scholarly journals Endorsement of Individualized Instruction and Learning Performance through Mobile-Based Learning Management

2020 ◽  
Author(s):  
Anil Shukla ◽  
Kshama Pandey
Keyword(s):  
Individualized Instruction ◽  
Learning Performance ◽  
Learning Management ◽  
Instruction And Learning

Analyzing the Functions and Benefits of Using Mobile Facebook as a Supplemental LMS in Higher Education

2017 ◽  
Vol 21 (6) ◽  
pp. 971-979 ◽  
Author(s):  
Dian-Fu Chang ◽  
Yu-Lan Huang ◽  
Berlin Wu ◽  
◽  
◽  
...  
Keyword(s):  
Social Communication ◽  
Social Networking Sites ◽  
Social Groups ◽  
Mobile App ◽  
Learning System ◽  
Learning Performance ◽  
Management Systems ◽  
University Administrators ◽  
National Organizations ◽  
Learning Management

The wide implementation of social networking sites (SNS) in many fields, for instance, government, celebrities, schools, social groups, events promoted by national organizations or private enterprises, NPOs, businesses, etc., attests to its popularity. Currently more and more educators and students have integrated these online social communication platforms into their learning environment. Learning Management Systems (LMS) also have great features and functions that may serve as a bridge between learners and educators leading to better communication, in addition to helping students increase their learning engagement and teachers in evaluating learning performance. Although many studies have investigated the effects of adopting Facebook as an additional learning management system (LMS), its functions and benefits differing from the LMS have hardly been systematically analyzed. Besides, due to the increasing popularity of mobile devices among the younger generation, university students are obviously likely to use their smart phones to access both Facebook Mobile App and school LMS. Therefore, the first purpose of this study is to determine students’ opinions on mobile Facebook course groups and a mobile LMS course group, through a survey conducted after a 2-semester experiment. The other objective of this study is to evaluate the benefits of each function of mobile FB course groups that may strengthen the current weaknesses of LMS. In addition, regression analysis and t-test were used to reveal the relationships among variables: the FB functions and its benefits for FB course group. The findings might provide a clear notion for teachers regarding the functions and advantages contributed by a mobile FB course group which can be implemented as a supplemental learning system. The results of the research will provide university administrators with more detailed information for improving the LMS’ features or developing new LMS Apps.

scholarly journals Intelligent Decision Support System for Predicting Student’s E-Learning Performance Using Ensemble Machine Learning

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2078
Author(s):  
Farrukh Saleem ◽  
Zahid Ullah ◽  
Bahjat Fakieh ◽  
Faris Kateb
Keyword(s):  
Machine Learning ◽  
Student Performance ◽  
Learning Management Systems ◽  
Machine Learning Algorithms ◽  
Learning Performance ◽  
Management Systems ◽  
Electronic Learning ◽  
Ensemble Techniques ◽  
Proposed Model ◽  
Learning Management

Electronic learning management systems provide live environments for students and faculty members to connect with their institutional online portals and perform educational activities virtually. Although modern technologies proactively support these online sessions, students’ active participation remains a challenge that has been discussed in previous research. Additionally, one concern for both parents and teachers is how to accurately measure student performance using different attributes collected during online sessions. Therefore, the research idea undertaken in this study is to understand and predict the performance of the students based on features extracted from electronic learning management systems. The dataset chosen in this study belongs to one of the learning management systems providing a number of features predicting student’s performance. The integrated machine learning model proposed in this research can be useful to make proactive and intelligent decisions according to student performance evaluated through the electronic system’s data. The proposed model consists of five traditional machine learning algorithms, which are further enhanced by applying four ensemble techniques: bagging, boosting, stacking, and voting. The overall F1 scores of the single models are as follows: DT (0.675), RF (0.777), GBT (0.714), NB (0.654), and KNN (0.664). The model performance has shown remarkable improvement using ensemble approaches. The stacking model by combining all five classifiers has outperformed and recorded the highest F1 score (0.8195) among other ensemble methods. The integration of the ML models has improved the prediction ratio and performed better than all other ensemble approaches. The proposed model can be useful for predicting student performance and helping educators to make informed decisions by proactively notifying the students.

scholarly journals Student Engagement using Learning Management System in Computer Science Education

2019 ◽  
Vol 8 (2S11) ◽  
pp. 743-747 ◽  
Keyword(s):  
Student Engagement ◽  
Computer Science ◽  
Learning Style ◽  
Management System ◽  
Learning Management System ◽  
Learning Preferences ◽  
Learning Performance ◽  
Management Systems ◽  
Learning Management ◽  
Teaching Learning

Combined learning among the world's top universities including Malaysia was commonly recognized. Many educational organizations, like Blackboard, WebCT and Moodle, have introduced Learning Management Systems (LMSs) or Course Management Systems (CMSs), depending on the capabilities and needs of the institutions ' programmes. The aim of this paper is to report the results of implementation of learning management system (LMS) using Moodle on student engagement in Computer Science (CS) classroom for two semesters. Furthermore, we also investigating the parameters that influence student engagement and how these scales relate to each stage of learning process to produce better learning performance. The respondents for this work are students who enrolled CS courses regardless of any year. The survey conducted using online and distributed to various type of subject taught in CS for the semester to confirm the students’ learning preferences using blended learning style. From the survey results, we examine the significance correlation of learning preference style with student engagement in campus-based learning. The results show that there is an impact of LMS usage on teaching, learning and assessment based on students’ learning preferences may show better learning engagement amongst students

scholarly journals Learning Management Systems: A Shift Toward Learning and Academic Analytics

2016 ◽  
Vol 11 (04) ◽  
pp. 77 ◽  
Author(s):  
Adam Marks ◽  
Maytha AL-Ali ◽  
Kees Rietsema
Keyword(s):  
Online Survey ◽  
Learning Management Systems ◽  
Learning Performance ◽  
Management Systems ◽  
Degree Programs ◽  
College Level ◽  
Learning Management ◽  
The University

This paper presents the major findings from a study conducted with six different universities in the U.S. regarding their use of the learning analytics (LA) capabilities available within their learning management systems (LMS). Data was collected from an online survey instrument, in-depth interviews with IT directors and academic administrators, and a case study in Embry-Riddle Aeronautical University. One observation is that universities are attempting to make better use of new analytics functions and the data stored in the university LMS in order to make more informed decisions regarding short-term and long-term goals and objectives. The new functions include analytics performed at the institutional level, college level, degree-program level, course level, and even course section level. Courses and degree programs as well as learning performance and objectives can be measured and analyzed using different goals, criteria, and accreditation requirements.

scholarly journals Prototyping a Learning Management System for Higher Education

10.28945/3213 ◽  
2008 ◽  
Author(s):  
Raafat Saade ◽  
Qiong Huang
Keyword(s):  
Online Learning ◽  
Management System ◽  
Learning Management System ◽  
Research Work ◽  
Content Management ◽  
Learning Objects ◽  
Learning Performance ◽  
Learning Tools ◽  
Learning Management ◽  
And Performance

This document presents a five year development initiative that sought to implement a learning management system clearly differentiated from the CMS domain. The present article reports on our research work showing our effort towards a design of a true learning management system which entails pedagogical strategies embedded into the system design and the online learning environment. This is characterized by its highly interactive and collaborative learning tools. The ability of the system to measure student effort and performance via the summation of the learning objects usage clearly differentiate the concept of true online learning from the traditional distance learning via content management systems. Results from student usage of the learning management system provide some insight into learning, performance and behavior in online learning. Due to limitations only three learning objects were briefly analyzed to demonstrate their value to learning specifically and to the value of the system in general.

Learning and Consolidation of Verbal Declarative Memory in Patients with Posttraumatic Stress Disorder

2010 ◽  
Vol 218 (2) ◽  
pp. 135-140 ◽  
Author(s):  
Slawomira J. Diener ◽  
Herta Flor ◽  
Michèle Wessa
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Verbal Memory ◽  
Stress Disorder ◽  
Declarative Memory ◽  
Memory Performance ◽  
Verbal Learning ◽  
Depression Scale ◽  
Learning Performance ◽  
Ptsd Symptoms

Impairments in declarative memory have been reported in posttraumatic stress disorder (PTSD). Fragmentation of explicit trauma-related memory has been assumed to impede the formation of a coherent memorization of the traumatic event and the integration into autobiographic memory. Together with a strong non-declarative memory that connects trauma reminders with a fear response the impairment in declarative memory is thought to be involved in the maintenance of PTSD symptoms. Fourteen PTSD patients, 14 traumatized subjects without PTSD, and 13 non-traumatized healthy controls (HC) were tested with the California Verbal Learning Test (CVLT) to assess verbal declarative memory. PTSD symptoms were assessed with the Clinician Administered PTSD Scale and depression with the Center of Epidemiological Studies Depression Scale. Several indices of the CVLT pointed to an impairment in declarative memory performance in PTSD, but not in traumatized persons without PTSD or HC. No group differences were observed if recall of memory after a time delay was set in relation to initial learning performance. In the PTSD group verbal memory performance correlated significantly with hyperarousal symptoms, after concentration difficulties were accounted for. The present study confirmed previous reports of declarative verbal memory deficits in PTSD. Extending previous results, we propose that learning rather than memory consolidation is impaired in PTSD patients. Furthermore, arousal symptoms may interfere with successful memory formation in PTSD.

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