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Direct linkDoroudi, Shayan; Aleven, Vincent; Brunskill, Emma – International Journal of Artificial Intelligence in Education, 2019
Since the 1960s, researchers have been trying to optimize the sequencing of instructional activities using the tools of reinforcement learning (RL) and sequential decision making under uncertainty. Many researchers have realized that reinforcement learning provides a natural framework for optimal instructional sequencing given a particular model…
Descriptors: Reinforcement, Learning Processes, Sequential Learning, Decision Making
Chase, Catherine C.; Connolly, Helena; Lamnina, Marianna; Aleven, Vincent – International Journal of Artificial Intelligence in Education, 2019
A successful instructional method is to engage learners with exploratory problem-solving before providing explanations of the canonical solutions and foundational concepts. A key question is whether and what type of guidance will lead learners to explore more productively and how this guidance will affect subsequent learning and transfer. We…
Descriptors: Computer Assisted Instruction, Teaching Methods, Learner Engagement, Problem Solving
Rummel, Nikol; Walker, Erin; Aleven, Vincent – International Journal of Artificial Intelligence in Education, 2016
In this position paper we contrast a Dystopian view of the future of adaptive collaborative learning support (ACLS) with a Utopian scenario that--due to better-designed technology, grounded in research--avoids the pitfalls of the Dystopian version and paints a positive picture of the practice of computer-supported collaborative learning 25 years…
Descriptors: Artificial Intelligence, Cooperative Learning, Futures (of Society), Electronic Learning
Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; van Velsen, Martin; Popescu, Octav; Demi, Sandra; Ringenberg, Michael; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2016
In 2009, we reported on a new Intelligent Tutoring Systems (ITS) technology, example-tracing tutors, that can be built without programming using the Cognitive Tutor Authoring Tools (CTAT). Creating example-tracing tutors was shown to be 4-8 times as cost-effective as estimates for ITS development from the literature. Since 2009, CTAT and its…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Programming, Educational Technology
Aleven, Vincent; Roll, Ido; McLaren, Bruce M.; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2016
Help seeking is an important process in self-regulated learning (SRL). It may influence learning with intelligent tutoring systems (ITSs), because many ITSs provide help, often at the student's request. The Help Tutor was a tutor agent that gave in-context, real-time feedback on students' help-seeking behavior, as they were learning with an ITS.…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Help Seeking, Feedback (Response)
Koedinger, Kenneth R.; Aleven, Vincent – International Journal of Artificial Intelligence in Education, 2016
Our 1997 article in "IJAIED" reported on a study that showed that a new algebra curriculum with an embedded intelligent tutoring system (the Algebra Cognitive Tutor) dramatically enhanced high-school students' learning. The main motivation for the study was to demonstrate that intelligent tutors that have cognitive science research…
Descriptors: Intelligent Tutoring Systems, Technology Uses in Education, Educational Technology, Algebra
