AI Article Synopsis
- The motivation to learn a foreign language is influenced by various factors, including the role of online tutors in e-learning environments.
- The study focuses on how Self-Determination Theory (SDT) and Computer Assisted Language Learning (CALL) can enhance understanding of motivation in learning English.
- Using qualitative methods like focus groups and discursive analysis of tutor messages, the research finds that tutors significantly impact students' motivation and communication in language learning.
Article Abstract
The motivation to learn a foreign language is a complex process. It is the analysis of related aspects such as the role of the tutor in E-learning. However, the study of the motivation based on Self-Determination Theory -SDT- and E-learning English with the Computer Assisted Language Learning approach -CALL can provide tools to understand and improve the teaching-learning processes. This qualitative study aims to identify and analyze the aspects around motivation to learn English related to online tutor's role. The main instruments used to collect data were a focus group and a discursive analysis of the messages sent by the selected tutors. The participants in the research were a group of tutors composed of 5 women and 1 man. The analysis was carried out through semantic categorizations and with the support of NVivo 12 software. The results let assume that the role of the tutor can influence in the motivation to learn a foreign language, while optimizing communication processes.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7415836 | PMC |
| http://dx.doi.org/10.1016/j.heliyon.2020.e04630 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Models for pure tone audiometry enabling computational evaluation: Introduction to Japanese extensive experiences.
Auris Nasus Larynx
January 2025
Department of Otolaryngology, Faculty of Medicine, Teikyo University, Tokyo, Japan. Electronic address:
Pure tone audiometry including "masking" is the most basic test in audiological medicine. Masking is based on theoretical models of sound perception and propagation and has been widely discussed since the 1950s. In Japan, such discussion has been conducted extensively, starting from early periods up to recent times, with success to enable mathematical simulation, but the achievements have little been disclosed to the English-speaking world.
View Article and Find Full Text PDFDeep learning aided determination of the optimal number of detectors for photoacoustic tomography.
Biomed Phys Eng Express
January 2025
Applied Sciences, Indian Institute of Information Technology Allahabad, Deoghat, Jhalwa, Allahabad, 211012, INDIA.
Photoacoustic tomography (PAT) is a non-destructive, non-ionizing, and rapidly expanding hybrid biomedical imaging technique, yet it faces challenges in obtaining clear images due to limited data from detectors or angles. As a result, the methodology suffers from significant streak artifacts and low-quality images. The integration of deep learning (DL), specifically convolutional neural networks (CNNs), has recently demonstrated powerful performance in various fields of PAT.
View Article and Find Full Text PDFRobustly interrogating machine learning-based scoring functions: what are they learning?
Bioinformatics
January 2025
Department of Statistics, University of Oxford, St Giles', Oxford, OX1 3LB, United Kingdom.
Motivation: Machine learning-based scoring functions (MLBSFs) have been found to exhibit inconsistent performance on different benchmarks and be prone to learning dataset bias. For the field to develop MLBSFs that learn a generalisable understanding of physics, a more rigorous understanding of how they perform is required.
Results: In this work, we compared the performance of a diverse set of popular MLBSFs (RFScore, SIGN, OnionNet-2, Pafnucy, and PointVS) to our proposed baseline models that can only learn dataset biases on a range of benchmarks.
Evidence that flocking behavior is rewarded by singing, flock mates, and mu opioid receptors in the nucleus accumbens.
PLoS One
January 2025
Department of Integrative Biology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
It has been proposed that social groups are maintained both by reward resulting from positive social interactions and by the reduction of a negative state that would otherwise be caused by social separation. European starlings, Sturnus vulgaris, develop strong conditioned place preferences for places associated with the production of song in flocks outside the breeding season (gregarious song) and singers are motivated to rejoin the flock following removal. This indicates that the act of singing in flocks is associated with a positive affective state and raises the possibility that reward induced by song in flocks may play a role in flock maintenance.
View Article and Find Full Text PDFGesture recognition from surface electromyography signals based on the SE-DenseNet network.
Biomed Tech (Berl)
January 2025
College of Ocean, Jiangsu University of Science and Technology, Zhenjiang, China.
Objectives: In recent years, significant progress has been made in the research of gesture recognition using surface electromyography (sEMG) signals based on machine learning and deep learning techniques. The main motivation for sEMG gesture recognition research is to provide more natural, convenient, and personalized human-computer interaction, which makes research in this field have considerable application prospects in rehabilitation technology. However, the existing gesture recognition algorithms still need to be further improved in terms of global feature capture, model computational complexity, and generalizability.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!