Intelligent Tutoring Systems

1996

Citations in the corpus

• Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI (2019, neutral): “…2006; Nakatsu and Benbasat, 2003; Polson and Richardson, 1988; Psotka, Massey, and Mutter, 1988; Ritter and Feurzeig, 1988; Silverman, 1992; Sleeman and Brown, 1982; Southwick, 1991; Swartout, Paris, and Moore, 1991; Tanner and Keuneke, 1991; Tintarev, 2007; Woolf, 2007; Woolf, Beck,…”
• Metrics for Explainable AI: Challenges and Prospects (2018, background): “In a sense, explanation is what and Intelligent Tutoring Systems were (and are) all about (Forbus & Feltovich, 2001; Poulson & Richardson, 1988; Psotka, Massey & Mutter, 1988; Ritter & Feurzeig, 1988; Sleeman & Brown, 1982).”
• The challenge of crafting intelligible intelligence (2018, background): “…generated sentences to include class discriminative information. descriptions images that have both high image relevance (from the captioning training data) and high class relevance (from the object recognition training The HCI community has long studied students’ knowledge and misconceptions [2].”
• Explanation Feedback Is Better Than Correct Answer Feedback for Promoting Transfer of Learning (2013, unknown): “Although elaborative feedback is assumed to benefit learners and it is often included in instructional methods (e.g., Corbett et al., 1997; Gibbons & Fairweather, 1998), reviewers of the feedback literature had concluded that increasing the complexity of the feedback message does not benefit…”
• Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm (2005, unknown): “…in a uniaxial nematic liquid crystal is given by: H ¼ X l m l I Z;l þ X l<m J lm I l Á I m þ X l<m D lm ð3I Z;l I Z;m À I l Á I m Þ ð1Þ where m l is the resonance frequency of nucleus l and J lm and D lm are the indirect spin–spin and the direct dipole–dipole couplings between nuclei l and m.”
• Studies of Expertise from Psychological Perspectives (2006, background): “(e.g. Clancey & Letsinger, 1981; Feltovich et al., 2001; Sleeman & Brown, 1982).”
• Improving Students' Ability to Identify and Use Source Information (2002, background): “Students’ responses are scored immediately, enabling students to take corrective action if the response is incorrect (Anderson, Boyle, & Reiser, 1985; Lewis & Anderson, 1985), and feedback is sufficiently frequent and fine-grained to provide many small rewards for continuing.”
• Intelligible Artificial Intelligence (2018, background): “Ideally, the explainer might build a model of the listener’s background over the course of many interactions, as have been proposed by the intelligent tutoring systems community [1].”
• Generic User Modeling Systems (2001, background): “artificial intelligence, natural-language dialog [58], and intelligent tutoring [39, 87].”
• Learning teaching strategies in an Adaptive and Intelligent Educational System through Reinforcement Learning (2009, methodology): “It also has been implemented with a set of production rules in LISP tutor [46], or with constraint rule , s as KERMIT system does [47], combining production rules with neural networks .”
• Exploring Teachers’ Perceptions of Artificial Intelligence as a Tool to Support their Practice in Estonian K-12 Education (2021, background): “design of computational tutoring systems that would “imitate” human tutors in the way they adapted instruction with respect to the student’s knowledge state (Corbett et al. 1997).”
• Supporting Self-Regulated Learning in Online Learning Environments and MOOCs: A Systematic Review (2018, background): “Dating back to the early 1970s, ITS aimed to “ engage each student in sustained reasoning activity and interact with the student based on a deep understanding of the student ’ s behavior ” (Corbett, Koedinger, & Anderson, 1997).”
• A meta-analysis of the effectiveness of intelligent tutoring systems on college students' academic learning (2014, unknown): “ITS are considered superior to CAI and CBT in that ITS allow an infinite number of possible interactions between the systems and the learners (Graesser et al., 2011). VanLehn (2006) described ITS as tutoring systems that have both an outer loop and an inner loop.”
• Knowing What Students Know: The Science and Design of Educational Assessment (2001, background): “The approach has been used in a wide variety of domains, from young children’s understanding of how balance scales work (Klahr and Siegler, 1978), to high schoolers’ learning of geometry (Anderson and Boyle, 1985), to adults’ performance on text editing (Singley and Anderson, 1988) and spatial navig”
• Learning to Teach (2018, background): “Second, teaching has gradually attracted attention from researchers and been evolved as a new research direction in recent years from its origin several decades ago (Anderson et al., 1985; Goldman & Kearns, 1995).”