By C.-K. Looi, G. McCalla, B. Bredeweg, J. Breuker
The sphere of synthetic Intelligence in schooling has persevered to expand and now contains study and researchers from many components of expertise and social technology. This learn opens possibilities for the cross-fertilization of knowledge and concepts from researchers within the many fields that make up this interdisciplinary learn sector, together with synthetic intelligence, different parts of computing device technology, cognitive technological know-how, schooling, studying sciences, academic know-how, psychology, philosophy, sociology, anthropology, linguistics, and the various domain-specific components for which synthetic Intelligence in schooling structures were designed and equipped. An specific objective is to attract these researchers who proportion the viewpoint that actual development in studying expertise calls for either deep perception into know-how and likewise deep perception into freshmen, studying, and the context of studying. The subject matter displays this easy duality.
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Additional resources for Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
We discuss our plans for an experiment to evaluate the impact of the Help Tutor on students’ help-seeking behavior and learning, including future learning, after their work with the Help Tutor. Introduction A number of instructional programs with a strong focus on meta-cognition have been shown to be effective, for example programs dealing with self-explanation (Bielaczyc, Pirolli, & Brown, 1995), comprehension monitoring (Palincsar & Brown, 1984), evaluating problem-solving progress (Schoenfeld, 1987), and reflective assessment (White & Frederiksen, 1998).
Four default teaching strategies were created (Table 1) based upon ones teachers had authored in previous studies . In addition, four optional strategies were devised that provided contrasting experiences such as using it in ‘exam style’ or in ‘pre-test’ mode (test me after the course, before section or course). Table 1. Teaching Strategies Name Default Description Simple Introduction Guided Practice NCL Guided Discovery Free Discovery Just Browsing Test me after the course Test me before each section Test me before the course CL No student control of material or questions; easy/medium questions (max one per page), 2 attempts per question, help available.
But, this does not have to be the case – interactions that people deem negative might lead to learning that people deem positive, or vice versa. The question for this talk is whether there is a “sweet spot” where interactions and learning complement one another and the values we hold most important. I will offer a pair of frameworks to address this question: one for characterizing learning by the dimensions of innovation and efficiency; and one for characterizing interactivity by the dimensions of initiative and idea incorporation.