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Göktepe Körpeoglu, Seda; Göktepe Yildiz, Sevda – Education and Information Technologies, 2023
Examining students' attitudes towards STEM (science, technology, engineering, and mathematics) fields starting from middle school level is important in their career choices and future planning. However, there is a need to investigate which variables affect students' attitudes towards STEM. Here, we aimed to estimate middle school students'…
Descriptors: Comparative Analysis, Algorithms, Data Collection, Student Attitudes
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Nahar, Khaledun; Shova, Boishakhe Islam; Ria, Tahmina; Rashid, Humayara Binte; Islam, A. H. M. Saiful – Education and Information Technologies, 2021
Information is everywhere in a hidden and scattered way. It becomes useful when we apply Data mining to extracts the hidden, meaningful, and potentially useful patterns from these vast data resources. Educational data mining ensures a quality education by analyzing educational data based on various aspects. In this paper, we have analyzed the…
Descriptors: Learning Analytics, College Students, Engineering Education, Data Collection
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Harvey, Annelie J.; Keyes, Helen – Innovations in Education and Teaching International, 2020
Learning Dashboards display analytics pertaining to student performance and attainment, often alongside scores for the class cohort average. Little research has considered the effects of this social comparison information on students' well-being, motivation, and engagement. The current study presented participants with hypothetical data that…
Descriptors: Self Esteem, College Students, Student Motivation, Information Management
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Strong, Kimberly Ann; Escamilla, Kathy – Bilingual Research Journal, 2020
Federal law requires states and school districts to institute accountability systems that report disaggregated student data to ensure that all children make academic progress. However, one of the mandated categories for disaggregation -- English Learner (EL) -- is reported as a single group despite representing students who are beginning,…
Descriptors: Language Proficiency, Accountability, Academic Achievement, English Language Learners
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Aguilar, Stephen J. – Journal of Research on Technology in Education, 2018
This qualitative study focuses on capturing students' understanding two visualizations often utilized by learning analytics-based educational technologies: bar graphs, and line graphs. It is framed by Achievement Goal Theory--a prominent theory of students' academic motivation--and utilizes interviews (n = 60) to investigate how students at risk…
Descriptors: Comparative Analysis, Visualization, At Risk Students, College Students
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Beemer, Joshua; Spoon, Kelly; Fan, Juanjuan; Stronach, Jeanne; Frazee, James P.; Bohonak, Andrew J.; Levine, Richard A. – Journal of Statistics Education, 2018
Estimating the efficacy of different instructional modalities, techniques, and interventions is challenging because teaching style covaries with instructor, and the typical student only takes a course once. We introduce the individualized treatment effect (ITE) from analyses of personalized medicine as a means to quantify individual student…
Descriptors: Learning Modalities, Academic Achievement, Intervention, Educational Research
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Williamson, Ben – Journal of Education Policy, 2016
Educational institutions and governing practices are increasingly augmented with digital database technologies that function as new kinds of policy instruments. This article surveys and maps the landscape of digital policy instrumentation in education and provides two detailed case studies of new digital data systems. The Learning Curve is a…
Descriptors: Visualization, Synchronous Communication, Governance, Data Collection
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Shin, Youhyun; Park, Junghyuk; Lee, Sang-goo – Interactive Learning Environments, 2018
Blended learning has steadily gained in popularity at the higher levels of education. This marks a change in pedagogical approaches from one-directional instruction to an interactive and technology-aided class. However, to manage fluent in-class activities and proper data analysis, real-time and fine-grained data collection activities are still…
Descriptors: Class Activities, Data Collection, Blended Learning, Feedback (Response)
Strecht, Pedro; Cruz, Luís; Soares, Carlos; Mendes-Moreira, João; Abreu, Rui – International Educational Data Mining Society, 2015
Predicting the success or failure of a student in a course or program is a problem that has recently been addressed using data mining techniques. In this paper we evaluate some of the most popular classification and regression algorithms on this problem. We address two problems: prediction of approval/failure and prediction of grade. The former is…
Descriptors: Comparative Analysis, Classification, Regression (Statistics), Mathematics
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Bendjebar, Safia; Lafifi, Yacine; Zedadra, Amina – International Journal of Distance Education Technologies, 2016
In e-learning systems, tutors have a significant impact on learners' life to increase their knowledge level and to make the learning process more effective. They are characterized by different features. Therefore, identifying tutoring styles is a critical step in understanding the preference of tutors on how to organize and help the learners. In…
Descriptors: Tutors, Tutoring, Tutor Training, Tutorial Programs
de Velasco, Jorge Ruiz; Gonzales, Daisy – Policy Analysis for California Education, PACE, 2017
California's alternative education options for youth vulnerable to dropping out of school have been established at different historical points and for different student age and target populations. For purposes of this brief, "alternative school" is defined as belonging to one of six legislatively authorized types of public (non-charter)…
Descriptors: Nontraditional Education, Accountability, Comparative Analysis, Alignment (Education)
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Carver, Lin B.; Mukherjee, Keya; Lucio, Robert – Online Learning, 2017
Online education is rapidly becoming a significant method of course delivery in higher education. Consequently, instructors analyze student performance in an attempt to better scaffold student learning. Learning analytics can provide insight into online students' course behaviors. Archival data from 167 graduate level education students enrolled…
Descriptors: Graduate Students, Correlation, Grades (Scholastic), Time on Task
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Ye, Li; Oueini, Razanne; Dickerson, Austin P.; Lewis, Scott E. – Chemistry Education Research and Practice, 2015
This study used a series of text message inquiries sent to General Chemistry students asking: "Have you studied for General Chemistry I in the past 48 hours? If so, how did you study?" This method for collecting data is novel to chemistry education research so the first research goals were to investigate the feasibility of the technique…
Descriptors: Computer Mediated Communication, Telecommunications, Science Instruction, Chemistry
Sweeney, Irene O. – ProQuest LLC, 2014
The inquiry to be addressed in this Action Research Study (ARS) is the effective teaching modality that will increase the class average pass rate and reduce the percent of students who do not score 850 or above on the HESI-RN exams. The researcher's intent was to provide data in support of a collaborative teaching environment in which to…
Descriptors: Action Research, Team Teaching, Nursing Students, Teacher Effectiveness
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Pinho-Lopes, Margarida; Macedo, Joaquim – European Journal of Engineering Education, 2016
Since 2007/2008 project-based learning models have been used to deliver two fundamental courses on Geotechnics in University of Aveiro, Portugal. These models have evolved and have encompassed either cooperative or collaborative teamwork. Using data collected in five editions of each course (Soil Mechanics I and Soil Mechanics II), the different…
Descriptors: Foreign Countries, Active Learning, Student Projects, Engineering Education
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