Educational Technology - Artificial Intelligence
M. Rezaei; E. Pazouki; R. Ebrahimpour
Abstract
Background and Objectives: Today, due to the increasing development of technology all over the world, e-learning systems are expanding rapidly. With the progress of electronic education, the movement from traditional education (the approach of providing one education for all) to personalized education ...
Read More
Background and Objectives: Today, due to the increasing development of technology all over the world, e-learning systems are expanding rapidly. With the progress of electronic education, the movement from traditional education (the approach of providing one education for all) to personalized education began. Personalized education is an educational approach that aims to customize learning based on a learner's strengths, skills, interests, and needs. This method of education, like any other new method, has its strengths and weaknesses. In fact, increasing motivation and acquiring self-defense skills can be considered as one of the important benefits of this type of training. On the other hand, as the weaknesses of this method, we can mention the time-consuming training, the challenge in implementation, and the lack of clarity in the method of application. Due to the availability of many data from learners, the use of artificial intelligence to personalize education will both increase the quality and make education more attractive. Nowadays, one of the ways to personalize education is to provide it based on the preferences of learners. Learner preferences can be self-identified and explicitly identified and extracted by directly asking the learner or implicitly and collecting and monitoring data. Today, modeling user preferences is one of the most challenging tasks in e-learning systems that deal with a large amount of information. The aim of this research was to extract the implicit preferences of the learner by using an online interactive intelligent educational system that models the learner's preferences using conceptualization for learning objects through profile expansion and the use of artificial intelligence algorithms. The model was trained with the collected interactive data and provides new learning objects based on the learner's preferences. This research was practical in terms of purpose.Methods: In this research, according to the society available to us, 29 male and female undergraduate students of computer sciences, with an average age of 21.5 years, who had not taken the machine learning course, were included as the participants. After registration, the participants were randomly divided into two control and experimental groups. The experimental group was presented with personalized content that matched their preferences, and the control group was presented with content that did not match their preferences. After the training, the learning rate and cognitive load of the participants were measured by the designed performance test and the NASA workload index questionnaire. At the end, the significance level of the obtained results of the two groups was evaluated using the independent t-test.Findings: Based on the obtained results, the average performance test scores of the experimental group who received content matching their preferences had no significant difference compared to the average of the control group with a value of p=0.7 (while learning), but the cognition of the control group was significantly lower with p=0.00 compared to that of the experimental group.Conclusion: Based on the findings of the research, providing personalized educational content based on learners' preferences using the profile expansion technique significantly reduced the cognitive load during learning. So, Providing educational content based on learners' preferences, as one of the personalized educational methods in e-learning, plays an important role in reducing the cognitive load of learners.
E-Lerning
T. Ashrafzade; J. Mesrabadi; B. Yargholi; S. Sheikhalizadeh
Abstract
Background and Objectives: Over the last few decades, electronic learning has been the focus of many studies and many researchers have examined the effect of electronic learning on academic performance, which yielded different results that highlighted a demand for a combination of research in this area. ...
Read More
Background and Objectives: Over the last few decades, electronic learning has been the focus of many studies and many researchers have examined the effect of electronic learning on academic performance, which yielded different results that highlighted a demand for a combination of research in this area. The aim of this research is a meta-analysis of the effect of electronic learning on academic performance.Methods: The present study was conducted using meta-analysis method. The corpus of the present study included all valid research published which was available in computer databases that examined the effectiveness of electronic learning on academic performance. The intended data were available in related studies between 1996-2022. For gathering data, Mesrabadi research proposal checklist (2011) was used. Using the purposive sampling method and extensive search based on the specified keywords and applying entry and exit criteria, 243 studies were selected as a sample and were entered into the meta-analysis process. Sensitivity analysis, fixed and random effects models, and heterogeneity analysis with CMA software were used for data analysis. From selected studies as a sample, in total, 311 effect sizes were extracted which 17 extreme effect sizes were eliminated in sensitivity analysis and the next analyzes were performed on 294 effect sizes. The value of “fail-safe N” statistic was obtained in 1911, which indicated that after entering this number of non-significant studies, the combined effect size would be non-significant.Findings: The findings indicated that the mean of the total effect of the studies was 0.726 for the fixed effects model and 1.009 for the random effects model; both of them were statistically significant (p<0.001) which indicated a positive and significant relationship between electronic learning and academic performance. As the effect sizes were heterogeneous, gender, type of sample, type of electronic learning, type of course, age, and type of research method were examined as the mediating variables. The results indicated that the effect size of electronic learning on academic performance is higher among the females compared to that of the males, and in preschool students more than others, in mobile-based instruction more than other types, in teaching methods courses more than other courses, and in experimental research more than correlation research. Also, the results of the research showed that the age of the subjects had a very small contribution to explaining the heterogeneity. The results showed that electronic learning had a significant effect on academic performance and based on Cohen's criterion, the effect size of this relationship was found to be high (ES=1/009).Conclusion: Supplying programs to educate the effect of electronic learning on academic performance is a necessity that needs to be considered more than before. Considering the obtained results and the quantity and quality of existing research studies, it is suggested that the studies of these two fields be carried out at a higher level in observance of the rules of academic paper writing and conducting research. Also, to achieve a reliable result in the first stage, parametric statistics in their design and strong statistical methods with appropriate sample and appropriate sampling methods in accordance with the population should be used.
e-learning
N. Tahmasbipour; F. Hamidi; Z. Kazemi
Abstract
Background and Objectives: The purpose of this study was to investigate the effectiveness of using the electronic content of mathematics course on self-Regulatory learning and academic achievement of students studying at the 9th grade.Methods: The method used in this study was semi-experimental, using ...
Read More
Background and Objectives: The purpose of this study was to investigate the effectiveness of using the electronic content of mathematics course on self-Regulatory learning and academic achievement of students studying at the 9th grade.Methods: The method used in this study was semi-experimental, using pre-test and post-test with a control group. Moreover, the statistical population of this study was comprised of the students studying at Parvin Etesami school of Aligudarz city in the academic year of 2018-2019. The sample size included 40 students who were selected by available sampling method from the third grade of junior high school. 20 people were selected as the experimental group and 20 people were selected as the control group. The experimental group was exposed to ten one-hour sessions of electronic teaching of the course of mathematics. Before conducting this study and after the end of the group teaching sessions, the Beaufort self-regulation questionnaire and the researcher-made questionnaire were administered on the students to determine the score of academic achievement in mathematics.Findings: The results showed that as compared to the students in the control group who did not receive this program, teaching the experimental group that received this program by using the electronic content had a significant impact leading to an increase in the self-regulation learning and academic achievement of the students in the experimental group in the course of mathematics (F=14/114, P<0.01)In other words, after adjusting the pre-test scores, the factor had a significant effect on the items being tested between the two groups. Therefore, it can be concluded that using electronic content is effective on the cognitive self-regulation of the students at 9th grade. The effect of using the electronic content on cognitive self-regulation was 27.6 percent.Conclusions: The students received appropriate feedback in this teaching method and benefitting from optimal approaches, they used the time they needed for the process of learning mathematics. On the other hand, paying attention to various audio, video, graphics and animation, and multimedia software potentials stimulates multiple senses at the same time, enabling students to perceive the math content in a more attractive, varied and comprehensive way as well as increasing their educational motivation in order to learn and understand mathematics more appropriately .The use of self-regulation technique in the context of multimedia tools strengthens data processing, facilitates the timely and appropriate application of these tools, enhances perceptual processes, simplifies cognitive situations, facilitates the problem-solving programs, increases self-regulation and the feeling of self-sufficiency, and enhances the amount of concentration and consciousness; or in other words, it causes a higher self-regulation in the process of learning. The conditions that are created in the path of teaching and learning and also in a long period of time are almost constant and generally stable.
E-Lerning
A. Poortavakoli; M. Alinejad; B. Daneshmand
Abstract
Background and Objectives: Despite the enormous potential of Electronic Learning (e-learning), learners sometimes decide to drop out of school and are reluctant to pursue educating; therefore, it is so important to find variables to accept it. Among these variables, satisfaction is a key factor Which ...
Read More
Background and Objectives: Despite the enormous potential of Electronic Learning (e-learning), learners sometimes decide to drop out of school and are reluctant to pursue educating; therefore, it is so important to find variables to accept it. Among these variables, satisfaction is a key factor Which is one of the important indicators in the quality of education. Experts consider several effective factors for satisfied e-learning including the quality of e-content. The role of content in the e-learning curriculum is much more prominent and influential than the role of content in the conventional education curriculum. Because in e-learning, content also plays a role in other elements of the curriculum, including; Teaching role, teaching-learning activities, time, place, evaluation and feedback. Therefore, in compiling electronic content, which is a process content, special attention should be paid to the basics of education sciences.; This issue is raised, can e-content be developed based on the factors those affect e-learning satisfaction? What are these factors? And how can a good e-content design model be created to satisfy e-learning? The general purpose of this study was to design a pattern for developing electronic content based on the factors affecting satisfaction in E- learning. The Sub- objectives of the study were as follows: 1) Identifying the factors affecting e-learner satisfaction with e-learning according to the research proposal 2) Determining the characteristics of e-content based on learner satisfaction from the perspective of experts 3) Determining the role of e-content characteristics on learner satisfaction Electronic. Methods: This was conducted with a hybrid and exploratory. Method in three stages. In the first stage, meta-analysis research method was used to identify the factors affecting satisfaction and in the next stage, a Descriptive - Survey method was used to analyze the experts’ opinions. The statistical population of this study consists of two groups: a) the research studies related to the factors affecting satisfaction in E-learning which have been published in the internal and external credible journals; b) the experts working in the field of E-learning all over the country. The statistical samples of this study consisted of ،three groups: A) In the meta-analysis section, the research that was most relevant to the research topic purposefully selected and evaluated (29 foreign studies and 19 domestic studies, a total of 48 studies). B) In the Qualitative section (interview), 30 e-learning professionals were identified nationwide through targeted sampling. In the quantitative section (questionnaire), 117 specialists were identified. In this study, the following three tools were used to collect data: 1- Checklist (in the meta-analysis section), 2- Interview without construction (in the qualitative section),3- researcher-made questionnaire (in the quantitative section).In order to perform data analysis, 48 studies were first studied in the first phase in the meta-analysis section And 209 satisfaction-related factors were identified, some of which were duplicate, that is, exactly one word was used and a number of words were different but synonymous and with the same meaning and purpose. In the analysis section, the researcher placed the same and synonymous factors in one class, which eventually formed 41 classes, and the frequency and percentage of their frequency were calculated. Then, in the second stage, after conducting the interviews and writing them, the researcher examined and analyzed the code for each of the interviews. In this way, the written content of the interviews was read and each significant unit that represented an electronic content feature (analysis unit) was written in the column below the category. After studying all the content of the interviews and identifying the units of analysis, it was the time to re-read and categorize them, and the columns of the categories were obtained and after studying and categorizing the categories, the main components were identified. In the third step, the data from the questionnaire were analyzed at the levels of descriptive and inferential statistics. Findings: The results of study in the meta-analysis stage are indicative of the fact that factors such as content, interaction, technology, teacher, service quality, design, ease of perceived use, personalization, perceived usefulness, learner, perceived value and self-efficacy are among the most important factors affecting satisfaction in E-learning. Regarding the interview, from the viewpoint of the experts developing electronic content, the principles of content development, learner, consequential implications, attention to the approaches related to learning and the role of teacher have the most significant impact on learner’s satisfaction in E-learning, respectively. Conclusion: All of the components are to measure the structure of electronic content characteristics in such a way that the component related to attention to the approaches of learning and the role of teacher with path coefficient (0.99) and attention to the consequential implications with path coefficient (0.89) principles of content design with path coefficient (0.85) attention to the features of the learner with path coefficient (0.82) were confirmed by the experts and are the ones developing the model. The model states that "attention should be paid to learning-related approaches in the polygonal rule, that is, this component is the basis of content development." The two components of "learner" and "teacher role" should be placed on both sides of the pattern, which is the characteristic of the two main elements of the electronic content processes. Implicit "and on the" reminder "side leads to" adherence to the principles of content design. " In total, paying attention to these five components will lead to the development of effective electronic content.
Electronic learning- virtual
Kh. Sarboland
Abstract
Background and Objective:The advent of information and communication technologies, increasing access to computers in higher education and universities’ challenges such as increasing demand for education, the need for economic activities to provide new resources and the use of information technology ...
Read More
Background and Objective:The advent of information and communication technologies, increasing access to computers in higher education and universities’ challenges such as increasing demand for education, the need for economic activities to provide new resources and the use of information technology to provide education services in the global market has caused universities to reconsider their traditional roles and create new organizational structures. E-learning is one of the advances of technology in education. Along with the growth of technology and its development in the field of learning, experts in this field conceived the idea that they can meet the educational needs of the learners by launching e-learning courses. Determining the level of student satisfaction is one of the most important indicators of achieving the desired quality. Studies also show that in order to continuously improve higher education system, it is necessary to evaluate the quality of educational, research and welfare services. Due to the above-mentioned reasons, examining the readiness and potential of the e-learning system is inevitable. Therefore, the purpose of this study was to evaluation the effectiveness of e-learning on the satisfaction of graduate students in Islamic Azad University. Methods: The research method is mixed (qualitative-quantitative). In qualitative section, a theme-based questionnaire/focal group and in quantities section, a surveying type was used. The statistical population of the research in the qualitative section was experts in the field of e-learning, academic elites, professors and experts, 22 of whom were selected by non-random and snowball sampling. The selection criteria was having more than 10 years of experience and being excellence in education and research. The statistical population of the quantitative section were postgraduate students of university units in northwestern Iran, among whom a sample size of 219 was selected by stratified sampling. The data collection method was interview in the qualitative section. In the quantitative section a 45-item researcher-made questionnaire was used based on a 5-point Likert scale. Spatial and local research area included university units in northwestern Iran consisting of 14 units in 2018: Tabriz, Bonab, Maragheh, Marand, Khoy, Parsabad Moghan, Ardabil, Garmi, Khalkhal, Meshkinshahr, and Azarshahr. These units were selected because their instructors had the following academic degrees: professors, associate professors and assistant professors. Findings: The results showed that all the components of the research was satisfactory and with the exception of user interface all features of e-learning were efficient. Conclusion:Inspired by theoretical foundations, research background, as well as the results of qualitative data, it was observed that the effectiveness of e-learning method has an impact on students’ satisfaction and also student satisfaction affects many variables in northwestern university units in Iran. These include motivation in relation to the goals of the organizational excellence, learning in anywhere any time, participatory learning, self-assessment and self-directedness, improving the functions of the educational system that provide a high return on extracurricular learning.
Educational computer games
Z. Batooli; F. Fahimnia; N. Naghshineh; F. Mirhosseini
Abstract
Background and Objective:Despite the advent of new technologies and the consequent change in lifestyle in recent decades, education systems have retained their traditional way of teaching and have not adapted to the characteristics of the digital generation. At the same time, the characteristics of digital ...
Read More
Background and Objective:Despite the advent of new technologies and the consequent change in lifestyle in recent decades, education systems have retained their traditional way of teaching and have not adapted to the characteristics of the digital generation. At the same time, the characteristics of digital people have also influenced their teaching-learning methods. One of the latest developments in the field of new technologies is the revitalization of educational environments. Despite the emergence and advancement of new technologies and, consequently, the change in lifestyle in recent decades, education systems have maintained the same traditional method of education and have not changed according to the characteristics of the digital generation. Meanwhile, digital generation features have been effective on their learning-teaching methods. One of the most important and recent developments in the field of modern technologies is gamified learning environments. The purpose of this study was to review the studies in the field of ‘Gamification in e-Learning’ and to provide the content analysis of this field and its effectiveness in education. Materials: After searching the databases with related keywords and based on input criteria, 60 relevant articles were selected in this study. The selected articles were analyzed in terms of the game elements, gamified e-learning courses and the purpose of the articles. The effectiveness of the gamification on participation, learning, motivation, anxiety, peer assessment, collaboration, website optimization, cost reduction and faculty load were among the subject areas of these articles. The programming languages and English language were the most gamified educational courses. The game element point, leaderboard, badge, levels, challenge and feedback were used more than other elements. Findings: The results indicated the effectiveness of gamified e-learning environments to increase learning, engagement and motivation of learners. Conclusion: The present study tries to have a comprehensive review of studies in the field of gamification in e-learning, although it was accompanied by limitations such as not reviewing articles in non-English languages and not reviewing studies published in a format other than journal and conference articles. Undoubtedly, in order to succeed in projects related to gamification in e-learning, looking at its different dimensions and planning in those areas will be very fruitful, and research such as the present study can provide a comprehensive view for designing long-term gamified e-learning environments. The subjects obtained from the analysis of the field studies of gamification in e-learning can be done in Iran, although additional and more detailed research with various methods will help to enrich it.
Electronic learning- virtual
B. Maghsoudi; S. Sulaimany; A. Amiri; M. Afsharchi
Abstract
Educational and technology based learning is the turning point of learning and so is utilizing networks for design, presentation, selection, management and development which includes learners, specialists and content providers. A large volume of data which is produced in user interaction with learning ...
Read More
Educational and technology based learning is the turning point of learning and so is utilizing networks for design, presentation, selection, management and development which includes learners, specialists and content providers. A large volume of data which is produced in user interaction with learning management systems, student selected courses and their course grades are stored. These data include valuable information for studying, analyzing student behavior and offering consulting services. Electronic learning systems need virtual consultants and online associate specialists because of user-teacher distance and lack of related assistance in order to help students make better decisions and improve the learning quality level. This study aims at gaining more experience than is acquired by an associate specialist and dean by means of data mining. It also uses the data mining results to conduct educational guidance in electronic learning systems. It finds hidden patterns in student's course selection and predicts their final grades. The research also investigates the effect of activity, entrance method, time of attendance, and semester in electronic learning systems
