Multiplatform software tool to disaggregate and adjust value-added learning scores

In 2016, Walstad and Wagner released an article that suggested practitioners should disaggregate value-added learning scores into four categories: positive, negative, retained, and zero learning. Positive learning is said to occur when a student answers a question incorrectly on the pre-test and correctly on the post-test. Negative learning is said to occur when the student correctly answers the question on the pre-test but incorrectly on the post-test. Retained learning is said to occur when the student answers the question correctly on both exams and zero learning is said to occur when the student answers the question incorrectly on both exams. Smith and Wagner (2017) improved on this work by adjusting the learning categories for guessing

Giving away the store: How the zero price constraint results in fewer add-on features

This paper discusses an issue impacting intellectual property products with nearly zero marginal cost: the zero price constraint. As established in the literature, aftermarkets result in a subsidization of the primary market, sometimes resulting in prices below marginal cost. While aftermarket add-ons are now common in intellectual property products such as software, the firms usually can\u27t charge a primary market price below zero. This paper shows that with the zero price constraint in effect, firms give more of the overall product away for free and pricing in the aftermarket is determined by the number of competitors in the primary market; despite assuming all consumers are initially unaware of the aftermarket\u27s existence. With the constraint in effect, consumers are better off and firms can potentially earn less profit

Strategies to Strengthen Youth Leadership and Youth Participation Opportunities in Central Appalachia

The purpose of this study was to assess opportunities for strengthening youth leadership and participation in the Central Appalachian region. In particular, authors Rebecca O’Doherty, Ada Smith, Ben Spangler, Elandria Williams, and Katie Richards-Schuster sought to understand and document the range of activities and strategies in the region as well as understand the nuances involved in promoting and sustaining youth leadership opportunities. Through interviews with key leaders in the region, they explored critical themes for strengthening youth leadership. To highlight the potential and opportunities for future development, they share a case study of an innovative approach to nurturing and sustaining youth leadership. They conclude with a set of recommendations for consideration by policy makers and stakeholders interested in developing sustainable youth leadership practices in Central Appalachia

Adjusting for guessing and applying a statistical test to the disaggregation of value-added learning scores

In 2016, Walstad and Wagner developed a procedure to split pre-test and post-test responses into four learning types: positive, negative, retained, and zero learning. This disaggregation is not only useful in academic studies; but also provides valuable insight to the practitioner: an instructor would take different mitigating actions in response to zero versus negative learning. However, the original disaggregation is sensitive to student guessing. This article extends the original work by accounting for guessing and provides adjusted estimators using the existing disaggregated values. Further, Monte Carlo simulations of the adjusted learning type estimates are provided. Under certain assumptions, an instructor can determine if a difference in positive (or negative) learning is the result of a true change in learning or “white noise.

Pundits: The confidence trick: Better confident than right?

Media pundits are the supreme example of self-belief and confidence in their own opinions. Through TV, newspapers and blogs they tell us with sublime certainty what will happen. But are they right? And does it matter if they are wrong? Ben Smith and Jadrian Wooten ask what we demand from pundits – accuracy or confidence

Let Them Tweet Cake: Estimating Public Dissent Using Twitter

This paper establishes a new method of estimating public dissent that is both cost-effective and adaptable. Twitter allows users to post short messages that can be viewed and shared by other users, creating a network of freely and easily observable information. Drawing data directly from Twitter, we collect tweets containing specified words and phrases from citizens voicing dissatisfaction with their government. The collected tweets are processed using a regular expression based algorithm to estimate individual dissent; which is aggregated to an overall measure of public dissent. A comparative case study of Canada and Kenya during the summer of 2016 provides proof of concept. Controlling for user base differences, we find there is more public dissent in Kenya than Canada. This obvious, but necessary, result suggests that our measure of public dissent is a better representation of each country’s internal dynamics than other more sporadic measures. As a robustness check, we test our estimates against real-world civil unrest events. Results show our estimates of public dissent are significantly predictive of civil unrest events days before they occur in both countries

Assessing proxies of knowledge and difficultywith rubric-based instruments

The fields of psychometrics, economic education, and education have developed statistically-valid methods of assessing knowledge and learning. These methods include item response theory, value-added learning models, and disaggregated learning. These methods, however, focus on multiple-choice or single response assessments. Faculty and administrators routinely assess knowledge through papers, thesis presentations, or other demonstrations of knowledge assessed with rubric rows. This paper presents a statistical approach to estimating a proxy for student ability and rubric row difficulty. Moreover, we have developed software so that practitioners can more easily apply this method to their instruments. This approach can be used in researching education treatment effects, practitioners measuring learning outcomes in their own classrooms, or estimating knowledge for administrative assessment. As an example, we have applied these new methods to projects in a large Labor Economics course at a public university

Create random assignments: A cloud-based tool to help implement alternative teaching materials

Research has shown that learning is enhanced by variety (Bransford, Brown, and Cocking 2000; Halpern and Hakel 2003) such as popular press books, podcasts and videos. However, these mediums do not contain question banks and further, while learning management systems (LMS) can be used to generate random quizzes, they are not designed for long-form open-ended responses that might be answered over the course of a few days to weeks; open-ended questions are often ideal in upper-level undergraduate and MBA courses where there are less definitive correct answers. We solve these problems by developing software to generate assignments with randomized open-ended questions

How Often Does Active Learning Actually Occur? Perception versus Reality

I. Measuring Active and Passive Learning There is now a robust literature touting the benefits of various active learning techniques relative to passive learning pedagogy such as lecturing (e.g., Freeman et al. 2014, Emerson and English 2016, Swoboda and Feiler 2016, Caviglia-Harris 2016). However, recent studies suggest that lecturing is still the dominant pedagogical choice in economics, even though most instructors believe that active learning methods are superior (Goffe and Kauper 2014, Watts and Schaur 2011). A limitation of these studies is that estimates of passive and active learning are based on instructors’ subjective, self-reported data

Simulating Confidence for the Ellison-Glaeser Index

The Ellison and Glaeser (1997) index is an unbiased statistic of industrial localization. Though the expected value of the index is known, ad hoc thresholds are used to interpret the extent of localization. We improve the interpretation of the index by simulating confidence intervals that a practitioner may use for a statistical test. In the data, we find cases whose index value is above the ad hoc threshold that are not statistically significant. We find many cases below the ad hoc threshold that are statistically significant. Our simulation program is freely available and is customizable for specific applications