TABLE OF CONTENTS
Bridget D. Arend, Ph.D. University of Denver
Abstract: Perhaps the most promising and understudied aspect of online education is course assessment. Course assessment is important because it has a strong impact on learning and is an indicator of the quality of learning occurring in a class. In the online environment, methods of assessment can be very different. However, the online education literature is currently lacking empirical data about the general status of assessment practices or how those practices relate to student learning. This article lays the groundwork for future studies by providing a description of formative and summative assessment and learning strategies in 60 online courses and suggesting some ways that assessment practices lead to different types of learning. In this study, instructors appear to follow effective practice by using multiple and alternative assessment methods, dispersing grades over time, and providing timely and frequent feedback to students. Students report focusing on relatively more complex learning strategies, such as elaboration and critical thinking over rehearsal. However, online instructors need to ensure that assessments are used strategically and that feedback is productive and able to be acted upon by students.
Maha Bali Center for Learning and Teaching, American University in Cairo, Egypt Adham R. Ramadan Department of Chemistry, American University in Cairo, Egypt
Abstract: This paper presents a case study of using course-specific rubrics combined with content analysis, together with instructor and student feedback, to assess learning via online discussion. Student feedback was gathered via Small Group Instructional Diagnosis, and instructor feedback was collected through formal interviews. Content analysis used emergent coding with different assessment criteria for each phase of the online discussion. Student participation was high, with a number of students feeling they learned beyond what was discussed in class. Some students however were overloaded by the large number of postings and repetitiveness during some of the phases of the discussion. The instructor was pleased to find students who were quiet in class being active in the online discussion. However, he found that student contributions demonstrated insufficient reflection and critical thinking. Content analysis showed that students met, on average, 59-82% of the essential assessment criteria in their postings, and that their contributions significantly improved as the online discussion progressed. However, a limited number of postings reflected critical thinking. In using online discussion, the use of assessment criteria is therefore commendable, as it was found that content analysis gave an insight beyond student and instructor perceptions. The insights gleaned from the methodology indicate its usefulness in assessing online discussion activities more objectively, and with respect to specific learning objectives.
Ross McKerlich and Terry Anderson Athabasca University
Abstract: This paper describes an exploratory, observational study using a purposive sample selection to determine if the presence indicators of the well regarded Community of Inquiry model can be a useful tool to observe and assess learning events which use a Multi User Virtual Environment (MUVE) as the mode of delivery [1]. Specific research questions addressed include whether the Community of Inquiry is recognizable in a MUVE learning environment, if new presence indicators are required if observing a MUVE learning event and finally, does the community of inquiry offer a base rubric to determine the educational effectiveness of learning events which take place in a MUVE? The results are promising; while new presence indicators add breadth to understanding the nature of learning in an immersive environment the core construct of the community of inquiry does indeed transfer to this emerging learning technology.
Dr. Katrina A. Meyer Associate Professor of Higher and Adult Education The University of Memphis
Abstract: Thirteen students in a graduate-level course on Historical and Policy Perspectives in Higher Education held face-to-face and online discussions on five controversial topics: Diversity, Academic Freedom, Political Tolerance, Affirmative Action, and Gender. Students read materials on each topic and generated questions for discussion that were categorized by Bloom’s taxonomy so that the level of questions in the two discussion settings would be closely parallel. Upon completion of each discussion, they answered questions that addressed depth and length of the discussion, ability to remember, and a self-assessment of how the student learned. Students’ assessments show a consistent preference for the face-to-face discussion but a small number of students preferred the online setting. However, what is perhaps more interesting is a minority of approximately one-third of the students who perceived no difference between the settings, or that the two settings were perhaps complementary.
Dr. James Theroux Flavin Professor of Entrepreneurship Isenberg School of Management University of Massachusetts
Abstract: The case method can be classified as a type of experiential learning because students treat the problem in the case as if it were real and immediate. Until the Internet there was no practical way for cases to actually be real and immediate. The Internet makes possible instantaneous distribution of cases, and it makes possible their creation in real time. This article describes a recent attempt to use the Internet to bring business reality to business courses, and to facilitate communication among instructors, students, and the case company. It explores the challenges and difficulties involved in producing a new type of case study, and it assesses the feasibility of doing so on a regular basis. The goal of the author is to stimulate a dialog about how the Internet can be used to move forward all of our teaching methods, but especially the one that is prominent in schools of business: the case method.
The Journal of Asynchronous Learning Networks (JALN) is published by the Sloan Consortium (Sloan-C™). Responsibility for the contents rests with the authors and not with Sloan-C™. Copyright © 2007 by Sloan-C™. All rights reserved.
