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Download full textMahoney, Bailey – Educational Considerations, 2023
During the pandemic, there were many discussions concerning how the pandemic was affecting students' learning and their ability to function in a remote classroom. However, the day-to-day routines and instructional strategies of teachers were being overlooked. The purpose of this research is twofold. The first is to provide examples and information…
Descriptors: COVID-19, Pandemics, Adjustment (to Environment), Teaching Methods
Direct linkSingh, Jitendra – Quality Assurance in Education: An International Perspective, 2019
Purpose: The purpose of this paper is to describe how lean management principles can be used in teaching and learning processes while preparing classes for non-traditional adult learners (NALs). Careful planning and the application of lean methods can result in NALs' enhanced engagement and success at academic institutions.…
Descriptors: Nontraditional Students, Adult Students, Curriculum Design, Administration
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection
