Defining complexity in the authoring process for adaptive instruction

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Abstract

Adaptive instruction is computer-based training or education that is tailored to match the difficulty of the content to the states and traits of the learner. Since the individual differences of learners vary widely and contribute greatly to the adaptation decisions by the tutor, adaptive instructional systems (e.g., Intelligent Tutoring Systems – ITSs) need much more content and make many more instructional decisions than non-adaptive instructional systems that instruct all learners only based on their performance level (e.g., low, moderate, high) using identical instructional strategies. Since the authoring of adaptive instruction varies with the complexity of its content and instructional decisions, it is difficult to compare the efficiency of the adaptive instructional authoring tools and methods, and the effort and skill required to use them in the construction of ITSs. This paper puts forth a methodology to assess ITS complexity and operationalize it in an index to enable adaptive instructional scientists to compare authoring tools and methods. The baseline for this initial comparative index is the Generalized Intelligent Framework for Tutoring (GIFT) authoring tools.

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APA

Sottilare, R., & Ososky, S. (2017). Defining complexity in the authoring process for adaptive instruction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10285 11th International Conference, AC 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part II, pp. 237–249). Springer Verlag. https://doi.org/10.1007/978-3-319-58625-0_17

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