Chaos theory, informational needs, and natural disasters

This study applies chaos theory to a system-wide analysis of crisis communication in a natural disaster. Specifically, we analyze crisis communication during the 1997 Red River Valley flood in Minnesota and North Dakota. This flood, among the worst in modern American history, consumed entire metropolitan areas, displacing thousands of people. The conditions and decisions leading to the disaster, and the subsequent reactions are retraced. Communication related to river crest predictions (fractals), the shock at the magnitude of the crisis (cosmology episode), novel forms of reorganizing (self-organization), and agencies that aided in establishing a renewed order (strange attractors) are evaluated. Ultimately, we argue that preexisting sensemaking structures favoring rationalized, traditional views of a complex system led officials to make inappropriately unequivocal predictions and ultimately diminished the effectiveness of the region's crisis communication and planning.     

Bakhtin Applied: Employing Dialogism to Analyze the Interplay of the Ideologies of Individualism and Community Within the Discourse of Alcoholics Anonymous

An ongoing debate regarding the nature of therapeutic communities concerns the extent to which these communities reinforce the ideologies of individualism and community. This article engages this discussion through a process of social text analysis informed by the dialogism theory of Russian philosopher and literary scholar Mikhail Bakhtin. Dialogism seeks to understand the multiple voices interpenetrating particular utterances, revealing an emergent social construction of meaning. Applying this approach to examples of discourse from a prominent therapeutic community, Alcoholics Anonymous, illustrates how meaning in the discourse of this movement can be understood to emerge among the interplay between the ideologies of individualism and community as expressed within the movement's narrative practice.     

A theory of instruction for introductory programming skills

ABSTRACT

Background and Context: Current introductory instruction fails to identify, structure, and sequence the many skills involved in programming.

Objective: We proposed a theory which identifies four distinct skills that novices learn incrementally. These skills are tracing, writing syntax, comprehending templates (reusable abstractions of programming knowledge), and writing code with templates. We theorized that explicit instruction of these skills decreases cognitive demand.

Method: We conducted an exploratory mixed-methods study and compared students’ exercise completion rates, error rates, ability to explain code, and engagement when learning to program. We compared material that reflects this theory to more traditional material that does not distinguish between skills.

Findings: Teaching skills incrementally resulted in improved completion rate on practice exercises, and decreased error rate and improved understanding of the post-test.

Implications: By structuring programming skills such that they can be taught explicitly and incrementally, we can inform instructional design and improve future research on understanding how novice programmers develop understanding.     

Building Women’s Innovation Capacities Through Undergraduate Experiences

Research in Higher Education - This study examines how collegiate climates and practices can promote innovation capacities among an international longitudinal sample of undergraduate women. Using a...     

The effects of informational complexity and working memory on problem-solving efficiency

This study investigated the influence of informational complexity and working memory capacity on problem-solving efficiency. We examined two predictions of thesituational efficiency hypothesis, which states that the efficiency of problem solving varies as a function of situational constraints. One prediction is that informational complexity affects problem-solving efficiency. A second prediction is that working memory capacity affects problem-solving efficiency. Students completed a working memory task and solved abstract and concrete syllogisms. Participants solved abstract syllogisms more accurately than concrete syllogisms and spent more time solving abstract syllogisms. Thus participants demonstrated greater problem-solving efficiency when solving concrete syllogisms. Results indicate that there is a trade-off between problem-solving accuracy and problem-solving time when information differs with respect to informational complexity, a phenomenon we refer to as theefficiency paradox. Working memory capacity did not affect accuracy or efficiency. The results support the conclusion that problem-solving efficiency is situational and a function of the complexity of information. Educational implications and directions for future research are suggested.     

Changing the English Classroom: When Large-scale ‘Common’ Testing Meets Secondary Curriculum and Instruction in the United States

This article explores the intersection of new, large-scale standards-based testing, teacher accountability policy, and secondary curriculum and instruction in the United States. Two federally funded consortia – the Smarter Balanced Assessment Consortium and the Partnership for Readiness of College and Careers – prove focal to this paper, as these two organisations are creating new tests that will assess 42–49% of the K–12 student population in the United States in 2014–2015. Because greater teacher accountability for student performance will be given for these tests, there is more reason to pay attention to what these tests measure and what they do not. Our analysis suggests that these new tests will hold secondary English teachers accountable for literacy and disciplinary knowledge outside the field of English and thus raise important questions about what English teachers should, can and will do, especially when their jobs are on the line.     

Risk attitude assessment using roulette and a supply chain simulation

Many topics that are taught in supply chain management (SCM) programs include elements of variability and risk. With quantitative tools in particular, it is assumed that the decision makers using the tools are risk neutral, which is typically not the case in real-life decision situations. The topic of an individual's attitude toward risk has received limited attention in SCM literature and is not a high-profile topic in SCM textbooks. The teaching exercise presented in this paper uses two games—roulette and a SCM simulation—to provide students with an assessment of their own attitude toward risk, and in doing so, facilitates a classroom discussion of risk and risk attitude. These games were developed by the authors and can be played either within Excel or a web application.     

Going Deep into Mechanisms for Moral Reasoning Growth: How Deep Learning Approaches Affect Moral Reasoning Development for First-year Students

The purpose of this paper was to determine the effects of deep approaches to learning on the moral reasoning development of 1,457 first-year students across 19 institutions. Results showed a modest positive relationship between our measures of deep approaches to learning and moral reasoning at the end of the first year of college even after controlling for precollege moral reasoning. After accounting for a host of demographic and relevant student characteristics and for the natural clustering of students, we found that the integrative learning subscale, which captures students’ participation in activities designed to integrate information from varied sources and diverse perspectives, positively affected moral reasoning among first-year students. Implications for researchers and practitioners are discussed.