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Doran, Elizabeth; Li, Ann; Aikens, Nikki; Dang, Myley; Kopack Klein, Ashley; Reid, Natalie; Scott, Myah; Rakibullah, Sharika; Cannon, Judy; Harrington, Jeff; Larson, Addison; Bernstein, Sara; Tarullo, Louisa; Malone, Lizabeth – Office of Planning, Research and Evaluation, 2022
Head Start is a national program that helps young children from families with low incomes get ready to succeed in school. It does this by working to promote their early learning and health and their families' well-being. The Head Start Family and Child Experiences Survey (FACES) provides national information about Head Start programs and…
Descriptors: Social Services, Low Income Students, Federal Programs, Family Relationship
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Ong, Nathan; Zhu, Jiaye; Mossé, Daniel – International Educational Data Mining Society, 2022
Student grade prediction is a popular task for learning analytics, given grades are the traditional form of student performance. However, no matter the learning environment, student background, or domain content, there are things in common across most experiences in learning. In most previous machine learning models, previous grades are considered…
Descriptors: Prediction, Grades (Scholastic), Learning Analytics, Student Characteristics
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Yin, Chengjiu; Hwang, Gwo-Jen – Knowledge Management & E-Learning, 2018
E-books have been introduced to educational institutions in many countries. The use of e-books in traditional classrooms enables the recording of learning logs. Recently, researchers have begun to carry out learning analytics on the learning logs of e-books. However, there has been limited attention devoted to understanding the types of learning…
Descriptors: Electronic Publishing, Learning Analytics, Learning Strategies, Student Behavior
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Nguyen, Quan; Rienties, Bart; Whitelock, Denise – Journal of Learning Analytics, 2020
The use of analytical methods from learning analytics (LA) research combined with visualizations of learning activities using learning design (LD) tools and frameworks has provided important insight into how instructors design for learning. Nonetheless, there are many subtle nuances in instructors' design decisions that might not easily be…
Descriptors: Instructional Design, Online Courses, Distance Education, Electronic Learning
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Lancaster, Alia; Moses, Scott; Clark, Martyn; Masters, Megan C. – Journal of Learning Analytics, 2020
Learning management systems (LMSs) are ubiquitous components of the academic technology experience for learners across a wide variety of instructional contexts. Learners' interactions within an LMS are often contingent upon how instructors architect a module, course, or program of study. Patterns related to these learner interactions, often…
Descriptors: Writing Instruction, Instructional Design, Learning Analytics, Integrated Learning Systems
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Walsh, Chris; Mital, Abhinav; Ratcliff, Michael; Yap, Ana; Jamaledine, Zeina – Australasian Journal of Educational Technology, 2020
Online education often struggles to maintain a consistent, high quality academic experience. High attrition rates and low student satisfaction continue to challenge higher education providers. We present an innovative public-private partnership that delivers a resources-sufficient model of fully online postgraduate education with high levels of…
Descriptors: Partnerships in Education, Electronic Learning, Distance Education, Academic Support Services
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Crescenzi-Lanna, Lucrezia – British Journal of Educational Technology, 2020
Learning Analytics and Multimodal Learning Analytics are changing the way of analysing the learning process while students interact with an educational content. This paper presents a systematic literature review aimed at describing practices in recent Multimodal Learning Analytics and Learning Analytics research literature in order to identify…
Descriptors: Learning Modalities, Learning Analytics, Student Behavior, Progress Monitoring
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Hassad, Rossi A. – Statistics Education Research Journal, 2020
Training programs for statisticians and data scientists in healthcare should give greater importance to fostering inductive reasoning toward developing a mindset for optimizing Big Data. This can complement the current predominant focus on the hypothetico-deductive reasoning model, and is theoretically supported by the constructivist philosophy…
Descriptors: Statistics, Data Analysis, Data Collection, Logical Thinking
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Zhang, Jia-Hua; Zou, Liu-cong; Miao, Jia-jia; Zhang, Ye-Xing; Hwang, Gwo-Jen; Zhu, Yue – Interactive Learning Environments, 2020
Extensive studies have been conducted to diagnose and predict students' academic performance by analyzing a large amount of data related to their learning behaviors in a blended learning environment. But there is a lack of research examining how individualized learning interventions could improve students' academic performance in such a learning…
Descriptors: Individualized Instruction, Academic Achievement, Interaction, Blended Learning
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Rodgers, T. L.; Cheema, N.; Vasanth, S.; Jamshed, A.; Alfutimie, A.; Scully, P. J. – European Journal of Engineering Education, 2020
Laboratory practicals are used throughout science and engineering education as it allows students to undertake active learning and develop technical skills. It is therefore important that students arrive to these sessions as prepared as possible to maximise their learning potential. This paper analyses how student preparation affects how prepared…
Descriptors: Video Technology, Instructional Effectiveness, Grades (Scholastic), Chemical Engineering
Webber, Karen L., Ed.; Zheng, Henry, Ed. – Johns Hopkins University Press, 2020
The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound…
Descriptors: Data Use, Decision Making, Learning Analytics, Higher Education
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Bertrand Schneider; Joseph Reilly; Iulian Radu – Journal for STEM Education Research, 2020
In an increasingly data-driven world, large volumes of fine-grained data are infiltrating all aspects of our lives. The world of education is no exception to this phenomenon: in classrooms, we are witnessing an increasing amount of information being collected on learners and teachers. Because educational practitioners have so much contextual and…
Descriptors: Learning Analytics, Classroom Techniques, Multimedia Materials, Graduate Students
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Zhongzhou Chen; Tom Zhang; Michelle Taub – Journal of Learning Analytics, 2024
The current study measures the extent to which students' self-regulated learning tactics and learning outcomes change as the result of a deliberate, data-driven improvement in the learning design of mastery-based online learning modules. In the original design, students were required to attempt the assessment once before being allowed to access…
Descriptors: Learning Analytics, Algorithms, Instructional Materials, Course Content
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Peter Crosthwaite; Brett Steeples – Computer Assisted Language Learning, 2024
Corpus-based approaches to language and literacy education, commonly known as data-driven learning (DDL), are increasing in prominence. However, the vast majority of DDL interventions involve adult tertiary level learners, leaving a dire need for comprehensive DDL studies for secondary education. The present study reports on a half-year DDL…
Descriptors: Single Sex Schools, Females, Secondary School Students, Grammar
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Abdulkadir Palanci; Rabia Meryem Yilmaz; Zeynep Turan – Education and Information Technologies, 2024
This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…
Descriptors: Learning Analytics, Distance Education, Educational Trends, Periodicals
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