Moving Forward as a Family: Crafting a 2-Generation Strategy for Central Texas, PRP 192

United Way for Greater Austin commissioned this policy research project to guide their focus on helping low socioeconomic families achieve greater financial stability through the development of a Two-Generation (2-Gen) strategy for the Central Texas region. Two-Gen programs emphasize the importance of education as a means for better economic outcomes. High-quality early childhood education programs allow children to make critical neural connections during a period of substantial growth and development, ultimately better preparing them for pre-kindergarten programs and academic success in subsequent years. Adults working low-paying jobs encounter barriers to career advancement due to lacking credentials or relevant education. It is not uncommon for parents working long hours for low wages to have at least one child in need of high-quality early childhood education, yet they are unable to enroll their child in such programs due to issues such as cost, transportation, and time away from work. Two-Gen programs seek to resolve the issues complicating this problem of financial instability by providing high-quality educational and training programs for both parents and children, which are even more effective when intentionally coordinated so that the family develops as a single unit in a positive direction. The research consisted of a literature review; a program scan at the local, state, and federal levels; and site visits within Austin, Dallas, and San Antonio, as well as Boston and Miami. Data collected specific to the Central Texas region include a labor market analysis, a needs assessment, and a mapping of current organizational assets. Obtaining and analyzing this data allowed the team to better understand 2-Gen program development, outcomes, impact measurements, and areas for improvement. The research team developed practical applications for the information collected, ultimately contributing to the proposed anti-poverty strategy through the intentional coordination of 2-Gen services by leveraging existing organizational assets to best address the area’s most salient needs. In addition, the team proposed an evaluation strategy involving cost-benefit equations, program evaluation metrics, and a screening tool to predict the likelihood of a program achieving successful outcomes. The report concludes with policy recommendations at the local, state, and federal levels, as well as a summary of the populations affected by financial instability and future directions for this field.United Way for Greater AustinPublic Affair

A Hybrid Recommender Strategy on an Expanded Content Manager in Formal Learning

The main topic of this paper is to find ways to improve learning in a formal Higher Education Area. In this environment, the teacher publishes or suggests contents that support learners in a given course, as supplement of classroom training. Generally, these materials are pre-stored and not changeable. These contents are typically published in learning management systems (the Moodle platform emerges as one of the main choices) or in sites created and maintained on the web by teachers themselves. These scenarios typically include a specific group of students (class) and a given period of time (semester or school year). Contents reutilization often needs replication and its update requires new edition and new submission by teachers. Normally, these systems do not allow learners to add new materials, or to edit existing ones. The paper presents our motivations, and some related concepts and works. We describe the concepts of sequencing and navigation in adaptive learning systems, followed by a short presentation of some of these systems. We then discuss the effects of social interaction on the learners’ choices. Finally, we refer some more related recommender systems and their applicability in supporting learning. One central idea from our proposal is that we believe that students with the same goals and with similar formal study time can benefit from contents' assessments made by learners that already have completed the same courses and have studied the same contents. We present a model for personalized recommendation of learning activities to learners in a formal learning context that considers two systems. In the extended content management system, learners can add new materials, select materials from teachers and from other learners, evaluate and define the time spent studying them. Based on learner profiles and a hybrid recommendation strategy, combining conditional and collaborative filtering, our second system will predict learning activities scores and offers adaptive and suitable sequencing learning contents to learners. We propose that similarities between learners can be based on their evaluation interests and their recent learning history. The recommender support subsystem aims to assist learners at each step suggesting one suitable ordered list of LOs, by decreasing order of relevance. The proposed model has been implemented in the Moodle Learning Management System (LMS), and we present the system’s architecture and design. We will evaluate it in a real higher education formal course and we intend to present experimental results in the near future

Principles in Patterns (PiP) : Project Evaluation Synthesis

Evaluation activity found the technology-supported approach to curriculum design and approval developed by PiP to demonstrate high levels of user acceptance, promote improvements to the quality of curriculum designs, render more transparent and efficient aspects of the curriculum approval and quality monitoring process, demonstrate process efficacy and resolve a number of chronic information management difficulties which pervaded the previous state. The creation of a central repository of curriculum designs as the basis for their management as "knowledge assets", thus facilitating re-use and sharing of designs and exposure of tacit curriculum design practice, was also found to be highly advantageous. However, further process improvements remain possible and evidence of system resistance was found in some stakeholder groups. Recommendations arising from the findings and conclusions include the need to improve data collection surrounding the curriculum approval process so that the process and human impact of C-CAP can be monitored and observed. Strategies for improving C-CAP acceptance among the "late majority", the need for C-CAP best practice guidance, and suggested protocols on the knowledge management of curriculum designs are proposed. Opportunities for further process improvements in institutional curriculum approval, including a re-engineering of post-faculty approval processes, are also recommended

Forging partnerships in health care: Process and measuring benefits

Universally, there is concern that much academic learning has dealt mainly in theory, removing knowledge from context with a resultant lack of practical experience. Here, the catalyst for strengthening university-community engagement, emanated from a desire to foster greater propensity within students to make connections between their academic courses and responsibility toward the community and people in need, and thus develop enhanced skills in social interaction, teamwork and effectiveness. This paper explores a variety of models of university-community engagement that aim to achieve and model good practice in policy making and planning around healthcare education and service development. Ways of integrating teaching and learning with community engagement, so there is reciprocal learning with significant benefits to the community, students, the university and industry are described. The communities of engagement for a transdisciplinary approach in healthcare are defined and the types of collaborative partnerships are outlined, including public/private partnerships, service learning approaches and regional campus engagement. The processes for initiating innovation in this field, forging sustainable partnerships, providing cooperative leadership and building shared vision are detailed. Measuring shared and sustained benefits for all participants is examined in the context of effecting changes in working relationships as well as the impact on students in terms of increased personal and social responsibility, confidence and competence. For the health professions, it is considered vital to adopt this approach in order to deliver graduates who feel aware of community needs, believe they can make a difference, and have a greater sense of community responsibility, ethic of service and more sophisticated understandings of social contexts. In the longer term, it is proposed the strategy will deliver a future healthcare workforce that is more likely to have a strengthened sense of community, social and personal responsibility and thus effect positive social change

Algorithmic Fairness from a Non-ideal Perspective

Inspired by recent breakthroughs in predictive modeling, practitioners in both industry and government have turned to machine learning with hopes of operationalizing predictions to drive automated decisions. Unfortunately, many social desiderata concerning consequential decisions, such as justice or fairness, have no natural formulation within a purely predictive framework. In efforts to mitigate these problems, researchers have proposed a variety of metrics for quantifying deviations from various statistical parities that we might expect to observe in a fair world and offered a variety of algorithms in attempts to satisfy subsets of these parities or to trade o the degree to which they are satised against utility. In this paper, we connect this approach to fair machine learning to the literature on ideal and non-ideal methodological approaches in political philosophy. The ideal approach requires positing the principles according to which a just world would operate. In the most straightforward application of ideal theory, one supports a proposed policy by arguing that it closes a discrepancy between the real and the perfectly just world. However, by failing to account for the mechanisms by which our non-ideal world arose, the responsibilities of various decision-makers, and the impacts of proposed policies, naive applications of ideal thinking can lead to misguided interventions. In this paper, we demonstrate a connection between the fair machine learning literature and the ideal approach in political philosophy, and argue that the increasingly apparent shortcomings of proposed fair machine learning algorithms reflect broader troubles faced by the ideal approach. We conclude with a critical discussion of the harms of misguided solutions, a reinterpretation of impossibility results, and directions for future researc

A Tripartite Framework for Leadership Evaluation

The Tripartite Framework for Leadership Evaluation provides a comprehensive examination of the leadership evaluation landscape and makes key recommendations about how the field of leadership evaluation should proceed. The chief concern addressed by this working paper is the use of student outcome data as a measurement of leadership effectiveness. A second concern in our work with urban leaders is the absence or surface treatment of race and equity in nearly all evaluation instruments or processes. Finally, we call for an overhaul of the conventional cycle of inquiry, which is based largely on needs analysis and leader deficits, and incomplete use of evidence to support recurring short cycles within the larger yearly cycle of inquiry

Providing behaviour awareness in collaborative project courses

Several studies show that awareness mechanisms can contribute to enhance the collaboration process among students and the learning experiences during collaborative project courses. However, it is not clear what awareness information should be provided to whom, when it should be provided, and how to obtain and represent such information in an accurate and understandable way. Regardless the research efforts done in this area, the problem remains open. By recognizing the diversity of work scenarios (contexts) where the collaboration may occur, this research proposes a behaviour awareness mechanism to support collaborative work in undergraduate project courses. Based on the authors previous experiences and the literature in the area, the proposed mechanism considers personal and social awareness components, which represent metrics in a visual way, helping students realize their performance, and lecturers intervene when needed. The trustworthiness of the mechanisms for determining the metrics was verified using empirical data, and the usability and usefulness of these metrics were evaluated with undergraduate students. Experimental results show that this awareness mechanism is useful, understandable and representative of the observed scenarios.Peer ReviewedPostprint (published version

Providing behaviour awareness in collaborative project courses

Several studies show that awareness mechanisms can contribute to enhance the collaboration process among students and the learning experiences during collaborative project courses. However, it is not clear what awareness information should be provided to whom, when it should be provided, and how to obtain and represent such information in an accurate and understandable way. Regardless the research efforts done in this area, the problem remains open. By recognizing the diversity of work scenarios (contexts) where the collaboration may occur, this research proposes a behaviour awareness mechanism to support collaborative work in undergraduate project courses. Based on the authors previous experiences and the literature in the area, the proposed mechanism considers personal and social awareness components, which represent metrics in a visual way, helping students realize their performance, and lecturers intervene when needed. The trustworthiness of the mechanisms for determining the metrics was verified using empirical data, and the usability and usefulness of these metrics were evaluated with undergraduate students. Experimental results show that this awareness mechanism is useful, understandable and representative of the observed scenarios.Peer ReviewedPostprint (published version

Student Perceptions of Teacher-Student Relationships in General and Special Education

Teacher-student relationships (TSRs) have largely been found to significantly impact student performance and achievement (Roorda, Koomen, Spilt, & Oort, 2011). The purpose of this investigation was to identify differences between the TSRs experienced by students in special education (SPED) and their typically developing peers, and analyze how these differences impacted academics (i.e., math achievement). Secondary analysis of data from the Measures of Effective Teaching (MET) project indicated no statistical or practical differences between the TSRs reported by SPED students and their peers in general education. Furthermore, teacher caring was found to predict math achievement for non-SPED students. However, student-perceived TSRs were not found to be related to math achievement for SPED students. Implications of these findings are discussed. Keywords: teacher-student relationships, math, special educatio

Engaging Opportunities: Connecting young people with contemporary research and researchers

This is the final report for ‘Engaging Opportunities’, an RCUK-funded School-University Partnership between the Open University and the Denbigh Teaching School Alliance. Informed by action research, this four-year project was designed to create structured, strategic, sustainable and equitable mechanisms for effective school-university engagement with research. The report describes an evidence-based strategy designed to embed school-university engagement with research within the University’s strategic planning for research and the operational practices of researchers. Through the early stages of our partnership we noted a lack of suitable planning tools that work for researchers, teachers and students. We therefore introduced a flexible and adaptable framework of four types of activity—open lectures, open dialogues, open inquiry and open creativity—combined with an upstream approach to planning based on a set of six principles. A sub-set of these activities were evaluated through a combination of surveys, interviews and interventions. In conclusion, we argue that institutional and professional cultures can be resistant to the prospect of fully embedding school-university engagement with research in a structured, strategic and sustainable manner, and offer suggestions for how this context could and should be changed