881 resultados para student performance standards


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This work extends a recent comparative study covering four different courses lectured at the Polytechnic of Porto - School of Engineering, in respect to the usage of a particular Learning Management System, i.e. Moodle, and its impact on students' results. A fifth course, which includes a number of resources especially supporting laboratory classes, is now added to the analysis. This particular course includes a number of remote experiments, made available through VISIR (Virtual Instrument Systems in Reality) and directly accessible through links included in the Moodle course page. We have analyzed the students' behavior in following these links and in effectively running experiments in VISIR (and also using other lab related resources, in Moodle). This data have been correlated with students' classifications in the lab component and in the exam, each one weighting 50% of their final marks. We aimed to compare students' performance in a richly Moodle-supported environment (with lab component) and in a poorly Moodle-supported environment (with only theoretical component). This question followed from conclusions drawn in the above referred comparative study, where it was shown that even though a positive correlation factor existed between the number of Moodle accesses and the final exam grade obtained by each student, its explanation behind was not straightforward, as the quality of the resources was preponderant over its quantity.

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Weekly monitoring of profiles of student performances on formative and summative coursework throughout the year can be used to quickly identify those who need additional help, possibly due to acute and sudden-onset problems. Such an early-warning system can help retention, but also assist students in overcoming problems early on, thus helping them fulfil their potential in the long run. We have developed a simple approach for the automatic monitoring of student mark profiles for individual modules, which we intend to trial in the near future. Its ease of implementation means that it can be used for very large cohorts with little additional effort when marks are already collected and recorded on a spreadsheet.

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This paper assesses the extent to which teachers’ actions in the classroom influence the school environment. The assessment is based on a statistical analysis of videotaped classroom observations of 51,329 teachers. The classroom environment was found to have a significant influence on students’ performance. More specifically, the teacher’s ability to handle the class as a group is consistently more significant than other measures of class environment. It was also founds that the overall school environment is a better predictor of students’ test results than the environment in the classrooms of the students whose test results are being reported. This suggests that the most effective course of action would be to improve the overall school environment, although individual teachers have less control over this factor.

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Tegrity Campus 2.0 is the first student achievement system that impacts learning across the entire institution, improving retention and student satisfaction. Tegrity makes class time available all the time by automatically capturing, storing and indexing every class on campus for replay by every student. With Tegrity, students quickly recall key moments or replay entire classes online, with digital notes, on their iPods and cell phones. [See PDF for complete abstract]

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Purpose: To assess the relationship between student utilization of learning resources, including streaming video (SV), and their performance in the pre-clinical curriculum. [See PDF for complete abstract]

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All previous studies comparing online and face-to-face format for instruction of economics compared courses that were either online or face-to-face format and regressed exam scores on selected student characteristics. This approach is subject to the econometric problems of self-selection omitted unobserved variables. Our study uses two methods to deal with these problems. First we eliminate self-selection bias by using students from a course that uses both instruction formats. Second, we use the exam questions as the unit of observation, and eliminate omitted variable bias by using an indicator variable for each student to capture the effect of differences in unobserved student characteristics on learning outcomes. We report the finding that students had a significantly greater chance of answering a question correctly if it came from a chapter covered online.

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Shipping list no.: 91-0049-p.

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Shipping list no.: 89-334-P.

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Originally presented as the author's thesis (M.A.), University of Illinois at Urbana-Champaign.

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Bibliography: p. 52.

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National Highway Safety Bureau, Washington, D.C.

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Mode of access: Internet.

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Alice Tully Hall, NYC. Joel Sachs, Barbara Hendricks, Rylann Jordan, Janet Sonres, Janet Eilber, Dorian Williams, Ange Wolf, Peter Sparling.