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Chun Yan Enoch Sit; Siu-Cheung Kong – Journal of Educational Computing Research, 2024
Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…
Descriptors: Learning Processes, Learning Analytics, Algorithms, Guidelines
A Learning Assistance Framework for Supporting and Analyzing Student Teams in Project-Based Learning
Youcef Haddou; Omar Talbi; Abdelkader Ouared; Abdelhafid Chadli – Education and Information Technologies, 2025
As Project-Based Learning (PjBL) becomes a cornerstone of modern education, effective support and analysis tools are crucial for enhancing collaborative learning experiences and achieving educational goals. However, challenges such as managing overload related to the rigor and demands of project-based activities (e.g., meetings, writing reports,…
Descriptors: Student Projects, Active Learning, Guidelines, Teamwork
Amaya, Edna Johanna Chaparro; Restrepo-Calle, Felipe; Ramírez-Echeverry, Jhon J. – Journal of Information Technology Education: Research, 2023
Aim/Purpose: This article proposes a framework based on a sequential explanatory mixed-methods design in the learning analytics domain to enhance the models used to support the success of the learning process and the learner. The framework consists of three main phases: (1) quantitative data analysis; (2) qualitative data analysis; and (3)…
Descriptors: Learning Analytics, Guidelines, Student Attitudes, Learning Processes
Ahmad Faza; Ilyana Agri Lestari – International Review of Research in Open and Distributed Learning, 2025
When students enter higher education, self-regulated learning (SRL) involving goal setting, planning, monitoring, and reflection is crucial for academic success. This study systematically reviews SRL strategies, supporting technologies, and their impacts, especially with the shift to online learning due to the COVID-19 pandemic. Following…
Descriptors: Metacognition, Educational Benefits, Learning Management Systems, Goal Orientation
Yikai Lu; Teresa M. Ober; Cheng Liu; Ying Cheng – Grantee Submission, 2022
Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…
Descriptors: Prediction, Statistics Education, Data Analysis, Learning Analytics
Perez, Zeke, Jr.; von Zastrow, Claus – Education Commission of the States, 2023
Data governance is a core obligation for leaders and staff across any agency that collects, stores or uses individuals' data. It ensures that individuals' personal information is protected, and can support the continuous improvement of data quality and use, particularly when it includes well-defined processes, structure and responsibilities.…
Descriptors: Governance, Data Use, Privacy, Information Management
Dina Foster; Caitlin McLemore; Brandon Olszewski; Ali Chaudhry; Ekaterina Cooper; Laurie Forcier; Rose Luckin – UK Department for Education, 2023
A rapid, exploratory review to establish a shared understanding of what constitutes good quality EdTech and implementation. The review: (1) examined existing frameworks and standards; and (2) identified the characteristics, quality components, essential conditions and evaluation criteria for the design and implementation of EdTech. The report…
Descriptors: Standards, Educational Technology, Guidelines, Evidence Based Practice

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