Any Time? Any Place? The impact on student learning of an on-line learning environment.

Original paper can be found at: http://www.actapress.com/Content_of_Proceeding.aspx?proceedingID=292#pages Copyright ACTA Press [Full text of this paper is not available in the UHRA]An increasing number of HE institutions are adopting virtual and managed learning environments (VLEs and MLEs), which offer flexible access to on-line learning materials all day and every day. There are multiple claims about e-learning enhancing learning and teaching (eg. [1] Britain and Liber, 1999; [2]Conole, 2002; [4]Allen, 2003; [5]Littlejohn and Higginson, 2003) such as supporting active learning, facilitative rather than didactic teaching and increased student motivation but these are not pre determined outcomes. Much depends on how lecturers use the available technology and how students respond to that use. This paper reports on a research project which has evaluated the students' own experience of on-line learning at the University of Hertfordshire. Using its own institution-wide MLE (StudyNet) academic staff at the university have been able to offer students on-line access to their study material from September 2001. Activities available for students using StudyNet include participating in discussion forums, using formative assessment materials and accessing journal articles as well as viewing and downloading courseware for each of their courses. Students were invited to participate in a questionnaire and focus groups to identify the characteristics of the on-line learning environment which benefited their learning

STATISTICAL CONSIDERATIONS WHEN USING HYSTERESIS TO ESTIMATE INTERNAL HEAT LOAD IN DAIRY COWS

Water is often used to manage heat stress in dairy cattle. Sprinklers are often placed over the feed bunk or used while cattle are waiting to be milked, however in this experiment cattle were given control over water with a cow-activated shower. Previous studies have focused on how wetting can lower body emperature or reduce respiration rates. An alternative way to investigate this management practice is to examine internal heat loads. Internal heat load can be quantified by fitting a hysteresis loop to daily field data. The hysteresis loop is formed by a phase diagram of body temperature versus an environmental input. Internal heat load is the area inside the loop. The area can be estimated using a number of environmental measures. In this paper three environmental measures are considered: ambientair temperature, the temperature-humidity index and the heat-load index. The two stage harmonic least squares methodis used to estimate internal heat load. Then a Bayesian MCMC model is used to predict internal heat load using the environmental inputs and test the effectiveness of allowing shower access on internal heat load reduction. Voluntary use of a shower reduces internal heat load and the strength of this effect increases with the degree of the heat challenge

ESTIMATING AREA AND LAG ASSOCIATED WITH THERMAL HYSTERESIS IN CATTLE

Thermal hysteresis in cattle becomes visible when the phase diagram of body temperature (Tb) vs ambient temperature (Ta) exhibits a loop. The hysteresis loop shows a rotated elliptical pattern which depends on the lag between Tb and Ta. The area of the loop can be used to quantify the amount of heat stress during thermal challenge. Three methods to estimate the area and lag of the elliptical hysteresis loop are: linear least squares method, ellipse-specific nonlinear least squares method, and Lapshin’s analytical method. Linear least squares method uses residual least squares to estimate the coefficients of the ellipse for which the sum of the squares of the distances to the observations is minimal. The estimated coefficients can be used to calculate both the rotated angle and area of the ellipse. The ellipse-specific method is based on quadratic constrained least mean squares fitting to simultaneously determine the best elliptical fit for a set of scattered data. It provides estimates of the rotated angle and semi-major and semi-minor axes to calculate the area of the ellipse. Lapshin’s analytical method is a two-stage procedure that fits a sinusoidal function to the input and then the output. It provides parameters in addition to lag and area which further characterize the hysteresis loop. The area and lag along with their standard errors are compared for the three methods using the delta method and bootstrapping. The delta method is used to calculate the standard errors of the derived parameter estimates and bootstrapping is used to assess the appropriateness of the delta method

USING NONLINEAR GROWTH CURVES TO ESTIMATE HEAT STRESS IN PROCESSING FEEDLOT CATTLE

Summertime heat waves cause excessive discomfort and, in extreme cases, death of feedlot cattle. During such emergencies, extension specialists are called upon for recommendations of management practices to minimize heat stress. Since moving cattle is believed to raise body temperature 1 degree, one recommendation is to move cattle before mid-day or reschedule to another day. More knowledge of body temperature dynamics could lead to more specific recommendations of how far cattle can be moved without stress. Several models are investigated - especially those involving exponential growth(challenge) and decay (recovery) such as the bi-exponential, single compartment and other models in pharmacokinetics. Data from feedlot trials can be messy and judgement calls involving starting and ending times, model parametrization, and statistical assumptions can influence the results. Analyzes from SAS: proc NLIN and checks on nonlinear assumptions are discussed

STATISTICAL ISSUES IN STUDIES OF THERMOREGULATION IN FARM ANIMALS

Patterns of tympanic temperature response were identified in ad-lib-fed cattle exposed to constant or cyclic (±7 C) conditions at two levels of air temperature: 10 C and 28 C. Use of time series analysis following the DDS approach of Pandit and Wu indicate the thermoregulatory control dynamics for steers at 28±7 C were markedly different from those at the other conditions. Preliminary evaluations using the ideas of chaos and non-linear dynamics show promise of further characterization of stress responses in farm animals

USING THE BI-LOGISTIC MODEL TO ESTIMATE BODY TEMPERATURE IN FEEDLOT CATTLE

Processing and handling cattle require an expenditure of energy causing an elevation of body temperature, depending on the ambient conditions. More knowledge of body temperature, Tb, dynamics could lead to more specific recommendations of how far cattle can be moved without stress. The bi-Iogistic model has been used to describe the handling process. This model estimates several important biological parameters: rate of increase in Tb (rate of heat challenge), the maximum Tb (max Tb), time to reach maximum Tb (tmax) and recovery rate (rate of decrease in Tb). The objectives of this study are: to compare parameter estimates from the bi-Iogistic model with a segmented version of the model; to investigate the robustness of the model for different definitions of recovery; and, to check for hormetic behavior using switching functions

USING TIME SERIES TO STUDY EFFECT OF AIR TEMPERATURE ON BODY TEMPERATURE OF COWS IN PUERTO RICO

Body temperature is an important measure for monitoring the health status of cows. The objective of this study is to (1) determine if a cow’s body temperature is related to ambient temperature, relative humidity, and/or temperature humidity index (THI); (2) look for signs of heat stress. The data are collected at five minute intervals during the summer months (December through February) in Puerto Rico. Regression analysis and a succession of time series analyses are conducted in time domains. Nonparametric spectral estimation and cross-spectra analysis are also performed in the frequency domain. A search for indications of heat stress is performed by characterizing the relationship between body temperature and environmental factors. Detailed approaches of regression with autocorrelated errors and transfer function model in time domain are presented, along with the comparison between two models

SPLINE MODELS FOR ESTIMATING HEAT STRESS THRESHOLDS IN CATTLE

Studies of the relationship between animal body temperature and air temperature suggest body temperature is essentially unresponsive until a threshold is reached, then it responds dramatically to increasing air temperature. The goal is to estimate the threshold between the thermoneutral plateau and the beginning of the heat stress challenge. One approach is to fit a polynomial to estimate the knot position and use spline functions to perform linear least squares piecewise polynomial fitting. Another alternative is to use nonlinear regression to estimate the knot or an inflection point of a nonlinear function. In both approaches the cyclic nature of body temperature is ignored. This paper explores the use of nonlinear regression to estimate the knot position and handles the hysteresis effect resulting from the cyclic nature of body temperature. Models are fit to data collected from cattle in chambers subjected to semicontrolled sinusoidal air temperature at the University of Missouri-Columbia Animal Science department and a procedure for estimating the heat stress threshold is proposed

COMPARING EXPERIMENTAL DESIGNS FOR A BI-LOGISTICAL MODEL USED TO ESTIMATE HEAT STRESS WHEN MOVING FEEDLOT CATTLE

Processing and handling cattle requires expenditure of energy causing an elevation of body temperature, depending on the ambient conditions. Therefore, caution should be exercised in moving cattle, especially during summer. More knowledge of the dynamics of body temperature, (Tb), could lead to specific recommendations on how far and under what conditions cattle can be moved before becoming thermally challenged. Data comes from feedlot trials conducted over four days. A bi-logistic mixed model of Tb is used to describe the effects of moving and handling on Tb. This model provides estimates for several important biological parameters describing the thermal challenge and recovery: the maximum Tb challenge, challenge rate constant (rate constant for increase in Tb), time to maximum rate of challenge (challenge inflection point), baseline for recovery, recovery rate constant (rate constant for decrease in Tb) and time to maximum recovery rate (recovery inflection point). Fitting a nonlinear mixed model with six parameters under extremely variable animal and environmental conditions is difficult especially when the treatment factor (distance) is introduced into the model. Additional difficulties in fitting the model arise as the experimental design increases in complexity from a CRD to a replicated Latin square. The objectives of this study are: to examine the bi-logistic model with distance as a treatment factor and estimate the relative efficiencies as the experimental design is simplified