E-learning enables learners to learn everywhere and at any time but this kind of learning lacks the necessary attractiveness. Therefore, adaptation is becoming increasingly important and the recent ...research interest in the adaptive e-learning system. Since emotions and personality are important parts of human characteristics, and they play a significant role in parts of adaptive e-learning systems, it is essential to consider them in designing these systems. This paper presents an empirical study on the impact of using an adaptive e-learning environment based on learner’s personality and emotion. This adaptive e-learning environment uses the Myers-Briggs Type Indicator (MBTI) model for personality and the Ortony, Clore & Collins (OCC) model for emotion modeling. The adaptive e-learning environment is compared with a simple e-learning environment. The results show that students deal with the adaptive e-learning environment (experimental group) gained high scores than others (control group). The rate of progress in quiz score of the experimental group is almost 4.6 times more than the control group. Also, the rate of hint use is decreased more among the experimental group rather than the control group because the level of their knowledge is increased through learning in an adaptive environment. Furthermore, the findings display that the control group tries more to answer the questions in post-quiz while the experimental group has a low effort. Finally, the students expressed the adaptive e-learning environment is more attractive and close to their personality traits. Moreover, it can understand their emotional state better, has a suitable reaction to them, and improves their learning rate.
Background
Probiotic supplementation has been used to alleviate abdominal pain in children and adolescents with irritable bowel syndrome (IBS), but the evidence is not compelling. Thus, a systematic ...review and meta-analysis of randomized clinical trials (RCTs) were performed to investigate the effects of probiotic supplementation on abdominal pain in pediatric patients with IBS.
Methods
PubMed/MEDLINE, Web of Science, Scopus, Cochrane Library, and Embase were the available databases searched to find relevant randomized clinical trials up to April 2021. The effect size was expressed as weighted mean difference (WMD) and 95% confidence interval (CI).
Results
Seven RCTs with 441 participants were included, from which the meta-analysis demonstrated that probiotic supplementation has a significant effect on reducing abdominal pain in pediatric patients with IBS (WMD = − 2.36; 95% CI − 4.12 to − 0.60;
P
= 0.009). Although our study involved children and adolescents (≤ 18 years), the effects of probiotic supplementation seem to be more potent in patients under 10 years old (WMD = − 2.55; 95% CI − 2.84 to − 2.27) compared to patients aged 10–18 years (WMD = − 1.70; 95% CI − 2.18 to − 1.22). The length of supplementation longer than four weeks was more effective (WMD = − 2.43; 95% CI − 2.76 to − 2.09).
Conclusion
Probiotic supplementation can reduce abdominal pain in pediatric patients with IBS.
The recent research in artificial intelligence shows an increasing interest in the modeling of human behavior factors such as personality, mood, and emotion for developing human-friendly systems. ...That is why there is an interest in developing models and algorithms to determine a human's emotions while interacting with a system to improve the quality of the interaction. In this paper, we propose a computational model to calculate a user's desirability based on personality in e-learning environments. The desirability is one of the most important variables in determining a user's emotions. The model receives several e-learning environmental events and predicts the desirability of the events based on the user's personality and his/her goals. The proposed model has been evaluated in a simulated and real e-learning environment. The results show that the model formulates the relationship between personality and emotions with high accuracy.
•Propose a computational model to calculate a user's desirability based on personality in e-learning environments.•Finding relationships between personality dimensions and desirability.•Predict desirability with a high accuracy in a simulated and in a real e-learning environments.
Background and Objectives: Obesity is a worrying problem in the present age and is the cause of many chronic non-communicable diseases. Several nutritional and non-nutritional factors are involved in ...the emergence of this health crisis. One of the important nutritional factors is the quality of nutrition. In this study, the relationship of the Alternative Healthy Eating Index (AHEI-2010) in relation to obesity, vitamin D3, and CRP, was investigated in the elderly. Methods: This descriptive-analytic (cross-sectional) study, was performed on 190 older adults referred to health centers of Tehran University of Medical Sciences using cluster sampling. Food intake was measured by Food Frequency Questionnaire. The level of vitamin D and hs-CRP were calculated in fasting blood, and variables of weight, height, and waist circumference, were measured .In the final analysis with logistic regression, confounding factors, were adjusted and p<0.05 was considered statistically significant. Results: The mean age of the subjects, was 67.31 and the mean BMI was estimated to be 29. 89. The distribution of the individuals in terms of weight, body mass index, and waist circumference, was not significant based on AHEI-2010. The odds ratio of abdominal obesity based on AHEI-2010, was estimated to be OR=0.85 after adjusting for confounders, which was not statistically significant, but this distribution was not significant for the odds ratio of general obesity (p=1.20). Conclusion: The findings of this study revealed that by increasing the score of AHEI-2010, the odds ratio of abdominal obesity decreases, but there is not significant relationship between the AHEI-2010 and general obesity, vitamin D3, and hs-CRP. :
Numerous research studies are conducted annually, and many researchers look for them in the scientific databases. In order to manage the research ecosystem, it is necessary to have sufficient ...knowledge about the research supply and demand. This study proposes a novel expert-independent framework to investigate the research supply and demand among the huge number of studies. In this framework, the combination of quantitative, bibliographic, and content analysis methods is applied via text mining techniques. To evaluate the proposed framework, environmental data from the Iran scientific information database is used (Ganj) 1 as a rich database. It includes more than 513,000 supplied records and more than 78 million search queries as the research demands. To analyze the research supply and demand, the research topics are extracted via the topic modeling approach from both the supply and demand side. The results showed that the educational category of environmental studies is moved from medical science to engineering in the last decades. Moreover, the gap analysis between research supply and demand identified "Extraction" and "Tourism" as hot topics, "Education," "Management," and "Culture" as cold topics, "Soil" and "Energy" as silent topics and finally, "International Rights" and "River" as gap topics. The findings can support environmental policymakers and research managers in making decisions and identifying environmental research needs and priorities. The proposed framework for other research areas can be used to examine and balance research supply and demand.
Iran scientific information database (Ganj) which includes almost one million scientific records provides the search opportunity in dissertations, domestic scientific journals, articles, conferences, ...research projects, and governmental reports. A large number of researchers meet the needs of their scientific and research resources from the Ganj database daily. Users’ needs and behaviors are variant and understanding it helps system administrators to use different strategies to manage the better databases and provide efficient services to users. One way to understand users’ needs is to cluster them based on their behavior and identify the features of each cluster. This study aims to cluster the users based on the analysis of their search behavior using the LRFM model. In this study, the search log data of Ganj users were collected for three months. In this research, the LRFM attributes were calculated, and then the K-means algorithm was applied to them. The optimal number of clusters was calculated based on different criteria. Based on customer value matrix, the results of customer clustering users in four groups are efficient, suspicious, unreliable, and intermittent and base on customer loyalty Marcus users categorizes in loyal, potential, insecure and newcomers.
Today, one of the most important and challenging issues in artificial intelligence is modeling human behavior in virtual environments. Furthermore, studying e-learning environments is in great demand ...in computer science which requires understanding human behaviors. Thus, considering human behavior factors, such as personality, mood, and emotion, and modeling them in e-learning environments is a challenging issue in artificial intelligence. The purpose of this paper is to review the psychological models of personality used in computer science. In addition, the most important applications of personality models and their direct related topics in learning, i.e. learning style issues in e-learning environments, are presented. The study shows that researchers tend to use models that are simple to implement in virtual world and are as comprehensive as possible to cover all the features of human behavior. Finally, we concluded that models such as the Five Factor Model, the Myers–Briggs Type Indicator personality model, and Felder–Silverman learning styles model have the two most important features, which are simplicity and comprehensiveness. These two features have made these psychology models the most favorable in the virtual world.
One of the most important goals of information systems is to provide services based on users’ cognitive characteristic. This increases the system efficiency, user satisfaction and interest in the use ...of information systems. Since e-learning has been widely used around the world in human-computer interaction domain, in this research the e-learning environment has been chosen to evaluate the model. The goal of this research is performance evaluating of an intelligent e-learning system compared with a simple e-learning system. The intelligent e-learning system which is based on user’s personality dimension and emotion. In this research, the intelligent e-learning system uses a specific model. The model considers desirability as an important variable to calculate emotions and interact with users based on this model. The model can detect users’ emotion based on personality dimension, user’ goals, and environmental event. Evaluating of the model is in two steps: the first step is checking generality of the model in different learning domains and the second one is to determine whether presenting suitable actions to users after predicting their emotion status has an influence on satisfaction and learning rate or not. In the first step, the model has been evaluated in two real e-learning environments which are designed to teach: “Introduction to computing systems and programming” course and “English language vocabulary”. The results show that accuracy in predicting desirability in emotion module in e-learning environments with different materials learning are the same and they confirm the generality of the model. In the second step, two e-learning environment is designed to teach English vocabulary. The e-learning environment has been implemented in two versions, i.e. a basic system with no intelligence and an intelligent system which can predict a user’s desirability. The intelligent e-learning environment acts according to the user’s status based on her/his desirability. The results in this step show that users believe the intelligent environment is believable and more attractive than the basic one. Also, they express this environment can understand their emotional status and react based on it, and it can improve their learning process.
The learning style of a learner is an important parameter in his learning process. Therefore, learning styles should be considered in the design, development, and implementation of e-learning ...environments to increase learners’ performance. Thus, it is important to be able to automatically determine learning styles of learners in an e-learning environment. In this paper, we propose a sequential pattern mining approach to extract frequent sequential behavior patterns, which can separate learners with different learning styles. In this research, in order to recognize learners’ learning styles, system uses the Myers-Briggs Type Indicator’s (MBTI). The approach has been implemented and tested in an e-learning environment and the results show that learning styles of learners can be predicted with high accuracy. We show that learners with similar learning styles have similar sequential behavior patterns in interaction with an e-learning environment. A lot of frequent sequential behavior patterns were extracted which some of them have a meaningful relation with MBTI dimensions.
The increasing growth of web usage has made the importance of search engines and their quality assessment more responsive to users' needs. One of the approaches to quality assessment is user ...satisfaction. The use of a search engine depends on user satisfaction, which is a measure of the quality of the search engine. Many search engines have been built in Iran, as well. Some of these engines are widely used to search for information on the web, and some are found in a database Iran scientific information database (GANJ) is one of the databases that have its search engine. It contains nearly 530,000 dissertations and thesis and is one of the key scientific databases in the country with many users. Therefore, assessing the satisfaction of users of this system with its broad audience is crucial. In this research, indicators based on the EQOAL model were developed to evaluate users' satisfaction with the GANJ System. Indices developed based on the Delphi method were screened and localized to assess users' satisfaction with GANJ System. User satisfaction was also assessed using an EQual questionnaire. The results of the data analysis of the 156 questionnaires collected show that usability, information, and service interaction are the significant determinants of users' satisfaction with the treasure system, respectively. In terms of usability, the ease of working with "GANJ" is a top priority. Likewise, the ease of interaction with the system and the apparent attractiveness of the system were introduced as the main factors.
PDF
