Learning Management Research Articles

Modeling of web-based collaborative learning management system

The challenges faced by most learning management systems (LMS) can be classified into two main areas: pedagogical and technical issues. A comprehensive exploration of these interrelated challenges provides valuable insights for developing a new and more effective model for LMS. In this paper, a novel conceptual model for a web-based collaborative LMS is introduced, merging two distinct learning theories: behaviorism and social constructivism. Through an analysis of the strengths and limitations of each theory, the study moves on to outline the fundamental principles and technical features of the proposed LMS model, which stems from this integration. In conclusion, the paper explores the implications of creating user-centered LMS solutions, with a specific focus on addressing the varied requirements of learners.

A Frame Work for Development of Hybrid-teaching Factory (H-TEFA) Model on Virtual Lab application

The core of Industry 4.0 is the extensive use of Information System in organizational business processes. The competency of System Analysis and Design is required by companies as an expert in Information System development. UNITAMA, a higher education institution, is developing a program of study in Information Systems that produces competent professionals with a discipline in Analysis and Information System Design. The university will strengthen student competencies through a collaborative approach between the learning process and IDUKA. The type of research is Research & Development (R&D) research so that the process of developing virtual learning media technology media for the Hybrid Teaching Factory (H-TEFA) model is directed and systematic, so in this research and development using the ADDIE development model which consists of five development stages (analysis, design, product manufacturing, implementation and evaluation). The Virtual Lab is a modern learning method based on the Learning Management System (LMS) that provides students with more dynamic and customized educational materials for practical learning. The Virtual Lab UNITAMA is the development of a practical learning method designed and adapted to the needs of the Analysis and Information System Design course based on the IDUKA Information System, utilizing web-based IT technology that allows learning to take place remotely, not limited to the classroom and specific hours. The model of collaboration between teachers, students, and IDUKA in the Analysis and Information System Design course is enabled by the rapid development of technology and information systems in the era of Industry 4.0, using e-learning/LMS systems that are integrated with Virtual Lab. The Link & Match policy between the education sector and IDUKA is expected to improve the competencies of graduates and align them with IDUKA's specific needs.

A comprehensive study to facilitate Student Space platform with collaborative learning

The Student Space Virtual Study Groups Platform is a groundbreaking solution designed to transform collaborative learning for students, addressing challenges in forming and sustaining study groups. This online platform integrates advanced technology to create a user-friendly environment, featuring an intuitive interface, dynamic group formation with smart algorithms, real-time collaboration through video conferencing and document editing, centralized resource sharing, and smart scheduling tools. Student Space aims to overcome the limitations of traditional study groups, offering an inclusive and adaptable virtual space for students to connect, collaborate, and excel academically. Anticipated impacts include improved academic performance and the creation of a vibrant academic community. Ongoing enhancements, such as integration with Learning Management Systems, a mobile app for on-the-go collaboration, and improved AI-driven matching algorithms, are planned for the future.

An Approach for Learning Management System

The process of the learning management system (LMS) in the New Normal period was observed in this study.a qualitative research design with a descriptive pattern was used to take a look at two main themes: the advantages of using LMS applications in education were indicated by the suitability of the LMS With the needs of lectures in creating ,disturbing, and managing learning content anytime and anywhere.It is concluded from these findings that using LMS requires strong network support throughout the region. This paper aims to reduce the difficulty coming for the new faculties while studying a particular course and its main focus is to give study material by which they can easily give guidance to the students.Study material like videos of experienced faculties for the particular they were being appointed to

A lightweight framework for cyber risk management in Western Balkan higher education institutions

Higher education institutions (HEIs) have a significant presence in cyberspace. Data breaches in academic institutions are becoming prevalent. Online platforms in HEIs are a new learning mode, particularly in the post-COVID era. Recent studies on information security indicate a substantial increase in cybersecurity attacks in HEIs, because of their decentralized e-learning structure and diversity of users. In Western Balkans, there is a notable absence of incident response plans in universities, colleges, and academic institutions. Moreover, e-learning management systems have been implemented without considering security. This study proposes a cybersecurity methodology called a lightweight framework with proactive controls to address these challenges. The framework aims to identify cybersecurity vulnerabilities in learning management systems in Western Balkan countries and suggest proactive controls based on a penetration test approach.

Examining the efficacies of instructor‐designed instructional videos in flipped classrooms on student engagement and learning outcomes: An empirical study

AbstractBackgroundInstructional videos constitute a pivotal component in flipped learning. Despite their significance, there is a dearth of research specifically dedicated to instructional videos within the context of flipped classrooms. This paucity has led to an empirical void in verifying the efficacy of instructional videos in flipped learning environments.ObjectivesThe present study endeavours to contribute to the extant literature on flipped pedagogical practices by providing empirical evidence regarding the effectiveness of instructional videos in flipped learning environments.MethodsThis study employs a convergent mixed‐methods design. Forty‐five instructional videos in three subtypes were administered in two classes over a 15‐week semester. Data, both quantitative (log data from the learning management system) and qualitative (from focus group discussions at two time points), were concurrently collected from a flipped class (n = 25) and a blended class (n = 28) with the aim of gauging student engagement and learning outcomes in the flipped class and understanding video‐viewing features typical of the flipped class.ResultsBoth datasets corroborated that participants in the flipped class outperformed their counterparts in the blended class in terms of video‐watching, peer interaction, knowledge retention, and transfer skills.ConclusionsThe instructional videos within the flipped classroom setting serve to enhance student engagement in the learning process and improve learning outcomes. The efficacy of these instructional videos in flipped learning can be further augmented through strategic approaches in both their design and implementation.

Improved Marine Predators Algorithm and Extreme Gradient Boosting (XGBoost) for shipment status time prediction

Shipment Status Time Prediction (STP) is a complex problem requiring expertise in many disciplines, including Machine Learning (ML) and logistics management, to develop effective solutions. Estimating every possible shipment step before creation plays a vital role in e-commerce sale channels. In this point of view, a novel STP approach was proposed to predict shipment status times. The proposed approach involves two phases. The first leg of the novel STP approach is to build an ML model for estimating shipment statuses using a dataset acquired from a real-world application. The Extreme Gradient Boosting (XGB) and popular ML algorithms were compared for the classification of shipment status prediction first. The XGB algorithm performed best among the compared algorithms, with 99.92% and 96.16% accuracy for training and test sets. Moreover, the ML algorithms were run on the public New York City taxi trip dataset. The XGB algorithm exhibited the best performance. The accuracy for training and test sets are 97.40% and 97.33%, respectively. The second phase of the proposed approach is shipment status time estimation, designed as an optimization problem. The Marine Predators Algorithm (MPA) is a recently proposed optimization algorithm for numerical function optimization. An improved MPA algorithm for STP (STPMPA) was proposed in this study. The performance of the STPMPA algorithm was scrutinized on numerical benchmark problems first. The STPMPA algorithm outperformed all the algorithms in the experiment. Then, the most feasible shipment status times are searched by optimizers using the XGB model. The proposed STPMPA algorithm put forth a superior performance for the STP problem than the compared optimization algorithms. Consequently, experimental studies reveal that the proposed STP approach is able to generate efficient estimations in reasonable times for real-time systems.

Understanding teacher burnout following COVID-19

ABSTRACT Teachers have faced a multitude of demands over the past two years and faced new challenges as schools returned in the fall of 2021. Using the Job Demands-Resources model as a framework, the current study identified factors contributing to teacher burnout following the COVID-19 pandemic. To examine predictors of teacher burnout, the authors collected survey data from 779 teachers across the USA. The analysis included hierarchical regression models including demographics, COVID-19 implementations, and demands/resources to predict teacher burnout. The results found using learning management systems, administrative support, teacher autonomy, and teacher mental health were all significant predictors of teacher burnout at the end of the 2021–22 school year. The results are important to consider for teacher retention and teacher well-being. School leaders must find ways to support teacher learning of learning management systems, provide administrative support within each building, allow for teacher autonomy within the classroom, and support teacher well-being.

Generative artificial intelligence in higher education learning: A review based on academic databases

Objective. The rapid integration of Generative Artificial Intelligence (AI), especially tools like ChatGPT, into educational sectors has spurred significant academic interest. This review article provides a systematic examination of the current scholarly landscape concerning the use of ChatGPT within higher education.
 Design/Methodology/Approach. Drawing from a range of academic databases between 2022 and 2024, we meticulously adhere to PRISMA guidelines, evaluating a final set of 28 out of 1740 initial articles based on predetermined inclusion and exclusion criteria.
 Results/Discussion. Our analysis reveals diverse global contributions predominantly from Asia and identifies a prevalent quantitative research approach among the studies. We delve into the selected articles' geographical distribution, methodologies, and thematic outcomes, highlighting a notable lack of research from Latin America. The review critically assesses the validity, utility, and time optimization aspects of ChatGPT in educational settings, uncovering a positive impact on student learning and time management. However, we pinpoint a significant gap in rigorous experimental research, underscoring the need for studies with random sampling and controlled settings to enhance the external validity of findings. Additionally, we call attention to the ethical considerations and the necessity for higher education institutions to adapt teaching methodologies to incorporate AI effectively.
 Conclusion. The article concludes with recommendations for future research to address the identified gaps and optimize the educational use of generative AI technologies like ChatGPT.

Improving undergraduate students' email etiquette with computer-based instruction.

Email etiquette is an important skill, especially in professional settings. Research demonstrates that undergraduate students follow email rules when given written instructions plus an example. The purpose of the present study was to evaluate the effects of computer-based email instruction on undergraduate students' email etiquette and to assess the social validity of that instruction. The email instruction package was delivered through an online learning management system and consisted of written instructions plus a model, a quiz, and quiz feedback. We measured email etiquette by scoring emails from course assignments using a checklist. The instruction package produced a replicated increase in mean email checklist scores across two sections of introductory psychology, and checklist scores were elevated when participants sent emails in a novel context. The results of the social-validity assessments suggest that the goals were important, the procedures were acceptable, and there were meaningful improvements in email etiquette for some participants.

Implementation of Learning Management Systems (LMS) in higher education systems through bipolar complex hesitant fuzzy Aczel-Alsina power aggregation operators: A case review for China.

A learning management system (LMS) is a web-based application or software platform computed to facilitate the development, tracking, management, reporting, and delivery of education and training programs. Many valuable and dominant factors are working behind the Learning Management System (LMS), but no one can find which factor is most important and valuable for LMS during COVID-19 among the following five alternatives, called Improved Accessibility, Blended Learning, Collaboration and Communications, Assessment and Evaluation, and Administrative Efficiency. For this, first, we derive the techniques of bipolar complex hesitant fuzzy (BCHF) sets, and then we evaluate some flexible operational laws, called Algebraic operational laws and Aczel-Alsina operational laws. Secondly, using the above techniques, we elaborate the technique of BCHF Aczel-Alsina power averaging (BCHFAAPA), BCHF Aczel-Alsina power weighted averaging (BCHFAAPWA), BCHF Aczel-Alsina power geometric (BCHFAAPG), and BCHF Aczel-Alsina power weighted geometric (BCHFAAPWG) operators. Some basic properties are also investigated for each proposed operator. Further, to evaluate the problem concerning LMS, we compute the multi-attribute decision-making (MADM) techniques for invented operators. Finally, we select some prevailing operators and try to compare their ranking results with our proposed results to enhance the worth and capability of the invented theory.

Framework For Performance Management, ICT-Based Digitalization in A Higher Education Institution

By improving teaching and learning, research, and governance, digital technology has altered the educational landscape in academic institutions. Adequate infrastructure, improved internet access, modern digital tools, a secure platform, and professionals with digital competency are all critically needed. Higher education institutions in India are clearly visible from the growing usage of ICT, cloud computing, AI, robotics, and virtual reality in daily operations, which improves competencies and aids in skill alignment with industry-based knowledge. Teaching in a regular classroom is becoming obsolete. The way that education is delivered has changed dramatically since the advent of technology. It provides the freedom for students to access learning at any time or location they want. The lines that were once drawn by understudies and educators being available in a similar spot simultaneously have likewise become more foggy because of education turning out to be more computerized. In the past ten years, internet and remote learning have grown in popularity in India. With the majority of the country now having access to digital technology, online learning courses are becoming more and more popular. Besides, understudy evaluation through digitalization technology is currently a chance on the grounds that to the improvement of learning management systems (LMS). Outside of the classroom, students can socialize with their peers. The pupils' soft skills have also been guided by the peer-centered learning component. LMS would enhance student evaluation and the teaching process.

The Use of Google Classroom in Physics Course: Students' Perception

The use of the learning management system (LMS) in online learning has impacted the development of science and technology in the field of education. One of the major LMS that is frequently used today is Google Classroom. This study intends to evaluate student impressions of utilizing Google Classroom as an LMS in online physics learning. The method utilized by the researcher is the qualitative method. A total of 12 physics education students from one of the universities in Indonesia were involved as respondents in the interviews performed. The interview data were evaluated through the stages of organization, transcription, exploration, coding, theme formulation, and description based on the theme. The conclusions in this study consist of advantages, disadvantages, challenges, and suggestions for Google Classroom as an LMS relating to accessibility, connectivity, features, navigation, notifications, data plans, bandwidth, device memory, and display. A further study employing more respondents or from a teachers’ or lecturers’ perspective can be undertaken to provide a more comprehensive understanding of student perceptions of using Google Classroom as an LMS.
 Keywords: google classroom, physics course, students’ perception

Students' Perspectives on Innovation of Mathematics Learning Online Course on Their Ability to Develop Innovative Textbooks

The responsibility for developing professional and high-quality teacher candidates lies with the Education Institution for Educational Personnel (LPTK). However, achieving this goal is certainly challenging to achieve during this pandemic. This research explores student perspectives on the effectiveness of lectures in developing the ability to create innovative textbooks. The research employed quantitative descriptive methods and involved students from the mathematics education study program Universitas Negeri Semarang who were enrolled in the Innovation of Mathematics Learning course. The data were collected through questionnaires and analyzed using descriptive statistics. The results of the study indicate that preparing learning resources in modules is crucial during lectures. Additionally, activities such as synchronous lecture activities, use of Learning Management System (LMS), resources like videos, discussions with colleagues, virtual face-to-face, discussions using WhatsApp Group, presentation of each assignment, group assignments, and projects should be prepared during lectures. These results highlight the necessity of implementing a team-based project model to develop students’ abilities in developing innovative textbooks.
 Keywords: innovative textbooks, mathematics learning online course, students’ perspectives.

Smart Class System Prototyping through Sustainable Infrastructure Based on Mobile Application SPACE (Smart Program - Class Architecture) Integrated Smart Building Management System

Optimizing innovation in the use of health technology in infrastructure will directly impact the conditions of social interaction in the community, including within the scope of the school area. The Smart Class concept collaborates with learning carried out in a hybrid way. However, it is not yet fully optimized by digitizing the existing infrastructure with the concept of managing school facilities and infrastructure. The implementation of the Smart Class uses the intelligent building management system (IBMS), where this system integrates all parts of the building with the Internet of Things (IoT), facilities, and infrastructure and can minimize pandemic transmission in the academic sphere by accessing via mobile app. This research aims to analyze the design of the smart program class architecture integrated monitoring system to implement IoT-integrated health protocols, especially in the middle school scope. This research uses qualitative and quantitative methods with descriptive analysis through the development of user research at the system design stage. The output of this innovation is how schools implement digital technology comprehensively, starting from the application of IoT, sensors, and databases in a real-time mobile app environment. There are three main things: the data input, data processing, and output value. The intervention of school needs can be expanded with the integration of the learning management system in the form of integrated learning management the learning process, which is in line with monitoring the use of infrastructure in schools. Through this Smart Class concept, schools can still operate optimally without any applicable health policies and can provide excellent academic services.
 Keywords: smart class system prototyping, sustainable infrastructure mobile application, SPACE smart building management system

Students' Perspectives on Selecta Capita of Mathematics Online Course on Their Ability to Develop Mathematics Task

The main problem in implementing online lectures is how to adjust what students expect with the achievement of learning quality. This study examines students’ perspectives on effective lectures on the ability to develop mathematics task. Quantitative descriptive research has been carried out on students of the mathematics education study program Universitas Negeri Semarang who took the Selecta Capita of Mathematics course. The subjects in this study were 101 first-year students in the mathematics education study program at Semarang State University for the 2021/2022 academic year. The data were obtained through questionnaires and analyzed by the descriptive statistics. The data that had been obtained and then tabulated in a table, the average value is searched, and presented in the appropriate graph. The results of the study indicate that the availability of learning modules and videos as learning resources is the most important thing that must be prepared during lectures. Furthermore, several other things such as synchronous lectures, discussions using the WhatsApp Group, the use of the learning management system, group assignments, virtual face-to-face meetings, and project assignments need to be prepared during lectures. These results are needed to be applied on team-based project learning models to develop students’ abilities in developing math tasks.
 Keywords: students’ perspectives, selecta capita, mathematics online course, mathematics task

Integral Learning Management in Vocational and Technological Education

A gestão do processo de ensino e aprendizagem requer um planejamento baseado em um arcabouço teórico que contribua para a organização do trabalho docente tendo em vista a aprendizagem integral dos estudantes. Desta forma, o objetivo deste trabalho foi propor um modelo teórico para o processo de gestão da aprendizagem de componentes curriculares de cursos da educação profissional e tecnológica, sob o paradigma da Educação Integral. O modelo proposto foi organizado a partir do materialismo emergentista de Bunge incorporando-se outros métodos voltados ao planejamento (Ciclo PDCA, Planejamento Reverso, Design Thinking). Foi realizado um estudo de caso na unidade curricular de Mecânica Geral do Curso Superior em Engenharia Civil do IFMS, campus Aquidauana, com o intuito de validar o modelo.

Decoding Student Success in Higher Education: A Comparative Study on Learning Strategies of Undergraduate and Graduate Students


 
 Learning management systems (LMS) provide a rich source of data about the engagement of students with courses and their materials that tends to be underutilized in practice. In this paper, we use data collected from the LMS to uncover learning strategies adopted by students and compare their effectiveness. Starting from a sample of over 11,000 enrollments at a Portuguese information management school, we extracted features indicative of self-regulated learning (SRL) behavior from the associated interactions. Then, we employed an unsupervised machine learning algorithm (k-means) to group students according to the similarity of their patterns of interaction. This process was conducted separately for undergraduate and graduate students. Our analysis uncovered five distinct learning strategy profiles at both the undergraduate and graduate levels: 1) active, prolonged and frequent engagement; 2) mildly frequent and task-focused engagement; 3) mildly frequent, mild activity in short sessions engagement; 4) likely procrastinators; and 5) inactive. Mapping strategies with the students' final grades, we found that students at both levels who accessed the LMS early and frequently had better outcomes. Conversely, students who exhibited procrastinating behavior had worse end-of-course grades. Interestingly, the relative effectiveness of the various learning strategies was consistent across instruction levels. Despite the LMS offering an incomplete and partial view of the learning processes students employ, these findings suggest potentially generalizable relationships between online student behaviors and learning outcomes. While further validation with new data is necessary, these connections between online behaviors and performance could guide the development of personalized, adaptive learning experiences.
 

Examining perceptions and outcomes of AI versus human course assistant discussions in the online classroom

ABSTRACT As technologies such as artificial intelligence (AI) and other forms of machine communication become more popular and readily available, the opportunities for use in an online class increase. This replication and extension sought to understand and test the use of AI versus human communication in an online learning space—specifically the learning management system (LMS) discussion board. More specifically, the differences in student perceptions and outcomes between those with a human course assistant and those assigned to an AI course assistant were examined. These perceptions were studied through the presence and absence of the identity heuristic and helper heuristic as outlined in previous literature. The study employed a four-condition randomized quasiexperimental design. Outcomes of interest included credibility, task attraction, social attraction, computer-mediated competence, student communication satisfaction, affect toward instructor, and affect toward taking classes with the instructor. Findings supported previous work regarding importance of helper heuristics and highlighted the preference for a human over AI/machine educational agent.

Crafting Compelling Argumentative Writing for Undergraduates: Exploring the Nexus of Digital Annotations, Conversational Agents, and Collaborative Concept Maps

Argumentative writing is a fundamental aspect of undergraduate students’ academic and scientific writing related to critical thinking and problem-solving skills. However, previous studies have shown that students face various difficulties with argumentative writing, such as unclear and illogical ideas, less-structured arguments, and unbalanced interpretation of issues, data, and evidence. This study aims to improve the argumentative writing skills of undergraduate students by integrating computer-supported argumentative writing tools, such as annotation, conversational agents (CAs), and collaborative concept maps, into an online learning management system. Since the study was conducted during the COVID-19 pandemic, these tools can support meaningful learning activities and investigation in argumentative writing. The researchers divided sixty participants into the experimental group ( N = 30) and the control group ( N = 30). The results showed that the experimental group’s writing achievements outperformed the control group, and the three tools effectively improved the five elements of argumentative writing, including claims, grounds, warrants, backings, and rebuttal. Furthermore, a deep analysis found that the number of annotations, valid CAs’ responses, and argument nodes on collaborative concept maps can significantly predict students’ argumentative writing development. Moreover, students perceived that the incorporated tools could effectively improve their argumentative writing skills.