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Title: Designing projects for motivating stufents towards scientific exploration: Application to student mentoring

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Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
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Conference: Presented at: SPIE 2016, San Diego, CA, United States, Aug 28 - Aug 30, 2016
Country of Publication:
United States

Citation Formats

Awwal, A. Designing projects for motivating stufents towards scientific exploration: Application to student mentoring. United States: N. p., 2016. Web.
Awwal, A. Designing projects for motivating stufents towards scientific exploration: Application to student mentoring. United States.
Awwal, A. 2016. "Designing projects for motivating stufents towards scientific exploration: Application to student mentoring". United States. doi:.
title = {Designing projects for motivating stufents towards scientific exploration: Application to student mentoring},
author = {Awwal, A},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2016,
month = 8

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  • Our efforts in Honduras and Guatemala were part of the Central America Energy Resource Project (CAERP) funded by the United States Agency for International Development (AID). Exploration core drilling operations at the Platanares, Honduras and Tecuamburro Volcano, Guatemala sites were part of a geothermal assessment for the national utility companies of these countries to locate and evaluate their geothermal resources for electrical power generation. In Honduras, country-wide assessment of all thermal areas determined that Platanares was the site with the greatest geothermal potential. In late 1986 to middle 1987, three slim core holes were drilled at Platanares to a maximummore » depth of 680 m and a maximum temperature of 165{degree}C. The objectives were to obtain information on the geothermal gradient, hydrothermal alterations, fracturing, and possible inflows of hydrothermal fluids. Two holes produced copious amounts of water under artesian conditions and a total of 8 MW(t) of energy. Geothermal investigations in Guatemala focused on the Tecuamburro Volcano geothermal site. The results of surface geological, volcanological, hydrogeochemical, and geophysical studies at Tecuamburro Volcano indicated a substantial shallow heat source. In early 1990 we drilled one core hole, TCB-1, to 808 m depth. The measured bottom hole temperature was 238{degree}C. Although the borehole did not flow, in-situ samples indicate the hole is completed in a vapor-zone above a probable 300{degree}C geothermal reservoir.« less
  • Data-driven assessments and adaptive feedback are becoming a cornerstone research in educational data analytics and involve developing methods for exploring the unique types of data that come from the educational context. For example, predicting college student performance is crucial for both the students and educational institutions. It can support timely intervention to prevent students from failing a course, increasing efficacy of advising functions, and improving course completion rate. In this paper, we present our efforts in using data analytics that enable educationists to design novel data-driven assessment and feedback mechanisms. In order to achieve this objective, we investigate temporal stabilitymore » of students grades and perform predictive analytics on academic data collected from 2009 through 2013 in one of the most commonly used learning management systems, called Moodle. First, we have identified the data features useful for assessments and predicting student outcomes such as students scores in homework assignments, quizzes, exams, in addition to their activities in discussion forums and their total Grade Point Average(GPA) at the same term they enrolled in the course. Second, time series models in both frequency and time domains are applied to characterize the progression as well as overall projections of the grades. In particular, the model analyzed the stability as well as fluctuation of grades among students during the collegiate years (from freshman to senior) and disciplines. Third, Logistic Regression and Neural Network predictive models are used to identify students as early as possible who are in danger of failing the course they are currently enrolled in. These models compute the likelihood of any given student failing (or passing) the current course. The time series analysis indicates that assessments and continuous feedback are critical for freshman and sophomores (even with easy courses) than for seniors, and those assessments may be provided using the predictive models. Numerical results are presented to evaluate and compare the performance of the developed models and their predictive accuracy. Our results show that there are strong ties associated with the first few weeks for coursework and they have an impact on the design and distribution of individual modules.« less
  • From third Health Physics Society midyear topical symposium; Los Angeles, California, USA (29 Jan 1969). See CONF-690103P1. Student laboratory and research projects involving exposure to radioactive hazards must receive close attention because of the varying backgrounds, capabilities, and particularly the varying interests of the students. Procedures establislied obviously should insure safety of the student. It is considered though that improvement of the student's background knowledge to equip him for further development is of almost equal importance, whether he plans to actively enter the nuclear energy field or not. Attention to proper indoctrination should not be relaxed even if working atmore » the lower end of the radiation hazard spectrum. Instead, education and training should aiways be aimed at a more severe and varied hazards condition, including accident in order to insure maximum development. (auth)« less
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