scholarly journals Learning Management Systems and Student Performance

2019 ◽  
Vol 8 (1) ◽  
pp. 582-591
Author(s):  
Khawlah Ahmed ◽  
Mujo Mesonovich
Keyword(s):  
Student Performance ◽  
Learning Management Systems ◽  
Management Systems ◽  
Learning Management

scholarly journals The Effects of Using a Fully Integrated Mobile Application to Access Learning Management Systems in Higher Education

2020 ◽  
Vol 26 (9) ◽  
pp. 1213-1229
Author(s):  
José Martín-Núñez ◽  
Susana Sastre ◽  
José Peiró ◽  
José Hilera
Keyword(s):  
Student Satisfaction ◽  
Student Performance ◽  
Mobile Application ◽  
Learning Experience ◽  
Learning Management Systems ◽  
Academic Major ◽  
Management Systems ◽  
Fully Integrated ◽  
Learning Management ◽  
The Web

The use of mobile devices in the classroom is increasingly frequent. However, the LMS are still not completely adapted to this format, preventing students from using all the LMS web-functionalities in their mobiles. Hence, we present and evaluate the use of a new mobile application fully integrated with Learning Management Systems (LMS). We examined access to LMS by 95 postgraduate university students, differentiating between the services accessed and the means used. Students belonged to four consecutive promotions. In the first two, access to the system was through the web, while in the third and fourth, an app fully integrated with the LMS was available. The results showed an overall increase in access to LMS, with a considerable reduction in access via the web in favor of access via the application. Significant differences were found in the access patterns to communication and assessment services depending on the students' age, gender, academic major and previous m-learning experience. Satisfaction with the LMS rose when the app was available, with greater growth within the academic major on IT and previous m-learning experience group. Finally, students with high performance accessed the system significantly more than those with low performance. In conclusion, the integration of the app with the system showed useful and efficient results. The app eased the use of the system, increased student satisfaction with LMS, and student performance improved with increased access.

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.

Using Learning Management System Activity Data to Predict Student Performance in Face-to-Face Courses

2020 ◽  
Vol 12 (3) ◽  
pp. 20-31 ◽  
Author(s):  
Najib Ali Mozahem
Keyword(s):  
Student Performance ◽  
Event History Analysis ◽  
Educational Data Mining ◽  
Learning Management Systems ◽  
Private University ◽  
Management Systems ◽  
Activity Data ◽  
Face To Face ◽  
History Analysis ◽  
Learning Management

Higher education institutes are increasingly turning their attention to web-based learning management systems. The purpose of this study is to investigate whether data collected from LMS can be used to predict student performance in classrooms that use LMS to supplement face-to-face teaching. Data was collected from eight courses spread across two semesters at a private university in Lebanon. Event history analysis was used to investigate whether the probability of logging in was related to the gender and grade of the students. Results indicate that students with higher grades login more frequently to the LMS, that females login more frequently than males, and that student login activity increases as the semester progresses. As a result, this study shows that login activity can be used to predict the academic performance of students. These findings suggest that educators in traditional face-to-face classes can benefit from educational data mining techniques that are applied to the data collected by learning management systems in order to monitor student performance.

scholarly journals Improvement of Student Attention Monitoring Supported by Precision Sensing in Learning Management Systems

2021 ◽  
Author(s):  
Andreia Filipa Valada Pereira Artífice ◽  
João Sarraipa ◽  
Ricardo Jardim-Goncalves
Keyword(s):  
Student Performance ◽  
Communication Systems ◽  
Learning Management Systems ◽  
Management Systems ◽  
Student Centered ◽  
Computer Mediated ◽  
E Learning ◽  
Learning Management ◽  
Automatic Attention ◽  
Student Attention

A Learning Management Systems (LMS) can benefit from the inclusion Computer-Mediated-Communications (CMC) software for delivering materials. Incorporating CMC tools in virtual classrooms or implementing educational blogs, can be very effective in e-learning platforms. In such student-centered interaction scenarios, it is important to monitor and manage student attention in a precise way to enhance student performance. Sensing with precision through 6G/7G technology allows to include electronic and software devices to produce such monitoring. This chapter contextualizes and describes an abstraction application scenario of sensing and monitoring student attention with high precision in Learning Management System with new communication systems. In that context, technology (e.g. sensors), is used to perform automatic attention monitoring, helping to manage students in e-Learning. Additionally, the document presents a possible scenario which supports intelligent services to the monitoring of student attention during e-learning activities in the context of Smart HEI (Higher Education Institutes).

scholarly journals Taking Advantage of the “Big Data” in Learning Management Systems

2019 ◽  
Author(s):  
Francis B. Lavoie ◽  
Pierre Proulx
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Student Performance ◽  
Management System ◽  
Learning Management Systems ◽  
Management Systems ◽  
Completion Status ◽  
Learning Management ◽  
Predicting Student Performance ◽  
The Web

This work presents a novel learning management system (LMS), named Catalyseur, which allows the students to easily access pedagogic contents as well as allowing them to directly complete the exercises on the web. Meanwhile, the LMS acquires data about the students’ completion status of exercises and lessons and the time before the examinations these exercises and lessons were completed. An artificial intelligence (AI) predicting student performance at an examination depending of their completion status is continuously updated with new data acquired by the LMS. This AI model is then used to automatically send messages to students about how they are expected to perform at the next examination.

Readiness of Universities for 21st Century Digital Economies: Case of Selected Lecturers from Universities in Buffalo City Metropolitan in Eastern Cape Province South Africa

10.31355/42 ◽  
2019 ◽  
Vol 3 ◽  
pp. 065-077
Author(s):  
Agyei Fosu
Keyword(s):  
Higher Education ◽  
21St Century ◽  
Teaching And Learning ◽  
Learning Management Systems ◽  
Management Systems ◽  
Eastern Cape ◽  
Next Generation ◽  
Web Based ◽  
Web Based Learning ◽  
Learning Management

NOTE: THIS ARTICLE WAS PUBLISHED WITH THE INFORMING SCIENCE INSTITUTE. Aim/Purpose...................................................................................................................................................................................................... The purpose of this study is to expand the knowledge base on factors likely to impede implementation and adoption of web-based learning management systems to blend with traditional methods of lecturing in universities to cater for the next generation of learners in Africa and Eastern Cape Province South Africa in particular. Background........................................................................................................................................................................................................ The shift from the industrial economies to 21st century digital and knowledge-based economies, fueled by rapid Information and Communication Technologies (ICTs) such as Internet, YouTube, Chartrooms, Skype, Social media networks and its introduction to the educational system not only resulted in a new teaching approach globally but also paved way to usher in new generation of learners (anytime, anywhere learners) in the higher education system. Despite the fact that universities and other institutions of higher education in developed countries and some Africa countries have since recognized that the 21st century global digital and knowledge-based economies evolution has ushered in the next generation of learners, and as a result have taken the necessary steps to blend the traditional method of lecturing in higher education with web-based learning management systems in order to accommodate these learners. However, in Africa not much research have been done on the readiness of higher education institutions in terms of blending web-based learning management systems with the traditional method of lecturing to cater for the next generation of learners. Methodology....................................................................................................................................................................................................... Quantitative and two non-probability sampling methods, namely, quota and purposive sampling was used to investigate the technological skills of selected lecturers from universities within Buffalo City Metropolitan as one of the core component to check the readiness of their faculty for the next generation of learners. Contribution........................................................................................................................................................................................................ This research will add to the growing knowledge about the blending of web-based learning management with the traditional style of lecturing in higher education in the 21st century digital economies. Findings.............................................................................................................................................................................................................. The results indicated that the participating lecturers need to be trained and sup-ported in the skills of using of the ICTs and computer programs applicable to enhance web-based learning in teaching and learning environment in higher education in order to cater for the next generation of learners associated with the 21st century digital economies. Recommendations for Practitioners................................................................................................................................................................. Much as there is a need for increased in investment in infrastructure within higher education institutions to support teaching and learning, continuous sup-port and training for academics to be technologically literate and also be abreast on rapidly evolving field of ICTs is paramount as it can expedite the teaching and learning process in higher education. Recommendation for Researchers................................................................................................................................................................... There is the need to explore in depth the other two components suggested by Mishra and Koehler (2007) which can serve as barriers for successfully integration of technology into teaching and learning by locus of knowledge. Impact on Society............................................................................................................................................................................................... The research will assist stakeholders, policy makers and agencies tasked with transforming institutions of higher learning to identify the barriers likely to hinder transformation efforts and address them accordingly. Future Research................................................................................................................................................................................................. Conducting research on technological skills of students are critical in this context.

scholarly journals An analysis of users’ preferences on learning management systems: a case on German versus Spanish students

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Hasan Tinmaz ◽  
Jin Hwa Lee
Keyword(s):  
Information And Communication Technologies ◽  
Age Groups ◽  
Learning Management Systems ◽  
Content Management ◽  
Ease Of Use ◽  
Management Systems ◽  
Smart Learning ◽  
School Year ◽  
Design For All ◽  
Learning Management

Abstract The recent advancements in information and communication technologies have altered instructional contexts and re-shaped them into smart learning environments. One of the most common practices of these environments are learning management systems (LMS) where the learners and instructors utilize a software platform to fulfill, support and manage instructional activities around predefined objectives. Successful implementations of LMS have brought a variety on its usage from different cultures, genders, age groups or schooling levels. Hence, this study focuses on understanding the role of culture on LMS design, in along with the effects of gender, age and school year variables. The study participants were German (n = 83) and Spanish (n = 83) university students attending a fully online course offered by a South Korean university. At the end of the course, the students were asked to fulfill a survey on effective LMS design by pointing which features of LMS were more important for them. The survey included twenty questions on four major design factors; content management (six items), ease of use (five items), communication within LMS (four item) and screen design (five items). The dataset was analyzed by non-parametric statistical techniques around four variables on four dimensions (and their related survey questions). The most important result was insufficiency of one unique LMS design for all students which demonstrates the necessity of student demographics tailored smart systems. Additionally, age and gender variables were not making significant differences on LMS design as much as culture and school year variables. The study also revealed that while German students would appreciate goal-oriented individual learning, Spanish students would value process-oriented group learning with active communication. Furthermore, many features of LMS were highly valued by the freshman students more than other levels. The paper discusses these variables with possible explanations from the literature and depicts implementations for future design practices.

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