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Marin, Rafael; Notargiacomo, Pollyana – International Journal of Web-Based Learning and Teaching Technologies, 2022
Financial literacy is a theme that integrates public policies for the social development of a country and an element to be worked on from different aspects to improve people's living standards, providing well-being. In this context, Stima is proposed, a system capable of acquiring knowledge from experts and tutors to help students to follow the…
Descriptors: Financial Literacy, Intelligent Tutoring Systems, Decision Making, Planning
Vannaprathip, Narumol; Haddawy, Peter; Schultheis, Holger; Suebnukarn, Siriwan – International Journal of Artificial Intelligence in Education, 2022
Virtual reality simulation has had a significant impact on training of psychomotor surgical skills, yet there is still a lack of work on its use to teach surgical decision making. This is particularly noteworthy given the recognized importance of decision making in achieving positive surgical outcomes. With the objective of filling this gap, we…
Descriptors: Intelligent Tutoring Systems, Decision Making, Surgery, Teaching Methods
The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues
Tack, Anaïs; Piech, Chris – International Educational Data Mining Society, 2022
How can we test whether state-of-the-art generative models, such as Blender and GPT-3, are good AI teachers, capable of replying to a student in an educational dialogue? Designing an AI teacher test is challenging: although evaluation methods are much-needed, there is no off-the-shelf solution to measuring pedagogical ability. This paper reports…
Descriptors: Artificial Intelligence, Dialogs (Language), Bayesian Statistics, Decision Making
Feng, Junchen – ProQuest LLC, 2017
The future of education is human expertise and artificial intelligence working in conjunction, a revolution that will change the education as we know it. The Intelligent Tutoring System is a key component of this future. A quantitative measurement of efficacies of practice to heterogeneous learners is the cornerstone of building an effective…
Descriptors: Intelligent Tutoring Systems, Learning Processes, Bayesian Statistics, Models
Hooshyar, Danial; Ahmad, Rodina Binti; Yousefi, Moslem; Fathi, Moein; Horng, Shi-Jinn; Lim, Heuiseok – Innovations in Education and Teaching International, 2018
In learning systems and environment research, intelligent tutoring and personalisation are considered the two most important factors. An Intelligent Tutoring System can serve as an effective tool to improve problem-solving skills by simulating a human tutor's actions in implementing one-to-one adaptive and personalised teaching. Thus, in this…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Skill Development, Programming
van Ravenzwaaij, Don; van der Maas, Han L. J.; Wagenmakers, Eric-Jan – Psychological Review, 2012
In their influential "Psychological Review" article, Bogacz, Brown, Moehlis, Holmes, and Cohen (2006) discussed optimal decision making as accomplished by the drift diffusion model (DDM). The authors showed that neural inhibition models, such as the leaky competing accumulator model (LCA) and the feedforward inhibition model (FFI), can mimic the…
Descriptors: Intelligent Tutoring Systems, Inhibition, Bayesian Statistics, Decision Making
Vos, Hans J. – 1994
Some applications of Bayesian decision theory to intelligent tutoring systems are considered. How the problem of adapting the appropriate amount of instruction to the changing nature of a student's capabilities during the learning process can be situated in the general framework of Bayesian decision theory is discussed in the context of the…
Descriptors: Bayesian Statistics, Decision Making, Foreign Countries, Intelligent Tutoring Systems
Vos, Hans J. – 1994
As part of a project formulating optimal rules for decision making in computer assisted instructional systems in which the computer is used as a decision support tool, an approach that simultaneously optimizes classification of students into two treatments, each followed by a mastery decision, is presented using the framework of Bayesian decision…
Descriptors: Achievement Tests, Bayesian Statistics, Classification, Computer Managed Instruction