Benefits to Students of Team-Based Learning in Large Enrollment Calculus
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DOI: 10.1080/10511970.2018.1542417
Abstract: Abstract Team-Based Learning (TBL) uses a flipped classroom model and involves students working collaboratively in small groups, with peer assessments to promote group accountability. We implemented TBL in Calculus I in both large () and… read more here.
Keywords: based learning; team based; benefits students; students team ... See more keywords
Increasing Active Learning in Large, Tightly Coordinated Calculus Courses
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DOI: 10.1080/10511970.2020.1772923
Abstract: ABSTRACT We discuss a decade of initiatives to improve the teaching and learning of calculus at The Ohio State University. Calculus at OSU is taught in lecture/recitation format with large lectures and is tightly coordinated,… read more here.
Keywords: tightly coordinated; active learning; large tightly; learning large ... See more keywords
Hybrid Beamforming With Deep Learning for Large-Scale Antenna Arrays
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DOI: 10.1109/access.2021.3069037
Abstract: The emergence of highly directional beamforming technology makes millimeter wave frequency band communication possible in future wireless communication networks. Based on the multipath characteristics of millimeter wave frequency communication, a high-precision multipath channel estimation algorithm… read more here.
Keywords: beamforming deep; communication; hybrid beamforming; large scale ... See more keywords
Learning Large Graph-Based MDPs With Historical Data
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DOI: 10.1109/tcns.2021.3128530
Abstract: Weconsider learning the dynamics and measurement model parameters of a graph-based Markov decision process (GMDP) given a history of measurements. Graph-based models have been used in modeling many data-based applications, such as recognition tasks, disease… read more here.
Keywords: large graph; graph based; mdps historical; learning large ... See more keywords
Ensemble Deep Learning on Large, Mixed-Site fMRI Datasets in Autism and Other Tasks
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DOI: 10.1142/s0129065720500124
Abstract: Deep learning models for MRI classification face two recurring problems: they are typically limited by low sample size, and are abstracted by their own complexity (the "black box problem"). In this paper, we train a… read more here.
Keywords: ensemble deep; mixed site; versus; large mixed ... See more keywords
Blended learning in large enrolment courses: Student perceptions across four different instructional models
Sign Up to like & getrecommendations! Published in 2019 at "Australasian Journal of Educational Technology"
DOI: 10.14742/ajet.4310
Abstract: Drawing on data from five large enrolment introductory courses in a public university, we compared students’ perceptions of blended learning on design, interaction, learning, and satisfaction in four different blended models. The models, which were… read more here.
Keywords: blended learning; large enrolment; four different; class ... See more keywords