Results 131 to 140 of about 788,441 (294)

Who’s doing all the work? Using a technology-enhanced learning resource to develop student autonomy

, 2012
This paper explores the efficacy of a technology-enhanced learning resource designed by tutors to develop their students’ understanding about academic writing and their confidence in working independently.
Scott, C, Scott, C.
core  

Neuroscience, Technology and Learning: Areas and Issues for Interdisciplinary Progress

, 2011
This workshop aimed to bring together TEL researchers and specialists in neuroscience to: (1) To identify areas of understanding where technology enhanced learning may benefit from neuroscience and (2) To discuss how interdisciplinary research capacity ...
van Leeuwen, Theo, Ott, Michela, de Smedt, Bert, Howard‐jones, Paul   +3 more
core   +1 more source

The Influence of Technostress on Cyberslacking of College Students in Technology-Enhanced Learning: Mediating Effects of Deficient Self-Control and Burnout. [PDF]

Int J Environ Res Public Health, 2022
Li X, Liu D.
europepmc   +1 more source

Additive Manufacturing of Continuous Fibre Reinforced Composites: Process, Characterisation, Modelling, and Sustainability

Advanced Engineering Materials, EarlyView.
Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley   +1 more source

Technology-enhanced learning: a role for video animation. [PDF]

Br Dent J, 2021
Stadlinger B, Jepsen S, Chapple I, Sanz M, Terheyden H.   +4 more
europepmc   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Contextualizing institutional strategies for technology enhanced learning

, 2016
An analysis of strategic planning documents for public universities in Australia identifies some patterns in institutional strategies for technology-enhanced learning (TEL).
Russell, Carol (R16902)
core  

“To flip or not to flip, that’s the question” – Findings from an exploratory study into factors that may influence tertiary teachers to consider a flipped classroom model

Journal of Open, Flexible and Distance Learning, 2018
The concept of ‘flipping the classroom’ is relatively recent, although elements of it have been around for many years. It is generally accepted that the ‘flipped classroom model’ consists of replacing direct instruction, or lectures, with video-clips to
Lakshmi Chellapan, Jacques Van der Meer, Keryn Pratt, Rob Wass   +3 more
doaj   +2 more sources

What do they TEL(L)? A systematic analysis of master programs in technology-enhanced learning. [PDF]

Int J Educ Technol High Educ, 2022
Fominykh M, Weidlich J, Kalz M, Hybertsen ID.   +3 more
europepmc   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source