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- Creators: Arizona State University
- Creators: Barrett, The Honors College
- Creators: Armfield, Jessica Ann
Description
As the frequency of US-based disasters increases, so does the need for effective governmental contingency planning and improvement. The current, external evaluation method presents several opportunities for improvement, including cost, efficacy of results, and turnaround time for results. Utilizing a tabletop exercise as it's model, this study designed a self-evaluation tool to test if the data provided by such a tool is similar to the data provided by an external evaluator. After testing it in a government-sanctioned tabletop exercise, the tool showed its ability to be utilized in an exercise and evaluate the participants, based off their perceived success in the exercise. The results of the study indicate a strong, positive correlation between the results of the participant and evaluator populations surveyed as well as statistical equality between the two groups.
ContributorsEisen, Bryan Matthew (Author) / Hristovski, Kiril (Thesis director) / Ulrich, Jon (Committee member) / Gibbons, Sheri (Committee member) / Environmental and Resource Management (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
STEM has increasingly become a buzz word in the world of education. According to Briener, et. al. (2012), the most common perspective of STEM education is teaching the integrated disciplines of science, technology, engineering, and mathematics as "one cohesive entity" instead of as separate subjects (p. 5). Prioritizing a STEM focus is a tactic many schools are beginning to adapt and one the United States government is financially backing, contributing significantly to the popularity of the movement (Briener, et.al., 2012). Across the nation, schools are making strides towards incorporating more STEM activities, and many school districts are designating entire schools as STEM schools. These STEM schools distinguish themselves with consistent commitment and attention to aspects of the STEM fields within instruction, including research opportunities for students, 21st Century skills, and a variety of learning environments. Bridges Elementary is one such identified STEM school that exemplifies these criteria, amongst others, setting a precedent for STEM schools to come.
ContributorsFefolt, Molly Lynn (Author) / Walters, Molina (Thesis director) / Oliver, Jill (Committee member) / Division of Teacher Preparation (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This is an evaluation of the Sandra Day O'Connor College of Law learning environment project which involved 120 participants (32 faculty and 88 students). In 2016, the Sandra Day O'Connor College of Law moved their main building to the newly built Beus Center for Law and Society building at the downtown Phoenix campus in order to bring the law students and faculty closer to the legal community that is present in downtown Phoenix. Prior to this move surveys regarding the Tempe campus were administered to the law students and faculty along with classroom observations and focus groups in order to conduct an evaluation of the environment. This evaluation examines the following six areas about the Tempe campus: the physical classroom environment; the instructional strategies used by instructors in the classroom; technology utilized in the classroom; frequency of technical difficulties by the instructor; and interactions between faculty, students, and the legal community. This evaluation only analyzed the quantitative data that was provided from the survey questions and not the qualitative data from classroom observations and focus groups. Within this evaluation is an explanation of the project that was conducted in part with the Sandra Day O'Connor College of Law and an overview of the participants involved in this evaluation. Additionally, this report will describe the methodology that was used to conduct the evaluation. Lastly, this evaluation includes the findings based off of the survey given to the evaluation participants and the recommendation for the new Beus Center for Law and Society based on the findings of the evaluation.
ContributorsLippincott, Megan Marie (Author) / Barnard, Wendy (Thesis director) / O'Donnell, Megan (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Science instructors need questions for use in exams, homework assignments, class discussions, reviews, and other instructional activities. Textbooks never have enough questions, so instructors must find them from other sources or generate their own questions. In order to supply instructors with biology questions, a semantic network approach was developed for generating open response biology questions. The generated questions were compared to professional authorized questions.
To boost students’ learning experience, adaptive selection was built on the generated questions. Bayesian Knowledge Tracing was used as embedded assessment of the student’s current competence so that a suitable question could be selected based on the student’s previous performance. A between-subjects experiment with 42 participants was performed, where half of the participants studied with adaptive selected questions and the rest studied with mal-adaptive order of questions. Both groups significantly improved their test scores, and the participants in adaptive group registered larger learning gains than participants in the control group.
To explore the possibility of generating rich instructional feedback for machine-generated questions, a question-paragraph mapping task was identified. Given a set of questions and a list of paragraphs for a textbook, the goal of the task was to map the related paragraphs to each question. An algorithm was developed whose performance was comparable to human annotators.
A multiple-choice question with high quality distractors (incorrect answers) can be pedagogically valuable as well as being much easier to grade than open-response questions. Thus, an algorithm was developed to generate good distractors for multiple-choice questions. The machine-generated multiple-choice questions were compared to human-generated questions in terms of three measures: question difficulty, question discrimination and distractor usefulness. By recruiting 200 participants from Amazon Mechanical Turk, it turned out that the two types of questions performed very closely on all the three measures.
To boost students’ learning experience, adaptive selection was built on the generated questions. Bayesian Knowledge Tracing was used as embedded assessment of the student’s current competence so that a suitable question could be selected based on the student’s previous performance. A between-subjects experiment with 42 participants was performed, where half of the participants studied with adaptive selected questions and the rest studied with mal-adaptive order of questions. Both groups significantly improved their test scores, and the participants in adaptive group registered larger learning gains than participants in the control group.
To explore the possibility of generating rich instructional feedback for machine-generated questions, a question-paragraph mapping task was identified. Given a set of questions and a list of paragraphs for a textbook, the goal of the task was to map the related paragraphs to each question. An algorithm was developed whose performance was comparable to human annotators.
A multiple-choice question with high quality distractors (incorrect answers) can be pedagogically valuable as well as being much easier to grade than open-response questions. Thus, an algorithm was developed to generate good distractors for multiple-choice questions. The machine-generated multiple-choice questions were compared to human-generated questions in terms of three measures: question difficulty, question discrimination and distractor usefulness. By recruiting 200 participants from Amazon Mechanical Turk, it turned out that the two types of questions performed very closely on all the three measures.
ContributorsZhang, Lishang (Author) / VanLehn, Kurt (Thesis advisor) / Baral, Chitta (Committee member) / Hsiao, Ihan (Committee member) / Wright, Christian (Committee member) / Arizona State University (Publisher)
Created2015
Description
There is a widespread inequality in health care access and insured rates suffered by the Latino, Spanish-speaking population in Arizona, resulting in poor health measures and economic burden. The passage of the Affordable Care Act in 2010 provided mechanisms to alleviate this disparity, however, many Latino communities lack accessible information and means to gain access to health insurance enrollment. Chicanos Por La Causa (CPLC) is a community based organizing that provides many services to low-income communities across Arizona, one of which is the CPLC Insurance Program. In collaboration with the Community Action Research Experiences (CARE) at Arizona State University, the program was studied to help address the need of a LOGIC model and evaluation plan to determine its effectiveness. Interviews with three executives within CPLC were conducted in conjunction with a literature review to determine the inputs, strategies, outputs, and outcomes of the LOGIC model that drive CPLC Insurance's mission. Evaluation measures were then created to provide the necessary quantitative data that can best show to what degree the program is achieving its goals. Specifically, the results indicated the key outcomes that drive the LOGIC model, and an evaluation plan designed to provide indicators of these outcomes was produced. The implications of this study are that the suggested data collection can verify how effectively the program's actions are creating positive change, as well as show where further improvements may be necessary to maximize effectiveness.
ContributorsCunningham, Matthew Lee (Author) / Fey, Richard (Thesis director) / Dumka, Larry (Committee member) / School of Molecular Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor)
Created2016-05
Description
A research project turned creative project focusing on the narrative of the student's perspective in the Next Generation Service Corps scholarship program. Using survey results from the program members, narratives of their experiences were compiled to offer insight and direction for the growth of the program.<br/><br/>A video of the defense can be found at this link: https://youtu.be/O63NRz0z1Ys
ContributorsJanezic, John Henry (Author) / Hunt, Brett (Thesis director) / Smith, Jacqueline (Committee member) / College of Integrative Sciences and Arts (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
The goal of the first study was to characterize the Miocene arkosic conglomerate in the Goldfield Mountains to determine the paleocurrent direction and source of the cobbles. This conglomerate is tilted to the northeast and unconformably overlies Proterozoic basement. Imbrication measurements are scattered but suggest the direction of paleoflow was toward the northwest and northeast, which suggests the cobbles were sourced from the southeast and southwest. The abundance of Dripping Spring Quartzite and the presence of Barnes Conglomerate in the cobbles, suggests an Apache Group source. In addition, south-southeast of the map area, there are several rock units composed of the same material as cobbles within the arkosic conglomerate. The arkosic conglomerate was likely deposited during onset of mid-Cenozoic extension, where the resulting highlands could provide a nearby source for the cobbles. This nearby source is interpreted to be south-southeast of the study area. A second study examined the effectiveness of course reform conducted on an introductory undergraduate course sequence. Questions of this study included: (1) How does the curriculum cater to a student population with diverse goals? (2) How do reformed courses add educational value as perceived by the student? (3) How does the redesigned curriculum and the instructional strategies, as implemented, address the goals of the reform?
The curriculum addressed the goals of the reform by (1) creating more opportunities for students to gain the skills relevant to their future goals, (2) having students utilize big data to make observations, interpretations, and predictions, (3) engaging students in scientific collaboration through group work and discussion, (4) giving students the opportunity to utilize computer programs that apply across various subjects and fields (i.e. Excel, MS Word, ArcGIS), and (5) requiring students to conduct original research to solve a problem and present their results orally and in written form. These redesign efforts were successful in meeting the objectives, and majority of the student participants reported one or more of the reformed experiences were valuable to their education and future goals. An understanding of teaching methods and educational values held by undergraduate students within the School of Earth and Space Exploration can be adapted and applied across subjects.
ContributorsAccetta, Danielle (Author) / Reynolds, Stephen J (Thesis advisor) / Johnson, Julia K (Committee member) / Semken, Steven (Committee member) / Arizona State University (Publisher)
Created2021
Description
“Bridging Success: Reviewing Effectiveness and Implementing Additional Programming” focuses on partnering with Arizona State University’s Bridging Success program to evaluate effective program components and propose additional programming for the upcoming Bridging Success Early Start (BSES) program. To effectively evaluate Bridging Success, this thesis is broken down into several sections: methods, literary analysis, landscaping, presentation of results, discussion of results, recommendations, and conclusions to ultimately address our central research questions: How is Bridging Success Early Start valued by previous program members, and does the program contribute to a successful transition to college for students who were formerly in foster care?
ContributorsBarrientos-Figueroa, Daniela (Author) / Forsythe, Molly (Co-author) / Gamboa, Jazmin (Co-author) / Gutierrez, Veronica (Thesis director) / Cheung, Justine (Committee member) / Barrett, The Honors College (Contributor) / School of Public Affairs (Contributor) / Division of Teacher Preparation (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor)
Created2023-05
Description
In natural language processing, language models have achieved remarkable success over the last few years. The Transformers are at the core of most of these models. Their success can be mainly attributed to an enormous amount of curated data they are trained on. Even though such language models are trained on massive curated data, they often need specific extracted knowledge to understand better and reason. This is because often relevant knowledge may be implicit or missing, which hampers machine reasoning. Apart from that, manual knowledge curation is time-consuming and erroneous. Hence, finding fast and effective methods to extract such knowledge from data is important for improving language models. This leads to finding ideal ways to utilize such knowledge by incorporating them into language models. Successful knowledge extraction and integration lead to an important question of knowledge evaluation of such models by developing tools or introducing challenging test suites to learn about their limitations and improve them further. So to improve the transformer-based models, understanding the role of knowledge becomes important. In the pursuit to improve language models with knowledge, in this dissertation I study three broad research directions spanning across the natural language, biomedical and cybersecurity domains: (1) Knowledge Extraction (KX) - How can transformer-based language models be leveraged to extract knowledge from data? (2) Knowledge Integration (KI) - How can such specific knowledge be used to improve such models? (3) Knowledge Evaluation (KE) - How can language models be evaluated for specific skills and understand their limitations?
I propose methods to extract explicit textual, implicit structural, missing textual, and missing structural knowledge from natural language and binary programs using transformer-based language models. I develop ways to improve the language model’s multi-step and commonsense reasoning abilities using external knowledge. Finally, I develop challenging datasets which assess their numerical reasoning skills in both in-domain and out-of-domain settings.
ContributorsPal, Kuntal Kumar (Author) / Baral, Chitta (Thesis advisor) / Wang, Ruoyu (Committee member) / Blanco, Eduardo (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2023
Description
Language Textbooks often play a major role in English for speakers of other languages (ESOL) classrooms, not only to provide information but also to help students construct their identities. Several studies showed that identity and language learning are inseparable, due to the simple fact that every learner has his/her own identity aspects like race, gender, social class, and speaker status (i.e., native speaker vs. non-native speaker of the target language). These aspects should be acknowledged because providing the students with limited identity options might cause the students to resist learning the language or be less invested in this practice (Norton & Toohey,2011).
However, there is limited support for teachers who wish to examine identity in ESOL textbooks. Several scholars attempted to evaluate the range of identity options offered in ESOL textbooks, but they all used either Critical Discourse Analysis or Content Analysis which can be effective; however, these procedures require training and can take a long time, so they may not be practical for teachers. This suggests that there is a need for a less complicated evaluation tool that can be easily used by teachers.
The purpose of this thesis is to develop a teacher-friendly identity-focused checklist for ESOL textbooks, and the thesis is guided by the following questions: (a) what would an evaluation checklist for identity in ESOL textbooks look like?; (b) what can this checklist reveal about ESOL textbooks? The purpose of this thesis was achieved by developing a qualitative checklist that covers, race, gender, social class, and speaker status, and demonstrating how to use it on a collection of five adult ESOL textbooks. The checklist revealed similarities and differences between the textbooks, including important shortcomings, and that kind of information can be useful for the teacher to make decisions about the textbook he/she uses.
However, there is limited support for teachers who wish to examine identity in ESOL textbooks. Several scholars attempted to evaluate the range of identity options offered in ESOL textbooks, but they all used either Critical Discourse Analysis or Content Analysis which can be effective; however, these procedures require training and can take a long time, so they may not be practical for teachers. This suggests that there is a need for a less complicated evaluation tool that can be easily used by teachers.
The purpose of this thesis is to develop a teacher-friendly identity-focused checklist for ESOL textbooks, and the thesis is guided by the following questions: (a) what would an evaluation checklist for identity in ESOL textbooks look like?; (b) what can this checklist reveal about ESOL textbooks? The purpose of this thesis was achieved by developing a qualitative checklist that covers, race, gender, social class, and speaker status, and demonstrating how to use it on a collection of five adult ESOL textbooks. The checklist revealed similarities and differences between the textbooks, including important shortcomings, and that kind of information can be useful for the teacher to make decisions about the textbook he/she uses.
ContributorsAlmatard, Abdulmajeed Mohammed (Author) / James, Mark (Thesis advisor) / Matsuda, Aya (Committee member) / Prior, Matthew (Committee member) / Arizona State University (Publisher)
Created2019