The field learning analytics is established with the promise for the education sector to embrace the use of data for decision making. There are many examples of successful use of learning analytics to enhance student experience, increase learning outcomes, and optimize learning environments.
Learning Analytics in the Classroom presents a coherent framework for the effective translation of learning analytics research for educational practice to its practical application in different education domains.
Fuzzy Loss functions for GANs, Learning Analytics, Next Generation AI and Sustainability, Deep Learning for Melodic Frameworks
Speakers:
Prof. Priti S. Sajja, Sardar Patel University, India
Prof. Elvira Popescu, University of Craiova, Romania
Dr. Celestine Iwendi, University of Bolton, UK
Dr. Vishnu S. Pendyala, San Jose State University, USA
Date: Tuesday, July 12, 2022
Probabilistic soft logic (PSL) is a machine learning framework for developing probabilistic models. PSL models are easy and fast, you can define them using a straightforward logical syntax and solve them with fast convex optimization.
Game Learning Analytics (GLA) is the process of applying Learning Analytics techniques to Serious Games in order to get insight about how the game is being used and improve the educational experience.
Last month, students and faculty took part in a key phase of eCampusOntario’s ongoing learning analytics initiative: a sprint designed to gather student insight and understand student learning experiences.
This presentation explores shortcomings of learning analytics for the wide adoption in educational organisations. It is NOT about ethics and privacy rather than focuses on shortcomings of learning analytics for teachers and students in the classroom (micro-level).