Supporting Use of Data and Evidence from Early Warning Indicator Systems in Research–Practice Partnerships

2020 ◽  
Vol 122 (14) ◽  
pp. 1-24
Author(s):  
William R. Penuel ◽  
Caitlin C. Farrell ◽  
Julia Daniel
Keyword(s):  
Decision Making ◽  
Early Warning ◽  
Research Practice ◽  
Evidence Use ◽  
Research On Research ◽  
Early Warning Indicator ◽  
Use Of Data ◽  
Implementation Studies ◽  
Decision Making Processes ◽  
Indicator Systems

Background/Context Research on data and evidence use suggest that productive use depends on interactive processes, including sustained interactions between educators and researchers. Recent research on research-practice partnerships (RPPs) has examined conditions under which these sustained collaborations support evidence use. Findings from these studies can inform research on early warning indicators, helping interpret implementation studies of productive use and creating conditions for use of data from early warning indicator systems. Purpose This chapter presents results of a review of studies of data and evidence use within RPPs. It investigates the claim that RPPs can support productive data and evidence use only under certain conditions, conditions that are relevant to studying and supporting the implementation of early warning indicator systems in education. Research Design The synthesis focused on identifying studies published between 2013 and 2019 as journal articles, book chapters, and technical reports that focused on data and evidence use in RPPs. To be included, studies had to be empirical and related to the focal topics. A total of 114 studies met criteria for inclusion. For all studies, members of the research team developed summaries, which the team then discussed. Themes emerged from summaries, grouped by RPP, and from team discussions. Findings The review found six supportive conditions were needed for productive use of data and evidence to guide decision-making and action. These were (1) valuation of knowledge, experience, and perspectives of partners; (2) processes for identifying sources of evidence needed to answer questions that are priorities for educators and community partners; (3) complementarity of knowledge of partners; (4) adoption of a learning perspective on systems change; (5) routines for sensemaking and collaboration; (5) synchrony with decision-making processes; and (6) a commitment to developing and using evidence among partner organizations. Conclusions Developers of early warning indicator systems should consider ways an RPP can support the creation of conditions for productive use of data from systems. Effective systems likely will depend on making room for educator voice and valuing of practitioner perspectives at all stages of design and implementation of systems. They will also require allocation of time and skill for structuring opportunities to make sense of data and developing a culture where evidence plays an important role in decision-making.

Evidence-Based Practice: An Alternative to Authority-Based Practice (Revisiting Our Heritage)

2018 ◽  
Vol 99 (3) ◽  
pp. 283-294
Author(s):  
Eileen Gambrill
Keyword(s):  
Decision Making ◽  
Social Work ◽  
Critical Appraisal ◽  
Evidence Based Practice ◽  
Evidence Based ◽  
Research Practice ◽  
Vital Part ◽  
Notable Feature ◽  
Decision Making Processes

Editor’s note: This article is reprinted from Volume 80-4 (1999) as part of the Revisiting Our Heritage series. Nearly 20 years ago, one of the earliest articles to appear in a social work journal on evidence-based practice (EBP) was presented by Eileen Gambrill. While many are familiar with Gambrill’s contributions as a pioneer of the EBP movement in social work, it is worth noting her emphasis on client voice as a vital part of EBP in advancing the field’s efficacy: “Evidence-based practice requires an atmosphere in which critical appraisal of practice-related claims flourishes, and clients are involved as informed participants. A notable feature of EBP is attention to clients’ values and expectations. Clients are involved as active participants in the decision-making processes.” As you reflect on two decades of EBP influence in research, practice, and policy, consider how successful (or not) social work has progressed in keeping the foundation of client self-determinism strong and relevant.

Characterizing Global Activity Schedule Adjustment Behavior by Using a Sequence Alignment Method

2005 ◽  
Vol 1926 (1) ◽  
pp. 26-32 ◽  
Author(s):  
Chang-Hyeon Joh ◽  
John W. Polak ◽  
Tomás Ruiz
Keyword(s):  
Decision Making ◽  
Sequence Alignment ◽  
Future Research ◽  
Alignment Method ◽  
Use Of Data ◽  
Factors Influencing ◽  
Activity Schedule ◽  
Decision Making Processes ◽  
Schedule Modification ◽  
Global Activity

Considerable interest has developed recently in the decision-making processes underlying activity schedule adjustment. This paper suggests a method, based on sequence alignment techniques, to measure schedule adjustment behavior and applies the method to develop a model of the factors influencing schedule adjustment, with the use of data from a recent Internet-administered survey. The results indicate that the amount of schedule modification that occurs is largely determined by characteristics of the planned schedule instead of background socioeconomic or activity-related variables. The implications of this finding for future research in this area are considered.

Early Warning Indicator Systems in Action: Considerations from Identification to Supports

2020 ◽  
Vol 122 (14) ◽  
pp. 1-24
Author(s):  
Hadar Baharav ◽  
Laurel Sipes
Keyword(s):  
Information Sharing ◽  
Early Warning ◽  
System Level ◽  
School Staff ◽  
Future Research ◽  
Academic Challenges ◽  
Early Warning Indicator ◽  
Student Supports ◽  
Indicator Systems ◽  
Share Information

Background/Context School transitions pose a variety of social-emotional and academic challenges to students, especially those who are more vulnerable due to home, health, or academic challenges. With this awareness, a growing number of school districts have developed and implemented early warning indicator systems (EWISs) aimed at early identification of and support to vulnerable students. Purpose/Objective/Research Question/Focus of Study While a growing body of research has documented EWISs use objective criteria to identify vulnerable students, there is scant scholarship about student identification using subjective tools, the processes that facilitate information sharing and collaboration between sending and receiving schools, and effective student supports. Our study aimed to narrow the gaps in the literature by providing insight about EWI identification, between-school communication, and student supports through the case study of one school district that implemented both objective and subjective EWISs. Our research questions were as follows: (1) Which students have been identified through the district's objective and subjective EWISs?; (2) How have school staff shared information stemming from the EWISs?; and (3) What supports do school staff offer students identified by the objective compared to the subjective EWISs? Research Design We used a mixed-methods approach, including statistical analysis of student-level administrative records, interviews with district staff, a survey of school staff, and multiple interviews with site staff at a sampling of schools. Conclusions/Recommendations: Identification Our study found that subjective criteria may be more effective in identifying students who are more likely to be missed by automated identification systems, such as “internalizers.” Moreover, stakeholder perception of specific indicators may have an impact on the selection of indicators in use. Sharing of information The practices that schools use to share information about transitioning students is an area ripe for future research. Our study revealed the importance of designing information-sharing mechanisms with the end user in mind. Developing a standardized rubric and incorporating a scale measure for relative urgency could increase the effectiveness and efficiency of the process. We also identified a tension between the need to share information and the will to protect students’ privacy. We see value in localized efforts to mitigate the unintended effects of such tension. Supports A primary consideration in an EWIS is its alignment to the district's model for the distribution of resources to support students. EWIS design considerations We identified the existence of tradeoffs between site-level autonomy and system-level coherence in the design of EWISs.

Big Data and Web Intelligence

Big Data ◽  
2016 ◽  
pp. 229-246 ◽  
Author(s):  
Alberto Pliego ◽  
Fausto Pedro García Márquez
Keyword(s):  
Decision Making ◽  
Decision Trees ◽  
Computational Cost ◽  
New Approach ◽  
Computational Costs ◽  
Use Of Data ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Unique Factor ◽  
Complex Decision

The growing amount of available data generates complex problems when they need to be treated. Usually these data come from different sources and inform about different issues, however, in many occasions these data can be interrelated in order to gather strategic information that is useful for Decision Making processes in multitude of business. For a qualitatively and quantitatively analysis of a complex Decision Making process is critical to employ a correct method due to the large number of operations required. With this purpose, this chapter presents an approach employing Binary Decision Diagram applied to the Logical Decision Tree. It allows addressing a Main Problem by establishing different causes, called Basic Causes and their interrelations. The cases that have a large number of Basic Causes generate important computational costs because it is a NP-hard type problem. Moreover, this chapter presents a new approach in order to analyze big Logical Decision Trees. However, the size of the Logical Decision Trees is not the unique factor that affects to the computational cost but the procedure of resolution can widely vary this cost (ordination of Basic Causes, number of AND/OR gates, etc.) A new approach to reduce the complexity of the problem is hereby presented. It makes use of data derived from simpler problems that requires less computational costs for obtaining a good solution. An exact solution is not provided by this method but the approximations achieved have a low deviation from the exact.

Big Data and Web Intelligence

2015 ◽  
pp. 190-207 ◽  
Author(s):  
Alberto Pliego ◽  
Fausto Pedro García Márquez
Keyword(s):  
Decision Making ◽  
Decision Trees ◽  
Computational Cost ◽  
New Approach ◽  
Computational Costs ◽  
Use Of Data ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Unique Factor ◽  
Complex Decision

The growing amount of available data generates complex problems when they need to be treated. Usually these data come from different sources and inform about different issues, however, in many occasions these data can be interrelated in order to gather strategic information that is useful for Decision Making processes in multitude of business. For a qualitatively and quantitatively analysis of a complex Decision Making process is critical to employ a correct method due to the large number of operations required. With this purpose, this chapter presents an approach employing Binary Decision Diagram applied to the Logical Decision Tree. It allows addressing a Main Problem by establishing different causes, called Basic Causes and their interrelations. The cases that have a large number of Basic Causes generate important computational costs because it is a NP-hard type problem. Moreover, this chapter presents a new approach in order to analyze big Logical Decision Trees. However, the size of the Logical Decision Trees is not the unique factor that affects to the computational cost but the procedure of resolution can widely vary this cost (ordination of Basic Causes, number of AND/OR gates, etc.) A new approach to reduce the complexity of the problem is hereby presented. It makes use of data derived from simpler problems that requires less computational costs for obtaining a good solution. An exact solution is not provided by this method but the approximations achieved have a low deviation from the exact.

scholarly journals Complex Partnerships: Self-authorship and Provocative Academic-Advising Practices

2006 ◽  
Vol 26 (1) ◽  
pp. 32-45 ◽  
Author(s):  
Jane E. Pizzolato
Keyword(s):  
Decision Making ◽  
Academic Advising ◽  
Research Practice ◽  
Academic Majors ◽  
Learning Partnerships ◽  
Decision Making Processes ◽  
Nonacademic Factors ◽  
Theory Research ◽  
Self Authorship ◽  
Selection Of

Self-authorship is an additional orientation to traditional college student, epistemological, development theories. Facilitation of self-authorship, via academic advising, may help students meet the desired outcomes outlined by the Council for the Advancement of Standards in Higher Education and integrate these abilities into their knowing and decision-making processes. Through investigation of 132 student narratives about advising and selection of academic majors, I examined advising practices that are consistent with Baxter Magolda's (2001) learning partnerships model for self-authorship development. Findings suggest that student decision-making and self-authoring abilities were enhanced by advising sessions that focused explicitly on goal reflection and associated volitional planning. Students benefited from advising in which nonacademic factors were addressed. Implications for practice are discussed. Relative emphasis: * theory, research, practice

scholarly journals Determinants of Evidence Use in Academic Librarian Decision Making

2015 ◽  
Vol 76 (1) ◽  
pp. 100-114 ◽  
Author(s):  
Denise Koufogiannakis
Keyword(s):  
Decision Making ◽  
Qualitative Study ◽  
Academic Libraries ◽  
Organizational Factors ◽  
Academic Librarians ◽  
Evidence Use ◽  
Complex Processes ◽  
Academic Librarian ◽  
Decision Making Processes ◽  
Main Determinants

The objective of this qualitative study was to identify and explain challenges encountered by academic librarians when trying to incorporate evidence into their practice. The findings resulted in the identification of five main determinants that act as either obstacles or enablers of evidence use. The identification of these determinants provide librarians with a greater understanding of the complex processes and individual as well as organizational factors that impact decision-making processes within academic libraries.

Trust, Organizational Decision-Making, and Data Analytics

2020 ◽  
Vol 11 (1) ◽  
pp. 22-37
Author(s):  
Joseph E. Kasten
Keyword(s):  
Decision Making ◽  
Data Analytics ◽  
Decision Makers ◽  
Organizational Decision Making ◽  
Organizational Benefits ◽  
Use Of Data ◽  
Information Products ◽  
Decision Making Processes ◽  
Almost All ◽  
Broad Understanding

The use of data analytics of all kinds is making inroads into almost all industries. There are many studies that explore the usefulness and organizational benefits of these tools. However, there has been relatively little attention paid to the other issues that accompany the implementation of these tools, namely the level of trust felt by the consumers of the information products of these tools and the changes in decision-making caused by the introduction of data analytics. It is important that the level of trust these decision-makers have in their analytics tools be understood as that will have great impact on how these tools will be used and how the firm will use them to build value. This study examines the level of trust organizations have in their analytics tools and how these tools have changed their decision-making processes. This study will add to the broad understanding of how and where data analytics tools fit into the data-driven organization.

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