6,938 research outputs found
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
Comparative Multiple Case Study into the Teaching of Problem-Solving Competence in Lebanese Middle Schools
This multiple case study investigates how problem-solving competence is integrated into teaching practices in private schools in Lebanon. Its purpose is to compare instructional approaches to problem-solving across three different programs: the American (Common Core State Standards and New Generation Science Standards), French (Socle Commun de Connaissances, de Compétences et de Culture), and Lebanese with a focus on middle school (grades 7, 8, and 9). The project was conducted in nine schools equally distributed among three categories based on the programs they offered: category 1 schools offered the Lebanese program, category 2 the French and Lebanese programs, and category 3 the American and Lebanese programs. Each school was treated as a separate case.
Structured observation data were collected using observation logs that focused on lesson objectives and specific cognitive problem-solving processes. The two logs were created based on a document review of the requirements for the three programs. Structured observations were followed by semi-structured interviews that were conducted to explore teachers' beliefs and understandings of problem-solving competence. The comparative analysis of within-category structured observations revealed an instruction ranging from teacher-led practices, particularly in category 1 schools, to more student-centered approaches in categories 2 and 3. The cross-category analysis showed a reliance on cognitive processes primarily promoting exploration, understanding, and demonstrating understanding, with less emphasis on planning and executing, monitoring and reflecting, thus uncovering a weakness in addressing these processes. The findings of the post-observation semi-structured interviews disclosed a range of definitions of problem-solving competence prevalent amongst teachers with clear divergences across the three school categories.
This research is unique in that it compares problem-solving teaching approaches across three different programs and explores underlying teachers' beliefs and understandings of problem-solving competence in the Lebanese context. It is hoped that this project will inform curriculum developers about future directions and much-anticipated reforms of the Lebanese program and practitioners about areas that need to be addressed to further improve the teaching of problem-solving competence
Endogenous measures for contextualising large-scale social phenomena: a corpus-based method for mediated public discourse
This work presents an interdisciplinary methodology for developing endogenous measures of group membership through analysis of pervasive linguistic patterns in public discourse. Focusing on political discourse, this work critiques the conventional approach to the study of political participation, which is premised on decontextualised, exogenous measures to characterise groups. Considering the theoretical and empirical weaknesses of decontextualised approaches to large-scale social phenomena, this work suggests that contextualisation using endogenous measures might provide a complementary perspective to mitigate such weaknesses.
This work develops a sociomaterial perspective on political participation in mediated discourse as affiliatory action performed through language. While the affiliatory function of language is often performed consciously (such as statements of identity), this work is concerned with unconscious features (such as patterns in lexis and grammar). This work argues that pervasive patterns in such features that emerge through socialisation are resistant to change and manipulation, and thus might serve as endogenous measures of sociopolitical contexts, and thus of groups.
In terms of method, the work takes a corpus-based approach to the analysis of data from the Twitter messaging service whereby patterns in users’ speech are examined statistically in order to trace potential community membership. The method is applied in the US state of Michigan during the second half of 2018—6 November having been the date of midterm (i.e. non-Presidential) elections in the United States. The corpus is assembled from the original posts of 5,889 users, who are nominally geolocalised to 417 municipalities. These users are clustered according to pervasive language features. Comparing the linguistic clusters according to the municipalities they represent finds that there are regular sociodemographic differentials across clusters. This is understood as an indication of social structure, suggesting that endogenous measures derived from pervasive patterns in language may indeed offer a complementary, contextualised perspective on large-scale social phenomena
PARAMETRIC APPROACHES TO BALANCE STORMWATER MANAGEMENT AND HUMAN WELLBEING WITHIN URBAN GREEN SPACE
Through rapid urbanisation, urban green spaces (UGS) have become increasingly limited and valuable in high-density urban environments. However, meeting the diverse requirements of sustainable urban development often leads to conflicts in UGS usage. For example, the presence of stormwater treatment facilities may hinder residents' access to adjacent UGS.
Traditional approaches to UGS design typically focus on separate evaluations of human wellbeing and stormwater management. However, using questionnaires, interviews, and surveys for human wellbeing evaluation can be challenging to generalise across different projects and cities. Additionally, professional hydrological models used for stormwater management require extensive knowledge of hydrology and struggle to integrate their 2D evaluation methods with 3D models.
To address these challenges, this thesis proposes a novel framework to integrate the two types of analysis within a system for balancing the needs of human wellbeing and stormwater management in UGS design. The framework incorporates criteria and parameters for evaluating human wellbeing and stormwater management in a 3D model and introduces an approach to compare these two needs in terms of UGS area and suitable location. The contributions of this thesis to multi-objective UGS design are as follows: (1) defining human wellbeing evaluation through Accessibility and Usability assessment, which considers factors such as connectivity, walking distance, space enclosure, and space availability; (2) simplifying stormwater evaluation using particle systems and design curves to streamline complex hydrological models; (3) integrating the two evaluations by comparing their quantified requirements for UGS area and location; and (4) incorporating parameters to provide flexibility and accommodate various design scenarios and objectives.
The advantages of this evaluation framework are demonstrated through two case studies: (1) the human wellbeing analysis based on spatial parameters in the framework shows sensitivity to site variations, including UGS quantity and distribution, population density, terrain, road context, height of void space, and more; (2) the simplified stormwater analysis effectively captures site variations represented by UGS quantity and distribution, building distribution, as well as terrain, providing recommendations for each UGS with different types and sizes of stormwater facilities. (3) With the features of spatial parameter evaluation, the framework is feasible to adjust relevant thresholds and include more parameters to respond to specific project needs. (4) By quantifying the two different requirements for UGS and comparing them, any UGS with high usage conflicts can be easily identified. By evaluating all proposed criteria for UGSs in the 3D model, designers can conveniently observe simulation and adjust design scenarios to address identified usage conflicts. Thus, the proposed evaluation framework in this thesis would be valuable in effectively supporting further multi-objective UGS design
2023-2024 Boise State University Undergraduate Catalog
This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State
The European AI Liability Directives -- Critique of a Half-Hearted Approach and Lessons for the Future
As ChatGPT et al. conquer the world, the optimal liability framework for AI
systems remains an unsolved problem across the globe. In a much-anticipated
move, the European Commission advanced two proposals outlining the European
approach to AI liability in September 2022: a novel AI Liability Directive and
a revision of the Product Liability Directive. They constitute the final
cornerstone of EU AI regulation. Crucially, the liability proposals and the EU
AI Act are inherently intertwined: the latter does not contain any individual
rights of affected persons, and the former lack specific, substantive rules on
AI development and deployment. Taken together, these acts may well trigger a
Brussels Effect in AI regulation, with significant consequences for the US and
beyond.
This paper makes three novel contributions. First, it examines in detail the
Commission proposals and shows that, while making steps in the right direction,
they ultimately represent a half-hearted approach: if enacted as foreseen, AI
liability in the EU will primarily rest on disclosure of evidence mechanisms
and a set of narrowly defined presumptions concerning fault, defectiveness and
causality. Hence, second, the article suggests amendments, which are collected
in an Annex at the end of the paper. Third, based on an analysis of the key
risks AI poses, the final part of the paper maps out a road for the future of
AI liability and regulation, in the EU and beyond. This includes: a
comprehensive framework for AI liability; provisions to support innovation; an
extension to non-discrimination/algorithmic fairness, as well as explainable
AI; and sustainability. I propose to jump-start sustainable AI regulation via
sustainability impact assessments in the AI Act and sustainable design defects
in the liability regime. In this way, the law may help spur not only fair AI
and XAI, but potentially also sustainable AI (SAI).Comment: under peer-review; contains 3 Table
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
The advent of large language models (LLMs) and their adoption by the legal
community has given rise to the question: what types of legal reasoning can
LLMs perform? To enable greater study of this question, we present LegalBench:
a collaboratively constructed legal reasoning benchmark consisting of 162 tasks
covering six different types of legal reasoning. LegalBench was built through
an interdisciplinary process, in which we collected tasks designed and
hand-crafted by legal professionals. Because these subject matter experts took
a leading role in construction, tasks either measure legal reasoning
capabilities that are practically useful, or measure reasoning skills that
lawyers find interesting. To enable cross-disciplinary conversations about LLMs
in the law, we additionally show how popular legal frameworks for describing
legal reasoning -- which distinguish between its many forms -- correspond to
LegalBench tasks, thus giving lawyers and LLM developers a common vocabulary.
This paper describes LegalBench, presents an empirical evaluation of 20
open-source and commercial LLMs, and illustrates the types of research
explorations LegalBench enables.Comment: 143 pages, 79 tables, 4 figure
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