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Quadir, Benazir; Chen, Nian-Shing; Isaias, Pedro – Interactive Learning Environments, 2022
The purpose of this study is to review journal papers on educational big data research published from 2010 to 2018. A total of 143 papers were selected. The papers were characterized based on three dimensions: (a) educational goals; (b) educational problems addressed; and (c) big data analytical techniques used. A qualitative content analysis…
Descriptors: Data, Educational Research, Educational Objectives, Data Analysis
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Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology
Simonsen, Brandi; Freeman, Jen; Swain-Bradway, Jessica; George, Heather Peshak; Putnam, Robert; Lane, Kathleen Lynne; Sprague, Jeffrey; Hershfeldt, Patti – Education and Treatment of Children, 2019
Research suggests (a) students benefit when educators implement positive and proactive classroom behavior support practices (e.g., maximizing structure, teaching expected behaviors, delivering engaging instruction) and (b) educators benefit when school leadership teams invest in positive and proactive professional development support systems…
Descriptors: Positive Behavior Supports, Student Behavior, Teaching Methods, Classroom Techniques
Center on Positive Behavioral Interventions and Supports, 2022
This practice guide is an updated version of "Supporting and Responding to Behavior: Evidence-based Classroom Strategies for Teachers" (see ED619696) that replaces, rather than supplements, the first version. This guide summarizes evidence-based, positive, and proactive practices that support and respond to students' social, emotional,…
Descriptors: Evidence Based Practice, Student Behavior, Intervention, Classroom Techniques
Himmele, Pérsida; Himmele, William – ASCD, 2021
Old habits die hard, particularly when they are part of the unexamined norms of schooling. In "Why Are We Still Doing That?," the best-selling authors of "Total Participation Techniques" lead a teacher-positive, empathetic inquiry into 16 common educational practices that can undermine student learning: (1) Round robin reading;…
Descriptors: Teaching Methods, Educational Practices, Elementary Secondary Education, Reading Instruction
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Pereira, Filipe D.; Oliveira, Elaine H. T.; Oliveira, David B. F.; Cristea, Alexandra I.; Carvalho, Leandro S. G.; Fonseca, Samuel C.; Toda, Armando; Isotani, Seiji – British Journal of Educational Technology, 2020
Tools for automatic grading programming assignments, also known as Online Judges, have been widely used to support computer science (CS) courses. Nevertheless, few studies have used these tools to acquire and analyse interaction data to better understand the students' performance and behaviours, often due to data availability or inadequate…
Descriptors: Introductory Courses, Programming, Outcomes of Education, Student Behavior
Center on Positive Behavioral Interventions and Supports, 2023
This practice guide is one of a set of resources for increasing equity in school discipline. The guides are based on the Center on PBIS's 5-Point Equity Approach, which has been shown to be effective in increasing equity in schools (link to…
Descriptors: Discipline, Data Use, Behavior Modification, Student Behavior
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Allbright, Taylor; Hough, Heather – State Education Standard, 2020
California's CORE Districts--a consortium of eight school districts serving a racially and socioeconomically diverse population of over one million students--have since 2014 led the way in deploying measures of social and emotional learning (SEL) and school climate and culture. Influenced by surging interest and research support over the past…
Descriptors: Social Development, Emotional Development, Elementary Secondary Education, Holistic Approach
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Araka, Eric; Oboko, Robert; Maina, Elizaphan; Gitonga, Rhoda – International Review of Research in Open and Distributed Learning, 2022
With the increased emphasis on the benefits of self-regulated learning (SRL), it is important to make use of the huge amounts of educational data generated from online learning environments to identify the appropriate educational data mining (EDM) techniques that can help explore and understand online learners' behavioral patterns. Understanding…
Descriptors: Data Analysis, Metacognition, Comparative Analysis, Behavior Patterns
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Kam Hong Shum; Samuel Kai Wah Chu; Cheuk Yu Yeung – Interactive Learning Environments, 2023
This study examines the use of data analytics to evaluate students' behaviours during their participation in an online collaborative learning environment called SkyApp. To visualise the learning traits of engagement, emotion and motivation, students' inputs and activity data were captured and quantified for analysis. Experiments were first carried…
Descriptors: Student Behavior, Online Courses, Cooperative Learning, Computer Software
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Livieris, Ioannis E.; Drakopoulou, Konstantina; Tampakas, Vassilis T.; Mikropoulos, Tassos A.; Pintelas, Panagiotis – Journal of Educational Computing Research, 2019
Educational data mining constitutes a recent research field which gained popularity over the last decade because of its ability to monitor students' academic performance and predict future progression. Numerous machine learning techniques and especially supervised learning algorithms have been applied to develop accurate models to predict…
Descriptors: Secondary School Students, Academic Achievement, Teaching Methods, Student Behavior
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de Carvalho, Walisson Ferreira; Zárate, Luis Enrique – International Journal of Information and Learning Technology, 2021
Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…
Descriptors: Causal Models, Algorithms, Learning Analytics, Correlation
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Cenka, Baginda Anggun Nan; Santoso, Harry B.; Junus, Kasiyah – Knowledge Management & E-Learning, 2022
Online learning implementation has been growing year by year across countries, including Indonesia. Many higher education institutions use a Learning Management System (LMS) to facilitate online learning. Unfortunately, many issues arise during online learning implementation, such as a lack of student behaviour monitoring. This study adopts an…
Descriptors: Knowledge Management, Electronic Learning, Integrated Learning Systems, Student Behavior
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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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Yeung, Cheuk Yu; Shum, Kam Hong; Hui, Lucas Chi Kwong; Chu, Samuel Kai Wah; Chan, Tsing Yun; Kuo, Yung Nin; Ng, Yee Ling – International Association for Development of the Information Society, 2017
Attributes of teaching and learning contexts provide rich information about how students participate in learning activities. By tracking and analyzing snapshots of these attributes captured continuously throughout the duration of the learning activities, teachers can identify individual students who need special attention and apply different…
Descriptors: Mathematics Instruction, Educational Technology, Technology Uses in Education, Handheld Devices
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