The Experts below are selected from a list of 279 Experts worldwide ranked by ideXlab platform
Michael Kollmer - One of the best experts on this subject based on the ideXlab platform.
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CCWC - Correlation discovery between high school Student Web Queries and their Grade Point Average
2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), 2020Co-Authors: Jigar Jadav, Andrew Burke, Greg Goldberg, Dawn Lindelin, Andrew Preciado, Charles C Tappert, Michael KollmerAbstract:In recent years, the K-12 learning space has been utilizing mobile devices to supplement student learning. To support the funding of school-issued mobile devices, the schools are interested in determining the degree to which the students use these devices for school-related activities. This study examined high school student web queries performed on school issued iPads using anonymized data from web filter logs. These web queries were first classified as either school-related or non-school-related using an earlier-developed algorithm. The classification results were then used to examine whether a correlation exists between web queries, especially the school-related ones, and the student's Grade Point Average. Regression analysis found a highly significant correlation (p < 0.00005) between the percentage of school-related web queries and the student's Grade Point Average.
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correlation discovery between high school student web queries and their Grade Point Average
IEEE Annual Computing and Communication Workshop and Conference, 2017Co-Authors: Jigar Jadav, Andrew Burke, Greg Goldberg, Dawn Lindelin, Andrew Preciado, Charles C Tappert, Michael KollmerAbstract:In recent years, the K-12 learning space has been utilizing mobile devices to supplement student learning. To support the funding of school-issued mobile devices, the schools are interested in determining the degree to which the students use these devices for school-related activities. This study examined high school student web queries performed on school issued iPads using anonymized data from web filter logs. These web queries were first classified as either school-related or non-school-related using an earlier-developed algorithm. The classification results were then used to examine whether a correlation exists between web queries, especially the school-related ones, and the student's Grade Point Average. Regression analysis found a highly significant correlation (p < 0.00005) between the percentage of school-related web queries and the student's Grade Point Average.
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Correlation discovery between high school Student Web Queries and their Grade Point Average
2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), 2017Co-Authors: Jigar Jadav, Andrew Burke, Greg Goldberg, Dawn Lindelin, Andrew Preciado, Charles C Tappert, Michael KollmerAbstract:In recent years, the K-12 learning space has been utilizing mobile devices to supplement student learning. To support the funding of school-issued mobile devices, the schools are interested in determining the degree to which the students use these devices for school-related activities. This study examined high school student web queries performed on school issued iPads using anonymized data from web filter logs. These web queries were first classified as either school-related or non-school-related using an earlier-developed algorithm. The classification results were then used to examine whether a correlation exists between web queries, especially the school-related ones, and the student's Grade Point Average. Regression analysis found a highly significant correlation (p
A I Mahadeen - One of the best experts on this subject based on the ideXlab platform.
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the effects of undergraduate nursing student faculty interaction outside the classroom on college Grade Point Average
Nurse Education in Practice, 2011Co-Authors: Mahmoud Alhussami, Mohammad Y N Saleh, Ferial A Hayajneh, Raghed Hussein Abdalkader, A I MahadeenAbstract:Abstract Background The effects of student–faculty interactions in higher education have received considerable empirical attention. However, there has been no empirical study that has examined the relation between student–faculty interaction and college Grade Point Average. Purpose This is aimed at identifying the effect of nursing student–faculty interaction outside the classroom on students' semester college Grade Point Average at a public university in Jordan. Methods The research was cross-sectional study of the effect of student–faculty interaction outside the classroom on the students' semester college Grade Point Average of participating juniors and seniors. Results Total interaction of the students was crucial as it is extremely significant ( t = 16.2, df = 271, P ≤ 0.001) in relation to students' academic scores between those students who had ≥70 and those who had Conclusion This study provides some evidence that student–faculty interactions outside classrooms are significantly associated with student's academically achievements.
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The effects of undergraduate nursing student–faculty interaction outside the classroom on college Grade Point Average
Nurse Education in Practice, 2011Co-Authors: Mahmoud Al-hussami, Mohammad Y N Saleh, Ferial A Hayajneh, Raghed Hussein Abdalkader, A I MahadeenAbstract:Abstract Background The effects of student–faculty interactions in higher education have received considerable empirical attention. However, there has been no empirical study that has examined the relation between student–faculty interaction and college Grade Point Average. Purpose This is aimed at identifying the effect of nursing student–faculty interaction outside the classroom on students' semester college Grade Point Average at a public university in Jordan. Methods The research was cross-sectional study of the effect of student–faculty interaction outside the classroom on the students' semester college Grade Point Average of participating juniors and seniors. Results Total interaction of the students was crucial as it is extremely significant ( t = 16.2, df = 271, P ≤ 0.001) in relation to students' academic scores between those students who had ≥70 and those who had Conclusion This study provides some evidence that student–faculty interactions outside classrooms are significantly associated with student's academically achievements.
Daniel Koretz - One of the best experts on this subject based on the ideXlab platform.
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Predicting Freshman Grade-Point Average from High-School Test Scores: are There Indications of Score Inflation?
2020Co-Authors: Daniel Koretz, Carol Yu, Meredith Langi, David BraslowAbstract:The current focus on “college and career readiness” highlights a long-standing question: how well does performance on high-school tests predict performance in college? The answer may depend not only on the content and difficulty of the tests, but also on the extent to which test preparation has inflated scores. This study uses data from the City University of New York to investigate how well scores on the Mathematics A, Integrated Algebra, and English Language Arts Regents examinations predict freshman Grade-Point Average. We find that in the aggregate, Regents scores predict roughly as well as SAT scores but that high school Grade-Point Average (HSGPA) based on only college-preparatory courses predicts substantially better than either set of tests. Starting with a conventional ordinary least squares prediction based on HSGPA and either set of tests, adding the second set of tests improves aggregate prediction only trivially but would change which students are selected. We found that these predictive relationships vary markedly among campuses, with a tendency for stronger prediction by test scores on campuses with higher scores.
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predicting freshman Grade Point Average from test scores effects of variation within and between high schools
Educational Measurement: Issues and Practice, 2018Co-Authors: Daniel Koretz, M LangiAbstract:Most studies predicting college performance from high-school Grade Point Average (HSGPA) and college admissions test scores use single-level regression models that conflate relationships within and between high schools. Because grading standards vary among high schools, these relationships are likely to differ within and between schools. We used two-level regression models to predict freshman Grade Point Average from HSGPA and scores on both college admissions and state tests. When HSGPA and scores are considered together, HSGPA predicts more strongly within high schools than between, as expected in the light of variations in grading standards. In contrast, test scores, particularly mathematics scores, predict more strongly between schools than within. Within-school variation in mathematics scores has no net predictive value, but between-school variation is substantially predictive. Whereas other studies have shown that adding test scores to HSGPA yields only a minor improvement in aggregate prediction, our findings suggest that a potentially more important effect of admissions tests is statistical moderation, that is, partially offsetting differences in grading standards across high schools.
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Predicting Freshman Grade‐Point Average from Test Scores: Effects of Variation Within and Between High Schools
Educational Measurement: Issues and Practice, 2017Co-Authors: Daniel Koretz, M LangiAbstract:Most studies predicting college performance from high-school Grade Point Average (HSGPA) and college admissions test scores use single-level regression models that conflate relationships within and between high schools. Because grading standards vary among high schools, these relationships are likely to differ within and between schools. We used two-level regression models to predict freshman Grade Point Average from HSGPA and scores on both college admissions and state tests. When HSGPA and scores are considered together, HSGPA predicts more strongly within high schools than between, as expected in the light of variations in grading standards. In contrast, test scores, particularly mathematics scores, predict more strongly between schools than within. Within-school variation in mathematics scores has no net predictive value, but between-school variation is substantially predictive. Whereas other studies have shown that adding test scores to HSGPA yields only a minor improvement in aggregate prediction, our findings suggest that a potentially more important effect of admissions tests is statistical moderation, that is, partially offsetting differences in grading standards across high schools.
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predicting freshman Grade Point Average from college admissions test scores and state high school test scores
AERA Open, 2016Co-Authors: Daniel Koretz, Carol Yu, Meredith Langi, Preeya P Mbekeani, Tasminda Kaur Dhaliwal, David BraslowAbstract:The current focus on assessing “college and career readiness” raises an empirical question: How do high school tests compare with college admissions tests in predicting performance in college? We explored this using data from the City University of New York and public colleges in Kentucky. These two systems differ in the choice of college admissions test, the stakes for students on the high school test, and demographics. We predicted freshman Grade Point Average (FGPA) from high school GPA and both college admissions and high school tests in mathematics and English. In both systems, the choice of tests had only trivial effects on the aggregate prediction of FGPA. Adding either test to an equation that included the other had only trivial effects on prediction. Although the findings suggest that the choice of test might advantage or disadvantage different students, it had no substantial effect on the over- and underprediction of FGPA for students classified by race-ethnicity or poverty.
M Langi - One of the best experts on this subject based on the ideXlab platform.
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predicting freshman Grade Point Average from test scores effects of variation within and between high schools
Educational Measurement: Issues and Practice, 2018Co-Authors: Daniel Koretz, M LangiAbstract:Most studies predicting college performance from high-school Grade Point Average (HSGPA) and college admissions test scores use single-level regression models that conflate relationships within and between high schools. Because grading standards vary among high schools, these relationships are likely to differ within and between schools. We used two-level regression models to predict freshman Grade Point Average from HSGPA and scores on both college admissions and state tests. When HSGPA and scores are considered together, HSGPA predicts more strongly within high schools than between, as expected in the light of variations in grading standards. In contrast, test scores, particularly mathematics scores, predict more strongly between schools than within. Within-school variation in mathematics scores has no net predictive value, but between-school variation is substantially predictive. Whereas other studies have shown that adding test scores to HSGPA yields only a minor improvement in aggregate prediction, our findings suggest that a potentially more important effect of admissions tests is statistical moderation, that is, partially offsetting differences in grading standards across high schools.
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Predicting Freshman Grade‐Point Average from Test Scores: Effects of Variation Within and Between High Schools
Educational Measurement: Issues and Practice, 2017Co-Authors: Daniel Koretz, M LangiAbstract:Most studies predicting college performance from high-school Grade Point Average (HSGPA) and college admissions test scores use single-level regression models that conflate relationships within and between high schools. Because grading standards vary among high schools, these relationships are likely to differ within and between schools. We used two-level regression models to predict freshman Grade Point Average from HSGPA and scores on both college admissions and state tests. When HSGPA and scores are considered together, HSGPA predicts more strongly within high schools than between, as expected in the light of variations in grading standards. In contrast, test scores, particularly mathematics scores, predict more strongly between schools than within. Within-school variation in mathematics scores has no net predictive value, but between-school variation is substantially predictive. Whereas other studies have shown that adding test scores to HSGPA yields only a minor improvement in aggregate prediction, our findings suggest that a potentially more important effect of admissions tests is statistical moderation, that is, partially offsetting differences in grading standards across high schools.
Jigar Jadav - One of the best experts on this subject based on the ideXlab platform.
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CCWC - Correlation discovery between high school Student Web Queries and their Grade Point Average
2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), 2020Co-Authors: Jigar Jadav, Andrew Burke, Greg Goldberg, Dawn Lindelin, Andrew Preciado, Charles C Tappert, Michael KollmerAbstract:In recent years, the K-12 learning space has been utilizing mobile devices to supplement student learning. To support the funding of school-issued mobile devices, the schools are interested in determining the degree to which the students use these devices for school-related activities. This study examined high school student web queries performed on school issued iPads using anonymized data from web filter logs. These web queries were first classified as either school-related or non-school-related using an earlier-developed algorithm. The classification results were then used to examine whether a correlation exists between web queries, especially the school-related ones, and the student's Grade Point Average. Regression analysis found a highly significant correlation (p < 0.00005) between the percentage of school-related web queries and the student's Grade Point Average.
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correlation discovery between high school student web queries and their Grade Point Average
IEEE Annual Computing and Communication Workshop and Conference, 2017Co-Authors: Jigar Jadav, Andrew Burke, Greg Goldberg, Dawn Lindelin, Andrew Preciado, Charles C Tappert, Michael KollmerAbstract:In recent years, the K-12 learning space has been utilizing mobile devices to supplement student learning. To support the funding of school-issued mobile devices, the schools are interested in determining the degree to which the students use these devices for school-related activities. This study examined high school student web queries performed on school issued iPads using anonymized data from web filter logs. These web queries were first classified as either school-related or non-school-related using an earlier-developed algorithm. The classification results were then used to examine whether a correlation exists between web queries, especially the school-related ones, and the student's Grade Point Average. Regression analysis found a highly significant correlation (p < 0.00005) between the percentage of school-related web queries and the student's Grade Point Average.
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Correlation discovery between high school Student Web Queries and their Grade Point Average
2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), 2017Co-Authors: Jigar Jadav, Andrew Burke, Greg Goldberg, Dawn Lindelin, Andrew Preciado, Charles C Tappert, Michael KollmerAbstract:In recent years, the K-12 learning space has been utilizing mobile devices to supplement student learning. To support the funding of school-issued mobile devices, the schools are interested in determining the degree to which the students use these devices for school-related activities. This study examined high school student web queries performed on school issued iPads using anonymized data from web filter logs. These web queries were first classified as either school-related or non-school-related using an earlier-developed algorithm. The classification results were then used to examine whether a correlation exists between web queries, especially the school-related ones, and the student's Grade Point Average. Regression analysis found a highly significant correlation (p
