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Online teaching and learning has been in transition for its entire existence. The number of courses offered at a distance has grown rapidly. According to the National Center for Education Statistics (Waits & Lewis, 2003), in 2000-2001 more than 56% of four-year colleges and universities in the United States offered distance education degree programs. Many classroom based higher education programs, which meet in person regularly throughout a semester, use online technologies as well. In San Francisco State University (SFSU), 70% of all courses use online technologies; some of these courses are taught in a traditional face to face delivery mode. Approximately 90% of SFSU faculty who use online technologies use the Blackboard Learning Management System (LMS) and the rest are engaged in a scalability test of an alternative to Blackboard, using a local installation of the open source Moodle LMS which SFSU calls "ilearn." This paper presents selections of the authors' experiences using the Moodle LMS for the first time in a recent semester at SFSU. The purpose of this paper is to provide a glimpse into some of the factors that may be important considerations as more universities transition from commercial LMSs to open-source systems such as Moodle. (Contains 7 figures.)

As part of the research carried out at the University of California, Santa Barbara's Center for Information Technology and Society (CITS), the Paper Authentication and Integrity Research (PAIR) project was launched. We began by investigating how one recent technology affected student learning outcomes. One aspect of this research was to study the effect plagiarism detection had on student attitudes and behaviors in regards to plagiarism detection. As a means of executing this research, we developed PAIRwise, a plagiarism detection system for instructors, students, and researchers. In this paper we describe its design and explore its capabilities with regards to efficiency and effectiveness. Our findings show that PAIRwise can handle large document collections efficiently and find instances of verbatim plagiarism as well as similar passages with modifications to verb tense. Researchers have also approached us with proposals to use PAIRwise for purposes other than plagiarism detection. The original system, PAIRwise 1.0, however, was slow, hard to maintain and not easily used by researchers from disciplines outside of computer science. Therefore, this release of PAIRwise, version 2.0, has many capabilities and applications beyond plagiarism detection. (Contains 5 figures and 1 note.)

Many universities are currently using Course Management Systems (CMSes) to conduct online learning, for example, by distributing course materials or submitting homework assignments. However, most CMSes do not include comprehensive activity tracking and analysis capabilities. This paper describes a method to track students' online learning activity, and provide this information to instructors to allow them to assess students' learning behavior and progress. Further, the information can be used by educational researchers to evaluate the contribution of CMSes to learning. A prototype of the proposed system, called the Moodle Watchdog, or "Moodog", has been implemented on top of the Moodle CMS. The Moodog system provides accurate tracking information with an easy-to-use interface, and offers a wide range of activity information to instructors and educational researchers. As a basis for evaluating Moodog, the system has been deployed in several courses taught at the University of California in Santa Barbara. Using the results and experiences obtained from this evaluation, Moodog has been shown to collect useful activity information for both educators and educational researchers. This information suggests different groups of students tend to have different behavior in some online learning activities, such as forum access, login sessions and course material access, but do not seem to have different behavior on lecture notes access. The information produced by Moodog and the analysis performed in this paper suggest that a more detailed analysis of the data by educational researchers would yield interesting results about the use of course management systems. (Contains 13 figures and 1 footnote.)

The article describes the research work of Louis-Philippe Morency, a research scientist at University of Southern California's Institute for Creative Technologies in California. Morency's research focuses on what he calls "multimodal perception" or the combination of various communication channels like spoken words, intonation and visual gestures, which allow computers to recognize, understand and respond to people's nonverbal behaviors. Morency's vision for the future of artificial intelligence is to see computer interfaces efficiently reacting to its users, enabling a more efficient and engaging interaction between robots and people.