Thesis advisor: Larry H. Ludlow / Teachers in the United States are increasingly tasked with using data to inform their classroom instruction both through federal policies, such as the Every Student Succeeds Act (ESSA, 2016), and state policies requiring the use of teacher-determined data-driven goals for performance evaluations (MA 603 CMR 35.07). Many teachers, however, report that they feel underprepared to engage in this type of work (Dunn et al., 2013), also called Data-Driven Decision Making (DDDM). In addition, there is currently a limited set of instruments to measure the construct of using data to inform classroom instruction and the instruments that currently exist measure this construct using a typical Classical Test Theory design.This work developed an instrument called the Using Data to Inform classroom Instruction (UDII) scale to measure teachers’ use of data to inform classroom instruction. It used the Rasch/Guttman Scenario (RGS) methodology, an approach that develops scenarios that reflect the rich lived experiences of individuals (Antipkina & Ludlow, 2020; Ludlow et al., 2014). The RGS approach utilizes the Rasch model, part of the family of Item Response Theory models, which conceptualizes a construct as a hierarchical continuum. Scenario items and people are plotted on the same variable map, which allows for the development of rich descriptions of individuals at particular raw score locations on the continuum. An interpretative variable map is included to help schools and districts use the results of the survey. This work adds to the growing body of literature utilizing the RGS approach, as well as the literature focused on the use of data to inform classroom instruction (or DDDM). The UDII scale can be utilized by schools and districts who are engaged in the work of using data to inform classroom instruction to identify the current skillsets of teachers and/or teams of teachers to provide differentiated support, or it can be used before and after an intervention focused on using data to inform classroom instruction to measure change. / Thesis (PhD) — Boston College, 2022. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement and Evaluation.

京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第18388号 / エネ博第300号 / 新制||エネ||62(附属図書館) / 31246 / 京都大学大学院エネルギー科学研究科エネルギー変換科学専攻 / (主査)教授 小西 哲之, 教授 宇根﨑 博信, 准教授 笠田 竜太 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM

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Precast concrete multistory buildings are used in an attempt to optimize the available construction space and reduce costs. However, little is known about predicting their capacity in a brittle response mode due to the sudden loss of a critical element that could induce a Progressive Collapse Scenario. Therefore, the National Institute for Standards and Technology (NIST) developed an explicit approach in the design of precast concrete systems that is intended to mitigate a progressive collapse by enhancing the rotational capacity of joints and the robustness of the structural system. A full-scale experiment was conducted to investigate the structural performance of a prototype design under a column-removal scenario. The test assembly frame, consisting of three columns and two beams, was subjected to a displacement controlled vertical force acting at the center to characterize the failure modes and collapse mechanisms. Brittleailures of critical structural elements were observed and significantly impacted the performance.

Stories about the future are a powerful tool for navigating uncertainty, building agency, and detecting opportunities for transformation. For communities that have weathered colonialism, future visions grounded in local values and knowledge are especially powerful. Futures based in diverse value systems are also valuable assets for global efforts toward sustainability transformation. This thesis project began with a participatory visioning workshop in Mombera Kingdom, a community located in Malawi. We invited the kingdom’s traditional leaders to imagine positive futures for nature and people in their district. This workshop was a case study application of the Nature Futures Framework (NFF), a heuristic tool that enables explicit discussion of different ways that people value nature. Following the workshop, I applied the NFF in a novel way to translate the rich and diverse participant visions into distinct, packaged future scenarios. First, I built a Causal Loop Diagram (CLD) that represents dynamics in the present. Second, I organized possible interventions according to their expected impact on the NFF’s value perspectives. Third, I used those interventions to build three desirable scenarios of the kingdom’s future, each of which is desirable according to different values. Finally, I gathered stakeholder feedback on the scenarios at a follow-up workshop. The CLD suggests that misalignment within agricultural and energy production institutions causes failure to mediate ecosystem health and human well-being. The intervention analysis demonstrates that value-diverse visions can be translated into value-discrete scenarios. The scenarios capture images of modernity firmly grounded in Mombera Kingdom’s cultural values, rather than the culture that once colonized them. These results suggest new problem framings and strategies in the case study context. This project is a useful step toward regional- and global-scale future scenarios able to include Africa’s locally situated value systems. / AFRICAN FUTURES

Food systems are complex social-ecological systems. Currently, they are the source of large-scale health problems and environmental impacts, and there is widespread agreement that transformative change is needed. Scenarios are useful tools for directing such change, as they provide engaging future visions that work well with complex systems.  This thesis is a part of Mistra Food Futures, a platform for a sustainable transformation of the Swedish food system, where scenarios for Swedish food futures are being developed. The thesis purpose is to contribute to the scenario development by the use of systems mapping and semi-quantitative scenario modelling. The thesis builds on four scenario narratives previously developed by Mistra Food Futures researchers. During the thesis process, these scenario narratives were re-interpreted as Causal Loop Diagrams. The diagrams were then used as the basis for constructing a food system model in the form of a Fuzzy Cognitive Map. Simulations were run to investigate the conditions under which the scenarios could be reproduced by modelling. The modelling uncovered several system dynamics: the competition or shared interests of different types of agriculture; the system impacts of novel foods; the vulnerabilities of localised food systems; the importance of food culture; and the interactions of environmental policy with farming systems. Another finding was system attractors where scenarios mix, and these are presented as alternative scenarios. The thesis contributes to the scenario development by making relationships, system feedbacks, and drivers explicit by systems mapping, as well as providing a user-friendly model that can be used for further system exploration. The analysis of specific dynamics can be used to inform upcoming scenario iterations, and alternative scenarios can be used to maintain analytical depth when scenario interactions are discussed. The process also provides a demonstration of the use of Fuzzy Cognitive Maps in scenario modelling.

The external environment, currently considered as VUCA environment, in which orgnaizations and individuals operate can be characterized by numerous uncertainties. As a result of these uncertainties, one significant aspect that is affected is the individual KSAOs as part of the human capital concept. A thorough understanding of how uncertainties affect KSAOs allows individuals and organizations to adapt, be resilient, and respond effectively to the changing environment. One research field that encompasses the external environment and its uncertainties as well as individual KSAOs is strategic human resource management (SHRM). However, the relationship between these key concepts has not yet been addressed. Also, much of SHRM research has been devoted to the company's perspective, largely ignoring the employees' point of view. Thus, this research aims to fill a gap in prior research by exploring the relationship between the external environment with its uncertainties and individual KSAOs from the employee's perspective. To further implement this knowledge in practice, two scenarios are created to demonstrate the factors companies should focus on in order to increase their human capital's resilience. To identify the relationship between external uncertainties and individual KSAOs, a conceptual framework was developed. The framework outlines the foundation for a qualitative case study with a Swedish consultancy company as a single case. A comprehensive data foundation was constructed through data triangulation, which involves combining both primary and secondary sources of data. In this study, organizational documents provided by the case company were used as secondary data, while primary data was gathered through semi-structured interviews with six employees of the case company. The findings indicate differences between prior literature and the collected empirical data. For example, employees' views on prioritizing different KSAOs (Knowledge, skills, abilities, and other characteristics) showed that soft skills were seen as far more important than hard skills when coping with uncertainties. This challenges the prior literature on human capital that has mostly focused on hard skills and the importance of their development through education and training. By using COVID-19 as a recent and accurate example of uncertainty, the data revealed changes in ways of working and work-life balance. It also revealed that environmental and technological uncertainties are currently considered the most effective. While they were seen to have unpredictable, and possibly even negative long-term effects, they were also considered as possibilities for the future. With subjective research philosophy, we could find contradictory opinions within the sample which further extended prior research by highlighting the need for considering individuality rather than the company perspective when making decisions that relate to the external environment , its uncertainties, and the individual KSAOs.

<p>    </p> <p>I worked on two chapters studying the labor markets in Colombia and Iraq. My third chapter analyzed health outcomes in the US. </p> <p><br></p> <p>My first chapter examines whether the three-year gap between the announcement (in 2014) and the start (in 2017) of the Illicit Crop Substitution Program (ICSP) increased child labor in Colombia. My results from a difference-in-differences model using differences in historical coca production show that due to the ICSP announcement, children became four percentage points more likely to work in municipalities with historical coca production than in non–coca-growing areas. </p> <p><br></p> <p>My second chapter ran a randomized control trial and a double-incentivized resume rating to elicit the preferences of employers and job seekers for candidates and vacancies in Iraq. After revealing the ob offer rate for female job seekers, women applied for jobs by three more percentage points than the men in the control group. This paper highlights the value of revealing employers’ preferences to improve the match between female candidates and employers when women underestimate the chances of finding a job. </p> <p><br></p> <p>In my third paper, I study how removing the black box warning on Chantix, a prescription drug used to reduce nicotine consumption, affects veterans’ visits to smoking cessation therapy. Using a difference-in-differences model, I found that veterans schedule almost two more medical consultations in counties with high-quality hospitals than in places with low-quality medical care centers. </p>

Today’s sustainability assessment frameworks are no longer applicable when evaluating the newautomotive vehicles. Therefore, the need for suitable automotive evaluation frameworks increasesas companies and scientists are trying to predict the important sustainability characteristics oftomorrows car and how it will affect our societies. The goal is to create a conceptual sustainabilityassessment framework to solve the very complex question of what the most important criteria areand how this new transportation type might affect our society. This is done using a systemapproach, a method that is suitable for studying interrelations between the influencing factors incomplex problems like the one between the sustainability dimensions. Scenario analysis has beenused in order to create the future environment and do a segmentation of the plausible concepts offuturistic transportation options. The evaluation criteria have been developed by gatheringinformation through a literature study and from primary sources via interviews.The resulting framework is composed of 19 evaluation criteria from the different dimensions ofsustainability. The framework allows the user to insert a futuristic concept and evaluate it tocompare a numeric score to other concepts to get indicators of how sustainable the concept is. Thesegmentation of futuristic vehicles shows that the most plausible types of automated vehicles areshared taxis, non-shared taxis and privately owned vehicles, all affecting society differently.The thematic analysis of the criteria has shown that there some relationships and types of criteriathat are more important than others. The most essential discovered correlations between criteriaare: Production and affordability and also maintenance &amp; operation and affordability, affordabilitywith accessibility, affordability &amp; accessibility and traffic volumes and further traffic Volumesand pollution. The developed framework is believed to have the desired function of creating a trustworthyassessment of autonomous vehicles based on the literature study and previous discoveries withinthe field. The evaluation of the different segments is left for future work. / Dagens ramverk för hållbarhetsbedömningar är inte längre användbara vid utvärdering av nyasjälvkörande fordon. Därför har behovet ökat av lämpliga ramverk som fokuserar påhållbarhetsutvärderingar när företag och forskare försöker förutse de viktigahållbarhetsegenskaperna av morgondagens fordon och hur de kommer att påverka vårt samhälleutifrån ett hållbarhetsperspektiv. Målet med studien är att skapa ett konceptuellt ramverk förhållbarhetsbedömning som kan hjälpa till att lösa den mycket komplexa frågan om vilka viktigakriterier bör inkluderas vid en evaluering av denna nya typ av transport. Studien har följt ettsystematiskt tillvägagångssätt kallat ”System approach”, en metod som är lämplig för studier därrelationer mellan olika påverkande faktorer är väldigt komplexa, som den mellanhållbarhetsdimensionerna. Scenarioanalys har används för att skapa en framtida miljö och ensegmentering av de mest trovärdiga koncepten av framtida transportalternativ. Utvärderingskriterierna har utvecklats genom att samla in information från en litteraturstudie ochfrån primära källor genom intervjuer. Det resulterande ramverket är sammansatt av 19 utvärderingskriterier inom de olikadimensionerna för hållbarhet. Med det resulterade ramverket kan användaren införa ett futuristisktfordonskoncept och bedöma detta för att få ett numeriskt resultat och jämföra dessa med andrautvärderingar för att få en indikation om hur hållbara koncepten är gentemot varandra. Segmenteringen av de futuristiska fordonstyperna visar att de mest trovärdiga typerna avautomatiserade färdmedel är delade taxitjänster, privata taxitjänster och privatägda fordon, allamed olika påverkan på samhället. Den tema-baserade analys av kriterierna har visat att det finns vissa relationer och typer av kriteriersom är viktigare än andra. De viktigaste upptäckta relationerna mellan kriterier är: Produktion ochekonomisk tillgänglighet, underhåll och ekonomisk tillgänglighet, ekonomisk tillgänglighet medtillgänglighet till transport, tillgänglighet till transport och trafikvolymer, ekonomisk tillgänglighetoch trafikvolymer och slutligen så påverkar trafikvolymerna utsläppet. Det utvecklade konceptuella ramverket antas ha den önskade funktionen att skapa en pålitligbedömning av autonoma fordon baserat på litteraturstudien och tidigare upptäckter inom fältet. Utvärderingen av de olika segmenten lämnas till framtida studier.

Road transport is responsible for a significant share of the global GHG emissions. In order to address the increasing trend of road vehicle emissions, due to its heavy reliance on oil, Nordic countries have set ambitious goals and policies for the reduction of road transport GHG emissions. Despite the fact that the latest developments in the passenger car segment are leading towards the progressive electrification of the fleet, the decarbonization of heavy-duty vehicle segment presents significant challenges that are yet to be overcome. This study focuses, on the first part, on the regulatory framework of fuel economy standards of road vehicles, highlighting the absence of a European regulation on fuel efficiency for the heavy-duty sector. Energy efficiency technologies can be grouped mainly in vehicle technologies, driveline and powertrain technologies, and alternative fuels. The fuel efficiency of HDVs can be positively improved at different vehicle levels, but the technology benefit and its economic feasibility are heavily dependent on the vehicle type and the operational cycle considered. The electrification pathway has the potential of reducing the carbon emission to a great extent, but the current battery technologies have proven to be not cost efficient for the heavy vehicles, because of the high purchase price and the low range, related to the battery cost and inferior energy density compared to conventional liquid fuels.   A scenario development model has been created in order to estimate and quantify the impact of future developments and emission reduction measures in Finland, Sweden and Norway for the timeframe 2016-2050, with a focus on 2030 results. Two scenarios concerning the powertrain developments of heavy-duty vehicles and buses have been created, a conservative scenario and electric scenario, as well as vehicle efficiency improvements and fuel consumption scenarios. Additional sets of parameters have been estimated as input for the model, such as national transport need and load assumptions. The results highlight the challenges of achieving the national GHG emission reduction targets with the current measures in all three countries. The slow fleet renewal rates and the high forecasted increase of transport need limit the benefits of alternative and more efficient powertrains introduced in the fleet by new vehicles. The heavy-duty transport is expected to maintain its heavy reliance on diesel fuel and hinder the improvements of the light-duty segments. A holistic approach is needed to reduce the GHG emissions from road transport, including more efficient powertrains, higher biofuel shares and progressive electrification.