NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 6 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
List, Alexandra; Grossnickle, Emily M.; Alexander, Patricia A. – Reading Psychology, 2016
The present study examined undergraduate students' multiple source use in response to two different types of academic questions, one discrete and one open-ended. Participants (N = 240) responded to two questions using a library of eight digital sources, varying in source type (e.g., newspaper article) and reliability (e.g., authors' credentials).…
Descriptors: Profiles, Questioning Techniques, Information Sources, Undergraduate Students
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Smith, Russell K. – Research in Higher Education Journal, 2014
A segmentation study is used to partition college students into groups that are more or less likely to adopt tablet technology as a learning tool. Because the college population chosen for study presently relies upon laptop computers as their primary learning device, tablet technology represents a "next step" in technology. Student…
Descriptors: College Students, Cluster Grouping, Student Attitudes, Laptop Computers
Xu, Beijie – ProQuest LLC, 2011
This research examined teachers' online behaviors while using a digital library service--the Instructional Architect (IA)--through three consecutive studies. In the first two studies, a statistical model called latent class analysis (LCA) was applied to cluster different groups of IA teachers according to their diverse online behaviors. The third…
Descriptors: Teacher Behavior, Online Searching, Library Services, Electronic Libraries
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Amershi, Saleema; Conati, Cristina – Journal of Educational Data Mining, 2009
In this paper, we present a data-based user modeling framework that uses both unsupervised and supervised classification to build student models for exploratory learning environments. We apply the framework to build student models for two different learning environments and using two different data sources (logged interface and eye-tracking data).…
Descriptors: Supervision, Classification, Models, Educational Environment
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Palsdottir, Agusta – Information Research: An International Electronic Journal, 2008
Introduction: The aim of this study is to gather knowledge about how different groups of Icelanders take advantage of information about health and lifestyle in their everyday life. Method: A random sample of 1,000 people was used in the study and data was gathered as a postal survey. Response rate was 50.8%. Analysis: K-means cluster analysis was…
Descriptors: Self Efficacy, Multivariate Analysis, Information Seeking, Health Behavior
Peer reviewed Peer reviewed
Direct linkDirect link
Karavirta, Ville; Korhonen, Ari; Malmi, Lauri – Computer Science Education, 2006
Automatic assessment systems generally support immediate grading and response on learners' submissions. They also allow learners to consider the feedback, revise, and resubmit their solutions. Several strategies exist to implement the resubmission policy. The ultimate goal, however, is to improve the learning outcomes, and thus the strategies…
Descriptors: Feedback (Response), Student Evaluation, Computer Managed Instruction, Foreign Countries