Matching Items (7)

From Narratives to Algorithms: Extending Archaeological Explanation beyond Archaeology

Description

The static, fragmentary archaeological record requires us to construct models of the human past. Traditionally, these have been narratives that make compelling stories but are difficult to evaluate. Recent advances

The static, fragmentary archaeological record requires us to construct models of the human past. Traditionally, these have been narratives that make compelling stories but are difficult to evaluate. Recent advances in geospatial and agent-based modeling technology offers the potential to create quantitative models of human systems, but also challenge us to conceive of human societies in ways that can be expressed in algorithmic form. Besides making our own explanations more robust, integrating such quantitative modeling into archaeological practice can produce more useful accounts of human systems and their long-term dynamics for other disciplines and policy makers.|abstract

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Created

Date Created
  • 2009

Lifecycle Assessment for a Devoted Religious Adherent

Description

While the scientific study of religion is not new, the topic has yet to be approached by Lifecycle Assessment (LCA). This work demonstrates a method for assessing the personal “cost”

While the scientific study of religion is not new, the topic has yet to be approached by Lifecycle Assessment (LCA). This work demonstrates a method for assessing the personal “cost” of “manufacturing” a mature religious adherent, or, a believer committed to a particular faith. By measuring such inputs as personal importance of faith, prayer, religious service attendance, religious experiences, and scripture reading, an assessment can be made of the quantity of such inputs required to engender enduring religious devotion. Ultimately, this study has demonstrated that the data typically collected in longitudinal surveys are insufficient to adequately support any firm quantitative conclusions, but the method proposed is sound and can be exploited when data becomes available.

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Created

Date Created
  • 2012-05

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Time metric in latent difference score models

Description

Time metric is an important consideration for all longitudinal models because it can influence the interpretation of estimates, parameter estimate accuracy, and model convergence in longitudinal models with latent variables.

Time metric is an important consideration for all longitudinal models because it can influence the interpretation of estimates, parameter estimate accuracy, and model convergence in longitudinal models with latent variables. Currently, the literature on latent difference score (LDS) models does not discuss the importance of time metric. Furthermore, there is little research using simulations to investigate LDS models. This study examined the influence of time metric on model estimation, interpretation, parameter estimate accuracy, and convergence in LDS models using empirical simulations. Results indicated that for a time structure with a true time metric where participants had different starting points and unequally spaced intervals, LDS models fit with a restructured and less informative time metric resulted in biased parameter estimates. However, models examined using the true time metric were less likely to converge than models using the restructured time metric, likely due to missing data. Where participants had different starting points but equally spaced intervals, LDS models fit with a restructured time metric resulted in biased estimates of intercept means, but all other parameter estimates were unbiased, and models examined using the true time metric had less convergence than the restructured time metric as well due to missing data. The findings of this study support prior research on time metric in longitudinal models, and further research should examine these findings under alternative conditions. The importance of these findings for substantive researchers is discussed.

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Date Created
  • 2016

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New directions in quantitative Hispanic sociolinguistics

Description

The present thesis explores how statistical methods are conceptualized, used, and interpreted in quantitative Hispanic sociolinguistics in light of the group of statistical methods espoused by Kline (2013) and named

The present thesis explores how statistical methods are conceptualized, used, and interpreted in quantitative Hispanic sociolinguistics in light of the group of statistical methods espoused by Kline (2013) and named by Cumming (2012) as the “new statistics.” The new statistics, as a conceptual framework, repudiates null hypothesis statistical testing (NHST) and replaces it with the ESCI method, or Effect Sizes and Confidence Intervals, as well as meta-analytic thinking. In this thesis, a descriptive review of 44 studies found in three academic journals over the last decade (2005 – 2015), NHST was found to have a tight grip on most researchers. NHST, much discredited outside of linguistics, confused authors who conflated the theories of Fisher and Neyman-Pearson, who themselves battled acrimoniously until the end of their publishing lives. Within the studies reviewed, with exceptions, dichotomous thinking ruled the quantitative approach, and binary reporting ruled the results and discussions. In addition, this thesis revealed that sociolinguistics, at least within the studies reviewed, is not exactly a “statistical monoculture” as suspected by Gorman and Johnson (2013), rather ANOVAs have joined Goldvarb’s logistic regression in its dominance. As described insightfully by Plonsky (2015), these two methods are exposed as extensions of the dichotomous thinking that attaches itself to NHST. Further, little evidence was found that the methods of the new statistics were being implemented in a coordinated fashion, including far too few meta-analyses. As such, quantitative Hispanic sociolinguistics, and linguistics in general, were shown to be vulnerable to problems with reliable quantitative theory building.

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Created

Date Created
  • 2015

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Data analysis discussions: from hesitancy to thirst

Description

A core reform area of President Obama’s Race to the Top (RTT) framework, the Statewide Longitudinal Data Systems (SLDS) program, offered funding to states for the development of their own

A core reform area of President Obama’s Race to the Top (RTT) framework, the Statewide Longitudinal Data Systems (SLDS) program, offered funding to states for the development of their own data systems. As a result, Arizona received funding to build a longitudinal student data system. However the targeted audience—teachers—needed training to move from a state of ‘data rich but information poor’ to one of developing actionable knowledge.

In this mixed methods action research study, six teachers from three schools participated in job-embedded data-informed decision making (DIDM) and root cause analysis (RCA) professional development to improve their abilities to employ DIDM and RCA strategies to determine root causes for student achievement gaps. This study was based on the theories of situated learning, specifically the concept of communities of practice (CoP), change theory, and the Concerns-Based Adoption Model (CBAM). Because teachers comprise most of the workforce in a district, it is important to encourage them to shift from working in isolation to effectively implement and sustain changes in practice. To address this concern, an online wiki provided an avenue for participants to interact, reflect, and share experiences across schools as they engaged in the application of new learning.

The results from this ten-week study indicated an increase in participant readiness levels to: (a) use and manage data sources, (b) apply strategies, and (c) collaborate with others to solve problems of practice. Results also showed that participants engaged in collaborative conversation using the online wiki when they wanted to share concerns or gain further information to make decisions. The online collaboration results indicated higher levels of online discussion occurred when participants were attempting to solve a problem of practice during the learning process.

Overall, participants (a) used collaborative strategies to seek, create, and/or utilize multiple sources of data, not just student learning data, (b) worked through implementation challenges when making changes in practice, and (c) sought further types of data collection to inform their decisions about root causes. Implications from this study warrant further investigation into the use of an online CoP as an avenue for increasing teacher collaboration across schools.

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Created

Date Created
  • 2016

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An evaluation of discussion board instructions in online courses

Description

The discussion board is a facet of online education that continues to confound students, educators, and researchers alike. Currently, the majority of research insists that instructors should structure and control

The discussion board is a facet of online education that continues to confound students, educators, and researchers alike. Currently, the majority of research insists that instructors should structure and control online discussions as well as evaluate such discussions. However, the existing literature has yet to compare the various strategies that instructors have identified and employed to facilitate discussion board participation. How should instructors communicate their expectations online? Should instructors create detailed instructions that outline and model exactly how students should participate, or should generalized instructions be communicated? An experiment was conducted in an online course for undergraduate students at Arizona State University. Three variations of instructional conditions were developed for use in the experiment: (1) detailed, (2) general, and (3) limited. The results of the experiment indentified a pedagogically valuable finding that should positively influence the design of future online courses that utilize discussion boards.

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Created

Date Created
  • 2012