Matching Items (11)
Description
Multimodal presentations have been found to facilitate learning, however, may be a disadvantage for low spatial ability students if they require spatial visualization. This disadvantage stems from their limited capacity to spatially visualize and retain information from both text and diagrams for integration. Similarly, working memory capacity (WMC) likely plays a key role in a learner's ability to retain information presented to them via both modalities. The present study investigated whether or not the act of self-explaining helps resolve deficits in learning caused by individual differences in spatial ability, working memory capacity, and prior knowledge when learning with text, or text and diagrams. No interactions were found, but prior knowledge consistently predicted performance on like posttests. The author presents methodological and theoretical explanations as to the null results of the present study.
ContributorsGutierrez, Pedro J (Author) / Craig, Scotty D. (Thesis advisor) / Branaghan, Russell (Committee member) / Sanchez, Cristopher (Committee member) / Arizona State University (Publisher)
Created2014
Description
Parkinson's disease (PD) is a neurodegenerative disorder that produces a characteristic set of neuromotor deficits that sometimes includes reduced amplitude and velocity of movement. Several studies have shown that people with PD improved their motor performance when presented with external cues. Other work has demonstrated that high velocity and large amplitude exercises can increase the amplitude and velocity of movement in simple carryover tasks in the upper and lower extremities. Although the cause for these effects is not known, improvements due to cueing suggest that part of the neuromotor deficit in PD is in the integration of sensory feedback to produce motor commands. Previous studies have documented some somatosensory deficits, but only limited information is available regarding the nature and magnitude of sensorimotor deficits in the shoulder of people with PD. The goals of this research were to characterize the sensorimotor impairment in the shoulder joint of people with PD and to investigate the use of visual feedback and large amplitude/high velocity exercises to target PD-related motor deficits. Two systems were designed and developed to use visual feedback to assess the ability of participants to accurately adjust limb placement or limb movement velocity and to encourage improvements in performance of these tasks. Each system was tested on participants with PD, age-matched control subjects and young control subjects to characterize and compare limb placement and velocity control capabilities. Results demonstrated that participants with PD were less accurate at placing their limbs than age-matched or young control subjects, but that their performance improved over the course of the test session such that by the end, the participants with PD performed as well as controls. For the limb velocity feedback task, participants with PD and age-matched control subjects were less accurate than young control subjects, but at the end of the session, participants with PD and age-matched control subjects were as accurate as the young control subjects. This study demonstrates that people with PD were able to improve their movement patterns based on visual feedback of performance and suggests that this feedback paradigm may be useful in exercise programs for people with PD.
ContributorsSmith, Catherine (Author) / Abbas, James J (Thesis advisor) / Ingalls, Todd (Thesis advisor) / Krishnamurthi, Narayanan (Committee member) / Buneo, Christopher (Committee member) / Rikakis, Thanassis (Committee member) / Arizona State University (Publisher)
Created2015
Description
Interactive remote e-learning is one of the youngest and most popular methods that is used in today's teaching method. WebRTC, on the other hand, has become the popular concept and method in real time communication. Unlike the old fashioned Adobe Flash, user will communicate directly to each other rather than calling server as the middle man. The world is changing from plug-in to web-browser. However, the WebRTC have not been widely used for school education.
By taking into consideration of the WebRTC solution for data transferring, we propose a new Cloud based interactive multimedia which enables virtual lab learning environment. Three modules were proposed along with an efficient solution for achieving optimized network bandwidth. The One-to-Many communication was introduced in the video conferencing and scalability was tested for the application. The key technical contribution is to establish a sufficient system that designed to utilize the WebRTC in its best way in educational world in the Vlab platform and reduces the tool cost and improves online learning experience.
By taking into consideration of the WebRTC solution for data transferring, we propose a new Cloud based interactive multimedia which enables virtual lab learning environment. Three modules were proposed along with an efficient solution for achieving optimized network bandwidth. The One-to-Many communication was introduced in the video conferencing and scalability was tested for the application. The key technical contribution is to establish a sufficient system that designed to utilize the WebRTC in its best way in educational world in the Vlab platform and reduces the tool cost and improves online learning experience.
ContributorsLi, Qingyun (Author) / Huang, Dijiang (Thesis advisor) / Davulcu, Hasan (Committee member) / Dasgupta, Partha (Committee member) / Arizona State University (Publisher)
Created2014
Description
The current study investigated the task of coloring static images with multimedia learning to determine the impact on retention and transfer scores. After watching a multimedia video on the formation of lightning participants were assigned to either a passive, active, or constructive condition based on the ICAP Framework. Participants colored static images on key concepts from the video, passive condition observed the images, active condition colored the images by applying the concepts, and the constructive condition colored the images by generating new ideas and concepts. The study did not support the hypothesis that the constructive condition would have increased retention and transfer scores over the active and passive conditions. The mental effort measures did not show significance among groups in relation to learning but perception measures did show an increase in participants enjoyment and engagement. Since the coloring craze has become more accepted for adults then could coloring be a way to increase participants learning through engagement.
ContributorsWilliams, Jennifer S (Author) / Craig, Scotty D. (Thesis advisor) / Roscoe, Rod (Committee member) / Branaghan, Russell (Committee member) / Arizona State University (Publisher)
Created2018
Description
ELearning, distance learning, has been a fast-developing topic in educational area. In 1999, Mayer put forward “Cognitive Theory of Multimedia learning” (Moreno, & Mayer, 1999). The theory consisted of several principles. One of the principles, Modality Principle describes that when learners are presented with spoken words, their performance are better than that with on-screen texts (Mayer, R., Dow, & Mayer, S. 2003; Moreno, & Mayer, 1999).It gave an implication that learners performance can be affected by modality of learning materials. A very common tool in education in literature and language is narrative. This way of storytelling has received success in practical use. The advantages of using narrative includes (a) inherent format advantage such as simple structure and familiar language and ideas, (b) motivating learners, (c) facilitate listening, (d) oral ability and (e)provide schema for comparison in comprehension.
Although this storytelling method has been widely used in literature, language and even moral education, few studies focused it on science and technology area.
The study aims to test the effect of narrative effect in multimedia setting with science topic. A script-based story was applied. The multimedia settings include a virtual human with synthetic speech, and animation on a solar cell lesson. The experiment design is a randomized alternative- treatments design, in which participants are requested to watch a video with pedagogical agent in story format or not. Participants were collected from Amazon Mechanical Turk.
Result of transfer score and retention score showed that no significant difference between narrative and non-narrative condition. Discussion was put forward for future study.
Although this storytelling method has been widely used in literature, language and even moral education, few studies focused it on science and technology area.
The study aims to test the effect of narrative effect in multimedia setting with science topic. A script-based story was applied. The multimedia settings include a virtual human with synthetic speech, and animation on a solar cell lesson. The experiment design is a randomized alternative- treatments design, in which participants are requested to watch a video with pedagogical agent in story format or not. Participants were collected from Amazon Mechanical Turk.
Result of transfer score and retention score showed that no significant difference between narrative and non-narrative condition. Discussion was put forward for future study.
ContributorsWu, Mengxuan (Author) / Craig, Scotty D. (Thesis advisor) / Branaghan, Russell (Committee member) / Chiou, Erin (Committee member) / Arizona State University (Publisher)
Created2018
Description
This study was conducted to assess the performance of 176 students who received algebra instruction through an online platform presented in one of two experimental conditions to explore the effect of personalized learning paths by comparing it with linearly flowing instruction. The study was designed around eight research questions investigating the effect of personalized learning paths on students’ learning, intrinsic motivation and satisfaction with their experience. Quantitative results were analyzed using Analysis of Variance (ANOVA), Analysis of Covariance (ANCOVA) and split-plot ANOVA methods. Additionally, qualitative feedback data were gathered from students and teachers on their experience to better explain the quantitative findings as well as improve understanding of how to effectively design an adaptive personalized learning platform. Quantitative results of the study showed no statistical difference between students assigned to treatments that compared linear and adaptive personalized instructional flows.
The lack of significant differences was explained by two main factors: (a) low usage and (b) platform and content related issues. Low usage may have prevented students from being exposed to the platforms long enough to create a potential for differences between the groups. Additionally, the reasons for low usage may in part be explained by the qualitative findings, which indicated that unmotivated and tired teachers and students were not very enthusiastic about the study because it occurred near the end of school year. Further, computer access was a challenging issue at the school throughout the study. On the other hand, platform and content related issues worked to inhibit the potential beneficial effects of the platforms. The three prominent issues were: (a) the majority of the students found the content boring or difficult, (b) repeated recommendations from the adaptive platform created frustration, and (c) a barely moving progress bar caused disappointment among participants.
The lack of significant differences was explained by two main factors: (a) low usage and (b) platform and content related issues. Low usage may have prevented students from being exposed to the platforms long enough to create a potential for differences between the groups. Additionally, the reasons for low usage may in part be explained by the qualitative findings, which indicated that unmotivated and tired teachers and students were not very enthusiastic about the study because it occurred near the end of school year. Further, computer access was a challenging issue at the school throughout the study. On the other hand, platform and content related issues worked to inhibit the potential beneficial effects of the platforms. The three prominent issues were: (a) the majority of the students found the content boring or difficult, (b) repeated recommendations from the adaptive platform created frustration, and (c) a barely moving progress bar caused disappointment among participants.
ContributorsBicer, Alpay (Author) / Bitter, Gary G. (Thesis advisor) / Buss, Ray R (Committee member) / Legacy, Jane M. (Committee member) / Arizona State University (Publisher)
Created2015
Description
Virtual environments are used for many physical rehabilitation and therapy purposes with varying degrees of success. An important feature for a therapy environment is the real-time monitoring of a participants' movement performance. Such monitoring can be used to evaluate the environment in addition to the participant's learning. Methods for monitoring and evaluation include tracking kinematic performance as well as monitoring muscle and brain activities through EMG and EEG technology. This study aims to observe trends in individual participants' motor learning based on changes in kinematic parameters and use those parameters to characterize different types of learners. This information can then guide EEG/EMG data analysis in the future. The evaluation of motor learning using kinematic parameters of performance typically compares averages of pre- and post-data to identify patterns of changes of various parameters. A key issue with using pre- and post-data is that individual participants perform differently and have different time-courses of learning. Furthermore, different parameters can evolve at independent rates. Finally, there is great variability in the movements at early stages of learning a task. To address these issues, a combined approach is proposed using robust regression, piece-wise regression and correlation to categorize different participant's motor learning. Using the mixed reality rehabilitation system developed at Arizona State University, it was possible to engage participants in motor learning, as revealed by improvements in kinematic parameters. A combination of robust regression, piecewise regression and correlation were used to reveal trends and characterize participants based on motor learning of three kinematic parameters: trajectory error, supination error and the number of phases in the velocity profile.
ContributorsAttygalle, Suneth Satoshi (Author) / He, Jiping (Thesis advisor) / Rikakais, Thanassis (Committee member) / Iasemidis, Leonidas (Committee member) / Arizona State University (Publisher)
Created2010
Description
This study investigated the ability to relate a test taker’s non-verbal cues during online assessments to probable cheating incidents. Specifically, this study focused on the role of time delay, head pose and affective state for detection of cheating incidences in a lab-based online testing session. The analysis of a test taker’s non-verbal cues indicated that time delay, the variation of a student’s head pose relative to the computer screen and confusion had significantly statistical relation to cheating behaviors. Additionally, time delay, head pose relative to the computer screen, confusion, and the interaction term of confusion and time delay were predictors in a support vector machine of cheating prediction with an average accuracy of 70.7%. The current algorithm could automatically flag suspicious student behavior for proctors in large scale online courses during remotely administered exams.
ContributorsChuang, Chia-Yuan (Author) / Femiani, John C. (Thesis advisor) / Craig, Scotty D. (Thesis advisor) / Bekki, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015
Description
Cancer is a disease involving abnormal growth of cells. Its growth dynamics is perplexing. Mathematical modeling is a way to shed light on this progress and its medical treatments. This dissertation is to study cancer invasion in time and space using a mathematical approach. Chapter 1 presents a detailed review of literature on cancer modeling.
Chapter 2 focuses sorely on time where the escape of a generic cancer out of immune control is described by stochastic delayed differential equations (SDDEs). Without time delay and noise, this system demonstrates bistability. The effects of response time of the immune system and stochasticity in the tumor proliferation rate are studied by including delay and noise in the model. Stability, persistence and extinction of the tumor are analyzed. The result shows that both time delay and noise can induce the transition from low tumor burden equilibrium to high tumor equilibrium. The aforementioned work has been published (Han et al., 2019b).
In Chapter 3, Glioblastoma multiforme (GBM) is studied using a partial differential equation (PDE) model. GBM is an aggressive brain cancer with a grim prognosis. A mathematical model of GBM growth with explicit motility, birth, and death processes is proposed. A novel method is developed to approximate key characteristics of the wave profile, which can be compared with MRI data. Several test cases of MRI data of GBM patients are used to yield personalized parameterizations of the model. The aforementioned work has been published (Han et al., 2019a).
Chapter 4 presents an innovative way of forecasting spatial cancer invasion. Most mathematical models, including the ones described in previous chapters, are formulated based on strong assumptions, which are hard, if not impossible, to verify due to complexity of biological processes and lack of quality data. Instead, a nonparametric forecasting method using Gaussian processes is proposed. By exploiting the local nature of the spatio-temporal process, sparse (in terms of time) data is sufficient for forecasting. Desirable properties of Gaussian processes facilitate selection of the size of the local neighborhood and computationally efficient propagation of uncertainty. The method is tested on synthetic data and demonstrates promising results.
Chapter 2 focuses sorely on time where the escape of a generic cancer out of immune control is described by stochastic delayed differential equations (SDDEs). Without time delay and noise, this system demonstrates bistability. The effects of response time of the immune system and stochasticity in the tumor proliferation rate are studied by including delay and noise in the model. Stability, persistence and extinction of the tumor are analyzed. The result shows that both time delay and noise can induce the transition from low tumor burden equilibrium to high tumor equilibrium. The aforementioned work has been published (Han et al., 2019b).
In Chapter 3, Glioblastoma multiforme (GBM) is studied using a partial differential equation (PDE) model. GBM is an aggressive brain cancer with a grim prognosis. A mathematical model of GBM growth with explicit motility, birth, and death processes is proposed. A novel method is developed to approximate key characteristics of the wave profile, which can be compared with MRI data. Several test cases of MRI data of GBM patients are used to yield personalized parameterizations of the model. The aforementioned work has been published (Han et al., 2019a).
Chapter 4 presents an innovative way of forecasting spatial cancer invasion. Most mathematical models, including the ones described in previous chapters, are formulated based on strong assumptions, which are hard, if not impossible, to verify due to complexity of biological processes and lack of quality data. Instead, a nonparametric forecasting method using Gaussian processes is proposed. By exploiting the local nature of the spatio-temporal process, sparse (in terms of time) data is sufficient for forecasting. Desirable properties of Gaussian processes facilitate selection of the size of the local neighborhood and computationally efficient propagation of uncertainty. The method is tested on synthetic data and demonstrates promising results.
ContributorsHan, Lifeng (Author) / Kuang, Yang (Thesis advisor) / Fricks, John (Thesis advisor) / Kostelich, Eric (Committee member) / Baer, Steve (Committee member) / Gumel, Abba (Committee member) / Arizona State University (Publisher)
Created2020
Description
Cancer is a worldwide burden in every aspect: physically, emotionally, and financially. A need for innovation in cancer research has led to a vast interdisciplinary effort to search for the next breakthrough. Mathematical modeling allows for a unique look into the underlying cellular dynamics and allows for testing treatment strategies without the need for clinical trials. This dissertation explores several iterations of a dendritic cell (DC) therapy model and correspondingly investigates what each iteration teaches about response to treatment.
In Chapter 2, motivated by the work of de Pillis et al. (2013), a mathematical model employing six ordinary differential (ODEs) and delay differential equations (DDEs) is formulated to understand the effectiveness of DC vaccines, accounting for cell trafficking with a blood and tumor compartment. A preliminary analysis is performed, with numerical simulations used to show the existence of oscillatory behavior. The model is then reduced to a system of four ODEs. Both models are validated using experimental data from melanoma-induced mice. Conditions under which the model admits rich dynamics observed in a clinical setting, such as periodic solutions and bistability, are established. Mathematical analysis proves the existence of a backward bifurcation and establishes thresholds for R0 that ensure tumor elimination or existence. A sensitivity analysis determines which parameters most significantly impact the reproduction number R0. Identifiability analysis reveals parameters of interest for estimation. Results are framed in terms of treatment implications, including effective combination and monotherapy strategies.
In Chapter 3, a study of whether the observed complexity can be represented with a simplified model is conducted. The DC model of Chapter 2 is reduced to a non-dimensional system of two DDEs. Mathematical and numerical analysis explore the impact of immune response time on the stability and eradication of the tumor, including an analytical proof of conditions necessary for the existence of a Hopf bifurcation. In a limiting case, conditions for global stability of the tumor-free equilibrium are outlined.
Lastly, Chapter 4 discusses future directions to explore. There still remain open questions to investigate and much work to be done, particularly involving uncertainty analysis. An outline of these steps is provided for future undertakings.
In Chapter 2, motivated by the work of de Pillis et al. (2013), a mathematical model employing six ordinary differential (ODEs) and delay differential equations (DDEs) is formulated to understand the effectiveness of DC vaccines, accounting for cell trafficking with a blood and tumor compartment. A preliminary analysis is performed, with numerical simulations used to show the existence of oscillatory behavior. The model is then reduced to a system of four ODEs. Both models are validated using experimental data from melanoma-induced mice. Conditions under which the model admits rich dynamics observed in a clinical setting, such as periodic solutions and bistability, are established. Mathematical analysis proves the existence of a backward bifurcation and establishes thresholds for R0 that ensure tumor elimination or existence. A sensitivity analysis determines which parameters most significantly impact the reproduction number R0. Identifiability analysis reveals parameters of interest for estimation. Results are framed in terms of treatment implications, including effective combination and monotherapy strategies.
In Chapter 3, a study of whether the observed complexity can be represented with a simplified model is conducted. The DC model of Chapter 2 is reduced to a non-dimensional system of two DDEs. Mathematical and numerical analysis explore the impact of immune response time on the stability and eradication of the tumor, including an analytical proof of conditions necessary for the existence of a Hopf bifurcation. In a limiting case, conditions for global stability of the tumor-free equilibrium are outlined.
Lastly, Chapter 4 discusses future directions to explore. There still remain open questions to investigate and much work to be done, particularly involving uncertainty analysis. An outline of these steps is provided for future undertakings.
ContributorsDickman, Lauren (Author) / Kuang, Yang (Thesis advisor) / Baer, Steven M. (Committee member) / Gardner, Carl (Committee member) / Gumel, Abba B. (Committee member) / Kostelich, Eric J. (Committee member) / Arizona State University (Publisher)
Created2020