Find research datasets worth reusing

opencc-by-4.0Sep 2022View details →

Interdisciplinary Composition of E-Learning Platforms based on Reusable Low-Code Adapters

E-learning platforms are becoming increasingly popular and, accordingly, are also being used more and more by teachers at schools and professors at universities. They are used to distribute educational material digitally to students, but also to offer the possibility to upload and collect assignments, solve tasks, and view grades. This thesis addresses the problems of the inflexibility of established platforms, assists lecturers in designing their courses, and motivates and supports students in their learning. Under the aspect of generalization, a concept for a software product line for the demands of various fields of study is designed, which provides lecturers with a basic platform and allows them to use low-code adapters to design and modify their courses according to their needs.

opencc-by-4.0Aug 2015View details →

Figure 1. e-Learning experience-How to Mix the Ingredients for a Blended Course Recipe

An important aspect of data analysis concerns the e-learning experience of our par-ticipants. Therefore, the first part of data analysis consisted of comparing the different types of experiences. Figure 1 illustrates the percentages of participants checking each type of answer. Thus, we may conclude that only 11.9 percent had no experiences in-volving e-learning. Among those who had some kind of e-learning experience, most participated in on-line courses (two thirds - 65.5%), blended learning (34.5%) or Massive Open Online Courses (32.1%); the percentage of those participating in MOOCs (nearly a third of the respondents) is quite impressive from the point of view of the interest in this trending model for personal and professional development. It is worth noting as well that almost one third of the responders have experience in facilitating online courses (31%) and more than a quarter (28.6%) facilitated blended courses, which demonstrates the increasing rate of e-learning integration in Romanian education. Nevertheless, we can observe that online courses represented the most common e-learning experience. It is important to mention that all percentages are relative to the total number of participants.

opencc-by-4.0Aug 2015View details →

Figure 3. e-Learning components assessment by domain-How to Mix the Ingredients for a Blended Course Recipe

The disadvantages of online/blended courses noted by participants are summarized in the following paragraph: • there isn’t a national policy related to the integration of new technologies/ pedagogies, OER in education; • teachers should be trained to be able to develop and facilitate online and blended courses; • there are no incentives to reward teachers using open technologies/pedagogies; • student assessment when using online collaboration and social media could be difficult; • there should be a team of experts to develop quality online courses; • the lack of digital skills of both students and teachers could be a barrier for such courses; • time management could be a challenge; • the lack of feedback from teachers could demotivate students.

BRAIN Journal-The Ambivalence of Strengths and Weaknesses of E-Learning Educational Services-Figure 2. Frequency of principal strong indices related to 102 'strong articles'

We ordered the obtained data for the identified strengths and weaknesses. This was done by giving a point for each presence of an index, or not giving it for its absence. Thus, we quantified a total of 63 strengths and 91 weaknesses. In addition to finding a great diversity of views captured in the selected texts, the primary data analysis allowed us to set the parameters with the highest frequency. So, the most important for strengths is flexibility representing 29.7% of the total of studied bibliography and an occurrence frequency of 13.6% from the total of identified strengths (Figure 2).

BRAIN Journal-The Ambivalence of Strengths and Weaknesses of E-Learning Educational Services-Figure 1. Frequencies of strengths and weaknesses through a survey of literature from 2000 to 2012

We identified 192 specific studies which analyze, directly or indirectly, the subject of the strengths and weaknesses of e-learning educational services, respectively those containing the idea of some of their strengths and weaknesses ambivalence. The frequencies of strengths and weaknesses reported to intervals corresponding to the years when they were published are shown in Figure1.

BRAIN Journal-The Ambivalence of Strengths and Weaknesses of E-Learning Educational Services-Figure 3.Frequency of principal week indices related to the 101 'week articles'

Reduced social interaction is the most important for weaknesses, representing 9.4% of the total of studied bibliography and an occurrence frequency of 5.5% (Figure3). A significant frequency difference of the weaknesses indices compared to the strengths indices was observed. If the top 5 strengths have frequencies ranging between 13.6% and 7%, none of the weaknesses has an occurrence frequency over 6%, all barely ranging between 5.5% and 3.4%, relative to the middle of strengths frequency range. For the practice of e-learning educational services, this may show either a still insufficient detection or theoretical analysis of weaknesses, or, indeed, the superiority of these services.

BRAIN Journal-The Ambivalence of Strengths and Weaknesses of E-Learning Educational Services-Figure 5. Frequency of common indices related to 102 'common articles'

An additional and very interesting perspective is provided by the analysis of common indices (ambivalent), based on the 102 works-common articles type, and their frequencies (Figure 5).  The data reading indicates 13 ambivalent indices as percentages in descending order: 1. flexibility, 19%; 2. interactivity, 15.4%; 3. cost, 13%; 4. accessibility, 12%; 5. time, 7%; 6. anxiety/reduce social impact, 7%; 7. usability, 6%; 8. connection, 4%; 9. develop skills, 4%; 10. responsibility, 4%; 11. quality, 4%; 12. diversity, 3%; 13. delivery, 1% (Figure 5).

BRAIN Journal-The Ambivalence of Strengths and Weaknesses of E-Learning Educational Services-Figure 4. Frequency of strong/weak indices related to the 102 'common articles'

Based on the data presented in Figure 2 and Figure 3 and carrying out a comparative and cumulative analysis to identify ambivalent strengths and weaknesses, the 102 ambivalent strong/weak indices related to the 'common articles' in Figure 4 were highlighted.  Their analysis shows that: 1. There are at least 13 ambivalent indicators identified in the studied literature (Table 1); 2. The strengths weight is 62% while the weight of weaknesses is 38.9%, resulting in a pretty big difference in favor of underlining and supporting the strengths, 23.1% more than in favor of weaknesses. These data indicate a significantly higher perception and approach in favor of appreciating the strengths of e-learning educational services, even in the case of their ambivalence. 3. In this context, the data illustrate the following three cases: 3.1. a huge gap between the perception and the interpretation of an index as strength and as weakness (e.g., flexibility is regarded 7.5 times more a strength rather than a weakness). It can be seen that this category of indices definitely belongs to strengths, acknowledged and validated by a large number of studies. In relation to these, efforts will be made for the development, improvement, elevation and obtaining superior parameters. 3.2. a relative correspondence between the perception and the interpretation of an index as strength and as weakness (e.g., the time required to design and implement educational services is considered a strength at a rate of 3.2% and a weakness at a rate of 3.3%). It results that this category of indices has to be studied thoroughly and watched in experimental studies, to replace the uncertainty area in their analysis, to determine which their area of predominance is, to what extent their identified limits and shortcomings have been reduced to allow their conversion into strengths or not; 3.3. a very large gap between the perception and interpretation of an index as a weakness and as a strength (e.g., lack of instructional delivery is considered as being a weakness 20 times more than a strength).This shows that this category of indices comes into focus as weaknesses which need to be analyzed, studied and experimented in order to reduce their negative impact.

opencc-by-4.0Jul 2021View details →

Perceived stress and e-learning readiness data set during COVID-19

The COVID-19 pandemic has restricted all educational institutions from the traditional campus-based education system to e-learning worldwide. However, adapting to this new platform, e-learning readiness may cause perceived stress among students. This study aimed to examine the association between e-learning readiness and perceived stress as well as the relationship with socio-demographic and e-learning related factors. This cross-sectional study was employed, where 1145 e-learning enrolled university students were surveyed.

opencc-by-4.0Dec 2022View details →

E-Learning Readiness In Higher Education Institutions In Nigeria during the COVID-19 Pandemic

Data set for the paper " E-Learning Readiness In Higher Education Institutions In Nigeria during the COVID-19 Pandemic"

opencc-by-4.0Dec 2021View details →

Availability and use of technology for e-learning in Bangladesh

There are 1162 responses in the dataset. Respondents’ gender, division, and residence were obtained. Here, 6 items stand (“availability_item_1” to “availability_item_6”) for availability and 11 items (“usability_item_1” to “usability_item_11”) for use of technology measure, where the initial responses were in 5 points Likert scale (1 for “strongly disagree” and 5 for “strongly agree”). On the other hand, 14 items’ (“pss_item_1” to “pss_item_14”) PSS scale was used for measuring stress, where responses were also in five-point Likert scale (0 for “Never” and 4 for “Very often”). However, reverse scoring for items 4, 5, 7, & 8 are given in this data set, according to the instruction of scale scoring. In the dataset, “availability_item_1_binary” to “availability_item_6_binary” and “usability_item_1_binary” to “usability_item_11_binary” represent the categories (1 for “sub-optimum” and 2 for “optimum”) of the availability and usability of technology measure.

opencc-by-4.0Mar 2022View details →

Students' Perception towards e-learning during COVID-19 Pandemic in Indonesia

The study explores university students' perceptions of e-learning in the context of the ongoing COVID-19 epidemic. The study finds that students prefer e-learning because it enables them to connect with their lecturers and fellow students and engage with their study materials at their leisure, and with the freedom to choose their preferred location and time. One of the key reason students choose e-learning is the ease with which they may obtain study resources. The research methods used with a quantitative model, where the sample tested represented the student of 1137 respondents from 43 universities in Indonesia.  The study's findings show the weakness of e-learning is that the majority of respondents responded in turn to interaction with lecturers (52,7%). The study also identified that the majority of respondents have a moderate mastery of technology, 1038 individuals (77.6%), while the remainder has poor knowledge of technology, as many as 52 people (3.9%).  According to the study, e-learning technology enables quick access to information, which results in students developing a favorable attitude toward it based on its utility, self-efficacy, the convenience of use, and student behavior related to e-learning. The study verifies the utility of e-learning by demonstrating how it enables students to study from any geographical location, which is not achievable with face-to-face instruction.

opencc-by-4.0Jun 2022View details →

College students' perception of e-learning during COVID-19 pandemic in Indonesia: a cross -sectional study

Covid-19 has prompted higher education institutions around the globe to relocate offline classes to online classes. Universities in Indonesia were no exception. Indonesia has already developed distance education systems, and there were many challenges to utilizing e-learning. Due to the pandemic, all colleges across Indonesia were compelled to use online platforms to resume their studies. This study indicates e-learning perceptions' importance in knowledge mastery, social competence, and media literacy abilities. The study assesses college students' attitudes toward e-learning during the ongoing COVID-19 and will be utilized as an evaluation tool by The Higher Education of Education and Culture of the Republic of Indonesia. The research methods used with a quantitative model, where the sample tested represented the student of 1137 <a href="#_msocom_1">[DJ1]</a> respondents from 43 universities in Indonesia. The study's findings show a commonly perceived weakness of e-learning was that the majority of respondents got a lack interaction with lecturers (57,6%). The study also identified that the majority of respondents have a moderate mastery of technology 1038 respondents (77.6%), while the remainder has poor and high knowledge of technology. One of the key reason students implement e-learning is the ease with which they may obtain study resources.  According to the study, e-learning technology enables quick access to information, which results in students developing a favorable attitude toward it based on its utility, self-efficacy, the convenience of use, and student behavior related to e-learning. The study verifies the utility of e-learning by demonstrating how it enables students to study from any geographical location, which is not achievable with face-to-face instruction.

opencc-by-4.0Apr 2024View details →

FunShield4Med e-learning module on Computational Toxicology

This is a two-module presentation about the use of computational methods in toxicology providing the audience with an introduction of molecular modelling techniques applied to toxicology assessment (first module, theoretical part). Taking advantage of selected case studies targeting ochratoxin A, interested persons are learning how in silico methods can be broadly applied to investigate the toxicodynamics and toxicokinetic of mycotoxins (second module, e-learning part), supporting the early stage of risk assessment (i.e. the hazard identification and characterization). The two modules are explaining in depth and step-by-step the procedure used and the underpinning rationale and base of knowledge to make anyone virtually able to reproduce such kind of analysis.