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Papers by Sahar Alqahtani

Journal of Theoretical and Applied Information Technology, 2024

Previous studies have demonstrated the effectiveness of Epistemic Network Analysis (ENA) to expla... more Previous studies have demonstrated the effectiveness of Epistemic Network Analysis (ENA) to explain
students' epistemic interaction with specific learning activities or tasks. However, the potential of ENA has
not been widely explored in investigating the relationship between students' self-regulated learning skills
and their reflective behaviors in a new learning experience. This paper demonstrates how ENA and cluster
analysis can reveal and analyze differences in the reflective behaviors of groups of students with varying
self-regulated learning constructs. The results of this study show that the most prominent reflections among
students with a high level of self-regulation use positive feeling about their good experience and try to
overcome their obstructing feelings that hinder their learning process. The following are the learning
constructs: intrinsic/extrinsic goal orientation, task value, expectancy beliefs, self-efficacy, test anxiety,
metacognitive awareness and metacognitive writing strategies. By contrast, students with low selfregulation in these learning constructs more frequently reflected by recollecting their negative feelings and
examining the knowledge obtained from the course. The analytical approaches proposed in this study reveal
that the reflective behaviors among students with both high and low motivation to learn through “intrinsic
goal orientation”, “expectancy beliefs” and “self-efficacy contain no negative feelings towards their
learning experience.

Engineering, Technology and Applied science research/Engineering, Technology and Applied Science Research, Jun 1, 2024

International Journal of Information Technology and Computer Science, Aug 8, 2016

Transactions on Machine Learning and Artificial Intelligence

In the past years, spammers have focused their attention on sending spam through short messages s... more In the past years, spammers have focused their attention on sending spam through short messages services (SMS) to mobile users. They have had some success because of the lack of appropriate tools to deal with this issue. This paper is dedicated to review and study the relative strengths of various emerging technologies to detect spam messages sent to mobile devices. Machine Learning methods and topic modelling techniques have been remarkably effective in classifying spam SMS. Detecting SMS spam suffers from a lack of the availability of SMS dataset and a few numbers of features in SMS. Various features extracted and dataset used by the researchers with some related issues also discussed. The most important measurements used by the researchers to evaluate the performance of these techniques were based on their recall, precision, accuracies and CAP Curve. In this review, the performance achieved by machine learning algorithms was compared, and we found that Naive Bayes and SVM produce...

Information has become a basic resource in economic systems, especially in enterprises. In order ... more Information has become a basic resource in economic systems, especially in enterprises. In order to maintain enterprises to continue and survive, it is necessary to collect and store everything that helps them serve their activity, and from here, enterprises need to work on collecting, processing, storing and transmitting such information through information systems. In light of globalization, the world has become deeply sophisticated and fast-paced economically speaking. As a result of the depth of this development and the rapid changes in the field of information technology, the world has entered the era of information society. In this era, KSA Small and Medium Enterprises have become a common factor in the growth of the KSA economy, especially when implementing and applying information system methods in enterprises. This paper aims to discuss the growth of KSA SMEs in recent years and explore the role of information systems in their prosperity.

In recent years, the healthcare sector has shown inclination towards restructuring of healthcare ... more In recent years, the healthcare sector has shown inclination towards restructuring of healthcare systems to harmonize with technological innovations and adopting decision support system in routine clin ical practices. The objective of th is paper is to summarize challenges of Clin ical Decision Support System (CDSS) and focus on the effectiveness of CDSS to imp rove clin ical practice. This paper also describes the experience of CDSS in healthcare sector in Saudi Arabia and addresses the requirements for imp lementing successful CDSS with a real examp le. This study concludes that healthcare sector is in dire need to increase quality of patients' care and improve clin ical practices by adopting CDSS.

SSRN Electronic Journal

Many universities use social media platforms as new communication channels to disseminate informa... more Many universities use social media platforms as new communication channels to disseminate information and promptly communicate with their audience. As Twitter is one of the widely used social media platforms, this research aims to explore the adaption and utilization of Twitter by universities. We propose a framework called "Social Network Analysis for Universities on Twitter" (SNAUT) to analyze the usage of Twitter by universities and to measure their interaction with public. The study includes a sample of around 110,000 tweets from 36 Saudi universities, including both public and private universities. Using SNAUT, we can (1) investigate the purpose of using Twitter by universities, (2) determine the broad topics discussed by them, and (3) identify the groups closely associated with the universities. The results show that most of the Saudi universities (whether public or private) actively use Twitter. Results also reveal that the public universities respond to public queries more frequently, but private universities stand out more in terms of information dissemination using retweets and diverse hashtags. Finally, we develop a ranking mechanism in SNAUT for ranking universities based on their social interaction with the public on Twitter.

Transactions on Machine Learning and Artificial Intelligence, 2019

This In the past years, spammers have focused their attention on sending spam through short messa... more This In the past years, spammers have focused their attention on sending spam through short messages services (SMS) to mobile users. They have had some success because of the lack of appropriate tools to deal with this issue. This paper is dedicated to review and study the relative strengths of various emerging technologies to detect spam messages sent to mobile devices. Machine Learning methods and topic modelling techniques have been remarkably effective in classifying spam SMS. Detecting SMS spam suffers from a lack of the availability of SMS dataset and a few numbers of features in SMS. Various features extracted and dataset used by the researchers with some related issues also discussed. The most important measurements used by the researchers to evaluate the performance of these techniques were based on their recall, precision, accuracies and CAP Curve. In this review, the performance achieved by machine learning algorithms was compared, and we found that Naive Bayes and SVM produce effective performance.

Journal of Theoretical and Applied Information Technology, 2024

Previous studies have demonstrated the effectiveness of Epistemic Network Analysis (ENA) to expla... more Previous studies have demonstrated the effectiveness of Epistemic Network Analysis (ENA) to explain
students' epistemic interaction with specific learning activities or tasks. However, the potential of ENA has
not been widely explored in investigating the relationship between students' self-regulated learning skills
and their reflective behaviors in a new learning experience. This paper demonstrates how ENA and cluster
analysis can reveal and analyze differences in the reflective behaviors of groups of students with varying
self-regulated learning constructs. The results of this study show that the most prominent reflections among
students with a high level of self-regulation use positive feeling about their good experience and try to
overcome their obstructing feelings that hinder their learning process. The following are the learning
constructs: intrinsic/extrinsic goal orientation, task value, expectancy beliefs, self-efficacy, test anxiety,
metacognitive awareness and metacognitive writing strategies. By contrast, students with low selfregulation in these learning constructs more frequently reflected by recollecting their negative feelings and
examining the knowledge obtained from the course. The analytical approaches proposed in this study reveal
that the reflective behaviors among students with both high and low motivation to learn through “intrinsic
goal orientation”, “expectancy beliefs” and “self-efficacy contain no negative feelings towards their
learning experience.

Engineering, Technology and Applied science research/Engineering, Technology and Applied Science Research, Jun 1, 2024

International Journal of Information Technology and Computer Science, Aug 8, 2016

Transactions on Machine Learning and Artificial Intelligence

In the past years, spammers have focused their attention on sending spam through short messages s... more In the past years, spammers have focused their attention on sending spam through short messages services (SMS) to mobile users. They have had some success because of the lack of appropriate tools to deal with this issue. This paper is dedicated to review and study the relative strengths of various emerging technologies to detect spam messages sent to mobile devices. Machine Learning methods and topic modelling techniques have been remarkably effective in classifying spam SMS. Detecting SMS spam suffers from a lack of the availability of SMS dataset and a few numbers of features in SMS. Various features extracted and dataset used by the researchers with some related issues also discussed. The most important measurements used by the researchers to evaluate the performance of these techniques were based on their recall, precision, accuracies and CAP Curve. In this review, the performance achieved by machine learning algorithms was compared, and we found that Naive Bayes and SVM produce...

Information has become a basic resource in economic systems, especially in enterprises. In order ... more Information has become a basic resource in economic systems, especially in enterprises. In order to maintain enterprises to continue and survive, it is necessary to collect and store everything that helps them serve their activity, and from here, enterprises need to work on collecting, processing, storing and transmitting such information through information systems. In light of globalization, the world has become deeply sophisticated and fast-paced economically speaking. As a result of the depth of this development and the rapid changes in the field of information technology, the world has entered the era of information society. In this era, KSA Small and Medium Enterprises have become a common factor in the growth of the KSA economy, especially when implementing and applying information system methods in enterprises. This paper aims to discuss the growth of KSA SMEs in recent years and explore the role of information systems in their prosperity.

In recent years, the healthcare sector has shown inclination towards restructuring of healthcare ... more In recent years, the healthcare sector has shown inclination towards restructuring of healthcare systems to harmonize with technological innovations and adopting decision support system in routine clin ical practices. The objective of th is paper is to summarize challenges of Clin ical Decision Support System (CDSS) and focus on the effectiveness of CDSS to imp rove clin ical practice. This paper also describes the experience of CDSS in healthcare sector in Saudi Arabia and addresses the requirements for imp lementing successful CDSS with a real examp le. This study concludes that healthcare sector is in dire need to increase quality of patients' care and improve clin ical practices by adopting CDSS.

SSRN Electronic Journal

Many universities use social media platforms as new communication channels to disseminate informa... more Many universities use social media platforms as new communication channels to disseminate information and promptly communicate with their audience. As Twitter is one of the widely used social media platforms, this research aims to explore the adaption and utilization of Twitter by universities. We propose a framework called "Social Network Analysis for Universities on Twitter" (SNAUT) to analyze the usage of Twitter by universities and to measure their interaction with public. The study includes a sample of around 110,000 tweets from 36 Saudi universities, including both public and private universities. Using SNAUT, we can (1) investigate the purpose of using Twitter by universities, (2) determine the broad topics discussed by them, and (3) identify the groups closely associated with the universities. The results show that most of the Saudi universities (whether public or private) actively use Twitter. Results also reveal that the public universities respond to public queries more frequently, but private universities stand out more in terms of information dissemination using retweets and diverse hashtags. Finally, we develop a ranking mechanism in SNAUT for ranking universities based on their social interaction with the public on Twitter.

Transactions on Machine Learning and Artificial Intelligence, 2019

This In the past years, spammers have focused their attention on sending spam through short messa... more This In the past years, spammers have focused their attention on sending spam through short messages services (SMS) to mobile users. They have had some success because of the lack of appropriate tools to deal with this issue. This paper is dedicated to review and study the relative strengths of various emerging technologies to detect spam messages sent to mobile devices. Machine Learning methods and topic modelling techniques have been remarkably effective in classifying spam SMS. Detecting SMS spam suffers from a lack of the availability of SMS dataset and a few numbers of features in SMS. Various features extracted and dataset used by the researchers with some related issues also discussed. The most important measurements used by the researchers to evaluate the performance of these techniques were based on their recall, precision, accuracies and CAP Curve. In this review, the performance achieved by machine learning algorithms was compared, and we found that Naive Bayes and SVM produce effective performance.