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Pytlarz, Ian; Pu, Shi; Patel, Monal; Prabhu, Rajini – International Educational Data Mining Society, 2018
Identifying at-risk students at an early stage is a challenging task for colleges and universities. In this paper, we use students' oncampus network traffic volume to construct several useful features in predicting their first semester GPA. In particular, we build proxies for their attendance, class engagement, and out-of-class study hours based…
Descriptors: College Freshmen, Grade Point Average, At Risk Students, Academic Achievement
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Gitinabard, Niki; Barnes, Tiffany; Heckman, Sarah; Lynch, Collin F. – International Educational Data Mining Society, 2019
Students' interactions with online tools can provide us with insights into their study and work habits. Prior research has shown that these habits, even as simple as the number of actions or the time spent on online platforms can distinguish between the higher performing students and low-performers. These habits are also often used to predict…
Descriptors: Blended Learning, Student Adjustment, Online Courses, Study Habits
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Griesbaum, Joachim; Thadathil, Tessy; März, Sophie – International Association for Development of the Information Society, 2019
This paper investigates learning related device usage of German and Indian students. For that purpose, an exploratory survey of students at the University of Hildesheim and the Symbiosis College of Arts and Commerce in Pune is executed. The aim of the research is to uncover basic patterns of overall device usage, studying behavior, employment of…
Descriptors: Student Surveys, Cross Cultural Studies, Student Needs, Electronic Learning
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Sibanyoni, Nhlanhla A.; Alexander, Patricia M. – International Association for Development of the Information Society, 2018
In theory, educational applications that are engaging and motivating should easily persuade learners to use a mobile device for studying. Since this technology is already familiar to learners, mobile learning should be easily accessible; given a suitable m-learning application, learners could practice mathematics anytime or anywhere. LevelUp is an…
Descriptors: Foreign Countries, Electronic Learning, Technology Uses in Education, Handheld Devices
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Allen, Keith; Hoyle, Amelia; Zhu, Fengkan; Husley, Jalen – AERA Online Paper Repository, 2017
This study on college student success examines factors students attribute toward improving their academic performance in college. Open coding, content analysis, and analytic induction methods were used to examine responses from 478 undergraduate students at an R-1 highly active, public research university in the southeastern region of the US. The…
Descriptors: Student Attitudes, College Students, Attribution Theory, Academic Achievement
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Dorime-Williams, Marjorie L.; Giani, Matt – AERA Online Paper Repository, 2016
Participation rates in postsecondary education vary greatly by race, ethnicity, gender, and socioeconomic status (SES). In addition to issues of access, there are also problems with retention and persistence across higher education; improving retention and degree attainment for students continues to be an issue for higher education professionals.…
Descriptors: Undergraduate Students, Student Participation, Racial Differences, Ethnicity
Werner, Katharina; Woessmann, Ludger – Annenberg Institute for School Reform at Brown University, 2021
If school closures and social-distancing experiences during the COVID-19 pandemic impeded children's skill development, they may leave a lasting legacy in human capital. To understand the pandemic's effects on school children, this paper combines a review of the emerging international literature with new evidence from German longitudinal time-use…
Descriptors: COVID-19, Pandemics, School Closing, Foreign Countries
Layng, Joe; Redding, Sam – Center on Innovations in Learning, Temple University, 2016
This field report is the seventh in a series produced by the Center on Innovations in Learning's League of Innovators. The series describes, discusses, and analyzes policies and practices that enable personalization in education. This report introduces sessions from the "Conversations with Innovators" event held at Temple University,…
Descriptors: Minimum Competencies, Minimum Competency Testing, Measurement Techniques, Academic Standards
Gentry, Ruben; Stokes, Dorothy – Online Submission, 2016
Many African Americans were imbued with the cliché that they must work twice as hard as others to be a success in life. Entering college, students with this belief put extensive effort into earning top grades to ensure quality preparation for their chosen career; yet, some fail to earn top scores. Why? This is the million dollar question, but the…
Descriptors: African American Students, College Students, Scores, Academic Achievement
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Lee, Ji Eun; Recker, Mimi M. – AERA Online Paper Repository, 2017
We describe the application of the Evidence-Centered Design (ECD) framework to measure the self-regulated learning (SRL) strategies of students' enrolled in an online mathematics course by using their trace logs captured by a Learning Management System (LMS). We found that the ECD framework was helpful in building evidentiary arguments for…
Descriptors: Learning Strategies, Integrated Learning Systems, Educational Technology, Technology Uses in Education
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Ren, Zhiyun; Rangwala, Huzefa; Johri, Aditya – International Educational Data Mining Society, 2016
The past few years has seen the rapid growth of data mining approaches for the analysis of data obtained from Massive Open Online Courses (MOOCs). The objectives of this study are to develop approaches to predict the scores a student may achieve on a given grade-related assessment based on information, considered as prior performance or prior…
Descriptors: Large Group Instruction, Online Courses, Educational Technology, Technology Uses in Education
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Kuo, Ying-Ying; Luo, Juan; Brielmaier, Jennifer – AERA Online Paper Repository, 2016
This study investigated student learning behaviors in a fully online psychology course in which students controlled their own course content usage. Data collection included students' real usage of the Blackboard course site over three semesters in 2014 and 2015, as well as a course survey at the end of each semester. Data mining techniques, such…
Descriptors: Student Behavior, Learning Processes, Online Courses, Learner Controlled Instruction
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Sibanyoni, Nhlanhla A.; Alexander, Patricia M. – International Association for Development of the Information Society, 2017
Good study behaviour after school hours is an important way of improving learners' chances of success. Learners, once they reach high school, particularly require support that will assist them to study effectively outside the classroom. South African schools are under pressure to improve results in mathematics but besides the homework that schools…
Descriptors: Mathematics Instruction, Handheld Devices, Telecommunications, Case Studies
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Plavšic, Marlena; Dikovic, Marina – Bulgarian Comparative Education Society, 2015
One of the roles of higher education is to prepare and encourage students for lifelong learning. However, no evidence can be found about students' plans for further learning and teaching related to formal, non-formal and informal context. The purpose of this study was to explore these students' plans in relation to their study group, level of…
Descriptors: Lifelong Learning, Informal Education, Nonformal Education, Conventional Instruction
Leong, Yew Hoong; Yap, Sook Fwe; Tay, Eng Guan – Mathematics Education Research Group of Australasia, 2013
In this paper, we propose and describe in some detail a framework for helping low achievers in mathematics that attends to the following areas: Mathematical content resources, Problem Solving disposition, Feelings towards the learning of mathematics, and Study habits.
Descriptors: Mathematics Achievement, Low Achievement, Problem Solving, Student Attitudes
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