Resource Access Patterns in Exam Preparation Activities

2015 ◽  
pp. 497-502 ◽  
Author(s):  
Sabrina Ziebarth ◽  
Irene-Angelica Chounta ◽  
H. Ulrich Hoppe
Keyword(s):  
Resource Access ◽  
Exam Preparation ◽  
Access Patterns

scholarly journals Analysis of Dynamic Resource Access Patterns in Online Courses

2014 ◽  
Vol 1 (3) ◽  
pp. 34-60 ◽  
Author(s):  
Tobias Hecking ◽  
Sabrina Ziebarth ◽  
Heinz Ulrich Hoppe
Keyword(s):  
Online Learning ◽  
Online Courses ◽  
Computer Mediated Communication ◽  
Mediated Communication ◽  
Resource Access ◽  
Wide Range ◽  
Master Level ◽  
Resource Networks ◽  
Online Learning Resources ◽  
Access Patterns

This paper presents an analysis of resource access patterns in two recently conducted online courses. One of these is an master level university lecture taught in form of a blended learning course with a wide range of online learning activities and materials, including collaborative wikis, self-tests and thematic videos. The other course on psychological aspects of computer mediated communication has been offered in the form of a MOOC. The specialty of this course was that master level students from two different universities could participate in the MOOC as a regular university class and receive credits for successful completion.In both courses, online learning resources such as videos, scientific literature and wikis played a central role. In this context, the motivation for our research was to investigate characteristic patterns of resource usage of the learners. To gain deeper insights into the usage of learning materials we have extracted dynamic bipartite student - resource networks based on event logs of resource access. These networks have been analyzed using methods adapted from social network analysis. In particular we detect bipartite clusters of students and resources in those networks and propose a method to identify patterns and traces of their evolution over time.

A COMPARATIVE STUDY ON THE PERFORMANCE OF STUDENTS OF PRIVATE SCHOOLS, GOVERNMENT SCHOOLS SITUATED IN URBAN & RURAL AREAS OF HARYANA IN THE SECONDARY EXAMINATIONS CONDUCTED BY THE BOARD OF SCHOOL EDUCATION HARYANA IN 2020.

2020 ◽  
pp. 38-43
Author(s):  
Balkar Singh
Keyword(s):  
Private Schools ◽  
Rural Areas ◽  
School Education ◽  
Government Schools ◽  
Poor Students ◽  
Exam Preparation ◽  
Urban City ◽  
Urban Rural ◽  
The Government ◽  
Exam Result

The capability or calibre cannot be judged based on Results, as it depends on the student to student & also the examination is testing of knowledge of a student, for the whole year in two or three hours. In July 2020 the exam result of the secondary standard was declared by the Board of School Education Haryana, Bhiwani and there is a discussion about topper & the schools in which these toppers were studying & strategy of these toppers regarding exam preparation, their interviews & photos were published in the Newspapers, why not? It must be but in this spark light, there is some darkness behind this. Everyone is congratulating these students, as they are studied from the Private Schools of the Urban City areas of the Haryana, a few are from the most educated families, whose parents their selves are teachers or professors. Through this, we are ignoring a bitter truth of the poor students of the Government Schools, who despite lack of all the big & small facilities, as compare of these Private schools’ performed equal to these toppers. KEYWORDS: Testing of knowledge, Education in Private Schools, Toppers and Calibre.

Evaluation of access patterns from log Ontology with DL-safe rules

2009 ◽  
Vol 29 (5) ◽  
pp. 1401-1404
Author(s):  
Ming SUN ◽  
Bo CHEN ◽  
Ming-tian ZHOU
Keyword(s):  
Access Patterns

scholarly journals Machine Learning–enabled Scalable Performance Prediction of Scientific Codes

2021 ◽  
Vol 31 (2) ◽  
pp. 1-28
Author(s):  
Gopinath Chennupati ◽  
Nandakishore Santhi ◽  
Phill Romero ◽  
Stephan Eidenbenz
Keyword(s):  
Machine Learning ◽  
Performance Prediction ◽  
Prediction Models ◽  
Radiation Transport ◽  
Discrete Event ◽  
Basic Block ◽  
Distribution Models ◽  
Scientific Application ◽  
High Level ◽  
Access Patterns

Hardware architectures become increasingly complex as the compute capabilities grow to exascale. We present the Analytical Memory Model with Pipelines (AMMP) of the Performance Prediction Toolkit (PPT). PPT-AMMP takes high-level source code and hardware architecture parameters as input and predicts runtime of that code on the target hardware platform, which is defined in the input parameters. PPT-AMMP transforms the code to an (architecture-independent) intermediate representation, then (i) analyzes the basic block structure of the code, (ii) processes architecture-independent virtual memory access patterns that it uses to build memory reuse distance distribution models for each basic block, and (iii) runs detailed basic-block level simulations to determine hardware pipeline usage. PPT-AMMP uses machine learning and regression techniques to build the prediction models based on small instances of the input code, then integrates into a higher-order discrete-event simulation model of PPT running on Simian PDES engine. We validate PPT-AMMP on four standard computational physics benchmarks and present a use case of hardware parameter sensitivity analysis to identify bottleneck hardware resources on different code inputs. We further extend PPT-AMMP to predict the performance of a scientific application code, namely, the radiation transport mini-app SNAP. To this end, we analyze multi-variate regression models that accurately predict the reuse profiles and the basic block counts. We validate predicted SNAP runtimes against actual measured times.

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