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Angela S. Kelling; Nicholas J. Kelling – Teaching of Psychology, 2025
Background: Given the increased emphasis on active learning in psychology, it is important to use data to enhance these experiences. In learning courses, both live animals and virtual training laboratories have been found to enhance learning, but less research has examined student preferences. Generally, live rats are preferred, but students may…
Descriptors: Student Attitudes, Preferences, Science Laboratories, Computer Simulation
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Victoria Brown; David Kumar – Distance Learning, 2024
In this technologically advanced time in history, distance learning has become a preferred mode of instructional delivery in higher education. From 2019 to 2021 there is a rise and fall of postbaccalaureate undergraduate students enrolled in at least one distance course and who enrolled in distance learning courses exclusively. In 2021 about 56%…
Descriptors: Mental Computation, Online Courses, Undergraduate Study, Blended Learning
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Guthrie, Kathy L.; McCracken, Holly – Journal of Computing in Higher Education, 2014
This article explores the use of critical reflection to facilitate the construction of knowledge resulting from participation in e-service-learning courses. Such an instructional approach integrates an interdisciplinary curricular framework with site-specific service-learning opportunities resulting in an environment richer and more accessible…
Descriptors: Reflection, Service Learning, Electronic Learning, Interdisciplinary Approach
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Tomas, Louisa; Lasen, Michelle; Field, Ellen; Skamp, Keith – Australian Journal of Teacher Education, 2015
At James Cook University, a core first-year subject within the Bachelor of Education, Foundations of Sustainability in Education (FSE), sees students investigate the underlying science and complexity of socioecological challenges through inquiry, place-based learning, experimentation and consideration of classroom practice. Given that this subject…
Descriptors: Online Courses, Experiential Learning, Guidelines, Teaching Methods
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Smith, Julian; Groves, Mark; Bowd, Belinda; Barber, Alison – International Journal of Higher Education, 2012
This study examined the effectiveness of a Blended Learning (BL) environment designed to facilitate the learning of study skills with a large (over 200) and diverse undergraduate student cohort in a Higher Education (HE) institution in the UK. A BL environment was designed using the model provided by Kerres & De Witt (2003), and was also…
Descriptors: Study Skills, Blended Learning, Skill Development, Learning Strategies
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Donovan, Judy – Journal of the Scholarship of Teaching and Learning, 2008
A graduate level education course utilized ee-learning (the combination of experiential and electronic learning) to break down barriers between theory and practice, and knowledge and experience. Students shared and reflected on experiences at volunteer sites, their personal lives, their individual school settings and coursework, to create a…
Descriptors: Graduate Study, Education Courses, Theory Practice Relationship, Learning Experience
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Tsoi, Mun Fie – Interactive Technology and Smart Education, 2009
Purpose: Research on the nature of blended learning and its features has led to a variety of approaches to the practice of blended learning. The purpose of this paper is to provide an alternative practice model, the TSOI hybrid learning model (HLM) to enhance the blended learning experiences in science education. Design/methodology/approach: The…
Descriptors: Electronic Learning, Feedback (Response), Constructivism (Learning), Web Sites
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