scholarly journals CAUSAL INFERENCE ON EDUCATION POLICIES: A SURVEY OF EMPIRICAL STUDIES USING PISA, TIMSS AND PIRLS

2017 ◽  
Vol 32 (3) ◽  
pp. 878-915 ◽  
Author(s):  
José M. Cordero ◽  
Víctor Cristóbal ◽  
Daniel Santín
Keyword(s):  
Causal Inference ◽  
Empirical Studies ◽  
Education Policies

Analyzing Participant Behaviors in Design Crowdsourcing Contests Using Causal Inference on Field Data

2018 ◽  
Vol 140 (9) ◽  
Author(s):  
Ashish M. Chaudhari ◽  
Zhenghui Sha ◽  
Jitesh H. Panchal
Keyword(s):  
Causal Inference ◽  
Engineering Design ◽  
Field Data ◽  
Task Complexity ◽  
Empirical Studies ◽  
Concept Generation ◽  
Related Factors ◽  
Factors Affecting ◽  
Future Design ◽  
Game Theoretic

Crowdsourcing is the practice of getting ideas and solving problems using a large number of people on the Internet. It is gaining popularity for activities in the engineering design process ranging from concept generation to design evaluation. The outcomes of crowdsourcing contests depend on the decisions and actions of participants, which in turn depend on the nature of the problem and the contest. For effective use of crowdsourcing within engineering design, it is necessary to understand how the outcomes of crowdsourcing contests are affected by sponsor-related, contest-related, problem-related, and individual-related factors. To address this need, we employ existing game-theoretic models, empirical studies, and field data in a synergistic way using the theory of causal inference. The results suggest that participants' decisions to participate are negatively influenced by higher task complexity and lower reputation of sponsors. However, they are positively influenced by the number of prizes and higher allocation to prizes at higher levels. That is, an amount of money on any following prize generates higher participation than the same amount of money on the first prize. The contributions of the paper are: (a) a causal graph that encodes relationships among factors affecting crowdsourcing contests, derived from game-theoretic models and empirical studies, and (b) a quantification of the causal effects of these factors on the outcomes of GrabCAD, Cambridge, MA contests. The implications of these results on the design of future design crowdsourcing contests are discussed.

Assessment for Monitoring of Education Systems: International Comparisons

2019 ◽  
Vol 683 (1) ◽  
pp. 75-92 ◽  
Author(s):  
Henry I. Braun ◽  
Judith D. Singer
Keyword(s):  
Education Policy ◽  
Causal Inference ◽  
Instrument Development ◽  
Global Education ◽  
Large Scale ◽  
International Comparisons ◽  
Education Policies ◽  
Country Rankings ◽  
History Of ◽  
Comparative Description

Over the last two decades, with the increase in both numbers of participating jurisdictions and media attention, international large-scale assessments (ILSAs) have come to play a more salient role in global education policies than they once did. This has led to calls for greater transparency with regard to instrument development and closer scrutiny of the use of instruments in education policy. We begin with a brief review of the history of ILSAs and describe the requirements and constraints that shape ILSA design, implementation, and analysis. We then evaluate the rationales of employing ILSA results for different purposes, ranging from those we argue are most appropriate (comparative description) to least appropriate (causal inference). We cite examples of ILSA usage from different countries, with particular attention to the widespread misinterpretations and misuses of country rankings based on average scores on an assessment (e.g., literacy or numeracy). Looking forward, we offer suggestions on how to enhance the constructive roles that ILSAs play in informing education policy.

scholarly journals Políticas públicas de educação do campo: Revisão sistemática das publicações brasileiras

2019 ◽  
Vol 27 ◽  
pp. 81
Author(s):  
Giuliano Alves Borges e Silva ◽  
Fernanda De Souza Gusmão Louredo ◽  
Frederico José Lustosa Da Costa
Keyword(s):  
Systematic Review ◽  
Public Policy ◽  
Rural Education ◽  
Empirical Studies ◽  
Descriptive Analysis ◽  
Scientific Progress ◽  
Strong Tendency ◽  
Education Policies ◽  
Thematic Framework

This research investigates the contemporary publications about rural education policies. The paper intends to verify both, the scientific progress and the subjects addressed in Brazilian journals. A systematic review was used in the “Periódicos Capes” database through the descriptors “rural education” and “public policy”, date “2009/2017”. The criteria for inclusions in the analysis were a clearly defined methodology and the possibility of setting a thematic framework. Ninety-three papers were analyzed, with 52 selected for general descriptive analysis, and 10 selected for in-depth discussion. Qualitative empirical studies predominated, and the main thematic trend was “regional trajectory” (31%). Consequently, a strong tendency was demonstrated throughout the publications: contemporary phenomena observed from the perspective of the country’s citizens. 

scholarly journals Outcome-Wide Longitudinal Designs for Causal Inference: A New Template for Empirical Studies

2020 ◽  
Vol 35 (3) ◽  
pp. 437-466 ◽  
Author(s):  
Tyler J. VanderWeele ◽  
Maya B. Mathur ◽  
Ying Chen
Keyword(s):  
Causal Inference ◽  
Empirical Studies

scholarly journals Evidence synthesis for constructing directed acyclic graphs (ESC-DAGs): a novel and systematic method for building directed acyclic graphs

2019 ◽  
Vol 49 (1) ◽  
pp. 322-329 ◽  
Author(s):  
Karl D Ferguson ◽  
Mark McCann ◽  
Srinivasa Vittal Katikireddi ◽  
Hilary Thomson ◽  
Michael J Green ◽  
...  
Keyword(s):  
Causal Inference ◽  
Modular Design ◽  
Evidence Synthesis ◽  
Empirical Studies ◽  
Directed Acyclic Graphs ◽  
Primary Data ◽  
Acyclic Graphs ◽  
Primary Data Analysis ◽  
Limited Experience ◽  
Direct Primary

Abstract Background Directed acyclic graphs (DAGs) are popular tools for identifying appropriate adjustment strategies for epidemiological analysis. However, a lack of direction on how to build them is problematic. As a solution, we propose using a combination of evidence synthesis strategies and causal inference principles to integrate the DAG-building exercise within the review stages of research projects. We demonstrate this idea by introducing a novel protocol: ‘Evidence Synthesis for Constructing Directed Acyclic Graphs’ (ESC-DAGs)’. Methods ESC-DAGs operates on empirical studies identified by a literature search, ideally a novel systematic review or review of systematic reviews. It involves three key stages: (i) the conclusions of each study are ‘mapped’ into a DAG; (ii) the causal structures in these DAGs are systematically assessed using several causal inference principles and are corrected accordingly; (iii) the resulting DAGs are then synthesised into one or more ‘integrated DAGs’. This demonstration article didactically applies ESC-DAGs to the literature on parental influences on offspring alcohol use during adolescence. Conclusions ESC-DAGs is a practical, systematic and transparent approach for developing DAGs from background knowledge. These DAGs can then direct primary data analysis and DAG-based sensitivity analysis. ESC-DAGs has a modular design to allow researchers who are experienced DAG users to both use and improve upon the approach. It is also accessible to researchers with limited experience of DAGs or evidence synthesis.

scholarly journals University Teacher Educators’ Professional Agency: A Literature Review

2020 ◽  
Vol 10 (2) ◽  
Author(s):  
Yenny Hinostroza
Keyword(s):  
Professional Development ◽  
Thematic Analysis ◽  
Research Agenda ◽  
Teacher Educators ◽  
Empirical Studies ◽  
Future Research ◽  
Inclusion Criteria ◽  
Education Policies ◽  
Future Research Agenda ◽  
Axial Coding

This paper presents a scoping review and thematic analysis of literature on university teacher educators’ professional agency between 2007 and 2019. Its aim is to map empirical studies to date and identify gaps in research to inform a future research agenda. 28 articles that met the inclusion criteria were subjected to thematic analysis, using line-by-line open and axial coding. Four main interrelated themes were identified: (i) education policies, (ii) professional development, (iii) identity, and (iv) social justice. This thematic intersection reflects intricated factors promoting and hindering the achievement of teacher educators’ professional agency. Findings suggest that more research is needed to develop theoretical and empirical understandings of the multidimensional character of their professional agency, and the myriad of opportunities and constraints impacting on it.

scholarly journals A note on co-occurrence, transitional probability, and causal inference

2020 ◽  
Author(s):  
Jeroen van Paridon ◽  
Phillip M. Alday
Keyword(s):  
Causal Inference ◽  
Language Processing ◽  
Empirical Studies ◽  
Transitional Probability ◽  
Causal Inferences ◽  
Information Theoretic ◽  
Current State ◽  
Information Theoretic Measures ◽  
Transitional Probabilities

Much has been written about the role of prediction in cognition in general, and language processing in particular, with some authors even claiming that prediction is the central goal of cognition. Attributing such a specific goal to cognition seems speculative, but prediction is generally held to play an important role in both perception and action. In empirical studies of language processing, however, measures of predictability such as forward transitional probability (or surprisal) are often no more effective in describing behavioral and neural phenomena than measures of post- or retrodictability such as backward transitional probability. We address this paradox by looking at the relationship between these different information theoretic measures and proposing a mechanistic account of how they are used in cognition. We posit that backward transitional probabilities support causal inferences about the occurrence of word sequences. Using Bayes' Theorem, we demonstrate that predictions (formalized as forward transitional probabilities) can be used in conjunction with the marginal probabilities of the current state/word and the upcoming state/word to compute these causal inferences. This conceptualization of causal inference in language processing both accounts for the role of prediction, and the surprising effectiveness of backwards transitional probability as a predictor of human behavior and its neural correlates.

Beyond metaphors and semantics: A framework for causal inference in neuroscience

2019 ◽  
Vol 42 ◽  
Author(s):  
Roberto A. Gulli
Keyword(s):  
Causal Inference ◽  
Causal Power

Abstract The long-enduring coding metaphor is deemed problematic because it imbues correlational evidence with causal power. In neuroscience, most research is correlational or conditionally correlational; this research, in aggregate, informs causal inference. Rather than prescribing semantics used in correlational studies, it would be useful for neuroscientists to focus on a constructive syntax to guide principled causal inference.

An empirical review of gambling expansion and gambling-related harm

2018 ◽  
Vol 64 (5-6) ◽  
pp. 295-306 ◽  
Author(s):  
Debi A. LaPlante ◽  
Heather M. Gray ◽  
Pat M. Williams ◽  
Sarah E. Nelson
Keyword(s):  
Literature Review ◽  
Peer Review ◽  
Empirical Data ◽  
Empirical Studies ◽  
Expansion Method ◽  
Responsible Gambling ◽  
Review Literature ◽  
Evidence Based ◽  
Empirical Comparison ◽  
Related Harm

Abstract. Aims: To discuss and review the latest research related to gambling expansion. Method: We completed a literature review and empirical comparison of peer reviewed findings related to gambling expansion and subsequent gambling-related changes among the population. Results: Although gambling expansion is associated with changes in gambling and gambling-related problems, empirical studies suggest that these effects are mixed and the available literature is limited. For example, the peer review literature suggests that most post-expansion gambling outcomes (i. e., 22 of 34 possible expansion outcomes; 64.7 %) indicate no observable change or a decrease in gambling outcomes, and a minority (i. e., 12 of 34 possible expansion outcomes; 35.3 %) indicate an increase in gambling outcomes. Conclusions: Empirical data related to gambling expansion suggests that its effects are more complex than frequently considered; however, evidence-based intervention might help prepare jurisdictions to deal with potential consequences. Jurisdictions can develop and evaluate responsible gambling programs to try to mitigate the impacts of expanded gambling.

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