Matching Items (7)
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- All Subjects: Educational Psychology
- All Subjects: Time Delay
- Creators: Craig, Scotty D.
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 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
One of the primary objective in a computer science related course is for students to be able to write programs implementing the concepts covered in that course. In educational psychology, however, learning gains are more commonly measured using recall or problem solving questions. While these types of questions are relevant to computer science exams, they do not necessarily reflect a student’s ability to apply concepts by writing an original program to solve a novel problem.
This thesis investigates the effectiveness of including questions within instructional multimedia content to improve student performance on a related programming assignment. Similar techniques have proven effective in educational psychology research using other measures. The objective of this thesis is to apply educational techniques used in other domains to an experiment with real world measures of students in a computer science course. The findings of this paper demonstrate that the techniques used were promising in improving student performance on a programming assignment.
This thesis investigates the effectiveness of including questions within instructional multimedia content to improve student performance on a related programming assignment. Similar techniques have proven effective in educational psychology research using other measures. The objective of this thesis is to apply educational techniques used in other domains to an experiment with real world measures of students in a computer science course. The findings of this paper demonstrate that the techniques used were promising in improving student performance on a programming assignment.
ContributorsMar, Christopher (Author) / Sohoni, Sohum (Thesis advisor) / Nelson, Brian C (Committee member) / Craig, Scotty D. (Committee member) / Arizona State University (Publisher)
Created2016
Description
Observational tutoring has been found to be an effective method for teaching a variety of subjects by reusing dialogue from previous successful tutoring sessions. While it has been shown content can be learned through observational tutoring it has yet to been examined if a secondary behavior such as goal-setting can be influenced. The present study investigated if observing virtual humans engaging in a tutoring session on rotational kinematics with embedded positive goal oriented dialogue would increase knowledge of the material and perpetuate a shift an observer's goal-orientation from performance avoidance goal orientation (PAVGO) to learning goal orientation (LGO). Learning gains were observed in pre to post test knowledge retention tests. Significant changes from pretest to posttest occurred across conditions for LGO. Additionally, significant changes from PAVGO pretest to posttest were observed in the control condition however PAVGO did not significantly change in the experimental condition.
ContributorsTwyford, Jessica (Author) / Craig, Scotty D. (Thesis advisor) / Niemczyk, Mary (Committee member) / Kuzel, Michael (Committee member) / Arizona State University (Publisher)
Created2014
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