Journal of e-Learning and Knowledge Society <h1 class="page-header" style="font-family: Raleway; margin-top: -50px;">Bibliometrics</h1> <p style="font-size: 18px; margin-top: -20px;"><strong>Italian ANVUR Ranking<br></strong>A-Class for Sector 10, 11-D1 and 11-D2</p> <p style="font-size: 18px; margin-bottom: -0px;"><strong>Publish-or-Perish (reference date: June 2021)<br></strong>- <strong>Scopus</strong> H-Index: <strong>18<br></strong>- <strong>Microsoft</strong> Academic H-Index: <strong>19</strong><br>- <strong>Google Scholar</strong> H-Index: <strong>30<br><br></strong><strong>Scopus (from 2009; reference year: 2020; reference date: June 2021)<br></strong>- Citescore (2020): <strong>1.9</strong><br>- CiteScore <span style="text-decoration: underline;">Rankings (2020)&nbsp;</span><br>&nbsp; - <strong>Education:</strong> <strong>Q2</strong>, <strong>61rd percentile</strong> (#504 out of 1319);<br>&nbsp;- <strong>Computer Science Application:</strong> <strong>Q3, 40st percentile</strong> (#404 out of 693);</p> <p style="font-size: 18px; margin-bottom: -45px;"><strong>Clarivate Web of Science (from 2015; reference date: June 2021)<br></strong>- H-Index: 10<strong><br></strong>- Average citation per Item:<strong> 1.57</strong></p> en-US <p>The author declares that the submitted to Journal of e-Learning and Knowledge Society (Je-LKS) is original and that is has neither been published previously nor is currently being considered for publication elsewhere.<br>The author agrees that SIe-L (Italian Society of e-Learning) has the right to publish the material sent for inclusion in the journal Je-LKS. <br>The author agree that articles may be published in digital format (on the Internet or on any digital support and media) and in printed format, including future re-editions, in any language and in any license including proprietary licenses, creative commons license or open access license. SIe-L may also use parts of the work to advertise and promote the publication.<br>The author declares s/he has all the necessary rights to authorize the editor and SIe-L to publish the work.<br>The author assures that the publication of the work in no way infringes the rights of third parties, nor violates any penal norms and absolves SIe-L from all damages and costs which may result from publication.</p> <p>The author declares further s/he has received written permission without limits of time, territory, or language from the rights holders for the free use of all images and parts of works still covered by copyright, without any cost or expenses to SIe-L.</p> <p>For all the information please check the Ethical Code of Je-LKS, available at</p> (Luciano CECCONI (Managing Editor)) (Je-LKS Staff) Wed, 28 Jul 2021 10:11:30 +0000 OJS 60 Second Cover Managing Editor Copyright (c) 2021 Italian e-Learning Association (SIe-L) Tue, 27 Jul 2021 17:28:07 +0000 The extent of South African schools’ preparedness to counteract 4IR challenges: learners’ perspectives <p>The aim of this paper was to explore learners’ perspectives on how their schools are preparing them to prosper in the Fourth Industrial Revolution (4IR) era which is powered by Artificial Intelligence (AI). Taking cognisance of the learners’ perspectives on how South African schools are preparing them is essential for enabling the education fraternity to ascertain its level of effectiveness and efficiency hence improving its state of readiness to face the challenges of the 4IR. Therefore, the exploration of the level of preparedness, in line with 4IR challenges, can assist educational policy makers and planners to be more proactive and craft mechanisms to ameliorate the obstacles and discrepancies inhibiting the acquisition of the 21st century educational competences and skills. Employing a qualitative paradigm, semi-structured focus group interviews were used to solicit data from a sample of 30 grade 10 and 11 learners. Findings reveal that computer technology was irregularly and insignificantly used indicating that South African schools are highly ineffective in dispensing grade-appropriate skills thus producing ill-prepared learners to prosper in the 4IRworld of work.</p> Munyaradzi Sikhakhane, Samantha Govender, Mncedisi Christian Maphalala Copyright (c) 2021 Italian e-Learning Association (SIe-L) Tue, 18 May 2021 05:40:12 +0000 The use of online learning environments in higher education as a response to the confinement caused by COVID-19 <p class="JELKS-Abstracttext"><span lang="EN-US">In Colombia, a developing country, higher education has a gross coverage rate of about 40% (supply concerning the entire population). However, although this value is low, ten years ago this rate barely exceeded 20%. The increase in coverage is largely due to a policy that has promoted training by cycles. This model allows education by levels with the granting of professional degrees at each stage, which allows for rapid employment. Even so, places are limited, particularly for medium and low economic levels (which concentrate the majority of the population), and access to them in public universities (those with state-funded enrolment) is very restricted. Access to education is a major concern for institutions and the state, in particular for vulnerable social groups, and has been further depressed by the security and control measures implemented to slow down the spread of the COVID-19 virus. In a short time, and with limited resources, institutions have had to adapt their models to guarantee continuity and quality in academic processes. In this context, digital platforms have come to play a fundamental role by allowing access while reducing social interaction. However, the use of these platforms implies the development of specific learning environments adapted to academic, economic, and social conditions. This paper explores the design, development, and impact of some of these learning environments in the process of technological training of students from low economic strata in the most important public university in the Colombian capital...</span></p> Fredy Martínez, Edwar Jacinto, Holman Montiel Copyright (c) 2021 Italian e-Learning Association (SIe-L) Mon, 31 May 2021 15:14:01 +0000 The effect of a Training Program based on Open Educational Resources on the Teachers Online Professional Development and their Attitudes towards it of AL-Dakhliya Governorate in Sultanate of Oman <p>This study aimed at investigating the effect of a training program based on OER on the professional development of AlDakhlia Governorate teachers. The study also investigated the teachers’ attitudes towards this form of training using an experimental research method. The training program was prepared as an interactive lecture presentation for 3 days of training; one session per day for 2 hours. The educational content was available on the SHMS platform and then the experiment was implemented on 40 teachers, where &nbsp;&nbsp;20 teachers were in the experimental group and the other 20 teachers were in the control group with professional years of experience ranged between 5 and 10 years. The results showed the significant role of the OER platforms in teachers' professional development in the form of an increase e in the level of knowledge and teaching skills. Also, the participated teachers' positive attitudes towards the online professional development indicated that these OER environments are rich in knowledge and cooperative activities. Generally speaking, these OER platforms encourage teachers to keep up with their professional development and self-learning throughout their career life.</p> Nader Shemy, Maida Al-Habsi Copyright (c) 2021 Italian e-Learning Association (SIe-L) Mon, 31 May 2021 15:22:48 +0000 Adults’ motives and barriers of participation in mixed and asynchronous learning training programs <p>This paper explores the motives, barriers and the facilitators of adults’ participation in two training programs, organized by the Center of Training and Lifelong Learning (KE.DI.VI.M.) of the Aristotle University of Thessaloniki, Greece. 215 trainees completed the questionnaire in the first program, entitled ‘Training of Lifelong Learning Adult Trainers’, while 70 students having attended the second program ‘Vocational Education and Training: Specialization of Adult Executives, Teachers and Trainers’ completed the questionnaire. It was found that the professional and personal development are the main reasons for participating in training. Regarding the barriers, the situational and institutional ones are the most important factors for non-participation in the training. Regarding the facilitators to participation in training, distance learning, recognition of certifications acquired from participation to training programs, salary’s improvement and dissemination of seminars taking place are the main facilitators for participating in lifelong learning programs.</p> Azarias Mavropoulos, Anastasia Pampouri, Konstantina Kiriatzakou Copyright (c) 2021 Italian e-Learning Association (SIe-L) Tue, 22 Jun 2021 14:06:18 +0000 Online learning amid Covid-19 pandemic: students' experience and satisfaction <p>and learning to online mode. This had huge impact on the students, especially for those who had not been used to being online for learning before. This mixed methods study utilized correlation, factor analysis and multiple regression techniques to identify significant predictors of students’ satisfaction with online learning in a higher education institution in Vietnam amid COVID-19 Pandemic. The study results show that learners’ interaction with content, peers and instructors correlated to and predicted student satisfaction. The study also indicated that although students valued the chance to be online for learning during the historic time, they viewed that interaction was limited and instructors should improve online teaching pedagogy. These findings provide learners, teachers and curriculum developers with new insights into learner interaction and its relation to course contents, teaching pedagogy and learning satisfaction in an Asian context.</p> Pham Thach, Phuong Lai, Vinh Nguyen, Hai Nguyen Copyright (c) 2021 Italian e-Learning Association (SIe-L) Tue, 29 Jun 2021 00:00:00 +0000 Classification models in the digital competence of higher education teachers based on the DigCompEdu Framework: logistic regression and segment tree <p>To promote and develop the digital competence of higher education teachers is a key aim in the 21st century. Teachers must have a leader or expert digital competence in order to prepare future school-leavers for a competent professional qualification. Therefore, the purpose of this study is to determine the predictor variables encouraging high digital competence, using two statistical classification techniques: multiple logistic regression and classification trees. The analysis of teachers’ digital competence was carried out in each of the areas of knowledge in which the teachers are assigned, as well as overall. For data collection, a non-experimental ex post facto design was used. A total of 1,104 higher education teachers from Andalusia (Spain) completed the DigCompEdu Check-In instrument prepared by the European Commission’s Joint Research Centre. In terms of general classification, the results found that the logistic regression technique ranked teachers’ digital competence with greater probability of success (83.7%) in comparison to the segment tree (81.7%). The results found that the level of digital competence of teachers in the creation and use of digital resources varies according to the area of knowledge to which the teachers are assigned. At a general level, the development of digital competence at the leader, expert or pioneer level is related to various factors, such as the time spent on creating web spaces and digital content, and the use of virtual reality, robotics, and gamification. Further research is recommended to validate these preliminary findings in each of the areas of knowledge.</p> Julio Cabero-Almenara, Francisco D. Guillen-Gamez, Julio Ruiz-Palmero, Antonio Palacios-Rodríguez Copyright (c) 2021 Italian e-Learning Association (SIe-L) Fri, 02 Jul 2021 07:36:10 +0000 Prediction of engineering students’ virtual lab understanding and implementation rates using SVM classification <p>In 2020 many universities were forced to switch to a distant form of education because of the COVID-19 lockdown. This was especially challenging for the engineering specialties, where laboratory and practical exercises are a fundamental part of the educational process. This study presents results from the electrical engineering education in two Bulgarian universities, where the Engine for Virtual Electrical Engineering Equipment was used as a tool for providing virtual labs. At the end of the semester the students were asked to fill in a survey, accounting for their learning program, years of studying, experience with virtual and real labs and the instructions delivery methods used. Data mining algorithms were utilized with the aim to predict students’ rate of understanding and rate of implementation when dealing with virtual labs. Initially, a regression analysis model was created which achieved R-squared above 95%. However, the verification of the model showed an unsatisfactory prediction success rate of 37%. Next, SVM classification was utilized. The verification showed its success rates for predicting the rate of understanding and rate of implementation were 83% and 86%, respectively. This approach could be used to optimize the educational experience of students, using virtual labs, as well as for identification of students that might need additional support and instructions.</p> Teodora Hristova, Katerina Gabrovska-Evstatieva, Boris Evstatiev Copyright (c) 2021 Italian e-Learning Association (SIe-L) Tue, 13 Jul 2021 10:05:44 +0000 The Structural Equation Model of Actual Use of Cloud Learning for Higher Education Students in the 21st Century <p>The purposes of this research were to 1) develop the structural equation model of the actual use of cloud learning for higher education students in the 21<sup>st</sup> century (SEMAC), 2) investigate the validity of the SEMAC, and 3) study the effects of the SEMAC. This study was a correlation research. The research sample consisted of 1,170 undergraduate students, randomly selected using multi-staging, from 18 universities in Thailand. The research instruments were questionnaires about system quality, convenience, social interaction, perceived ease of use, perceived usefulness, and actual use. Data analyses were descriptive statistics and the analysis for model validation used LISREL 9.2. The study found that the validation of the structural equation model indicating actual use of cloud learning showed that the model fit to the empirical data (χ2 = 34.659 df = 23 p = .056 GFI = .989 AGFI = .974 RMR = .006). The variables in the structural equation model could explain 62.4 of the variance in actual use. The research results can be used as data to improve the actual use of cloud learning.</p> Thanyatorn Amornkitpinyo, Sathaporn Yoosomboon, Sunti Sopapradit, Pimprapa Amornkitpinyo Copyright (c) 2021 Italian e-Learning Association (SIe-L) Mon, 26 Jul 2021 21:29:54 +0000 Distance learning and teaching as a consequence of the Covid-19 pandemic: A survey of teachers and students of an Italian high school taking into account technological issues, attitudes and beliefs toward distance learning, metacognitive skills <p>The Covid-19 pandemic has forced the education system to a rapid and unprepared transition to distance learning, inducing many teachers to organize lessons via information and communication technologies (ICTs), albeit often without sufficient technological and organizational support. Our study aims to evaluate teachers’ and students’ experience with ICTs during the first lockdown, considering three categories of relevant factors: technical issues, attitudes and beliefs towards online learning, and metacognitive skills. Participants were 486 students and 83 teachers of a Northern Italy high school, who were administered a self-reported online questionnaire. Video-lessons and audio-lessons emerged as overlooked teaching modalities. The desktop was the less used device, teachers preferred the tablet, while students preferred the smartphone. In general, students displayed appreciation of distance learning, even if they wished for more interactive activities. Teachers’ level of metacognitive competence and self-efficacy were rather high. For students, the perception of the e-learning environment predicted positively the perception of distance education and negatively the experienced anxiety, with anxiety also being higher among females. For teachers, the evaluation of distance learning was positively predicted by their beliefs about ICTs. This demonstrates the importance of promoting positive ICTs beliefs to motivate teachers in engaging in distance learning. Moreover, higher perceived self-efficacy was associated with lower levels of anxiety, thus showing the need to engage in training activities enabling teachers to feel confident when using ICTs.</p> Alessia Cadamuro, Elisa Bisagno, Sandro Rubichi, Lino Rossi, Daniele Cottafavi, Eleonora Crapolicchio, Loris Vezzali Copyright (c) 2021 Italian e-Learning Association (SIe-L) Mon, 26 Jul 2021 21:49:28 +0000 E-Learning & decision making system for automate students assessment using remote laboratory and machine learning <p class="JELKS-Abstracttext"><span lang="EN-US">This paper describes an implementation of a remote laboratory system for the practical works (PW) of electronics, this system make available to target and analysis the gaps, weaknesses and lack of scientific knowledge of students in the context of electric engineering through data mining algorithms and students’ study behavior. Experimental work has traditionally been developed in laboratories. However, the increase in the number of higher education students in the last decades has put pressure on the physical structures and resources of laboratories. To overcome this, computational simulations and remote laboratories have been developed enabling the expansion of educational boundaries. this paper provides new opportunities to enhance the student’s learning process. The results are presented and discussed according to two levels. The first is development a complete system of remote laboratory E@Slab and compare it with the related work. second level, we present an algorithms of Intelligence Artificial that automate evaluation and classify students in different groups attending to an assessment rubric. After this classification we compare the obtained results from algorithms of Intelligence Artificial with the levels obtained from interviews with the students and from the practical work review for to be a validation of sorts. Finally we compare the two results and we remark that algorithm classifies correctly the students with an accuracy of more than 90%.</span></p> Fahd Ouatik, Mustapha Raoufi, Farouk Ouatik, Mohammed Skouri Copyright (c) 2021 Italian e-Learning Association (SIe-L) Tue, 27 Jul 2021 15:08:57 +0000