factors, such as age, educational backgrounds, prior experience in foreign language learning and in TELL as well as their ability to use PC and the World Wide Web could...
Show moreThis quantitative research, carried out at the military environment at the Defense Language Institute investigated whether learning approaches could predict learners' language proficiency and learners' attitude towards technology-enhanced language learning (TELL). In addition, it also examined whether learners' demographic factors, such as age, educational backgrounds, prior experience in foreign language learning and in TELL as well as their ability to use PC and the World Wide Web could predict the above mentioned language proficiency and attitude. A cluster sampling method was adopted and data was collected in four Chinese departments at the institute. Both the learning approaches inventory ASSIST and the attitudes towards TELL survey were administered to 158 Chinese language learners. 137 valid responses were obtained. All data were input into SPSS for regression and correlation analyses. Conclusions of the study are as follows: 1. The surface and apathetic approach (p<.01) was a significant predictor for both learners' measured language proficiency and their self-perception of academic performance. 2. The strategic approach was a positive predictor for learners' attitudes towards TELL; whereas, surface and apathetic approach was a negative predictor for learners' attitudes towards TELL. 3. None of the learners' demographic variables could not predict either learners' language proficiency or their attitudes towards TELL. Implications for instructional design, curriculum development, teacher education, as well as relevant research issues were discussed.
Show less - Date Issued
- 2005
- Identifier
- CFE0000829, ucf:46675
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000829
- Title
- LEARNING TECHNIQUES FOR INFORMATION RETRIEVAL AND MINING IN HIGH-DIMENSIONAL DATABASES.
- Creator
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Cheng, Hao, Hua, Kien A., University of Central Florida
- Abstract / Description
-
The main focus of my research is to design effective learning techniques for information retrieval and mining in high-dimensional databases. There are two main aspects in the retrieval and mining research: accuracy and efficiency. The accuracy problem is how to return results which can better match the ground truth, and the efficiency problem is how to evaluate users' requests and execute learning algorithms as fast as possible. However, these problems are non-trivial because of the...
Show moreThe main focus of my research is to design effective learning techniques for information retrieval and mining in high-dimensional databases. There are two main aspects in the retrieval and mining research: accuracy and efficiency. The accuracy problem is how to return results which can better match the ground truth, and the efficiency problem is how to evaluate users' requests and execute learning algorithms as fast as possible. However, these problems are non-trivial because of the complexity of the high-level semantic concepts, the heterogeneous natures of the feature space, the high dimensionality of data representations and the size of the databases. My dissertation is dedicated to addressing these issues. Specifically, my work has five main contributions as follows. The first contribution is a novel manifold learning algorithm, Local and Global Structures Preserving Projection (LGSPP), which defines salient low-dimensional representations for the high-dimensional data. A small number of projection directions are sought in order to properly preserve the local and global structures for the original data. Specifically, two groups of points are extracted for each individual point in the dataset: the first group contains the nearest neighbors of the point, and the other set are a few sampled points far away from the point. These two point sets respectively characterize the local and global structures with regard to the data point. The objective of the embedding is to minimize the distances of the points in each local neighborhood and also to disperse the points far away from their respective remote points in the original space. In this way, the relationships between the data in the original space are well preserved with little distortions. The second contribution is a new constrained clustering algorithm. Conventionally, clustering is an unsupervised learning problem, which systematically partitions a dataset into a small set of clusters such that data in each cluster appear similar to each other compared with those in other clusters. In the proposal, the partial human knowledge is exploited to find better clustering results. Two kinds of constraints are integrated into the clustering algorithm. One is the must-link constraint, indicating that the involved two points belong to the same cluster. On the other hand, the cannot-link constraint denotes that two points are not within the same cluster. Given the input constraints, data points are arranged into small groups and a graph is constructed to preserve the semantic relations between these groups. The assignment procedure makes a best effort to assign each group to a feasible cluster without violating the constraints. The theoretical analysis reveals that the probability of data points being assigned to the true clusters is much higher by the new proposal, compared to conventional methods. In general, the new scheme can produce clusters which can better match the ground truth and respect the semantic relations between points inferred from the constraints. The third contribution is a unified framework for partition-based dimension reduction techniques, which allows efficient similarity retrieval in the high-dimensional data space. Recent similarity search techniques, such as Piecewise Aggregate Approximation (PAA), Segmented Means (SMEAN) and Mean-Standard deviation (MS), prove to be very effective in reducing data dimensionality by partitioning dimensions into subsets and extracting aggregate values from each dimension subset. These partition-based techniques have many advantages including very efficient multi-phased pruning while being simple to implement. They, however, are not adaptive to different characteristics of data in diverse applications. In this study, a unified framework for these partition-based techniques is proposed and the issue of dimension partitions is examined in this framework. An investigation of the relationships of query selectivity and the dimension partition schemes discovers indicators which can predict the performance of a partitioning setting. Accordingly, a greedy algorithm is designed to effectively determine a good partitioning of data dimensions so that the performance of the reduction technique is robust with regard to different datasets. The fourth contribution is an effective similarity search technique in the database of point sets. In the conventional model, an object corresponds to a single vector. In the proposed study, an object is represented by a set of points. In general, this new representation can be used in many real-world applications and carries much more local information, but the retrieval and learning problems become very challenging. The Hausdorff distance is the common distance function to measure the similarity between two point sets, however, this metric is sensitive to outliers in the data. To address this issue, a novel similarity function is defined to better capture the proximity of two objects, in which a one-to-one mapping is established between vectors of the two objects. The optimal mapping minimizes the sum of distances between each paired points. The overall distance of the optimal matching is robust and has high retrieval accuracy. The computation of the new distance function is formulated into the classical assignment problem. The lower-bounding techniques and early-stop mechanism are also proposed to significantly accelerate the expensive similarity search process. The classification problem over the point-set data is called Multiple Instance Learning (MIL) in the machine learning community in which a vector is an instance and an object is a bag of instances. The fifth contribution is to convert the MIL problem into a standard supervised learning in the conventional vector space. Specially, feature vectors of bags are grouped into clusters. Each object is then denoted as a bag of cluster labels, and common patterns of each category are discovered, each of which is further reconstructed into a bag of features. Accordingly, a bag is effectively mapped into a feature space defined by the distances from this bag to all the derived patterns. The standard supervised learning algorithms can be applied to classify objects into pre-defined categories. The results demonstrate that the proposal has better classification accuracy compared to other state-of-the-art techniques. In the future, I will continue to explore my research in large-scale data analysis algorithms, applications and system developments. Especially, I am interested in applications to analyze the massive volume of online data.
Show less - Date Issued
- 2009
- Identifier
- CFE0002882, ucf:48022
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002882
- Title
- THE EFFECT OF APPLYING WIKIS IN AN ENGLISH AS A FOREIGN LANGUAGE (EFL) CLASS IN TAIWAN.
- Creator
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Chen, Yu-ching, Witta, Lea, University of Central Florida
- Abstract / Description
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Incorporating technology into learning has brought major benefits to learners and has greatly changed higher education. Since there is limited number of experimental research investigating the effectiveness of applying wikis, this study collected experimental data to investigate its effectiveness. The purpose of the study was to examine the effectiveness of applying wikis in terms of students' learning outcomes, to investigate the changes regarding students' attitude towards language...
Show moreIncorporating technology into learning has brought major benefits to learners and has greatly changed higher education. Since there is limited number of experimental research investigating the effectiveness of applying wikis, this study collected experimental data to investigate its effectiveness. The purpose of the study was to examine the effectiveness of applying wikis in terms of students' learning outcomes, to investigate the changes regarding students' attitude towards language learning, to explore the communication channels in wikis that facilitate students' interaction in the e-learning environment as well as students' experience of using wikis. Results showed that there existed statistically significant difference between the group with and without wikis, which means the group applying wikis performed better in listening and reading abilities. When compared with the non-wiki group, the wiki group had a more favorable attitude towards the class, their English ability improvement, and cooperative learning. Moreover, the students agreed that wikis helped them complete their assignment, they felt comfortable in the wiki environment, and it was easy for them to use wikis. From the experiences of using wikis shared by the students, they provided recommendations about the interface and the edit functions in the wiki environment. Their interaction with other team members and the course material increased but they expressed that the main interaction was through face-to-face and instant message software. Finally, the wiki environment allowed students to fulfill their role duties, cooperate, negotiate, manage their contribution, and modeling from each other.
Show less - Date Issued
- 2008
- Identifier
- CFE0002227, ucf:47919
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002227
- Title
- Investigating Instructional Designers' Decisions Regarding The Use Of Multimedia Learning Principles in E-learning Course Design.
- Creator
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Arguelles, Victor, Hartshorne, Richard, Gill, Michele, Vitale, Thomas, Swan, Bonnie, University of Central Florida
- Abstract / Description
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This study employed a qualitative research design using the Decomposed Theory of Planned Behavior (DTPB) to investigate instructional designers' use of multimedia learning principles (MLPs) in e-learning course design. While MLPs have been extensively studied in educational research and are largely associated with positive results, evidence suggests that instructional designers are not uniformly implementing these strategies when designing e-learning environments. The purpose of this study...
Show moreThis study employed a qualitative research design using the Decomposed Theory of Planned Behavior (DTPB) to investigate instructional designers' use of multimedia learning principles (MLPs) in e-learning course design. While MLPs have been extensively studied in educational research and are largely associated with positive results, evidence suggests that instructional designers are not uniformly implementing these strategies when designing e-learning environments. The purpose of this study was twofold: (a) to understand better the alignment between instructional designers' knowledge and demonstrated implementation of MLPs; and (b) to understand the factors that influence instructional designers' intent and actual implementation of MLPs in their e-learning course design. Based on two interviews conducted with seven instructional designers and an analysis of representative work samples, this study produced seven findings. Participants were recruited using homogenous purposive sampling method from two small corporate organizations whose primary business is the development of e-learning environments. Overall, these findings suggest that, despite being exposed to MLPs and holding positive behavioral beliefs regarding the usefulness of them, instructional designers may hold negative beliefs and face constraining conditions that pose significant barriers to the utilization of MLPs in e-learning course design. Other findings regarding MLP use in design are discussed and future directions for practice, policy, and research are offered.
Show less - Date Issued
- 2017
- Identifier
- CFE0006716, ucf:51898
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006716
- Title
- Decision-making for Vehicle Path Planning.
- Creator
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Xu, Jun, Turgut, Damla, Zhang, Shaojie, Zhang, Wei, Hasan, Samiul, University of Central Florida
- Abstract / Description
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This dissertation presents novel algorithms for vehicle path planning in scenarios where the environment changes. In these dynamic scenarios the path of the vehicle needs to adapt to changes in the real world. In these scenarios, higher performance paths can be achieved if we are able to predict the future state of the world, by learning the way it evolves from historical data. We are relying on recent advances in the field of deep learning and reinforcement learning to learn appropriate...
Show moreThis dissertation presents novel algorithms for vehicle path planning in scenarios where the environment changes. In these dynamic scenarios the path of the vehicle needs to adapt to changes in the real world. In these scenarios, higher performance paths can be achieved if we are able to predict the future state of the world, by learning the way it evolves from historical data. We are relying on recent advances in the field of deep learning and reinforcement learning to learn appropriate world models and path planning behaviors.There are many different practical applications that map to this model. In this dissertation we propose algorithms for two applications that are very different in domain but share important formal similarities: the scheduling of taxi services in a large city and tracking wild animals with an unmanned aerial vehicle.The first application models a centralized taxi dispatch center in a big city. It is a multivariate optimization problem for taxi time scheduling and path planning. The first goal here is to balance the taxi service demand and supply ratio in the city. The second goal is to minimize passenger waiting time and taxi idle driving distance. We design different learning models that capture taxi demand and destination distribution patterns from historical taxi data. The predictions are evaluated with real-world taxi trip records. The predicted taxi demand and destination is used to build a taxi dispatch model. The taxi assignment and re-balance is optimized by solving a Mixed Integer Programming (MIP) problem.The second application concerns animal monitoring using an unmanned aerial vehicle (UAV) to search and track wild animals in a large geographic area. We propose two different path planing approaches for the UAV. The first one is based on the UAV controller solving Markov decision process (MDP). The second algorithms relies on the past recorded animal appearances. We designed a learning model that captures animal appearance patterns and predicts the distribution of future animal appearances. We compare the proposed path planning approaches with traditional methods and evaluated them in terms of collected value of information (VoI), message delay and percentage of events collected.
Show less - Date Issued
- 2019
- Identifier
- CFE0007557, ucf:52606
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007557
- Title
- An Engineering Analytics Based Framework for Computational Advertising Systems.
- Creator
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Chen, Mengmeng, Rabelo, Luis, Lee, Gene, Keathley, Heather, Rahal, Ahmad, University of Central Florida
- Abstract / Description
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Engineering analytics is a multifaceted landscape with a diversity of analytics tools which comes from emerging fields such as big data, machine learning, and traditional operations research. Industrial engineering is capable to optimize complex process and systems using engineering analytics elements and the traditional components such as total quality management. This dissertation has proven that industrial engineering using engineering analytics can optimize the emerging area of...
Show moreEngineering analytics is a multifaceted landscape with a diversity of analytics tools which comes from emerging fields such as big data, machine learning, and traditional operations research. Industrial engineering is capable to optimize complex process and systems using engineering analytics elements and the traditional components such as total quality management. This dissertation has proven that industrial engineering using engineering analytics can optimize the emerging area of Computational Advertising. The key was to know the different fields very well and do the right selection. However, people first need to understand and be experts in the flow of the complex application of Computational Advertising and based on the characteristics of each step map the right field of Engineering analytics and traditional Industrial Engineering. Then build the apparatus and apply it to the respective problem in question.This dissertation consists of four research papers addressing the development of a framework to tame the complexity of computational advertising and improve its usage efficiency from an advertiser's viewpoint. This new framework and its respective systems architecture combine the use of support vector machines, Recurrent Neural Networks, Deep Learning Neural Networks, traditional neural networks, Game Theory/Auction Theory with Generative adversarial networks, and Web Engineering to optimize the computational advertising bidding process and achieve a higher rate of return. The system is validated with an actual case study with commercial providers such as Google AdWords and an advertiser's budget of several million dollars.
Show less - Date Issued
- 2018
- Identifier
- CFE0007319, ucf:52118
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007319
- Title
- Improving Student Learning in Undergraduate Mathematics.
- Creator
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Rejniak, Gabrielle, Young, Cynthia, Brennan, Joseph, Martin, Heath, University of Central Florida
- Abstract / Description
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The goal of this study was to investigate ways of improving student learning, par-ticularly conceptual understanding, in undergraduate mathematics courses. This studyfocused on two areas: course design and animation. The methods of study were thefollowing: Assessing the improvement of student conceptual understanding as a result of teamproject-based learning, individual inquiry-based learning and the modied empo-rium model; and Assessing the impact of animated videos on student learning with...
Show moreThe goal of this study was to investigate ways of improving student learning, par-ticularly conceptual understanding, in undergraduate mathematics courses. This studyfocused on two areas: course design and animation. The methods of study were thefollowing: Assessing the improvement of student conceptual understanding as a result of teamproject-based learning, individual inquiry-based learning and the modied empo-rium model; and Assessing the impact of animated videos on student learning with the emphasis onconcepts.For the first part of our study (impact of course design on student conceptual understanding) we began by comparing the following three groups in Fall 2010 and Fall2011:1. Fall 2010: MAC 1140 Traditional Lecture (&) Fall 2011: MAC 1140 Modied Empo-rium2. Fall 2010: MAC 1140H with Project (&) Fall 2011: MAC 1140H no Project3. Fall 2010: MAC 2147 with Projects (&) Fall 2011: MAC 2147 no ProjectsAnalysis of pre-tests and post-tests show that all three courses showed statistically significant increases, according to their respective sample sizes, during Fall 2010. However, in Fall 2011 only MAC 2147 continued to show a statistically significant increase. Therefore in Fall 2010, project-based learning - both in-class individual projects and out-of-class team projects - conclusively impacted the students' conceptual understanding. Whereas, in Fall 2011, the data for the Modified Emporium model had no statistical significance and is therefore inconclusive as to its effectiveness. In addition the difference in percent ofincrease for MAC 1140 between Fall 2010 - traditional lecture model - and Fall 2011 -modified emporium model - is not statistically significant and we cannot say that either model is a better delivery mode for conceptual learning. For the second part of our study, the students enrolled in MAC 1140H Fall 2011 and MAC 2147 Fall 2011 were given a pre-test on sequences and series before showing them an animated video related to the topic. After watching the video, students were then given the same 7 question post test to determine any improvement in the students' understanding of the topic. After two weeks of teacher-led instruction, the students tookthe same post-test again. The results of this preliminary study indicate that animated videos do impact the conceptual understanding of students when used as an introduction into a new concept. Both courses that were shown the video had statistically significant increases in the conceptual understanding of the students between the pre-test and the post-animation test.
Show less - Date Issued
- 2012
- Identifier
- CFE0004320, ucf:49481
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004320
- Title
- Human Action Localization and Recognition in Unconstrained Videos.
- Creator
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Boyraz, Hakan, Tappen, Marshall, Foroosh, Hassan, Lin, Mingjie, Zhang, Shaojie, Sukthankar, Rahul, University of Central Florida
- Abstract / Description
-
As imaging systems become ubiquitous, the ability to recognize human actions is becoming increasingly important. Just as in the object detection and recognition literature, action recognition can be roughly divided into classification tasks, where the goal is to classify a video according to the action depicted in the video, and detection tasks, where the goal is to detect and localize a human performing a particular action. A growing literature is demonstrating the benefits of localizing...
Show moreAs imaging systems become ubiquitous, the ability to recognize human actions is becoming increasingly important. Just as in the object detection and recognition literature, action recognition can be roughly divided into classification tasks, where the goal is to classify a video according to the action depicted in the video, and detection tasks, where the goal is to detect and localize a human performing a particular action. A growing literature is demonstrating the benefits of localizing discriminative sub-regions of images and videos when performing recognition tasks. In this thesis, we address the action detection and recognition problems. Action detection in video is a particularly difficult problem because actions must not only be recognized correctly, but must also be localized in the 3D spatio-temporal volume. We introduce a technique that transforms the 3D localization problem into a series of 2D detection tasks. This is accomplished by dividing the video into overlapping segments, then representing each segment with a 2D video projection. The advantage of the 2D projection is that it makes it convenient to apply the best techniques from object detection to the action detection problem. We also introduce a novel, straightforward method for searching the 2D projections to localize actions, termed Two-Point Subwindow Search (TPSS). Finally, we show how to connect the local detections in time using a chaining algorithm to identify the entire extent of the action. Our experiments show that video projection outperforms the latest results on action detection in a direct comparison.Second, we present a probabilistic model learning to identify discriminative regions in videos from weakly-supervised data where each video clip is only assigned a label describing what action is present in the frame or clip. While our first system requires every action to be manually outlined in every frame of the video, this second system only requires that the video be given a single high-level tag. From this data, the system is able to identify discriminative regions that correspond well to the regions containing the actual actions. Our experiments on both the MSR Action Dataset II and UCF Sports Dataset show that the localizations produced by this weakly supervised system are comparable in quality to localizations produced by systems that require each frame to be manually annotated. This system is able to detect actions in both 1) non-temporally segmented action videos and 2) recognition tasks where a single label is assigned to the clip. We also demonstrate the action recognition performance of our method on two complex datasets, i.e. HMDB and UCF101. Third, we extend our weakly-supervised framework by replacing the recognition stage with a two-stage neural network and apply dropout for preventing overfitting of the parameters on the training data. Dropout technique has been recently introduced to prevent overfitting of the parameters in deep neural networks and it has been applied successfully to object recognition problem. To our knowledge, this is the first system using dropout for action recognition problem. We demonstrate that using dropout improves the action recognition accuracies on HMDB and UCF101 datasets.
Show less - Date Issued
- 2013
- Identifier
- CFE0004977, ucf:49562
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004977
- Title
- CONTRIBUTIONS BY INDIVIDUAL AND GROUP STRATEGIES FOR ORGANIZATIONAL LEARNING IN ARCHITECTURAL, ENGINEERING, AND CONSTRUCTION FIRMS.
- Creator
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Beaver, Robert, Kotnour, Timothy, University of Central Florida
- Abstract / Description
-
Organizations with multiple operating requirements require support functions to assist in execution of strategic goals. This effort, in turn, requires management of engineering activities in control of projects and in sustaining facilities. High level strategies include employing engineering support that consists of a project management function encompassing technical and managerial disciplines. The architecture/engineering, and construction office (AEC) is the subject of this research....
Show moreOrganizations with multiple operating requirements require support functions to assist in execution of strategic goals. This effort, in turn, requires management of engineering activities in control of projects and in sustaining facilities. High level strategies include employing engineering support that consists of a project management function encompassing technical and managerial disciplines. The architecture/engineering, and construction office (AEC) is the subject of this research. Engineering and construction oriented organizations have experienced challenges to their abilities to learn and grow. This has potential detrimental implications for these organizations if support functions cannot keep pace with changing objectives and strategy. The competitive nature and low industry margins as well as uniqueness of projects as challenges facing engineering and construction. The differentiated nature of projects tasks also creates a need for temporary and dedicated modes of operation and thereby tends to promote highly dispersed management practices that do not dovetail very well with other organizational processes. Organizational learning is a means to enhance and support knowledge management for improving performance. The problem addressed through this research is the gap between desired and achieved individual and group learning by members of the AEC, and the members' abilities to distinguish between the need for adaptive learning or innovation. This research addresses learning by individuals and groups, and the strategies employed through an empirical study (survey). A conceptual model for organizational learning contributions by individuals and groups is presented and tested for confirmation of exploitive or explorative learning strategies for individuals, and directions composed of depth and breadth of learning. Strategies for groups are tested for internal or external search orientations and directions toward the single or multi-discipline unit. The survey is analyzed by method of principal components extraction and further interpreted to reveal factors that are correlated by Pearson product moment coefficients and tested for significance for potential relationships to factors for outcomes. Correlation across dependent variables prevented interpretation of the most significant factors for group learning strategies. However, results provide possible support for direction in supporting processes that promote networking among individuals and group structures that recognize the dual nature of knowledge - that required for technical competency and that required for success in the organization. Recommendations for practitioners include adjustments to knowledge acquisition direction, promoting external collaboration among firms, and provision of dual succession pathways through technical expertise or organizational processes for senior staff.
Show less - Date Issued
- 2009
- Identifier
- CFE0002682, ucf:48194
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002682
- Title
- BIOSIGNAL PROCESSING CHALLENGES IN EMOTION RECOGNITIONFOR ADAPTIVE LEARNING.
- Creator
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Vartak, Aniket, Mikhael, Wasfy, University of Central Florida
- Abstract / Description
-
User-centered computer based learning is an emerging field of interdisciplinary research. Research in diverse areas such as psychology, computer science, neuroscience and signal processing is making contributions the promise to take this field to the next level. Learning systems built using contributions from these fields could be used in actual training and education instead of just laboratory proof-of-concept. One of the important advances in this research is the detection and assessment of...
Show moreUser-centered computer based learning is an emerging field of interdisciplinary research. Research in diverse areas such as psychology, computer science, neuroscience and signal processing is making contributions the promise to take this field to the next level. Learning systems built using contributions from these fields could be used in actual training and education instead of just laboratory proof-of-concept. One of the important advances in this research is the detection and assessment of the cognitive and emotional state of the learner using such systems. This capability moves development beyond the use of traditional user performance metrics to include system intelligence measures that are based on current neuroscience theories. These advances are of paramount importance in the success and wide spread use of learning systems that are automated and intelligent. Emotion is considered an important aspect of how learning occurs, and yet estimating it and making adaptive adjustments are not part of most learning systems. In this research we focus on one specific aspect of constructing an adaptive and intelligent learning system, that is, estimation of the emotion of the learner as he/she is using the automated training system. The challenge starts with the definition of the emotion and the utility of it in human life. The next challenge is to measure the co-varying factors of the emotions in a non-invasive way, and find consistent features from these measures that are valid across wide population. In this research we use four physiological sensors that are non-invasive, and establish a methodology of utilizing the data from these sensors using different signal processing tools. A validated set of visual stimuli used worldwide in the research of emotion and attention, called International Affective Picture System (IAPS), is used. A dataset is collected from the sensors in an experiment designed to elicit emotions from these validated visual stimuli. We describe a novel wavelet method to calculate hemispheric asymmetry metric using electroencephalography data. This method is tested against typically used power spectral density method. We show overall improvement in accuracy in classifying specific emotions using the novel method. We also show distinctions between different discrete emotions from the autonomic nervous system activity using electrocardiography, electrodermal activity and pupil diameter changes. Findings from different features from these sensors are used to give guidelines to use each of the individual sensors in the adaptive learning environment.
Show less - Date Issued
- 2010
- Identifier
- CFE0003301, ucf:48503
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003301
- Title
- AN INVESTIGATION OF THE EFFECTS OF USING DIGITAL FLASH CARDS TO INCREASE BIOLOGY VOCABULARY KNOWLEDGE IN HIGH SCHOOL STUDENTS WITH LEARNING DISABILITIES.
- Creator
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Grillo, Kelly, Dieker, Lisa, University of Central Florida
- Abstract / Description
-
The field of science education, specifically biology, is becoming more challenging due to richer and more rigorous content demands. Along with new demands is the emergence of National Common Core Standards and End of Course Exams. Despite these changes, one factor remains consistent: As content knowledge increases, language demands also increase. For students with learning disabilities (LD), specifically those with language-based disabilities, the increasing vocabulary demand can lead to...
Show moreThe field of science education, specifically biology, is becoming more challenging due to richer and more rigorous content demands. Along with new demands is the emergence of National Common Core Standards and End of Course Exams. Despite these changes, one factor remains consistent: As content knowledge increases, language demands also increase. For students with learning disabilities (LD), specifically those with language-based disabilities, the increasing vocabulary demand can lead to failure due not to a lack of understanding biology but the vocabulary associated with the content. In an attempt to impact high school students with learning disabilities'success in biology, a vocabulary intervention was investigated. Research suggests as more and more content is compressed into science courses, teachers are looking toward technology to assist with vocabulary mastery. The current research study examined the effects of a digital flash card intervention, Study Stack, versus a paper flash card intervention in biology for students with LD by measuring students'word knowledge and overall biology course achievement. Findings from repeated measures ANOVA showed a statistically significant increase on both the vocabulary assessment as well as the course grades in biology over time. However, the test of between effects considering card type yielded no differential change on vocabulary assessment and course grades in biology. Based on qualitative data, students interviewed liked the tool and found it to be helpful in learning biology terminology.
Show less - Date Issued
- 2011
- Identifier
- CFE0003972, ucf:48662
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003972
- Title
- Is there a difference in learning styles of honors versus non-honors students as assessed by the GEFT?.
- Creator
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Hollister, Debra Lee, Kubala, Thomas, Education
- Abstract / Description
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University of Central Florida College of Education Thesis; The goal of this research was to find if there was a discernible difference in the preferred learning style of an honors student versus a non-honors student based on the Group Embedded Figures Test. Although many instructors use the lecture method to teach, it many not be the most productive tool for students to learn. The information from this study could be of help when an instructor is preparing to instruct a group of students in...
Show moreUniversity of Central Florida College of Education Thesis; The goal of this research was to find if there was a discernible difference in the preferred learning style of an honors student versus a non-honors student based on the Group Embedded Figures Test. Although many instructors use the lecture method to teach, it many not be the most productive tool for students to learn. The information from this study could be of help when an instructor is preparing to instruct a group of students in an honors, AP (advanced placement) or gifted class as to determine what activities would provide the best retention of material. The results of this study were analyzed to examine the variables of being an honors or non-honors student, gender, age, ethnicity, degree being pursued and being a full time or part time student. According to the Chi2 analysis, it was found that there is no one learning style that is preferred by students who take honors classes versus other students. It was also discovered that gender, age, ethnicity, degree being pursued and being either a full time or part time student did not impact preferred learning style for the students on the East Campus of Valencia Community College. Suggested use for this study would be to inform instructors and faculty that there is no one learning style preferred by the honors student. This information can not be reiterated enough to ensure that students are given many different types of opportunities to successfully accomplish their academic goals.
Show less - Date Issued
- 2001
- Identifier
- CFR0011946, ucf:53105
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFR0011946
- Title
- A Correlational Study of Emerging Modalities of Developmental Education and Learning Styles in a Florida State College.
- Creator
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Britt, John, Cox, Dr. Thomas, King, Kathy (Kathleen), Vitale, Thomas, Penfold Navarro, Catherine, University of Central Florida
- Abstract / Description
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Developmental education course modalities in Florida were drastically changed in 2013 with the passage of Senate Bill 1720. These courses can no longer be offered in a traditional 16-week format as other postsecondary courses are offered. Developmental education courses must now be offered in a compressed, contextualized, or corequisite instruction modality; or direct enrollment into a gateway course (1720-Education, 2013). This changes the student's experience in the courses. This research...
Show moreDevelopmental education course modalities in Florida were drastically changed in 2013 with the passage of Senate Bill 1720. These courses can no longer be offered in a traditional 16-week format as other postsecondary courses are offered. Developmental education courses must now be offered in a compressed, contextualized, or corequisite instruction modality; or direct enrollment into a gateway course (1720-Education, 2013). This changes the student's experience in the courses. This research was framed by Kolb's experiential learning theory, which states that people learn through their experiences (Kolb, 1984). Chi-Square correlational tests were conducted to examine the relationship between students' learning types and their final grades in an accelerated developmental math course and in a combined developmental math course. The results indicate no statistically significant relationships between the variables in both modalities of developmental math. Furthermore, students were surveyed on their preferences of the developmental math modalities. The results showed positive preferences toward both modalities of developmental math. With the limited amount of research in the area of developmental math modalities, this research helps to further understand the area and provides a basis for future research.
Show less - Date Issued
- 2016
- Identifier
- CFE0006445, ucf:51473
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006445
- Title
- Improved Multi-Task Learning Based on Local Rademacher Analysis.
- Creator
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Yousefi, Niloofar, Mollaghasemi, Mansooreh, Rabelo, Luis, Zheng, Qipeng, Anagnostopoulos, Georgios, Xanthopoulos, Petros, Georgiopoulos, Michael, University of Central Florida
- Abstract / Description
-
Considering a single prediction task at a time is the most commonly paradigm in machine learning practice. This methodology, however, ignores the potentially relevant information that might be available in other related tasks in the same domain. This becomes even more critical where facing the lack of a sufficient amount of data in a prediction task of an individual subject may lead to deteriorated generalization performance. In such cases, learning multiple related tasks together might offer...
Show moreConsidering a single prediction task at a time is the most commonly paradigm in machine learning practice. This methodology, however, ignores the potentially relevant information that might be available in other related tasks in the same domain. This becomes even more critical where facing the lack of a sufficient amount of data in a prediction task of an individual subject may lead to deteriorated generalization performance. In such cases, learning multiple related tasks together might offer a better performance by allowing tasks to leverage information from each other. Multi-Task Learning (MTL) is a machine learning framework, which learns multiple related tasks simultaneously to overcome data scarcity limitations of Single Task Learning (STL), and therefore, it results in an improved performance. Although MTL has been actively investigated by the machine learning community, there are only a few studies examining the theoretical justification of this learning framework. The focus of previous studies is on providing learning guarantees in the form of generalization error bounds. The study of generalization bounds is considered as an important problem in machine learning, and, more specifically, in statistical learning theory. This importance is twofold: (1) generalization bounds provide an upper-tail confidence interval for the true risk of a learning algorithm the latter of which cannot be precisely calculated due to its dependency to some unknown distribution P from which the data are drawn, (2) this type of bounds can also be employed as model selection tools, which lead to identifying more accurate learning models. The generalization error bounds are typically expressed in terms of the empirical risk of the learning hypothesis along with a complexity measure of that hypothesis. Although different complexity measures can be used in deriving error bounds, Rademacher complexity has received considerable attention in recent years, due to its superiority to other complexity measures. In fact, Rademacher complexity can potentially lead to tighter error bounds compared to the ones obtained by other complexity measures. However, one shortcoming of the general notion of Rademacher complexity is that it provides a global complexity estimate of the learning hypothesis space, which does not take into consideration the fact that learning algorithms, by design, select functions belonging to a more favorable subset of this space and, therefore, they yield better performing models than the worst case. To overcome the limitation of global Rademacher complexity, a more nuanced notion of Rademacher complexity, the so-called local Rademacher complexity, has been considered, which leads to sharper learning bounds, and as such, compared to its global counterpart, guarantees faster convergence rates in terms of number of samples. Also, considering the fact that locally-derived bounds are expected to be tighter than globally-derived ones, they can motivate better (more accurate) model selection algorithms.While the previous MTL studies provide generalization bounds based on some other complexity measures, in this dissertation, we prove excess risk bounds for some popular kernel-based MTL hypothesis spaces based on the Local Rademacher Complexity (LRC) of those hypotheses. We show that these local bounds have faster convergence rates compared to the previous Global Rademacher Complexity (GRC)-based bounds. We then use our LRC-based MTL bounds to design a new kernel-based MTL model, which enjoys strong learning guarantees. Moreover, we develop an optimization algorithm to solve our new MTL formulation. Finally, we run simulations on experimental data that compare our MTL model to some classical Multi-Task Multiple Kernel Learning (MT-MKL) models designed based on the GRCs. Since the local Rademacher complexities are expected to be tighter than the global ones, our new model is also expected to exhibit better performance compared to the GRC-based models.
Show less - Date Issued
- 2017
- Identifier
- CFE0006827, ucf:51778
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006827
- Title
- A Multiple Case Study Examining How Third-Grade Students Who Struggle in Mathematics Make Sense of Fraction Concepts.
- Creator
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Gault, Rebecca, Ortiz, Enrique, Dixon, Juli, Nickels, Megan, Little, Mary, University of Central Florida
- Abstract / Description
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A qualitative multiple case study was conducted to reveal the sense-making processes third-grade students who struggle in mathematics used to build an understanding of fraction concepts. Purposive sampling identified three participants who were struggling in a local school's third grade mathematics classes. This research describes how these participants made sense of fraction concepts through their strengths and struggles while engaged in 15 small-group intervention sessions. Vygotsky's (1934...
Show moreA qualitative multiple case study was conducted to reveal the sense-making processes third-grade students who struggle in mathematics used to build an understanding of fraction concepts. Purposive sampling identified three participants who were struggling in a local school's third grade mathematics classes. This research describes how these participants made sense of fraction concepts through their strengths and struggles while engaged in 15 small-group intervention sessions. Vygotsky's (1934/1986/2012) theory that children's optimal learning is supported by teacher-student interactions was used as an interpretive framework. Tasks were developed over the course of the intervention sessions with consideration of a model developed by Lesh, Post, and Behr (1987) for connecting mathematical representations and the Common Core State Standards for Mathematics (National Governors Association Center for Best Practices (&) Council of Chief State School Officers, 2010). Data, including transcripts, tapes, and artifacts, were analyzed using two frameworks. These were Geary's (2003) classification of three subtypes of learning disabilities in mathematics and Anghileri's (2006) descriptions of social-constructivist scaffolding techniques. The first analysis resulted in a description of each participant's strengths and struggles, including alignment with Geary's subtypes, and how these strengths and struggles interacted with participant's construction of knowledge about fractions. The second analysis described episodes of learning that were supported by social-constructivist scaffolding techniques and revealed how participants made sense of fractions through their interactions with each other, the researcher, and intervention tasks. The researcher found that each participant's learning process, including struggles, was unique, with each interacting in different ways with tasks, manipulatives, pictorial representations, and questioning. For each participant, however, scaffolding techniques oriented around prompting and probing questions, participant verbalizations, and interactions with connected fraction representations were critical in their learning process.
Show less - Date Issued
- 2016
- Identifier
- CFE0006307, ucf:51587
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006307
- Title
- Examining the Effect of the Universal Design for Learning Expression Principle on Students with learning Disabilities in Science.
- Creator
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Finnegan, Lisa, Dieker, Lisa, Wienke, Wilfred, Hines, Rebecca, Everett, Robert, University of Central Florida
- Abstract / Description
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ABSTRACT The significance of students being able to express and demonstrate their knowledge and understanding in all content areas has always been important especially in the sciences. Students under the Next Generation Science Standards will be required to participate in science discourse through a variety of approaches. This study examined student engagement and student demonstration of content knowledge in inclusive science classrooms through a quasi-experimental research design which...
Show moreABSTRACT The significance of students being able to express and demonstrate their knowledge and understanding in all content areas has always been important especially in the sciences. Students under the Next Generation Science Standards will be required to participate in science discourse through a variety of approaches. This study examined student engagement and student demonstration of content knowledge in inclusive science classrooms through a quasi-experimental research design which included four case study participants with a learning disability. The researcher also evaluated student content knowledge through the implementation of Universal Design for Learning-Expression (UDL-E) through a non-replicated control group design. Data were collected through a variety of sources including: researcher observations, review of student academic records, interviews, surveys, UDL-E products, and pre-test and posttest scores. Researcher observations spanned over a 10 week period and were coded and analyzed quantitatively. Findings from a Repeated ANOVA demonstrated no statistical significance, however based on interviews with students; findings show that the students did enjoy exploring the opportunity to express their knowledge using the Expression principle of Universal Design for Learning. Student time-on-task did remain equally as high during UDL-E and students' inattentive behaviors decreased.
Show less - Date Issued
- 2013
- Identifier
- CFE0004840, ucf:49709
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004840
- Title
- The Effect of Input Modality on Pronunciation Accuracy of English Language Learners.
- Creator
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Farina, Marcella, Nutta, Joyce, Ehren, Barbara, Mihai, Florin, Xu, Lihua, Ryalls, John, University of Central Florida
- Abstract / Description
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The issues relative to foreign accent continue to puzzle second language researchers, educators, and learners today. Although once thought to be at the root, maturational constraints have fallen short of definitively accounting for the myriad levels and rates of phonological attainment (Bialystok (&) Miller, 1999, p. 128). This study, a Posttest-only Control Group Design, examined how the pronunciation accuracy of adult, English language learners, as demonstrated by utterance length, was...
Show moreThe issues relative to foreign accent continue to puzzle second language researchers, educators, and learners today. Although once thought to be at the root, maturational constraints have fallen short of definitively accounting for the myriad levels and rates of phonological attainment (Bialystok (&) Miller, 1999, p. 128). This study, a Posttest-only Control Group Design, examined how the pronunciation accuracy of adult, English language learners, as demonstrated by utterance length, was related to two input stimuli: auditory-only input and auditory-orthographic input. Utterance length and input modality were further examined with the added variables of native language, specifically Arabic and Spanish, and second language proficiency as defined by unofficial TOEFL Listening Comprehension and Reading Comprehension section scores.Results from independent t tests indicated a statistically significant difference in utterance length based on input modality (t(192) = -3.285. p = .001), while with the added variable of native language, factorial ANOVA results indicated no statistically significance difference for the population studied. In addition, multiple linear regression analyses examined input modality and second language proficiency as predictors of utterance length accuracy and revealed a statistically significant relationship (R2 = .108, adjusted R2 = .089, F(3, 144) = 5.805, p = .001), with 11% of the utterance length variance accounted for by these two factors predictors. Lastly, hierarchical regressions applied to two blocks of factors revealed statistical significance: (a) input modality/native language (R2 = .069, adjusted R2 = .048, F(2, 87) = 3.230, p = .044) and ListenComp (R2 = .101, adjusted R2 = .070, F(3, 86) = 3.232, p = .026), with ListenComp increasing the predictive power by 3%; (b) input modality/native language (R2 = .069, adjusted R2 = .048, F(2, 87) = 3.230, p = .044) and ReadComp (R2 = .112, adjusted R2 = .081, F(1, 86) = 3.629, p = .016), with ReadComp increasing the predictive power by 4%; and (c) input modality/native language (R2 = .069, adjusted R2 = .048, F(2, 87) = 3.230, p = .044) and ListenComp/ReadComp (R2 = .114, adjusted R2 = .072, F(2, 85) = 2.129, p = .035), with ListenComp/ReadComp increasing the predictive power by 4%.The implications of this research are that by considering issues relative to input modality and second language proficiency levels especially when teaching new vocabulary to adult second language learners, the potential for improved pronunciation accuracy is maximized. Furthermore, the heightened attention to the role of input modality as a cognitive factor on phonological output in second language teaching and learning may redirect the manner in which target language phonology is approached.
Show less - Date Issued
- 2013
- Identifier
- CFE0004838, ucf:49687
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004838
- Title
- A Multimedia Approach to Game-Based Training: Exploring the Effects of the Modality and Temporal Contiguity Principles on Learning in a Virtual Environment.
- Creator
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Serge, Stephen, Mouloua, Mustapha, Bohil, Corey, Bowers, Clint, Priest Walker, Heather, University of Central Florida
- Abstract / Description
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There is an increasing interest in using video games as a means to deliver training to individuals learning new skills or tasks. However, current research lacks a clear method of developing effective instructional material when these games are used as training tools and explaining how gameplay may affect learning. The literature contains multiple approaches to training and GBT but generally lacks a foundational-level and theoretically relevant approach to how people learn specifically from...
Show moreThere is an increasing interest in using video games as a means to deliver training to individuals learning new skills or tasks. However, current research lacks a clear method of developing effective instructional material when these games are used as training tools and explaining how gameplay may affect learning. The literature contains multiple approaches to training and GBT but generally lacks a foundational-level and theoretically relevant approach to how people learn specifically from video games and how to design instructional guidance within these gaming environments. This study investigated instructional delivery within GBT. Video games are a form of multimedia, consisting of both imagery and sounds. The Cognitive Theory of Multimedia Learning (CTML; Mayer 2005) explicitly describes how people learn from multimedia information, consisting of a combination of narration (words) and animation (pictures). This study empirically examined the effects of the modality and temporal contiguity principles on learning in a game-based virtual environment. Based on these principles, it was hypothesized that receiving either voice or embedded training would result in better performance on learning measures. Additionally, receiving a combination of voice and embedded training would lead to better performance on learning measures than all other instructional conditions.A total of 128 participants received training on the role and procedures related to the combat lifesaver (-) a non-medical soldier who receives additional training on combat-relevant lifesaving medical procedures. Training sessions involved an instructional presentation manipulated along the modality (voice or text) and temporal contiguity (embedded in the game or presented before gameplay) principles. Instructional delivery was manipulated in a 2x2 between-subjects design with four instructional conditions: Upfront-Voice, Upfront-Text, Embedded-Voice, and Embedded-Text. Results indicated that: (1) upfront instruction led to significantly better retention performance than embedded instructional regardless of delivery modality; (2) receiving voice-based instruction led to better transfer performance than text-based instruction regardless of presentation timing; (3) no differences in performance were observed on the simple application test between any instructional conditions; and (4) a significant interaction of modality-by-temporal contiguity was obtained. Simple effects analysis indicated differing effects along modality within the embedded instruction group, with voice recipients performing better than text (p = .012). Individual group comparisons revealed that the upfront-voice group performed better on retention than both embedded groups (p = .006), the embedded-voice group performed better on transfer than the upfront text group (p = .002), and the embedded-voice group performed better on the complex application test than the embedded-text group (p =.012). Findings indicated partial support for the application of the modality and temporal contiguity principles of CTML in interactive GBT. Combining gameplay (i.e., practice) with instructional presentation both helps and hinders working memory's ability to process information. Findings also explain how expanding CTML into game-based training may fundamentally change how a person processes information as a function of the specific type of knowledge being taught. Results will drive future systematic research to test and determine the most effective means of designing instruction for interactive GBT. Further theoretical and practical implications will be discussed.
Show less - Date Issued
- 2014
- Identifier
- CFE0005548, ucf:50271
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005548
- Title
- EVALUATING COMPETITION BETWEEN VERBAL AND IMPLICIT SYSTEMS WITH FUNCTIONAL NEAR-INFRARED SPECTROSCOPY.
- Creator
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Schiebel, Troy A, Bohil, Corey, University of Central Florida
- Abstract / Description
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In category learning, explicit processes function through the prefrontal cortex (PFC) and implicit processes function through the basal ganglia. Research suggested that these two systems compete with each other. The goal of this study was to shed light on this theory. 15 undergraduate subjects took part in an event-related experiment that required them to categorize computer-generated line-stimuli, which varied in length and/or angle depending on condition. Subjects participated in an...
Show moreIn category learning, explicit processes function through the prefrontal cortex (PFC) and implicit processes function through the basal ganglia. Research suggested that these two systems compete with each other. The goal of this study was to shed light on this theory. 15 undergraduate subjects took part in an event-related experiment that required them to categorize computer-generated line-stimuli, which varied in length and/or angle depending on condition. Subjects participated in an explicit "rule-based" (RB) condition and an implicit "information-integration" (II) condition while connected to a functional near-infrared spectroscopy (fNIRS) apparatus, which measured the hemodynamic response (HR) in their PFC. Each condition contained 2 blocks. We hypothesized that the competition between explicit and implicit systems (COVIS) would be demonstrated if, by block 2, task-accuracy was approximately equal across conditions with PFC activity being comparatively higher in the II condition. This would indicate that subjects could learn the categorization task in both conditions but were only able to decipher an explicit rule in the RB condition; their PFC would struggle to do so in the II condition, resulting in perpetually high activation. In accordance with predictions, results revealed no difference in accuracy across conditions with significant difference in channel activation. There were channel trends (p<.1) which showed PFC activation decrease in the RB condition and increase in the II condition by block 2. While these results support our predictions, they are largely nonsignificant, which could be attributed to the event-related design. Future research should utilize a larger samples size for improved statistical power.
Show less - Date Issued
- 2016
- Identifier
- CFH2000086, ucf:45502
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH2000086
