Methods, instrumentation, and preliminary evaluation of data for the hydrologic budget assessment of Lake Lucerne, Polk County, Florida

Introduction: In 2017, the School of Medicine of the University of Notre Dame Australia implemented a data-informed mentoring program as part of a more substantial shift towards programmatic assessment. Data-informed mentoring, in an educational context, can be challenging with boundaries between mentor, coach and assessor roles sometimes blurred. Mentors may be required to concurrently develop trust relationships, guide learning and development, and assess student performance. The place of data-informed mentoring within an overall assessment design can also be ambiguous. This paper is a preliminary evaluation study of the implementation of data informed mentoring at a medical school, focusing specifically on how students and staff reacted and responded to the initiative. Methods: Action research framed and guided the conduct of the research. Mixed methods, involving qualitative and quantitative tools, were used with data collected from students through questionnaires and mentors through focus groups. Results: Both students and mentors appreciated data-informed mentoring and indications are that it is an effective augmentation to the School’s educational program, serving as a useful step towards the implementation of programmatic assessment. Conclusion: Although data-informed mentoring is valued by students and mentors, more work is required to: better integrate it with assessment policies and practices; stimulate students’ intrinsic motivation; improve task design and feedback processes; develop consistent learner-centred approaches to mentoring; and support data-informed mentoring with appropriate information and communications technologies. The initiative is described using an ecological model that may be useful to organisations considering data-informed mentoring.

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Preliminary evaluation of data derived from the recently completed Alaska home radon survey

10.14509/1439 ◽

1990 ◽

Author(s):

C. J. Nye ◽

J. T. Kline

Keyword(s):

Preliminary Evaluation ◽

Evaluation Of Data ◽

Radon Survey

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Influence of evaporation, ground water, and uncertainty in the hydrologic budget of Lake Lucerne, Florida, October 1985-September 1986

Open-File Report ◽

10.3133/ofr9326 ◽

1994 ◽

Cited By ~ 2

Author(s):

T.M. Lee ◽

Amy Swancar

Keyword(s):

Ground Water ◽

Lake Lucerne ◽

Hydrologic Budget

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Preliminary Evaluation of a Weibull Function for Fitting Slow-Component Eye Velocity over the Time Course of Caloric-Induced Nystagmus

Journal of Speech Language and Hearing Research ◽

10.1044/jshr.3203.681 ◽

1989 ◽

Vol 32 (3) ◽

pp. 681-687 ◽

Cited By ~ 1

Author(s):

C. Formby ◽

B. Albritton ◽

I. M. Rivera

Keyword(s):

Time Course ◽

Slow Component ◽

Weibull Function ◽

Preliminary Evaluation ◽

Mathematical Function ◽

Before And After ◽

Best Fitting ◽

Eye Velocity ◽

Fitting Parameters ◽

Weibull Equation

We describe preliminary attempts to fit a mathematical function to the slow-component eye velocity (SCV) over the time course of caloric-induced nystagmus. Initially, we consider a Weibull equation with three parameters. These parameters are estimated by a least-squares procedure to fit digitized SCV data. We present examples of SCV data and fitted curves to show how adjustments in the parameters of the model affect the fitted curve. The best fitting parameters are presented for curves fit to 120 warm caloric responses. The fitting parameters and the efficacy of the fitted curves are compared before and after the SCV data were smoothed to reduce response variability. We also consider a more flexible four-parameter Weibull equation that, for 98% of the smoothed caloric responses, yields fits that describe the data more precisely than a line through the mean. Finally, we consider advantages and problems in fitting the Weibull function to caloric data.

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