Criteria for Inclusion in the Published Research List of Papers
1. Papers included in this database must be empirical studies of the
effectiveness of learning networks and have been published in a refereed journal
or conference proceedings, in the English language. They must be full papers,
not just extended abstracts. This is operationally defined as at least five
pages in length.
2. "Learning networks" technology and pedagogy refers to the use of
computer mediated communication among students as well as between instructor and
students, for a substantial part of the course work. They may be used
asynchronously and/or synchronously, though we are mainly concerned with courses
that include substantial use of asynchronous (anytime) media. They may be used
alone or in combination with other media, such as face to face lectures,
videotapes, Web postings of lecture or reading or tutorial material, etc. Not
all web based courses use learning networks; some just post lecture type
materials or exams for downloading, do not involve extensive interaction among
students in a class, and therefore do not qualify as "learning
networks" courses. One synonym for learning networks is
"computer-supported cooperative learning" (CSCL).
3. "Effectiveness" is defined as primarily concerned with learning
outcomes for students, but also includes effectiveness from the instructor's
point of view. It thus includes studies that look at student perceptions,
student performance, or faculty perceptions, satisfaction, or performance in
this mode of course delivery.
4. To be considered as an empirical research study, the paper must include
research questions or hypotheses ( at least implicitly), describe some data
collection methods, and report some empirical results. In order to be considered
an adequate empirical study, it must have a reasonable number of subjects on
which conclusions are based. We have operationally defined this for the time
being as a minimum of at least 20 subjects included in the study.
5. Is this an important paper that would be useful or of interest to future ALN researchers?