EAI Endorsed Transactions on e-Learning

EAI Endorsed Transactions on e-Learning is an open access, peer-reviewed scholarly journal focused on topics belonging to the variegated and engaging e-Learning landscape, ranging from various types of distance learning (e.g., online, mobile, cloud, hybrid) to virtual laboratory environments supported by sound pedagogies, cutting-edge technologies and much more. The journal publishes research articles, review articles, commentaries, editorials, technical articles, and short communications with a triannual frequency. Authors are not charged for article submission and processing.

Editor(s)-in-Chief: Yu-Dong Zhang (Eugene) and Marco Zappatore

Aims & Scope
Indexing
Editors in Chief
Editorial Board
Special Issues

Education is one domain that has accompanied civilization through the centuries, adapting its tools to fulfill the expectations of the students and the needs of the teachers. Such tools can be as obvious and traditional as pencils and a notebook, or as complex and innovative as online courses, virtual, augmented and mixed reality environments.

As the development of technology offers a rapidly increasing number of outlets for creativity and communications, the world of education is undergoing significant renovations. Each day more instructions and open educational resources can be accessed from anywhere, at any time, and at no or little cost. Many universities, public institutions and private businesses are moving into the online and virtual worlds to reach their customers, creating rich virtual presence that cannot be delivered through a simple website. Showcasing these innovative changes in education through scientific research lens is the mission of this publication.

Launched in 2011, the EAI Endorsed Transactions on e-Learning aims at exploring innovative e-learning solutions that facilitate teaching and also spark the attention and imagination of students through interactivity, immersion, variety of content, and emerging technologies. We invite submissions from e-learning leaders, researchers, and practitioners around the world. This journal has published research reports as listed in Topics and will continue to observe the trend of development. In particular, articles published have primarily addressed:

educational environments that are friendly, smart or intelligent, open, personalized, and can seamlessly support anytime anywhere learning or training.
teaching innovations such as virtual reality, mixed reality, mobile learning systems that can interact with students and teachers at a pedagogical level.
learning solutions that can support the learning of practical skills, such as science and engineering laboratories that are critical to students following STEM courses.
and the design and implementation of social learning through the integration of learning management systems and social media.
Accessibility and usability of online learning
Assessment of e-learning strategies and outcomes
Augmented reality and associated pedagogies
Best Practices of e-Learning around the world
Big Data in global e-Learning
Blended learning
Collaborative learning in in various learning environments
High-impact practices in e-Learning
Immersive learning and mixed reality
Innovative solutions for e-Learning
Intelligent learning and intelligent learning management systems
Learning analytics
Massive open online courses
Mobile learning and its large-scale implementation
Security and privacy in education and e-learning systems
Social learning and social networks
Social and organizational perspectives
Standards and infrastructures
Student engagement in various learning settings
Educational Models and Frameworks
Virtual and Augmented Learning Environments

Call for Papers: Special issue on: Intelligent Application in Special Education (IASE) (Manuscript submission deadline: 2021-06-30; Notification of acceptance: 2021-07-30; Submission of final revised paper: 2021-08-30; Publication of special issue (tentative): 2021-09-17)

Lead Guest Editor: Xianwei Jiang (Nanjing Normal University of Special Education, China)

Alberto Bucciero (Università del Salento, Italy)
Amruth Kumar (Ramapo College of New Jersey, USA)
Anasol Pena Rios (University of Essex and British Telecom)
Andrea Pandurino (Università del Salento, Italy)
Andrey Lyamin (ITMO University, Russia)
Athanassios Jimoyiannis (University of Peloponnese, Greece)
Dagmar Caganova (Slovak University of Technology)
Debbie Holley (Bournemouth University, UK)
Ed Currie (Middlesex University, UK)
Edward Currie (Middlesex University)
Eusebio Scornavacca (University of Baltimore, USA)
Evgeniy Efimchik (ITMO University, Russia)
Francisco Bellido (Universidad de Córdoba, Spain)
George Evangelinos (Anglia Ruskin University, UK)
Goran Trajkovski (Western Governors University, USA)
Gordon Hunter (Kingston University, UK)
Jaime Meza (Universitat Politècnica de Catalunya, Spain)
Jamshid Beheshti (McGill University, Canada)
Jia Chen (Shanghai International Studies University)
John Carfora (Loyola Marymount University, USA)
John O'Connor (Dublin Institute of Technology, Ireland)
Jonathon Richter (Director of iLRN)
Luca Ferrari (Università di Bologna, Italy)
Mark J. W. Lee (School of Education Charles Sturt University, Australia)
Markus Helfert (Dublin City University, Ireland)
Matthias Glowatz (University College Dublin, Ireland)
Melody Buckner (University of Arizona, USA)
Michelle Crosby-Nagy (International Business School, Hungary)
Nian-Shing Chen (Editor of Educational Technology and Society)
Nicoletta Adamo-Villani (Purdue University, USA)
Nurul Badrul (Centre for Instructor and Advanced Skill Training, Malaysia)
Radhika Pai (Manipal Institute of Technology, India)
Regina Kaplan-Rakowski (Southern Illinois University, USA)
Richard Boateng (University of Ghana, Ghana)
Sabrina Leone (Università Politecnica delle Marche, Italy)
Shuai Liu (Hunan Normal University, China)
Stefano Za (LUISS University, Italy)
Steven Truxal (City University of London, UK)
Sujan Shrestha (University of Baltimore, USA)
Victor Zamudio (Instituto Tecnologico de Leon, Mexico)
Vladimír Bradáč (Ostravská Univerzita, Czech Republic)
Vladimir Uskov (Bradley University, USA)
Xuesong Zhai (Science and Technology University of China)
Xianwei Jiang (Nanjing Normal University of Special Education, China)
S. Suman Rajest George (Vels Institute of Science, Technology & Advanced Studies, India)

Yu-Dong Zhang (Eugene)¹

Prof. Yu-Dong Zhang worked as a postdoc from 2010 to 2012 with Columbia University, USA; and as an assistant research scientist from 2012 to 2013 with Research Foundation of Mental Hygiene (RFMH), USA. He served as a Full Professor from 2013 to 2017 with Nanjing Normal University. Now he serves as Professor with Department of Informatics, University of Leicester, UK. His research interests include deep learning and medical image analysis. Prof. Zhang is the Fellow of IET (FIET), and Senior Members of IEEE and ACM. He was included in “Most Cited Chinese researchers (Computer Science)” by Elsevier from 2014 to 2018. He was the 2019 recipient of “Highly Cited Researcher” by Web of Science. He won “Emerald Citation of Excellence 2017” and “MDPI Top 10 Most Cited Papers 2015”. He was included in "Top Scientist" in Guide2Research. He is the author of over 200 peer-reviewed articles, including 16 “ESI Highly Cited Papers”, and 2 “ESI Hot Papers”.

Marco Zappatore²

Marco Zappatore is a telecommunications engineer who currently acts as a postdoctoral research fellow at the Department of Engineering for Innovation, University of Salento (Italy).

His main research interests are focused on data and knowledge management techniques, mobile crowd sensing and citizen science, semantic Web and ontologies. He is also involved in research activities dealing with sensor data management, remote engineering and applications of new learning paradigms (e.g., collaborative learning, mobile learning, BYOD, etc.). His expertise also deals with electromagnetic field measurements, radio-propagation analysis, wireless communication system (2G to 4G) planning and optimization. He is also involved in teaching activities dealing with software solutions for translators and interpreters. He has also co-authored more than 60 papers for national and international conferences and journals. He is member of several technical program committees in international conferences and journals. He acts as scientific reviewer for 12 international annual conferences and 14 international journals.

In 2014, he started collaborating with the European Alliance for Innovation (EAI) as Web Chair and TPC member/chair for several international conferences.

1: University of Leicester, UK
2: Marco Zappatore is a telecommunications engineer who currently acts as a postdoctoral research fellow at the Department of Engineering for Innovation, University of Salento (Italy).

Recently Published
Most Popular

Review on One-Stage Object Detection Based on Deep Learning
Appears in:
el 22(23): e5

Authors:
Hang Zhang, Rayan S Cloutier

Published:
9th Jun 2022

Abstract:
As a popular research direction in computer vision, deep learning technology has promoted breakthroughs in the field of object detection. In recent years, the combination of object detection and the Internet of Things (IoT) has been widely used in the fields of face recognition, pedestrian detect…As a popular research direction in computer vision, deep learning technology has promoted breakthroughs in the field of
object detection. In recent years, the combination of object detection and the Internet of Things (IoT) has been widely used
in the fields of face recognition, pedestrian detection, unmanned driving, and customs detection. With the development of
object detection, two different detection algorithms, one-stage, and two-stage have gradually formed. This paper mainly
introduces the one-stage object detection algorithm. Firstly, the development process of the convolutional neural network
is briefly reviewed, Then, the current mainstream one-stage object detection model is summarized. Based on YOLOv1, it
is continuously optimized, and the improvements and shortcomings are summarized in detail. Finally, a summary is made
based on the difficulties and challenges of one-stage object detection algorithms.
more »
Recognition system for fruit classification based on 8-layer convolutional neural network
Appears in:
el 22(23): e4

Author:
Jia-Ji Wang

Published:
17th Feb 2022

Abstract:
INTRODUCTION: Automatic fruit classification is a challenging task. The types, shapes, and colors of fruits are all essential factors affecting classification. OBJECTIVES: This paper aimed to use deep learning methods to improve the overall accuracy of fruit classification, thereby improving…INTRODUCTION: Automatic fruit classification is a challenging task. The types, shapes, and colors of fruits are all
essential factors affecting classification.

OBJECTIVES: This paper aimed to use deep learning methods to improve the overall accuracy of fruit classification,
thereby improving the sorting efficiency of the fruit factory.

METHODS: In this study, our recognition system is based on an 8-layer convolutional neural network (CNN) combined
with the RMSProp optimization algorithm to classify fruits. It is verified through 10 times 10-fold crossover validation.

CONCLUSION: Our method achieves an accuracy of 91.63%, which is superior to the other four state-of-the-art methods.
more »
Covid-19 Recognition by Chest CT and Deep Learning
Appears in:
el 22(23): e3

Authors:
Lin Yang, Dimas Lima

Published:
7th Jan 2022

Abstract:
INTRODUCTION: The current RT-qPCR approach to identify Covid-19 diseases is slow and non-optimal for a large number of candidates. OBJECTIVES: Several studies have demonstrated that deep learning can help healthcare professionals diagnose Covid-19 patients. The deep learning model proposed i…INTRODUCTION: The current RT-qPCR approach to identify Covid-19 diseases is slow and non-optimal for a large
number of candidates.

OBJECTIVES: Several studies have demonstrated that deep learning can help healthcare professionals diagnose Covid-19
patients. The deep learning model proposed in this paper significantly enhanced the accuracy of identifying Covid-19
patients compared to prior approaches.

METHODS: This paper applies transfer learning and deep residual network ResNet152V2 to detect Covid-19 patients with
the help of CT scan images. Monte Carlo Cross-Validation has been applied to obtain an accurate and valid result.

RESULTS: The proposed model can identify Covid-19 disease with an overall accuracy of 95.06%, along with an average
precision and recall of 97.19% and 92.81%, respectively. It also obtained a specificity of 93.14% and a F1-score of
94.96%.

CONCLUSION: The performance of this proposed ResNet152V2 model is superior to most of the current Covid-19
detection models.
more »
Teachers’ Use of Technology: Examining the Domains of Laptop Competence
Appears in:
el 22(23): e2

Authors:
Priscilla Moses, Su Luan Wong

Published:
26th Oct 2021

Abstract:
INTRODUCTION: The current coronavirus pandemic has forced the transition from face-to-face teaching and learning to fully online in Malaysia. OBJECTIVES: To examine the domains of laptop competence and its relationship with laptop use among teachers. METHODS: A quantitative descripti…INTRODUCTION: The current coronavirus pandemic has forced the transition from face-to-face teaching and learning to fully online in Malaysia.

OBJECTIVES: To examine the domains of laptop competence and its relationship with laptop use among teachers.

METHODS: A quantitative descriptive survey design using questionnaires involved 133 Mathematics and Science secondary school teachers.

RESULTS: Based on the results, the teachers are highly competent in word processor; basic laptop operation skills; telecommunication; spreadsheet; multimedia integration; and setup, maintenance, and troubleshooting of laptop but only moderately competent in media communication; and database. There was a significant positive relationship between teachers’ laptop competence and laptop use.

CONCLUSION: Act as a guide to plan effectual training according to the needs of the teachers based on each item of the domains outlined to promote more rigorous use of laptops among the teachers.
more »
Alzheimer’s disease diagnosis via 5-layer Convolutional Neural Network and Data Augmentation
Appears in:
el 22(23): e1

Author:
Shuangshuang Gao

Published:
16th Sep 2021

Abstract:
OBJECTIVES: Alzheimer's disease (AD) is a progressive neurodegenerative disease with insidious onset and one of the biggest challenges in geriatrics. Because the cause of the disease is unknown and there is currently no cure, AD Early diagnosis is particularly import…OBJECTIVES: Alzheimer's disease (AD) is a progressive neurodegenerative disease with insidious onset and one of the biggest challenges in geriatrics. Because the cause of the disease is unknown and there is currently no cure, AD Early diagnosis is particularly important.

METHODS: In this paper, we built a 5-layer convolutional neural network based on deep learning technology. We used six data augmentation methods to increase the size of the training set. Batch normalization and dropout techniques are also used,
which are respectively associated with the convolutional layer and the fully connected layer, Form convolution batch normalization (CB) and dropout fully connected (DOFC) block respectively.

RESULTS: Our 5-layer CNN has shown excellent results on the training set, a sensitivity of 94.80%, a specificity of 93.98%, a precision of 94.04% and an accuracy of 94.39%, and has good performance compared with several other state-of-the-art
methods.

CONCLUSION: In terms of classification performance, our method performs better than 8 state-of-the-art approaches and the performance of human observers. Therefore, this proposed method is effective in the detection of Alzheimer’s disease.
more »
Six-layer Optimized Convolutional Neural Network for Lip Language Identification
Appears in:
el 21(22): e5

Authors:
Yifei Qiao, Hongli Chen, Xi Huang, Juan Lei, Xiangyu Cheng, Huibao Huang, Jinghan Wu, Xianwei Jiang

Published:
20th Aug 2021

Abstract:
INTRODUCTION: Lip language is one of the most important communication methods in social life for people with hearing impairment and impaired expression ability. This communication method relies on visual recognition to understand the meaning expressed in communicati…INTRODUCTION: Lip language is one of the most important communication methods in social life for people with
hearing impairment and impaired expression ability. This communication method relies on visual recognition to
understand the meaning expressed in communication.

OBJECTIVES: In order to improve the accuracy of this natural language recognition, we propose six-layer optimized
convolutional neural network for lip recognition.

METHODS: The calculation method of the convolutional layer in the CNN model is used, and two pooling methods are
compared: the maximum pooling operation and the average pooling operation to analyse the most important feature data in
the picture. In order to reduce the simulation in the model training process, the closing rate has been optimized by
introducing Dropout technology.

RESULTS: It shows that the recognition accuracy rate based on the six-layer convolutional neural network can reach
85.74% on average. This method can effectively recognize lip language.

CONCLUSION: We propose a six-layer optimized convolutional neural network method for lip language recognition, and
the identification of lip language features of this method is better than 3D+ DenseNet +1 × 1 Conv +resBi-LSTM,
3D+CNN, ConvNet+2 -256-LSTM+VGG-16 three advanced methods.
more »
Lip language identification via Wavelet entropy and K-nearest neighbor algorithm
Appears in:
el 21(22): e4

Authors:
Ran Wang, Yifan Cui, Xinyu Gao, Wei Chen, Mingbo Hu, Qian Li, Jiahui Wei, XianWei Jiang

Published:
11th Aug 2021

Abstract:
INTRODUCTION: Image processing technology is widely used in lip recognition, which can automatically detect and analyse the unstable shape of human lips. OBJECTIVES: In this paper, we propose a new algorithm using Wavelet entropy (WE) and K-nearest neighbor (KNN) …INTRODUCTION: Image processing technology is widely used in lip recognition, which can automatically detect and analyse the unstable shape of human lips.

OBJECTIVES: In this paper, we propose a new algorithm using Wavelet entropy (WE) and K-nearest neighbor (KNN) improves the accuracy of lip recognition.

METHODS: At present, the two most commonly used technologies are wavelet transform and 𝐾𝐾-nearest neighbor algorithm. Wavelet transform is a set of image descriptors, and the 𝐾𝐾-nearest neighbor algorithm has high accuracy. After a large
number of experiments, we propose a lip recognition method based on Wavelet entropy and 𝐾𝐾-nearest neighbor, which combines Wavelet entropy, 𝐾𝐾-nearest neighbor and K-fold cross validation.

RESULTS: This method reduces the calculation time and improves the training speed. The best result of the experiment improves the accuracy to 80.08%.

CONCLUSION: Therefore, our algorithm is superior to other state-of-the-art approaches of lip recognition.
more »
Gray level co-occurrence matrix and Schmitt neural network for Covid-19 diagnosis
Appears in:
el 21(22): e3

Author:
Pengpeng Pi

Published:
11th Aug 2021

Abstract:
INTRODUCTION: When COVID-19 spreads to most of the world, chest CT imaging is widely regarded as a convenient and feasible method for the diagnosis of suspected patients. In the traditional diagnosis method, doctors and experts judge these CT images and draw conclusions. However, with the …INTRODUCTION: When COVID-19 spreads to most of the world, chest CT imaging is widely regarded as a convenient and feasible method for the diagnosis of suspected patients. In the traditional diagnosis method, doctors and experts judge these CT images and draw conclusions. However, with the surge in the number of suspected patients, relying solely on traditional manual diagnosis methods can no longer meet people's demand for efficiency.

OBJECTIVES: A number of previous studies have shown that it is possible to use machine learning methods to help people diagnose suspected SARS-CoV-2 patients. However, the accuracy of the existing scheme still needs to be improved.

METHODS: In order to make a more accurate diagnosis of suspected patients with SARS-CoV-2, we proposed a new model. We first preprocessed the CCT images of the tested objects to seek for higher accuracy, then extracted the texture features from the processed CCT images, and finally divided the CCT images of the tested objects into two categories: sick and normal using Schmidt neural network.

RESULTS: The accuracy of the proposed model is (76.33±1.18%), while the accuracy of the existing model RBFNN, ELM-BA, WEBBO and GLCM-SVM are (73.45±0.69%), (74.88±0.86%), (70.48±0.81%) and (64.42±0.88%), respectively. Compared with the existing RBFNN, ELM-BA, WEBBO and GLCM-SVM models, the accuracy of our proposed model is
1.45% higher than that of the best ELM-BA model. More importantly, the proposed model has better stability.

CONCLUSION: The model we proposed is feasible for the corresponding diagnosis of suspected patients. This is not only conducive to timely treatment of patients, but more importantly, effective isolation of confirmed patients as soon as possible can prevent the further spread of the epidemic.
more »
An immersive game of simulated visually impaired
Appears in:
el 21(22): e2

Authors:
Juan Lei, Xi Huang, Tao Chang, Qijun Wu, Yingying Long, Xianwei Jiang

Published:
1st Jul 2021

Abstract:
INTRODUCTION: "Inverse light" is the experience of visually impaired people an immersive gaming experience, reducing the blind of the difficulties in life and study, etc., to bring players to experience the real life scene, the hearing, sight, touch, fully integrated into the g…INTRODUCTION: "Inverse light" is the experience of visually impaired people an immersive gaming experience, reducing the blind of the difficulties in life and study, etc., to bring players to experience the real life scene, the hearing, sight, touch, fully integrated into the game, let the players from the Angle of view of the blind, rational view of the nowadays social existence of accessibility issues, It also analyses several important issues, such as fun, playability, education in games, etc. This paper will elaborate the connotation of educational games and gamified learning, the source of creativity, and the design and implementation of games.

OBJECTIVES: In order to raise the public's attention to the visually impaired people and strengthen quality education, mobile games are combined with the inconveniences that the visually impaired people encounter in life to arouse the players' thinking and call on people to be more patient and helpful to the visually impaired.

METHODS: This game is mainly based on the black screen effect. In the case of limited vision, the direction is judged by clicking, holding down, sliding and other keys as well as the background sound effect, so as to bypass the obstacles. Finally, through the level, the background and animation in the game are designed with Photoshop, and the modeling is completed with 3DMAX. Microsoft Visual Studio was used to write C# scripts, and Unity was used for scene construction and overall coordination.

RESULTS: The experiment proves that the game can analyse the current situation of quality education very well and combine quality education with games. The system framework of the game has clear logic, moderate operation difficulty, and appropriate sounds are used to simulate visually impaired people, which increases the immersive sense of the game. At the same time, the problem of boring game and easy loss of players is solved, and the win-win effect of education and playability of the game is realized.

CONCLUSION: " Inverse light " game from the design ideas, game development framework, difficulty and other aspects of the analysis, has a very good reflection, and the game interface design is exquisite, has a certain level of art, can meetthe experience of visually impaired people's feelings of the original intention of game development.
more »
Tea category classification via 5-layer customized convolutional neural network
Appears in:
el 21(22): e1

Authors:
Xiang Li, Mengyao Zhai, Junding Sun

Published:
5th May 2021

Abstract:
INTRODUCTION: Green tea, oolong, and black tea are the three most popular teas in the world. If classified tea by manual, it will not only take a lot of time, but also be affected by other factors, such as smell, vision, emotion, etc. OBJECTIVES: Other methods of tea category classification have…INTRODUCTION: Green tea, oolong, and black tea are the three most popular teas in the world. If classified tea by manual, it will not only take a lot of time, but also be affected by other factors, such as smell, vision, emotion, etc.

OBJECTIVES: Other methods of tea category classification have the shortcomings of low classification accuracy, weak robustness. To solve the above problems, we proposed a method of deep learning.

METHODS: This paper proposed a 5-layer customized convolutional neural network for 3 tea categories classification.

RESULTS: The experimental results show that the method has fast speed and high accuracy of tea classification, which is 97.96%.

CONCLUSION: Compared with state-of-the-art methods, our method has better performance than six state-of-the-art methods.
more »

UTAUT: Integrating Achievement Goals and Learning Styles for Undergraduates’ Behavioural Intention to Use Technology
Appears in:
el 18(17): e2

Authors:
T.C.Y. Tey, P. Moses

Downloads:
2356

Abstract:
In Malaysia, technology use is much emphasised as the Ministry of Education foresees great potential of technology use in amplifying students’ learning. However, the great potential of technology use has not been fully realised. Therefore, the purpose of this study was to explore the influence of t…In Malaysia, technology use is much emphasised as the Ministry of Education foresees great potential of technology use in amplifying students’ learning. However, the great potential of technology use has not been fully realised. Therefore, the purpose of this study was to explore the influence of the existing antecedents in the Unified Theory of Acceptance and Use of Technology (UTAUT) model with two additional variables (achievement goal and learning styles) on undergraduates’ behavioural intention to use technology. This study also aimed to determine the best predictor of undergraduates’ intention to use technology. Hence, a quantitative survey method involving 699 undergraduates was employed in this study. The findings indicated that the undergraduates’ effort expectancy, performance expectancy, social influence and achievement goals had significant influence on their behavioural intention to use technology. This study provides insights to the education stakeholders on the necessity to enhance pedagogical technology innovations in the higher education system.
more »
Enhancing Student Engagement Through Social Media A School of Business Case Study
Appears in:
el 14(4): e4

Authors:
M. Glowatz, L. Bofin

Downloads:
1932

Abstract:
While many universities have been deploying both electronic learning (eLearning) and social media applications for academic purposes, there is currently little research on the impact on their use on students’ overall learning experiences and associated learning possibilities. This paper elaborates …While many universities have been deploying both electronic learning (eLearning) and social media applications for academic purposes, there is currently little research on the impact on their use on students’ overall learning experiences and associated learning possibilities. This paper elaborates on several online academic activities, such as Facebook, Twitter and quizzes for one classroom taught school of business undergraduate (UG) module. The similarities and differences discovered across all aspects of this paper’s research findings are examined against Chickering & Gamson’s [1] seven principles of good practice teaching and Astin’s [2] five tenets of engagement. Online activities were tracked over a period of one academic semester (fifteen weeks) and results insinuate that innovative and sustainable social media can indeed be utilised in higher education to enhance student learning and engagement.
more »
From structured to unstructured learning via a technology-mediated learning framework
Appears in:
el 18(17): e5

Authors:
Lindsay Miller, Junjie Gavin Wu

Downloads:
1654

Abstract:
In this paper we propose a simple technology-mediated framework for course design. By way of a group project, students were asked to discuss issues about their local culture using their second language. We illustrate that this type of out-of-class learning stimulated the students to use a technolog…In this paper we propose a simple technology-mediated framework for course design. By way of a group project, students were asked to discuss issues about their local culture using their second language. We illustrate that this type of out-of-class learning stimulated the students to use a technologically enhanced learning environment by engaging them with meaningful communication and we show instances from the project data where the following areas were covered: content, collaboration, and learner autonomy. Smartphones, when used appropriately, can be a useful tool for content and language learning.
more »
On the importance of social network sites in the transitions which characterize ‘emerging adulthood’
Appears in:
el 11(1): e4

Authors:
Gianluca Frozzi, Elvis Mazzoni

Downloads:
1543

Abstract:
Modern-day economic and socio-cultural developments require people to be ever more specialized and mobile in their educational and professional choices. This is particularly relevant for ‘emerging adults’, that is to say, those who find themselves at that stage of life when their scholastic or univ…Modern-day economic and socio-cultural developments require people to be ever more specialized and mobile in their educational and professional choices. This is particularly relevant for ‘emerging adults’, that is to say, those who find themselves at that stage of life when their scholastic or university education ends, and they begin to make choices regarding their professional working life. Transitions between different activity systems, and changes of residence which they entail, make ‘emerging adulthood’ a particularly unstable period in which young people continually dissolve, create and recreate relationship networks of varying degrees of importance which are able to support them through these changes. Beginning with empirical evidence and theoretical starting points typical of the psychology of education and development, this contribution proposes a theoretical reflection which attempts to analyze the efficacy of Social Network Sites in facilitating and supporting emerging adults during their education and vocational training and the important transitions which they have to face as they develop.
more »
Sub-pixel Edge Detection of LED Probes Based On Partial Area Effect
Appears in:
el 15(7): e3

Authors:
Chung-Yen Su, Li-An Yu, Nai-Kuei Chen, Jheng-Jyun Wang, Ying-Hao Liu, Shuen-De Wu

Downloads:
1515

Abstract:
In recent years, the demands for LED are increasing. For testing the quality of LEDs, a lot of LED probes are necessary, so the high precision and efficient methods are paid more attention by industrial applications. This paper is focused on the measurement of the angle and the radius of a LED prob…In recent years, the demands for LED are increasing. For testing the quality of LEDs, a lot of LED probes are necessary, so the high precision and efficient methods are paid more attention by industrial applications. This paper is focused on the measurement of the angle and the radius of a LED probe by computer vision. In previous paper, we proposed an effective method based on Canny edge detection and curve fitting method with iteration. In this paper we add a new sub-pixel edge detection method: partial area effect. We improve the preciseness of angle from error 2.3% to 1.43% and enhance the accuracy of radius more than 30%.
more »
Blended learning for developing effective virtual teams: a proposed intervention format
Appears in:
el 16(12): e4

Authors:
Cristiano Ghiringhelli, Alessandra Lazazzara

Downloads:
1508

Abstract:
The aim of this exploratory study was to develop a blended learning approach to fostering the skills and competencies required by leaders and members of international virtual teams. Three levels of analysis were brought to bear in designing the proposed intervention format: first, the factors likel…The aim of this exploratory study was to develop a blended learning approach to fostering the skills and competencies required by leaders and members of international virtual teams. Three levels of analysis were brought to bear in designing the proposed intervention format: first, the factors likely to influence the effectiveness of a virtual team; second, the needs and challenges related to the early stages of the virtual team membership; third, the role of the human resource function in promoting – via training and development programmes – the knowledge and skills needed for virtual teams to be successful. The research questions included: What are the perceived benefits and challenges associated with the early stages of virtual collaboration? What factors must be carefully defined and managed when running a virtual team? What training needs are perceived by inexperienced virtual team members? How can training and development initiatives contribute to the effectiveness of virtual teams? A qualitative approach based on the model developed by Bal & Gundry was used to analyse data from five interviews with virtual team members at Nielsen TAM Italy. The outcomes informed the proposed blended training programme.
more »
Animating Instructional Materials in Computer Education: An Approach to Designing and Teaching Concepts in Data Structures Using LATEX
Appears in:
el 12(1): e3

Authors:
Damilola Osikoya, Adeleke Oluwalani

Downloads:
1494

Abstract:
Animation gives a different perception on what is being visually presented. Research has shown that students are likely to understand what is being taught from the combination of animation and text than just with text. Students easily understand scientific concepts in narrative and animated forms…Animation gives a different perception on what is being visually presented. Research has shown that students
are likely to understand what is being taught from the combination of animation and text than just with text.
Students easily understand scientific concepts in narrative and animated forms. Data structure is a way of
storing and arranging data. The efficacy of searching these stored data is very important, so is it vital that they
are stored with the right algorithm. This paper presents animations designed to support teaching in computer
education. Our main focus is to present controlled animated instructional materials in teaching topics in data
structures. We have created three scientifically animated instructional materials in data structures consisting
of the Stacks, Queues and Trees. These scientific spheres have been chosen to demonstrate the basic ideas
of this work, because of its simplicity in representing the animations. We hope to develop reasonable sets
of instructional material of different subject areas that will be stored in a database repository. These are
intended to be delivered to students through an e-learning website and/or Mobile phones to support them
with additional learning opportunities.
more »
Using arcade games to engage students in the learning of foreign and mother languages
Appears in:
el 15(2): e2

Author:
Adelina Moura

Downloads:
1432

Abstract:
It is imperative to continue thinking about and reinventing education because mobile technologies and the Web are redefining where, when and from whom we learn. Authors from different study fields have recognised the multiple possibilities of video games for language learning and for interdiscipli…It is imperative to continue thinking about and reinventing education because mobile technologies and the Web are redefining where, when and from whom we learn. Authors from different study fields have recognised the multiple
possibilities of video games for language learning and for interdisciplinary use. Education can benefit from the potential of these artefacts if properly integrated into the educational process. This article describes a language learning experience
based on electronic games – of the ARCADE type. This research has been carried out in order to study the learning of vocabulary, grammar and other school curriculum in Portuguese and French classes, both in Elementary and Vocational Education. The results show that video games have a positive impact on motivation for learning and cognitive development. Students’ perceptions show that ARCADE games were helpful in improving vocabulary and language skills.
Interest in these games was the same for boys and girls, however further studies are needed.
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Digital Competence and Capability Frameworks in Higher Education: Importance of Life-long Learning, Self-Development and Well-being
Appears in:
el 17(13): e1

Authors:
D. Biggins, D. Holley, M. Zezulkova

Downloads:
1410

Abstract:
The paper compares the EU’s 2013 and 2016 digital competence (DigComp) framework with the UK education’s 2009 and 2015 digital capabilities (DigCap) framework. The similarities are in the increased focus on data within privacy/overall literacy and the inclusion of well-being. Among the differences,…The paper compares the EU’s 2013 and 2016 digital competence (DigComp) framework with the UK education’s 2009 and 2015 digital capabilities (DigCap) framework. The similarities are in the increased focus on data within privacy/overall literacy and the inclusion of well-being. Among the differences, DigComp focuses on life-long learning whereas DigCap is more holistic. This is explained by diverse target audiences, as DigComp has to be relevant to various stakeholders across the EU, whilst DigCap serves the UK higher and further education sector. Although education is dominant within DigCap, both frameworks agree on the importance of digital skills, knowledge and attitudes to the fields of education, training and employment. The paper discusses a UK HE case study of a technology enhanced learning toolkit. It concludes by arguing for a human-centred approach to digital competence and capability frameworks, in which learning, self-development and well-being play a vital role.
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Learning and gamification: a possible relationship?
Appears in:
el 17(16): e1

Authors:
Leonardo Caporarello, Massimo Magni, Ferdinando Pennarola

Downloads:
1390

Abstract:
One of the most interesting and disruptive trends in the current elearning scenario is gamification, that is, the use of game design elements in non-game contexts. After providing a brief overview of the main contemporary gamification applications in organizations, this paper especially focuses on …One of the most interesting and disruptive trends in the current elearning scenario is gamification, that is, the use of game design elements in non-game contexts. After providing a brief overview of the main contemporary gamification applications in organizations, this paper especially focuses on gamification in the educational field. It discusses the existing studies on the effectiveness of gamification for learning purposes, analyzing their impact on students’ attitude, knowledge and behavior. Finally, it highlights the main gaps in the current literature, pointing to new directions of research.
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Publisher: EAI
ISSN: 2032-9253
Number of Volumes: 7

Last Published: 2022-06-09

EAI Endorsed Transactions on e-Learning

Yu-Dong Zhang (Eugene)1

Marco Zappatore2

Yu-Dong Zhang (Eugene)¹

Marco Zappatore²