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Sarwar, Sohail; García-Castro, Raul; Qayyum, Zia Ul; Safyan, Muhammad; Munir, Rana Faisal – International Association for Development of the Information Society, 2017
Learner categorization has a pivotal role in making e-learning systems a success. However, learner characteristics exploited at abstract level of granularity by contemporary techniques cannot categorize the learners effectively. In this paper, an architecture of e-learning framework has been presented that exploits the machine learning based…
Descriptors: Student Characteristics, Profiles, Courseware, Electronic Learning
Tyagi, Himanshu – ProQuest LLC, 2013
This dissertation concerns the secure processing of distributed data by multiple terminals, using interactive public communication among themselves, in order to accomplish a given computational task. In the setting of a probabilistic multiterminal source model in which several terminals observe correlated random signals, we analyze secure…
Descriptors: Computation, Correlation, Computers, Data Processing
O'Reilly, Una-May; Veeramachaneni, Kalyan – Research & Practice in Assessment, 2014
Because MOOCs bring big data to the forefront, they confront learning science with technology challenges. We describe an agenda for developing technology that enables MOOC analytics. Such an agenda needs to efficiently address the detailed, low level, high volume nature of MOOC data. It also needs to help exploit the data's capacity to reveal, in…
Descriptors: Data, Technology Uses in Education, Online Courses, Open Education
Alaimo, Peter J.; Langenhan, Joseph M.; Suydam, Ian T. – Journal of Chemical Education, 2014
Many traditional organic chemistry lab courses do not adequately help students to develop the professional skills required for creative, independent work. The overarching goal of the new organic chemistry lab series at Seattle University is to teach undergraduates to think, perform, and behave more like professional scientists. The conversion of…
Descriptors: Undergraduate Students, Organic Chemistry, Alignment (Education), Science Process Skills
Waters, John K. – Campus Technology, 2013
The latest data alert: By 2020, the amount of data generated daily will reach 40 zettabytes, or roughly 5,247 gigabytes for every person on earth. That's one of the findings in a new report published by IT industry analysts at IDC. The study casts doubt on the ability to capture the value of all this data, especially since schools barely tapped…
Descriptors: Information Management, Data, Data Collection, Data Processing
Ortiz, Jorge Jose – ProQuest LLC, 2013
This thesis examines the state of the art of building information systems and evaluates their architecture in the context of emerging technologies and applications for deep analysis of the built environment. We observe that modern building information systems are difficult to extend, do not provide general services for application development, do…
Descriptors: Buildings, Architecture, Data Processing, Information Systems
Strizek, Gregory A.; Tourkin, Steve; Erberber, Ebru – National Center for Education Statistics, 2014
This technical report is designed to provide researchers with an overview of the design and implementation of the Teaching and Learning International Survey (TALIS) 2013. This information is meant to supplement that presented in OECD publications by describing those aspects of TALIS 2013 that are unique to the United States. Chapter 2 provides…
Descriptors: Learning, Instruction, Research Design, Program Implementation
Yannakoudakis, Helen; Andersen, Øistein E.; Geranpayeh, Ardeshir; Briscoe, Ted; Nicholls, Diane – Applied Measurement in Education, 2018
There are quite a few challenges in the development of an automated writing placement model for non-native English learners, among them the fact that exams that encompass the full range of language proficiency exhibited at different stages of learning are hard to design. However, acquisition of appropriate training data that are relevant to the…
Descriptors: Automation, Data Processing, Student Placement, English Language Learners
Data Quality Campaign, 2014
District and state data systems are constructed to ensure that individuals can access only the data that are appropriate for their role. Still, questions from the public about how these data systems work and how student privacy is protected have been increasing. A recurring concern is the feared existence of a "permanent record"--a…
Descriptors: Data Collection, Student Records, Data Processing, Access to Information
Sabourin, Jennifer; Kosturko, Lucy; FitzGerald, Clare; McQuiggan, Scott – International Educational Data Mining Society, 2015
While the field of educational data mining (EDM) has generated many innovations for improving educational software and student learning, the mining of student data has recently come under a great deal of scrutiny. Many stakeholder groups, including public officials, media outlets, and parents, have voiced concern over the privacy of student data…
Descriptors: Privacy, Student Records, Data Processing, Data Collection
Rodriguez, Sheila M.; Estacion, Angela – Regional Educational Laboratory Northeast & Islands, 2014
As the name indicates, the College Readiness Data Catalog Tool focuses on identifying data that can indicate a student's college readiness. While college readiness indicators may also signal career readiness, many states, districts, and other entities, including the U.S. Virgin Islands (USVI), do not systematically collect career readiness…
Descriptors: College Readiness, Data, Educational Indicators, Data Collection
Blagdanic, Casandra; Chinnappan, Mohan – Australian Mathematics Teacher, 2013
Numeracy in schools is becoming an increasingly important part of mathematics learning and teaching. This is because educators want students to engage with mathematical concepts more deeply, use mathematics to make sense of their environment and make decisions that are based on the analysis of mathematical information. In order to be numerate,…
Descriptors: Statistical Analysis, Statistics, Data Interpretation, Numeracy
Ghergulescu, Ioana; Muntean, Cristina Hava – International Journal of Artificial Intelligence in Education, 2016
Engagement influences participation, progression and retention in game-based e-learning (GBeL). Therefore, GBeL systems should engage the players in order to support them to maximize their learning outcomes, and provide the players with adequate feedback to maintain their motivation. Innovative engagement monitoring solutions based on players'…
Descriptors: Case Studies, Questionnaires, Electronic Learning, Educational Games
Ting, Choo-Yee; Ho, Chiung Ching – British Journal of Educational Technology, 2015
This paper presents the dataset collected from student interactions with INQPRO, a computer-based scientific inquiry learning environment. The dataset contains records of 100 students and is divided into two portions. The first portion comprises (1) "raw log data", capturing the student's name, interfaces visited, the interface…
Descriptors: Inquiry, Educational Environment, Scientific Methodology, Interaction
Saini, Sheetal – ProQuest LLC, 2012
Rapid advances in data-rich domains of science, technology, and business has amplified the computational challenges of "Big Data" synthesis necessary to slow the widening gap between the rate at which the data is being collected and analyzed for knowledge. This has led to the renewed need for efficient and accurate algorithms, framework,…
Descriptors: Data Analysis, Data Processing, Classification, Mathematics

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