Search results for author:"L. Zhang"
Total records matched: 9 Search took: 0.058 secs
You may get more results with author:"L. Zhang".
35th Anniversary - SITE 2024 Attendees: if you are looking for papers from this conference, please use this special attendee-only 35th Anniversary - SITE 2024 search
-
Listening Strategy Use and Influential Factors in Web-Based Computer Assisted Language Learning
L Chen; R Zhang; C Liu
Journal of Computer Assisted Learning Vol. 30, No. 3 (June 2014) pp. 207–219
This study investigates second and foreign language (L2) learners' listening strategy use and factors that influence their strategy use in a Web-based computer assisted language learning (CALL) system. A strategy inventory, a factor...
-
Listening strategy use and influential factors in Web-based computer assisted language learning
L. Chen; R. Zhang; C. Liu
Journal of Computer Assisted Learning Vol. 30, No. 3 (Jun 23, 2014) pp. 207–219
This study investigates second and foreign language (L2) learners' listening strategy use and factors that influence their strategy use in a Web-based computer assisted language learning (CALL) system. A strategy inventory, a factor questionnaire...
-
Comparisons of Four Methods for Estimating a Dynamic Factor Model
Zhiyong Zhang; Ellen L. Hamaker; John R. Nesselroade
Structural Equation Modeling: A Multidisciplinary Journal Vol. 15, No. 3 (July 2008) pp. 377–402
Four methods for estimating a dynamic factor model, the direct autoregressive factor score (DAFS) model, are evaluated and compared. The first method estimates the DAFS model using a Kalman filter algorithm based on its state space model...
-
Understanding Mobile Learning from the Perspective of Self-Regulated Learning
L Sha; C-K Looi; W Chen; B H. Zhang
Journal of Computer Assisted Learning Vol. 28, No. 4 (August 2012) pp. 366–378
Cognizant of the research gap in the theorization of mobile learning, this paper conceptually explores how the theories and methodology of self-regulated learning (SRL), an active area in contemporary educational psychology, are inherently suited to ...
-
Understanding MOOC students: motivations and behaviours indicative of MOOC completion
B.K. Pursel; L. Zhang; K.W. Jablokow; G.W. Choi; D. Velegol
Journal of Computer Assisted Learning Vol. 32, No. 3 (June 2016) pp. 202–217
Massive open online courses (MOOCs) continue to appear across the higher education landscape, originating from many institutions in the USA and around the world. MOOCs typically have low completion rates, at least when compared with traditional...
-
What WorldCat (The OCLC Online Union Catalog) Means to Me
George E. Bishop; Donald O. Case; Patricia L. Hassan; Jeanette C. Smith; Daofu Zhang
Journal of Library Administration Vol. 25, No. 2 (1998) pp. 3–9
Marking the 25th anniversary (August 26, 1996) of WorldCat (the Online Computer Library Center (OCLC) Online Union Catalog) OCLC and the U.S. regional networks sponsored an essay contest for librarians and library users to write essays describing...
-
Persistence of learning gains from computer assisted learning: Experimental evidence from China
D. Mo; L. Zhang; J. Wang; W. Huang; Y. Shi; M. Boswell; S. Rozelle
Journal of Computer Assisted Learning Vol. 31, No. 6 (Dec 01, 2015) pp. 562–581
Computer assisted learning (CAL) programs have been shown to be effective in improving educational outcomes. However, the existing studies on CAL have almost all been conducted over a short period of time. There is very little evidence on how the...
-
Exploring the Communication Preferences of MOOC Learners and the Value of Preference-Based Groups: Is Grouping Enough?
Qing Zhang; Kyle L. Peck; Adelina Hristova; Kathryn W. Jablokow; Vicki Hoffman; Eunsung Park; Rebecca Yvonne Bayeck
Educational Technology Research and Development Vol. 64, No. 4 (2016) pp. 809–837
Approximately 10% of learners complete Massive Open Online Courses (MOOCs); the absence of peer and professor support contributes to retention issues. MOOC leaders often form groups to supplement in-course forums and Q&A sessions, and students...
-
Working Together for Better Student Learning: A Multi-University, Multi-Federal Partner Program for Asynchronous Learning Module Development for Radar-Based Remote Sensing Systems
M B. Yeary; T Yu; R D. Palmer; H Monroy; Ruin ; G Zhang; P B. Chilson; M I. Biggerstaff; C Weiss; K A. Mitchell; L D. Fink
IEEE Transactions on Education Vol. 53, No. 3 (August 2010) pp. 504–515
Students are not exposed to enough real-life data. This paper describes how a community of scholars seeks to remedy this deficiency and gives the pedagogical details of an ongoing project that commenced in the Fall 2004 semester. Fostering deep...