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Pramathevan, G. Sundari; Fraser, Barry J. – Learning Environments Research, 2020
Because there has been very little past research into gifted students' science learning environments, especially in Singapore, we selected from four established questionnaires six learning environment scales that are consistent with Van Tassel-Baska and Stambaugh's guidelines for gifted education. These scales were modified slightly to enhance…
Descriptors: Foreign Countries, Academically Gifted, Educational Environment, Science Instruction
Isaacs, Talia; Hu, Ruolin; Trenkic, Danijela; Varga, Julia – Language Testing, 2023
The COVID-19 pandemic has changed the university admissions and proficiency testing landscape. One change has been the meteoric rise in use of the fully automated Duolingo English Test (DET) for university entrance purposes, offering test-takers a cheaper, shorter, accessible alternative. This rapid response study is the first to investigate the…
Descriptors: Predictive Validity, Educational Technology, Handheld Devices, Language Tests
Mihai Dascalu; Scott A. Crossley; Danielle S. McNamara; Philippe Dessus; Stefan Trausan-Matu – Grantee Submission, 2018
A critical task for tutors is to provide learners with suitable reading materials in terms of difficulty. The challenge of this endeavor is increased by students' individual variability and the multiple levels in which complexity can vary, thus arguing for the necessity of automated systems to support teachers. This chapter describes…
Descriptors: Reading Materials, Difficulty Level, Natural Language Processing, Artificial Intelligence
Almeda, Ma. Victoria; Zuech, Joshua; Utz, Chris; Higgins, Greg; Reynolds, Rob; Baker, Ryan S. – Online Learning, 2018
Online education continues to become an increasingly prominent part of higher education, but many students struggle in distance courses. For this reason, there has been considerable interest in predicting which students will succeed in online courses and which will receive poor grades or drop out prior to completion. Effective intervention depends…
Descriptors: Performance Factors, Online Courses, Electronic Learning, Models
Gobert, Janice D.; Sao Pedro, Michael; Raziuddin, Juelaila; Baker, Ryan S. – Journal of the Learning Sciences, 2013
We present a method for assessing science inquiry performance, specifically for the inquiry skill of designing and conducting experiments, using educational data mining on students' log data from online microworlds in the Inq-ITS system (Inquiry Intelligent Tutoring System; www.inq-its.org). In our approach, we use a 2-step process: First we use…
Descriptors: Intelligent Tutoring Systems, Science Education, Inquiry, Science Process Skills
Chang, Yoo Kyung – ProQuest LLC, 2010
Metacognition is widely studied for its influence on the effectiveness of learning. With Exploratory Computer-Based Learning Environments (ECBLE), metacognition is found to be especially important because these environments require adaptive metacognitive control by the learners due to their open-ended structure that allows for multiple learning…
Descriptors: Self Efficacy, Protocol Analysis, Construct Validity, Verbal Learning
Koutromanos, George; Styliaras, Georgios; Christodoulou, Sotiris – Education and Information Technologies, 2015
The aim of this study was to use the Technology Acceptance Model (TAM) in order to investigate the factors that influence student and in-service teachers' intention to use a spatial hypermedia application, the HyperSea, in their teaching. HyperSea is a modern hypermedia environment that takes advantage of space in order to display content nodes…
Descriptors: Hypermedia, Intention, Technology Uses in Education, Technology Integration
Silva-Maceda, Gabriela; Arjona-Villicaña, P. David; Castillo-Barrera, F. Edgar – IEEE Transactions on Education, 2016
Learning to program is a complex task, and the impact of different pedagogical approaches to teach this skill has been hard to measure. This study examined the performance data of seven cohorts of students (N = 1168) learning programming under three different pedagogical approaches. These pedagogical approaches varied either in the length of the…
Descriptors: Programming, Teaching Methods, Intermode Differences, Cohort Analysis
Rockinson-Szapkiw, Amanda J.; Wendt, Jillian; Wighting, Mervyn; Nisbet, Deanna – International Review of Research in Open and Distributed Learning, 2016
The Community of Inquiry framework has been widely supported by research to provide a model of online learning that informs the design and implementation of distance learning courses. However, the relationship between elements of the CoI framework and perceived learning warrants further examination as a predictive model for online graduate student…
Descriptors: Graduate Students, Higher Education, Grades (Scholastic), Synchronous Communication
Yu, Fu-Yun; Wu, Chun-Ping – Educational Technology & Society, 2013
This study examined the individual and combined predictive effects of two types of feedback (i.e., quantitative ratings and descriptive comments) in online peer-assessment learning systems on the quality of produced work. A total of 233 students participated in the study for six weeks. An online learning system that allows students to contribute…
Descriptors: Predictor Variables, Peer Evaluation, Feedback (Response), Computer Mediated Communication
Velazquez, Cesareo Morales – Computers in the Schools, 2008
Data from Mexico City, Mexico (N = 978) and from Texas, USA (N = 932) were used to test the predictive validity of the teacher professional development component of the Will, Skill, Tool Model of Technology Integration in a cross-cultural context. Structural equation modeling (SEM) was used to test the model. Analyses of these data yielded…
Descriptors: Structural Equation Models, Technology Integration, Predictive Validity, Foreign Countries
Grosch, Michael – Electronic Journal of e-Learning, 2013
The web 2.0 has already penetrated the learning environment of students ubiquitously. This dissemination of online services into tertiary education has led to constant changes in students' learning and study behaviour. Students use services such as Google and Wikipedia most often not only during free time but also for learning. At the same…
Descriptors: Higher Education, Mass Media Use, Postsecondary Education, Technology Uses in Education
Hall, Michael – Online Journal of Distance Learning Administration, 2011
The McVay Revised Readiness for Online Learning questionnaire was given to 116 traditional on-campus and 31 distance education students. The students were enrolled in an introductory class in computer applications on an urban campus of a mid-western community college. Multiple regression equations were developed with the survey scores and the…
Descriptors: Electronic Learning, On Campus Students, Distance Education, Online Courses
Liu, Leping; Maddux, Cleborne – Computers in the Schools, 2008
This article reports the results of a study examining the predictive validity of a computer attitude instrument. The researchers attempted to determine the extent to which this instrument predicts student learning. Data from two universities were collected using this instrument over a nine-year period and were sorted into three sets with a random…
Descriptors: Computer Attitudes, Academic Achievement, Predictive Validity, Attitude Measures
Kay, Robin H.; Knaack, Liesel – Educational Technology Research and Development, 2009
Learning objects are interactive web-based tools that support the learning of specific concepts by enhancing, amplifying, and/or guiding the cognitive processes of learners. Research on the impact, effectiveness, and usefulness of learning objects is limited, partially because comprehensive, theoretically based, reliable, and valid evaluation…
Descriptors: Instructional Design, Construct Validity, Predictive Validity, Measures (Individuals)