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Jie Wei – International Journal of Web-Based Learning and Teaching Technologies, 2024
Due to the growth of China's social economy and culture, the demand for psychology is becoming more and more urgent. Environmental health is the unity of people's behavioral health that constitutes the environment and environmental conditions that meet people's basic needs. In this paper, the improved a priori algorithm is combined with…
Descriptors: Foreign Countries, Chinese, English (Second Language), Bilingual Education
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Juanjuan Niu – International Journal of Web-Based Learning and Teaching Technologies, 2024
The internet, which is constantly advancing in technology, together with the rapidly changing internet communication technology terminals, has formed a new internet media, which has penetrated into all fields of human material life and spiritual life. This article proposes a design scheme for optimizing the impact of internet environment health on…
Descriptors: Influence of Technology, Internet, College Students, Ethical Instruction
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Jialun Pan; Zhanzhan Zhao; Dongkun Han – IEEE Transactions on Learning Technologies, 2025
Properly predicting students' academic performance is crucial for elevating educational outcomes in various disciplines. Through precise performance prediction, schools can quickly pinpoint students facing challenges and provide customized educational materials suited to their specific learning needs. The reliance on teachers' experience to…
Descriptors: Prediction, Academic Achievement, At Risk Students, Artificial Intelligence
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Jeff Ford; Rachel Erickson; Ha Le; Kaylee Vick; Jillian Downey – PRIMUS, 2024
In this study, we analyzed student participation and success in a college-level Calculus I course that utilized standards-based grading. By measuring the level to which students participate in this class structure, we were able to use a clustering algorithm that revealed multiple groupings of students that were distinct based on activity…
Descriptors: Calculus, Mathematics Instruction, Mathematics Achievement, Grades (Scholastic)
Taylor V. Williams – ProQuest LLC, 2022
Clustering, a prevalent class of machine learning (ML) algorithms used in data mining and pattern-finding--has increasingly helped engineering education researchers and educators see and understand assessment patterns at scale. However, a challenge remains to make ML-enabled educational inferences that are useful and reliable for research or…
Descriptors: Multivariate Analysis, Data Analysis, Student Evaluation, Large Group Instruction
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Hark Söylemez, Nesrin – Shanlax International Journal of Education, 2023
This study aims to determine the independent variables that have a significant effect on the level of students' adaptation to online education and their order of importance. Relational screening model was used in the study. Adaptability Level in Online Education dataset provided by Kaggle repository constitutes the main data source for this study.…
Descriptors: Student Adjustment, Online Courses, COVID-19, Pandemics
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Meaney, Michael J.; Fikes, Tom – Journal of Learning Analytics, 2023
This paper leverages cluster analysis to provide insight into how traditionally underrepresented learners engage with entry-level massive open online courses (MOOCs) intended to lower the barrier to university enrolment, produced by a major research university in the United States. From an initial sample of 260,239 learners, we cluster analyze a…
Descriptors: MOOCs, Ethics, Equal Education, Socioeconomic Status
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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
Wiggins, Afi Y.; Stelling, Laura – Online Submission, 2015
This supplemental report provides technical documentation for the full report (published separately) concerning the 63% of AISD's Class of 2013 graduates who enrolled in a postsecondary institution the year after high school, and 74% of Class of 2012 graduates persisted in college for a second year. [For the full report, see ED626498.]
Descriptors: Postsecondary Education, College Attendance, Enrollment Trends, High School Graduates