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Yao, Ching-Bang; Wu, Yu-Ling – International Journal of Information and Communication Technology Education, 2022
With the impacts of COVID-19 epidemic, e-learning has become a popular research issue. Therefore, how to upgrade the interactivity of e-learning, and allow learners to quickly access personalized and popular learning information from huge digital materials, is very important. However, chatbots are mostly used in automation, as well as simple…
Descriptors: Electronic Learning, Artificial Intelligence, Individualized Instruction, Bayesian Statistics
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Nesra Yannier; Scott E. Hudson; Henry Chang; Kenneth R. Koedinger – International Journal of Artificial Intelligence in Education, 2024
Adaptivity in advanced learning technologies offer the possibility to adapt to different student backgrounds, which is difficult to do in a traditional classroom setting. However, there are mixed results on the effectiveness of adaptivity based on different implementations and contexts. In this paper, we introduce AI adaptivity in the context of a…
Descriptors: Artificial Intelligence, Computer Software, Feedback (Response), Outcomes of Education
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Starns, Jeffrey J.; Cohen, Andrew L.; Vargas, John M.; Lougee-Rodriguez, William F. – Journal of Statistics and Data Science Education, 2021
We developed and tested strategies for using spatial representations to help students understand core probability concepts, including the multiplication rule for computing a joint probability from a marginal and conditional probability, interpreting an odds value as the ratio of two probabilities, and Bayesian inference. The general goal of these…
Descriptors: Active Learning, Probability, Statistics Education, Concept Formation
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Eadie, Gwendolyn; Huppenkothen, Daniela; Springford, Aaron; McCormick, Tyler – Journal of Statistics Education, 2019
We present an active-learning strategy for undergraduates that applies Bayesian analysis to candy-covered chocolate m&m's®. The exercise is best suited for small class sizes and tutorial settings, after students have been introduced to the concepts of Bayesian statistics. The exercise takes advantage of the nonuniform distribution of…
Descriptors: Undergraduate Students, Bayesian Statistics, Active Learning, Learning Activities