systems, dating back to the 1960s, which aim to simulate a human tutor; the system
presents information to the student and offers examples for practice. As the students
practice, the system computes their knowledge state from their actions, and offers
dynamically generated hints and scaffolds, that take into account both the current
knowledge state of the student and the knowledge/skills that the student is supposed to
learn. For a project that did not make much headway in the 1960s, the ITS community,
with its center of gravity at Carnegie Mellon University (CMU), has been startlingly
successful, culminating with the establishment in 1998 of the for-profit spinoff Carnegie
Learning—whose signature product, Cognitive Tutor, is now used in more than 1000
schools across the US. In 2005, the US National Science Foundation (NSF) awarded
Carnegie Learning, CMU and the University of Pittsburgh a 50 million grant (over 10
years) to form the Pittsburgh Science of Learning Center (PSLC). The PSLC, in turn,
has been the key institution that sustains at least three research communities (in terms
of sponsorship, data, and people): Artificial Intelligence in Education (AIED), the
learning sciences (LS) and Education Data Mining (EDM) communities. ITSes are a
perfect bridge across the multiple social contexts of Artificial Intelligence: they have links
to cognitive science, expert systems (i.e. "good old-fashioned artificial intelligence" or
GOFAI), and machine learning; they span both university research labs and for-profit
corporations, they are also experimental systems built to produce knowledge about
learning as well as practical systems meant to help students learn concepts.
ITS systems then represent an unusual success of the much maligned GOFAI; yet, a
closer examination reveals that their makers took several unconventional steps to make
them successful: in order to get Pittsburgh schools to use these systems, they had to
devolve substantial authority to teachers, necessitating a fundamental reconception of
the ITS itself. Rather than seeing the tutoring system as mimicking a human tutor—a
conceptualization that is classically symbolic AI in its framing—they came to realize that
it was best to frame it instead as a learning aids for both teachers and students working
together. Along the way, however, the makers of ITSes were able to secure
professional authority as “learning scientists” whose expertise on learning and cognitive
science was separate and more important than expertise in subject-matter or
technology.
See more of: Society for the History of Technology
See more of: Affiliated Society Sessions