Toward Computer-Based Support of Meta-Cognitive Skills: a Computational Framework to Coach Self-Explanation

By Cristina Conati, Kurt VanLehn. 2000

310 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9673360bc7209ea31de82367376d1276086cb5d2

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Citations in the corpus

Using Bayesian Networks to Manage Uncertainty in Student Modeling (2002, methodology): “, 2000), Andes also helps students study examples e¡ectively, a novel task that adds new sources of uncertainty to the student modeling problem (Conati and VanLehn, 2000; Conati et al., 1997).”
Can learning from molar and modular worked examples be enhanced by providing instructional explanations and prompting self-explanations? * (2006, methodology): “These scaffolds may include (adaptive) feedback in case of incorrect self-explanations (Aleven & Koedinger, 2002; Conati & VanLehn, 2000) and the provision of instructional explanations to exploit their specific advantages (Renkl, 1999, 2002), particularly for learners with very low knowledge…”
A New Paradigm for Intelligent Tutoring Systems: Example-Tracing Tutors (2009, unknown): “…systems that use case-based reasoning techniques for purposes of student modeling (e.g., Weber & Brusilovsky, 2001), or systems that present examples to students (e.g., Conati & VanLehn, 2000; McLaren, Lim & Koedinger, 2008a; 2008b; Salden, Aleven, Renkl, & Schwonke, 2009; Schwonke et al., 2009).”
Peer reviewers learn from giving comments (2011, background): “A number of studies have found that eliciting selfexplanations has been effective in improving learning (Chi et al. 1994; Conati and Vanlehn 2000; Renkl et al. 1998).”
Transitioning From Studying Examples to Solving Problems: Effects of Self-Explanation Prompts and Fading Worked-Out Steps. (2003, background): “Taken together, the learning environment, including type of self-explanation prompting used by Conati and VanLehn (1999, 2000), may have imposed so much processing demands that many learners may have been cognitively overloaded.”
Promoting transfer: effects of self-explanation and direct instruction. (2006, background): “Other studies have failed to find a benefit for eliciting selfexplanations during direct instruction in a variety of mathematical and scientific domains (Conati & Vanlehn, 2000; Didierjean & Cauzinille Marmeche, 1997; Gro e & Renkl, 2003; Mwangi & Sweller, 1998).”
Synthesizing Results From Empirical Research on Computer-Based Scaffolding in STEM Education (2016, methodology): “The SE-Coach provided feedback and self-explanation prompts to students based on a continuous assessment of the students’ actions and domain knowledge (Conati & Vanlehn, 2000).”
The impact of text coherence on learning by self-explanation (2007, background): “It is evident that these effects are observed in a wide variety of domains (e.g. physics problem solving (Chi et al., 1989; Conati & VanLehn, 2000) probability (Renkl, 1997); cardio-vascular system (Chi et al., 1994, 2001), geometry (Aleven & Koedinger, 2002), history (Wolfe & Goldman, 2005), and…”
Explaining the Gap: Visualizing One's Predictions Improves Recall and Comprehension of Data (2017, background): “Self-explanation techniques have been widely applied in on-line learning environments, typically to text-based learning materials [13, 14, 3, 4, 40, 25].”
Active-Constructive-Interactive: A Conceptual Framework for Differentiating Learning Activities (2009, methodology): “…et al., 2007), summarizing paragraphs using delete and substitution rules (Brown & Day, 1983), manipulating video tapes such as pausing and rewinding them (Chi, Roy, & Hausmann, 2008), rotating objects (James et al., 2002), selecting from a menu of choices (Conati & VanLehn, 2000), and so forth.”
The Andes Physics Tutoring System: Lessons Learned (2005, methodology): “The same technique was used in the Self-Explanation Coach ( Conati & VanLehn, 2000; Conati & VanLehn, 2001) in order to assess rule mastery by observing which lines in a worked example were studied by students.”
Toward Meta-cognitive Tutoring: A Model of Help Seeking with a Cognitive Tutor (2006, background): “…shown that self-explanation, an important meta-cognitive skill, can be supported with a positive effect on the learning of domain-specific skills and knowledge (Aleven & Koedinger, 2002; Bunt, Conati, & Muldner, 2004; Conati & VanLehn, 2000; Mitrovic, 2003; Renkl, 2002; Trafton & Tricket, 2001).”
Scaffolding Self-regulated Learning and Metacognition – Implications for the Design of Computer-based Scaffolds (2005, background): “Research about the effectiveness of scaffolds in CBLEs is challenging to conduct because these environments use a variety of different scaffolding techniques delivered by a variety of agents (human, peer, computer) (e.g., Luckin & DuBoulay, 1999; Conati & VanLehn, 2000; Aleven & Koedinger, 2002; B”
The ICAP Framework: Linking Cognitive Engagement to Active Learning Outcomes (2014, unknown): “An example of an active way of self-explaining is a computer-based example-studying task that asks students to select a justiﬁcation for each solution step from a menu of choices (Conati & VanLehn, 2000).”
Handbook of Research on Learning and Instruction (2011, methodology): “When learning in the psychomotor domain, children tend to demonstrate patterns in competence conceptions similar to those in classrooms as described by Dweck (1999).”