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- Creators: Arizona State University
Description
South Sudanese refugees are among the most vulnerable immigrants to the U.S.. Many have spent years in refugee camps, experienced trauma, lost members of their families and have had minimal or no schooling or literacy prior to their arrival in the U.S. Although most South Sudanese aspire to become U.S. citizens, finally giving them a sense of belonging and participation in a land they can call their own, they constitute a group that faces great challenges in terms of their educational adaptation and English-language learning skills that would lead them to success on the U.S. citizenship examination. This dissertation reports findings from a qualitative research project involving case studies of South Sudanese students in a citizenship preparation program at a South Sudanese refugee community center in Phoenix, Arizona. It focuses on the links between the motivations of students seeking citizenship and the barriers they face in gaining it. Though the South Sudanese refugee students aspiring to become U.S. citizens face many of the same challenges as other immigrant groups, there are some factors that in combination make the participants in this study different from other groups. These include: long periods spent in refugee camps, advanced ages, war trauma, absence of intact families, no schooling or severe disruption from schooling, no first language literacy, and hybridized forms of second languages (e.g. Juba Arabic). This study reports on the motivations students have for seeking citizenship and the challenges they face in attaining it from the perspective of teachers working with those students, community leaders of the South Sudanese community, and particularly the students enrolled in the citizenship program.
ContributorsJohnson, Erik (Author) / Adams, Karen (Thesis advisor) / Renaud, Claire (Committee member) / James, Mark (Committee member) / Arizona State University (Publisher)
Created2014
Description
Cyber-Physical Systems (CPS) are being used in many safety-critical applications. Due to the important role in virtually every aspect of human life, it is crucial to make sure that a CPS works properly before its deployment. However, formal verification of CPS is a computationally hard problem. Therefore, lightweight verification methods such as testing and monitoring of the CPS are considered in the industry. The formal representation of the CPS requirements is a challenging task. In addition, checking the system outputs with respect to requirements is a computationally complex problem. In this dissertation, these problems for the verification of CPS are addressed. The first method provides a formal requirement analysis framework which can find logical issues in the requirements and help engineers to correct the requirements. Also, a method is provided to detect tests which vacuously satisfy the requirement because of the requirement structure. This method is used to improve the test generation framework for CPS. Finally, two runtime verification algorithms are developed for off-line/on-line monitoring with respect to real-time requirements. These monitoring algorithms are computationally efficient, and they can be used in practical applications for monitoring CPS with low runtime overhead.
ContributorsDokhanchi, Adel (Author) / Fainekos, Georgios (Thesis advisor) / Lee, Yann-Hang (Committee member) / Sarjoughian, Hessam S. (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2017
Description
Automated driving systems are in an intensive research and development stage, and the companies developing these systems are targeting to deploy them on public roads in a very near future. Guaranteeing safe operation of these systems is crucial as they are planned to carry passengers and share the road with other vehicles and pedestrians. Yet, there is no agreed-upon approach on how and in what detail those systems should be tested. Different organizations have different testing approaches, and one common approach is to combine simulation-based testing with real-world driving.
One of the expectations from fully-automated vehicles is never to cause an accident. However, an automated vehicle may not be able to avoid all collisions, e.g., the collisions caused by other road occupants. Hence, it is important for the system designers to understand the boundary case scenarios where an autonomous vehicle can no longer avoid a collision. Besides safety, there are other expectations from automated vehicles such as comfortable driving and minimal fuel consumption. All safety and functional expectations from an automated driving system should be captured with a set of system requirements. It is challenging to create requirements that are unambiguous and usable for the design, testing, and evaluation of automated driving systems. Another challenge is to define useful metrics for assessing the testing quality because in general, it is impossible to test every possible scenario.
The goal of this dissertation is to formalize the theory for testing automated vehicles. Various methods for automatic test generation for automated-driving systems in simulation environments are presented and compared. The contributions presented in this dissertation include (i) new metrics that can be used to discover the boundary cases between safe and unsafe driving conditions, (ii) a new approach that combines combinatorial testing and optimization-guided test generation methods, (iii) approaches that utilize global optimization methods and random exploration to generate critical vehicle and pedestrian trajectories for testing purposes, (iv) a publicly-available simulation-based automated vehicle testing framework that enables application of the existing testing approaches in the literature, including the new approaches presented in this dissertation.
One of the expectations from fully-automated vehicles is never to cause an accident. However, an automated vehicle may not be able to avoid all collisions, e.g., the collisions caused by other road occupants. Hence, it is important for the system designers to understand the boundary case scenarios where an autonomous vehicle can no longer avoid a collision. Besides safety, there are other expectations from automated vehicles such as comfortable driving and minimal fuel consumption. All safety and functional expectations from an automated driving system should be captured with a set of system requirements. It is challenging to create requirements that are unambiguous and usable for the design, testing, and evaluation of automated driving systems. Another challenge is to define useful metrics for assessing the testing quality because in general, it is impossible to test every possible scenario.
The goal of this dissertation is to formalize the theory for testing automated vehicles. Various methods for automatic test generation for automated-driving systems in simulation environments are presented and compared. The contributions presented in this dissertation include (i) new metrics that can be used to discover the boundary cases between safe and unsafe driving conditions, (ii) a new approach that combines combinatorial testing and optimization-guided test generation methods, (iii) approaches that utilize global optimization methods and random exploration to generate critical vehicle and pedestrian trajectories for testing purposes, (iv) a publicly-available simulation-based automated vehicle testing framework that enables application of the existing testing approaches in the literature, including the new approaches presented in this dissertation.
ContributorsTuncali, Cumhur Erkan (Author) / Fainekos, Georgios (Thesis advisor) / Ben Amor, Heni (Committee member) / Kapinski, James (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2019
Description
Testing and Verification of Cyber-Physical Systems (CPS) is a challenging problem. The challenge arises as a result of the complex interactions between the components of these systems: the digital control, and the physical environment. Furthermore, the software complexity that governs the high-level control logic in these systems is increasing day by day. As a result, in recent years, both the academic community and the industry have been heavily invested in developing tools and methodologies for the development of safety-critical systems. One scalable approach in testing and verification of these systems is through guided system simulation using stochastic optimization techniques. The goal of the stochastic optimizer is to find system behavior that does not meet the intended specifications.
In this dissertation, three methods that facilitate the testing and verification process for CPS are presented:
1. A graphical formalism and tool which enables the elicitation of formal requirements. To evaluate the performance of the tool, a usability study is conducted.
2. A parameter mining method to infer, analyze, and visually represent falsifying ranges for parametrized system specifications.
3. A notion of conformance between a CPS model and implementation along with a testing framework.
The methods are evaluated over high-fidelity case studies from the industry.
In this dissertation, three methods that facilitate the testing and verification process for CPS are presented:
1. A graphical formalism and tool which enables the elicitation of formal requirements. To evaluate the performance of the tool, a usability study is conducted.
2. A parameter mining method to infer, analyze, and visually represent falsifying ranges for parametrized system specifications.
3. A notion of conformance between a CPS model and implementation along with a testing framework.
The methods are evaluated over high-fidelity case studies from the industry.
ContributorsHoxha, Bardh (Author) / Fainekos, Georgios (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / Maciejewski, Ross (Committee member) / Ben Amor, Heni (Committee member) / Arizona State University (Publisher)
Created2017
Description
This study investigated the effects of distributed presentation microlearning and the testing effect on mobile devices and student attitudes about the use of mobile devices for learning in higher education. For this study, a mobile device is considered a smartphone. All communication, content, and testing were completed remotely through participants’ mobile devices.
The study consisted of four conditions: (a) an attitudinal and demographic pre-survey, (b) five mobile instructional modules, (c) mobile quizzes, and (d) an attitudinal post-survey. A total of 311 participants in higher education were enrolled in the study. One hundred thirty-seven participants completed all four conditions of the study. Participants were randomly assigned to experimental conditions in a 2 x 2 factorial design. The levels of the first factor, distribution of instructional content, were: once-per-day and once-per-week. The levels of the second factor, testing, were: a quiz after each module plus a comprehensive quiz and a single comprehensive quiz after all instruction. The dependent variable was learning outcomes in the form of quiz-score results. Attitudinal survey results were analyzed using Principal Axis Factoring to reveal three components, (a) student perceptions about the use of mobile devices in education,
(b) student perceptions about instructors’ beliefs for mobile devices for learning, and (c) student perceptions about the use of mobile devices post-instruction.
The results revealed several findings. There was no significant effect for type of delivery of instruction in a one-way ANOVA. There was a significant effect for testing in a one-way ANOVA There were no main effects of delivery and testing in a 2 x 2 factorial design and there was no main interaction effect, and there was a significant effect of testing on final quiz scores controlling for technical beliefs in a 2 x 2 ANCOVA. The significant difference in testing was contradictory to some literature.
Ownership of personal mobile devices in persons aged 18–29 is practically all-inclusive. Thus, future research on student attitudes and the implementation of personal smartphones for microlearning and testing is still needed to develop and integrate mobile-ready content for higher education.
The study consisted of four conditions: (a) an attitudinal and demographic pre-survey, (b) five mobile instructional modules, (c) mobile quizzes, and (d) an attitudinal post-survey. A total of 311 participants in higher education were enrolled in the study. One hundred thirty-seven participants completed all four conditions of the study. Participants were randomly assigned to experimental conditions in a 2 x 2 factorial design. The levels of the first factor, distribution of instructional content, were: once-per-day and once-per-week. The levels of the second factor, testing, were: a quiz after each module plus a comprehensive quiz and a single comprehensive quiz after all instruction. The dependent variable was learning outcomes in the form of quiz-score results. Attitudinal survey results were analyzed using Principal Axis Factoring to reveal three components, (a) student perceptions about the use of mobile devices in education,
(b) student perceptions about instructors’ beliefs for mobile devices for learning, and (c) student perceptions about the use of mobile devices post-instruction.
The results revealed several findings. There was no significant effect for type of delivery of instruction in a one-way ANOVA. There was a significant effect for testing in a one-way ANOVA There were no main effects of delivery and testing in a 2 x 2 factorial design and there was no main interaction effect, and there was a significant effect of testing on final quiz scores controlling for technical beliefs in a 2 x 2 ANCOVA. The significant difference in testing was contradictory to some literature.
Ownership of personal mobile devices in persons aged 18–29 is practically all-inclusive. Thus, future research on student attitudes and the implementation of personal smartphones for microlearning and testing is still needed to develop and integrate mobile-ready content for higher education.
ContributorsRettger, Elaine (Author) / Bitter, Gary (Thesis advisor) / Legacy, Jane (Committee member) / Savenye, Wilhelmina (Committee member) / Arizona State University (Publisher)
Created2017