Chapter 3: What is AI? people and computers, we may frame policies for AI in education that miss the mark. 3.2. Perspective: An Algorithm that Pursues a Goal “Any computational method that is made to act independently towards a goal based on inferences from theory or patterns in data.” This second definition emphasizes that AI systems and tools identify patterns and choose actions to achieve a given goal. These pattern recognition capabilities and automated recommendations will be used in ways that impact the educational process, including student learning and teacher instructional decision making. For example, today’s personalized learning systems may recognize signs that a student is struggling and may recommend an alternative instructional sequence. The scope of pattern recognition and automated recommendations will expand. Correspondingly, humans must determine the types and degree of responsibility we will grant to technology within educational processes, which is not a new dilemma. For decades, the lines between the role of teachers and computers have been discussed in education, for example, in debates using terms such as “’computer-aided instruction,” “blended instruction,” and “personalized learning.” Yet, how are instructional choices made in systems that include both humans and algorithms? Today, AI systems and tools are already enabling the adaptation of instructional sequences to student needs to give students feedback and hints, for example, during mathematics problem solving or foreign language learning. This discussion about the use of AI in classroom pedagogy and student learning P a g e | 21
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