Sage on the Stage: Big Data, Customized Learning, and the Desire for Human Interaction

A research question arising in academia is whether the desire by administrators to collect, analyze, and disseminate ‘big data’ has become a driving force in how education is delivered. One area where data is being collected on students is through the use of Virtual Learning Environments (VLEs). We wanted to explore whether students believed that the mass information collected on them would lead to improved customized education, or whether it would be used a cost-cutting mechanism to eliminate the lecturer. Lecturers salaries tend to make up the majority of academic budgets. Focus groups were conducted among first, second and final year undergraduate business students. Participants report that they do not wish to see VLEs replace traditional lectures or tutorials and there is some push-back by students in that they do not want the ‘sage on the stage’ to be replaced the use of data to customized student led learning. Business students in this sample view the value in VLEs to disseminate textbook and journal article information and to promote collaborative learning and contribute to employability. Implications for higher education are discussed

Exploiting the Cointegration Properties of China’s Monthly Cotton Import Market and World Apparel Market Conditions: A Preliminary Analysis

Crop Production/Industries, International Relations/Trade,

Cointegrated Vector Autoregression Methods: An Application to Non-Normally Behaving Data on Selected U.S. Sugar-Related Markets

The methods of the cointegrated vector autoregression/error correction (VAR/VEC) model are applied to monthly U.S. markets for sugar and for sugar-using markets for confectionary, soft drink, and bakery products. Primarily a methods paper, Johansen and Juselius' methods are applied, with a special focus on addressing well-known issues that preclude statistically normal behavior, and that confront the modelled sugar-based data. In so doing, we illustrate the effectiveness and the benefits of modelling this sugar-related set of markets as a cointegrated system. Perhaps for the first time, cointegrated VEC model results are used to estimate crucial policy-relevant market parameters that drive the markets, as well as to illuminate the dynamic nature of the relationships linking these sugar-based markets.cointegration, sugar-based U.S. markets, vector autoregression, vector error correction models, Industrial Organization, Research Methods/ Statistical Methods,

Improving Medication Reconciliation Using Provider Education and an EHR Hard Stop

AIM: By using a sequence of two distinct interventions, we aim to improve the rate of medication reconciliation at Jefferson Internal Medicine Assoc.https://jdc.jefferson.edu/patientsafetyposters/1026/thumbnail.jp

Design and implementation of a pilot orientation program for new NASA engineering employees

This paper describes the design and field testing of an orientation program for new employees of NASA Lewis Research Center's Engineering Directorate. A group of new employees designed the program using a series of TQM analysis techniques. The program objectives were: provide consistent treatment for new employees; assist management and clerical staff with their responsibility for orientation; introduce the employee to as many facets of the organization as possible; allow the employee to feel like a member of the organization as early as possible; maximize the use of existing services; and use up-to-date information. The major aspects of the program included: training of management and clerical staff; lab tours and briefings describing the organization; shepherding, using senior employees as shepherds; a handbook of information about the center and the directorate; a package of information about northeast Ohio; and social activities involving the new employees and shepherds. The program was tested on a pilot group of six new employees over a four month period and was considered to be highly successful by both the employees and management. Aspects of the program have subsequently been adopted for center-wide use

Dynamic Economic Relationships Among U.S. Soy Product Markets: Using a Cointegrated Vector Autoregression Approach with Directed Acyclic Graphs

This paper applies a combined methodology of a recently developed directed acyclic graph (DAG) analysis with Johansen and Juselius' methods of the cointegrated vector autoregression (VAR) model to a monthly U.S. system of markets for soybeans, soy meal, and soy oil. Primarily a methods paper, Johansen and Juselius' procedures are applied, with a special focus on statistically addressing information inherent in well-known sources of non-normal data behavior to illustrate the effectiveness of modeling the system as a cointegrated multi-market system. Perhaps for the first time, methods of the cointegrated VAR model are combined with DAG analysis to account for contemporaneously correlated residuals, and are applied to this U.S. soy-based system. Analysis of the error correction or cointegration space illuminates the empirical nature of policy-relevant market elasticities, price transmission parameters, and effects of important policy and institutional changes/events on U.S. soy-related markets at long-run horizons beyond a single crop cycle. A statistically strong U.S. demand for soybeans emerged as the primary cointegrating relation in the error-correction space. Analysis of the DAG-adjusted cointegrated VAR model's forecast error variance decomposition illuminates how the soy-related variables and the three U.S. soy product markets dynamically interact at alternative time horizons extending up to two-years.directed acyclic graphs, cointegration, vector error correction and vector autoregression models, monthly U.S. soy-based markets., Industrial Organization, Research Methods/ Statistical Methods,

Boosting graduates' confidence in statistics

Recent research points to a lack of statistics knowledge in today’s graduate students

Dynamic Relationships Among Selected U.S. Commodity-Based, Value Added Markets: Applying Directed Acyclic Graphs to a Time Series Model

This paper demonstrates the application of a recently developed methodology, the combination of directed acyclic graphs (DAGs) with Bernanke structural vector autoregression (VAR) models, to model a system of U.S. commodity-related and value-added markets. As an example, the paper applies this methodology to a quarterly system of U.S. markets: the wheat market and a set of downstream milling and bakery markets that use wheat as an input. Analyses of the model's impulse response simulations and forecast error variance decompositions provide updated estimates of market elasticity parameters that drive these markets, and updated policy-relevant information on how these quarterly markets run and dynamically interact. Results suggest that movements in commodity-based markets strongly influence each other, although most of these effects occur in the long run beyond a single crop cycle. The paper illuminates how important U.S. food prices respond to wheat farm market shocks in price and quantity.Bernanke structural VARs, directed acyclic graphs, quarterly wheat-related markets, Industrial Organization, Marketing, Research Methods/ Statistical Methods,

THE CORN-EGG PRICE TRANSMISSION MECHANISM

A vector autoregression (VAR) model of corn, farm egg, and retail egg prices is estimated and shocked with a corn price increase. Impulse responses in egg prices, t-statistics for the impulse responses, and decompositions of forecast error variance are presented. Analyses of results provide insights on the corn/egg price transmission mechanism and on how corn price shocks pulsate through the egg-related economy.Demand and Price Analysis,

A TIME-SERIES ANALYSIS OF THE U.S. DURUM WHEAT AND PASTA MARKETS

A quarterly, partial-equilibrium vector-autoregression model of the U.S. durum wheat and pasta markets was estimated and simulated under three trade-barrier changes that are of potential relevance for the current round of WTO agricultural negotiations: a rise in the U.S. market-clearing durum wheat quantity from increased imports; a policy- or tariff- reduction-induced decline in U.S. durum wheat price; and a tariff-induced rise in U.S. pasta product prices. In response to each shock, an array of quarterly dynamic response characteristics are examined: response reaction times, direction and pattern of quarterly responses, response durations, response multipliers, and strength of durum/pasta market interrelationships.Industrial Organization,