ExamNet asynchronous learning network: augmenting face-to-face courses with student-developed exam questions
ARTICLE
E.Vance Wilson
Computers & Education Volume 42, Number 1, ISSN 0360-1315 Publisher: Elsevier Ltd
Abstract
This paper investigates how students’ attitude and performance are affected by using an asynchronous learning network (ALN) to augment exams in a traditional lecture/lab course. Students used the ExamNet ALN to create, critique, and revise a database of questions that subsequently was drawn upon for course exams. Overall, students considered ExamNet to be useful and important in understanding course material, reviewing for exams, and succeeding in the course. Most found the process of developing exam questions to be intrinsically motivating and an interesting part of the course.
Citation
Wilson, E.V. (2004). ExamNet asynchronous learning network: augmenting face-to-face courses with student-developed exam questions. Computers & Education, 42(1), 87-107. Elsevier Ltd. Retrieved June 10, 2023 from https://www.learntechlib.org/p/66647/.
This record was imported from
Computers & Education
on January 30, 2019.
Computers & Education is a publication of Elsevier.
Keywords
Cited By
View References & Citations Map-
Machine-Learning-Based Automatic Difficulty Estimation of Quizzes in Question-Posing Learning
Kazuki Harayama & Yoshio Yamagishi, Kanazawa Institute of Technology, Japan
E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2018 (Oct 15, 2018) pp. 754–761
These links are based on references which have been extracted automatically and may have some errors. If you see a mistake, please contact info@learntechlib.org.
