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Showing 1 to 15 of 38 results Save | Export
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Gregory Chernov – Evaluation Review, 2025
Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most…
Descriptors: Replication (Evaluation), Prediction, Scientific Research, Failure
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Khajonmote, Withamon; Chinsook, Kittipong; Klintawon, Sununta; Sakulthai, Chaiyan; Leamsakul, Wicha; Jansawang, Natchanok; Jantakoon, Thada – Journal of Education and Learning, 2022
The system architecture of big data in massive open online courses (BD-MOOCs System Architecture) is composed of six components. The first component was comprised of big data tools and technologies such as Hadoop, YARN, HDFS, Spark, Hive, Sqoop, and Flume. The second component was educational data science, which is composed of the following four…
Descriptors: MOOCs, Data Collection, Student Behavior, Computer Software
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Lorusso, Nicholas S.; Gemmellaro, M. Denise – Biochemistry and Molecular Biology Education, 2023
One significant impact of the COVID-19 pandemic for educators in forensic science was adapting what is traditionally a very applied field to a virtual learning environment. Because of this, science classes with a practical laboratory component had to implement significant adjustments to ensure that student learning objectives were still met,…
Descriptors: Crime, Science Education, Distance Education, Electronic Learning
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Worsley, Marcelo; Martinez-Maldonado, Roberto; D'Angelo, Cynthia – Journal of Learning Analytics, 2021
Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (LASI). In this paper, we articulate a set of 12…
Descriptors: Learning Analytics, Artificial Intelligence, Data Collection, Statistical Inference
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Wright, Suzie; Watson, Jane; Smith, Caroline; Fitzallen, Noleine – Teaching Science, 2021
Life would not be possible without plants. Plants supply food to many organisms (including people), produce oxygen, absorb carbon dioxide from the air, provide products for human use, and homes for many other living things. It is not surprising, therefore, that plant growth is a familiar topic in the primary school science curriculum. This paper…
Descriptors: Science Instruction, Plants (Botany), Grade 6, STEM Education
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Callanan, Gerard A.; Perri, David F.; Tomkowicz, Sandra M. – Journal of Education for Business, 2018
The authors present a pedagogical primer on the highly controversial business strategies of data mining and automated prediction. They provide a summary that allows business professors and students the opportunity to better understand the privacy and ethical issues that arise from high-tech, Internet-based organizations implementing programs to…
Descriptors: Automation, Prediction, Discussion (Teaching Technique), Privacy
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Zehner, Fabian; Eichmann, Beate; Deribo, Tobias; Harrison, Scott; Bengs, Daniel; Andersen, Nico; Hahnel, Carolin – Journal of Educational Data Mining, 2021
The NAEP EDM Competition required participants to predict efficient test-taking behavior based on log data. This paper describes our top-down approach for engineering features by means of psychometric modeling, aiming at machine learning for the predictive classification task. For feature engineering, we employed, among others, the Log-Normal…
Descriptors: National Competency Tests, Engineering Education, Data Collection, Data Analysis
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Hansen, David M. – Strategic Enrollment Management Quarterly, 2020
In recent years we have developed a data analytics pipeline using artificial neural networks to predict prospective student matriculation for university admissions using very limited demographic data. Predictions are generated at the earliest stages of the admissions process and successfully inform recruiting and admissions staff about the…
Descriptors: Artificial Intelligence, Data Analysis, College Admission, Enrollment Management
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Pierratos, Theodoros – Physics Education, 2021
Due to the conditions imposed worldwide by the pandemic, students' access to school laboratories is limited, if not impossible. To provide students with raw experimental data to assess, analyse and reason out, we have filmed experiments that can be used in a flipped classroom. This paper presents an experiment which makes use of an array of six…
Descriptors: Science Instruction, Physics, Flipped Classroom, Science Laboratories
Porter, Kristin E.; Balu, Rekha; Hendra, Richard – MDRC, 2017
This post is one in a series highlighting MDRC's methodological work. Contributors discuss the refinement and practical use of research methods being employed across the organization. Across policy domains, practitioners and researchers are benefiting from a trend of greater access to both more detailed and frequent data and the increased…
Descriptors: Social Services, At Risk Persons, Caseworker Approach, Probability
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Drachsler, H.; Kalz, M. – Journal of Computer Assisted Learning, 2016
The article deals with the interplay between learning analytics and massive open online courses (MOOCs) and provides a conceptual framework to situate ongoing research in the MOOC and learning analytics innovation cycle (MOLAC framework). The MOLAC framework is organized on three levels: On the micro-level, the data collection and analytics…
Descriptors: Online Courses, Data Collection, Data Analysis, Reflection
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Bush, Sarah B.; Albanese, Judith; Karp, Karen S. – Mathematics Teaching in the Middle School, 2016
Historically, some baby names have been more popular during a specific time span, whereas other names are considered timeless. The Internet article, "How to Tell Someone's Age When All You Know Is Her Name" (Silver and McCann 2014), describes the phenomenon of the rise and fall of name popularity, which served as a catalyst for the…
Descriptors: Mathematics Instruction, Grade 6, Prediction, Data Collection
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Baker, Ryan S. – International Journal of Artificial Intelligence in Education, 2016
The initial vision for intelligent tutoring systems involved powerful, multi-faceted systems that would leverage rich models of students and pedagogies to create complex learning interactions. But the intelligent tutoring systems used at scale today are much simpler. In this article, I present hypotheses on the factors underlying this development,…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Hypothesis Testing, Data Collection
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Casey, Kevin – Journal of Learning Analytics, 2017
Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…
Descriptors: Keyboarding (Data Entry), Educational Research, Data Collection, Data Analysis
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Hunnicutt, Sally S.; Grushow, Alexander; Whitnell, Robert – Journal of Chemical Education, 2015
The POGIL-PCL project implements the principles of process-oriented, guided-inquiry learning (POGIL) in order to improve student learning in the physical chemistry laboratory (PCL) course. The inquiry-based physical chemistry experiments being developed emphasize modeling of chemical phenomena. In each experiment, students work through at least…
Descriptors: Inquiry, Science Instruction, Science Experiments, Chemistry
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