Intelligent Tutoring Systems AI and Critical Thinking: A Teaching Resource

Education
Futuristic Robot in School Environment

In our increasingly complex educational landscape, Intelligent Tutoring Systems (ITS) offer promising tools for developing critical thinking skills in students. These computerized learning environments incorporate models from cognitive sciences, learning sciences, artificial intelligence, and other fields to create personalized learning experiences (Graesser et al., 2011).

Critical thinking, defined as “the intellectually disciplined process of actively and skillfully conceptualizing, applying, analyzing, synthesizing, and/or evaluating information gathered from, or generated by, observation, experience, reflection, reasoning, or communication, as a guide to belief and action” (Scriven & Paul, 2003), represents a crucial skill for today’s learners. ITS can help develop these skills through adaptive interaction.

Research shows that “learning is more effective and deeper when the learner must actively generate explanations, justifications, and functional procedures than when merely given information to read” (Bransford et al., 2000). This constructivist approach is embedded in systems like AutoTutor, which helps students learn critical thinking through tutorial dialogue in natural language (Graesser et al., 1999).

VanLehn’s (2011) comprehensive review suggests that the effectiveness of tutoring systems depends significantly on their interactivity level. His research indicates that step-based tutoring systems can achieve effectiveness comparable to human tutoring. The key is “granularity of interaction: the lower the level of discussions between the (human or artificial) tutor and the student, the higher the effectiveness” (VanLehn, 2011).

ITS employ different techniques to foster critical thinking:

  • Metacognitive scaffolding that supports planning, monitoring, and evaluation processes
  • Adaptive feedback responding to individual student approaches
  • Dialogue-based interactions that prompt explanation and justification
  • Knowledge tracing to identify areas of difficulty (Corbett & Anderson, 1995)

Classroom Application: Integrate ITS as a complementary tool alongside traditional instruction. Start by using systems like Cognitive Tutor for specific content areas where students need individualized assistance. When selecting an ITS, prioritize those with robust scaffolding features that prompt students to explain their thinking rather than simply providing answers. Schedule regular reflection sessions where students discuss their experiences with the ITS, analyzing how the system’s questions and prompts helped develop their reasoning skills.

By thoughtfully implementing ITS in your teaching practice, you can create an environment where technology enhances rather than replaces human instruction, ultimately fostering deeper critical thinking abilities in your students.

References

VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197-221. doi: Not available ( Retrieved from https://www.public.asu.edu/~kvanlehn/Stringent/PDF/EffectivenessOfTutoring_Vanlehn.pdf )

Koedinger, K. R., & Aleven, V. (2007). Exploring the assistance dilemma in experiments with cognitive tutors. Educational Psychology Review, 19(3), 239-264. ( Retrieved from https://www.andrew.cmu.edu/course/85-412/readings/koedinger.pdf )

Graesser, A. C., Wiemer-Hastings, K., Wiemer-Hastings, P., & Kreuz, R. & the Tutoring Research Group. (1999). AutoTutor: A simulation of a human tutor. Journal of Cognitive Systems Research, 1(1), 35-51. doi: Not available ( Retrieved from https://reed.cs.depaul.edu/peterh/papers/Graesserjcsr1999.pdf )

University of Louisville. (n.d.) What is Critical Thinking? Retrieved from https://louisville.edu/ideastoaction/about/criticalthinking/what

VanLEHN, K. (2011). The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems. Educational Psychologist, 46(4), 197–221. https://doi.org/10.1080/00461520.2011.611369