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Lenhart, Cindy; Bouwma-Gearhart, Jana – Education Sciences, 2021
This paper explores the affordances and constraints of STEM faculty members' instructional data-use practices and how they engage students (or not) in reflection around their own learning data. We found faculty used a wide variety of instructional data-use practices. We also found several constraints that influenced their instructional data-use…
Descriptors: STEM Education, Data Use, Reflection, College Faculty
Huang, Changqin; Han, Zhongmei; Li, Ming; Wang, Xizhe; Zhao, Wenzhu – Australasian Journal of Educational Technology, 2021
Sentiment evolution is a key component of interactions in blended learning. Although interactions have attracted considerable attention in online learning contexts, there is scant research on examining sentiment evolution over different interactions in blended learning environments. Thus, in this study, sentiment evolution at different interaction…
Descriptors: Learning Analytics, Interaction, Blended Learning, Electronic Learning
Yilmaz, Fahri; Çakir, Hasan – Journal of Learning and Teaching in Digital Age, 2021
The purpose of this study is to define learning analytics, to introduce concepts related to learning analytics and to introduce potential study topics related to learning analytics. Today's education model has changed with evolving social and economic conditions over time. This change in education has created such new situations as individualized…
Descriptors: Learning Analytics, Definitions, Educational Change, Individualized Instruction
Patel, Nirmal; Sharma, Aditya; Shah, Tirth; Lomas, Derek – Journal of Educational Data Mining, 2021
Process Analysis is an emerging approach to discover meaningful knowledge from temporal educational data. The study presented in this paper shows how we used Process Analysis methods on the National Assessment of Educational Progress (NAEP) test data for modeling and predicting student test-taking behavior. Our process-oriented data exploration…
Descriptors: Learning Analytics, National Competency Tests, Evaluation Methods, Prediction
Palit, Shamik; Roy, Chandrima Sinha – International Society for Technology, Education, and Science, 2021
Big Data Technology (BDT) and Analytics have gained immense recognition in recent years. BDT plays an essential role in various sectors. This study intends to provide a review of BDT in the education sector which includes analyzing, predicting learner's results based on behavior patterns, assessing their performance regularly. Education…
Descriptors: Learning Analytics, Data Analysis, Educational Administration, Educational Improvement
Saleeb, Noha – International Journal of Information and Learning Technology, 2021
Purpose: One of the misconceptions of teaching and learning for practical-based programmes, such as engineering, sciences, architecture, design and arts, is the necessity to deliver via face-to-face physical modality. This paper refutes this claim by providing case studies of best practices in delivering such courses and their hands-on skillsets…
Descriptors: Learning Analytics, Computer Simulation, Educational Environment, Electronic Learning
Zhang, Qiao; Maclellan, Christopher J. – International Educational Data Mining Society, 2021
Knowledge tracing algorithms are embedded in Intelligent Tutoring Systems (ITS) to keep track of students' learning process. While knowledge tracing models have been extensively studied in offline settings, very little work has explored their use in online settings. This is primarily because conducting experiments to evaluate and select knowledge…
Descriptors: Electronic Learning, Mastery Learning, Computer Simulation, Intelligent Tutoring Systems
Zhang, Mo; Guo, Hongwen; Liu, Xiang – International Educational Data Mining Society, 2021
We present an empirical study on the use of keystroke analytics to capture and understand how writers manage their time and make inferences on how they allocate their cognitive resources during essay writing. The results suggest three distinct longitudinal patterns of writing process that describe how writers approach an essay task in a writing…
Descriptors: Keyboarding (Data Entry), Learning Analytics, Data Collection, Cognitive Processes
Shi, Yang; Schmucker, Robin; Chi, Min; Barnes, Tiffany; Price, Thomas – International Educational Data Mining Society, 2023
Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…
Descriptors: Computer Science Education, Data Analysis, Programming, Coding
Khan, Md Akib Zabed; Polyzou, Agoritsa – International Educational Data Mining Society, 2023
Academic advising plays an important role in students' decision-making in higher education. Data-driven methods provide useful recommendations to students to help them with degree completion. Several course recommendation models have been proposed in the literature to recommend courses for the next semester. One aspect of the data that has yet to…
Descriptors: Course Selection (Students), Learning Analytics, Academic Advising, Decision Making
Aziman Abdullah – International Society for Technology, Education, and Science, 2023
This study explores the potential of using screen time data in learning management systems (LMS) to estimate student learning time (SLT) and validate the credit value of courses. Gathering comprehensive data on actual student learning time is difficult, so this study uses LMS Moodle logs from a computer programming course with 490 students over 16…
Descriptors: Time Factors (Learning), Handheld Devices, Computer Use, Television Viewing
Tran, Tich Phuoc; Meacheam, David – IEEE Transactions on Learning Technologies, 2020
The use of learning management systems (LMSs) for learning and knowledge sharing has accelerated quickly both in education and corporate worlds. Despite the benefits brought by LMSs, the current systems still face significant challenges, including the lack of automation in generating quiz questions and managing courses. Over the past decade, more…
Descriptors: Integrated Learning Systems, Test Construction, Test Items, Automation
Camacho, Vicente Lopez; de la Guia, Elena; Olivares, Teresa; Flores, M. Julia; Orozco-Barbosa, Luis – IEEE Transactions on Learning Technologies, 2020
Increasing school dropout rates are a problem in many educational systems, with student disengagement being one significant factor. Learning analytics is a new field with a key role in educational institutions in the coming years. It may help make strategic decisions to reduce student disengagement. The use of technology in educational…
Descriptors: Learning Analytics, Learner Engagement, Measurement Equipment, Technology Uses in Education
Çebi, Ayça; Güyer, Tolga – Education and Information Technologies, 2020
In this study, students' interactions with different learning activities are examined and the relation among learning performance with different interaction patterns, learning performance, self-regulated learning (SRL) strategies and motivation is presented. Learning materials including different kinds of activities are prepared and presented to…
Descriptors: Interaction, Behavior Patterns, Learning Analytics, Electronic Learning
Han, Jeongyun; Huh, Sun Young; Cho, Young Hoan; Park, SoHyun; Choi, Jinhan; Suh, Bongwon; Rhee, Wonjong – Educational Technology Research and Development, 2020
This study investigates the possibility of utilizing online learning data to design face-to-face activities in a flipped classroom. We focus on heterogeneous group formation for effective collaborative learning. Fifty-three undergraduate students (18 males, 35 females) participated in this study, and 8 students (3 males, 5 females) among them…
Descriptors: Electronic Learning, Learning Analytics, Data Use, Synchronous Communication