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Hanqiang Liu; Xiao Chen; Feng Zhao – Education and Information Technologies, 2024
Massive open online courses (MOOCs) have become one of the most popular ways of learning in recent years due to their flexibility and convenience. However, high dropout rate has become a prominent problem that hinders the further development of MOOCs. Therefore, the prediction of student dropouts is the key to further enhance the MOOCs platform.…
Descriptors: MOOCs, Video Technology, Behavior Patterns, Prediction
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Nuo Cheng; Wei Zhao; Xiaoqing Xu; Hongxia Liu; Jinhong Tao – Education and Information Technologies, 2024
Learning analytics dashboards are becoming increasingly common tools for providing feedback to learners. However, there is limited empirical evidence regarding the effects of learning analytics dashboard design features on learners' cognitive load, particularly in digital learning environments. To address this gap, we developed goal-based,…
Descriptors: Learning Analytics, Learning Management Systems, Cognitive Ability, Online Courses
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Hui Han; Silvana Trimi – Education and Information Technologies, 2024
Cloud computing-based online education has played a vital role in enabling uninterrupted learning during crises such as the COVID-19 pandemic. This study explored the key variables associated with cloud computing that can effectively support the operation of online education platforms. By analyzing real data from 63 online learning platforms, the…
Descriptors: Computer Software, Learning Management Systems, Online Courses, Correlation
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Guang Jiang; Jiahui Zhu; Yunsong Li; Pengcheng An; Yunlong Wang – Education and Information Technologies, 2024
Teacher-student interaction (TSI) is essential for learning efficiency and harmonious teacher-student interpersonal relationships. However, studies on TSI support tools often focus on teacher needs while neglecting student needs and autonomy. To enhance both lecturer competence in delivering interpersonal interaction and student autonomy in TSI,…
Descriptors: Teacher Student Relationship, Computer Software, Teaching Methods, Computer Simulation
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Macak, Martin; Kruzelova, Daniela; Chren, Stanislav; Buhnova, Barbora – Education and Information Technologies, 2021
Understanding the processes in education, such as the student learning behavior within a specific course, is a key to continuous course improvement. In online learning systems, students' learning can be tracked and examined based on data collected by the systems themselves. However, it is non-trivial to decide how to extract the desired students'…
Descriptors: Student Projects, Learning Analytics, Data Collection, Computer Science Education
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Karolína Dockalová Burská; Jakub Rudolf Mlynárik; Radek Ošlejšek – Education and Information Technologies, 2024
In cyber security education, hands-on training is a common type of exercise to help raise awareness and competence, and improve students' cybersecurity skills. To be able to measure the impact of the design of the particular courses, the designers need methods that can reveal hidden patterns in trainee behavior. However, the support of the…
Descriptors: Computer Science Education, Information Security, Computer Security, Training Methods
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Eryilmaz, Evren; Thoms, Brian; Ahmed, Zafor; Lee, Kuo-Hao – Education and Information Technologies, 2021
As asynchronous online discussions gain a broader usage due to the COVID-19 epidemic, the need for understanding of students' ideas from unstructured textual data becomes more pressing. In this experimental study, we examine the effects of recommendations on message quality and community formation from voluminous online discussions. Drawing on…
Descriptors: Asynchronous Communication, Computer Mediated Communication, Cooperative Learning, Learning Analytics
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Yunus Kökver; Hüseyin Miraç Pektas; Harun Çelik – Education and Information Technologies, 2025
This study aims to determine the misconceptions of teacher candidates about the greenhouse effect concept by using Artificial Intelligence (AI) algorithm instead of human experts. The Knowledge Discovery from Data (KDD) process model was preferred in the study where the Analyse, Design, Develop, Implement, Evaluate (ADDIE) instructional design…
Descriptors: Artificial Intelligence, Misconceptions, Preservice Teachers, Natural Language Processing
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Mutahar Qassem; Buthainah M. Al Thowaini – Education and Information Technologies, 2024
Leveraging technological tools in educational research expands investigations into participants' behaviors and provides insights into learning patterns and teaching effectiveness through innovative data collection and analysis methods. Using keylogging data software, this study explored trainee translators' process and product behaviors under two…
Descriptors: Journalism, Translation, Keyboarding (Data Entry), Language Processing
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Parhizkar, Amirmohammad; Tejeddin, Golnaz; Khatibi, Toktam – Education and Information Technologies, 2023
Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…
Descriptors: Algorithms, Grade Point Average, Interdisciplinary Approach, Prediction