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Journal articles on the topic 'Learning management systems'

To see the other types of publications on this topic, follow the link: Learning management systems.

Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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1

Irfan, C. M. Althaff, Karim Ouzzane, Shusaku Nomura, and Yoshimi Fukumura. "211 AN ACCESS CONTROL SYSTEM For E-Learning MANAGEMENT SYSTEMS." Proceedings of Conference of Hokuriku-Shinetsu Branch 2010.47 (2010): 59–60. http://dx.doi.org/10.1299/jsmehs.2010.47.59.

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2

Wuttke, Heinz‐Dietrich, and Karsten Henke. "Learning management systems." Interactive Technology and Smart Education 6, no. 2 (May 14, 2009): 97–107. http://dx.doi.org/10.1108/17415650910968107.

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3

Cavus, Nadire. "Distance Learning and Learning Management Systems." Procedia - Social and Behavioral Sciences 191 (June 2015): 872–77. http://dx.doi.org/10.1016/j.sbspro.2015.04.611.

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4

Soumplis, Alexandros, Eleni Koulocheri, Nektarios Kostaras, Nikos Karousos, and Michalis Xenos. "Learning Management Systems and Learning 2.0." International Journal of Web-Based Learning and Teaching Technologies 6, no. 4 (October 2011): 1–18. http://dx.doi.org/10.4018/jwltt.2011100101.

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The unprecedented growth of Web 2.0 has affected learning and has made the growth of learning networks possible. Learning networks are shaped by communities to help their members acquire knowledge in specific areas and are the most notable feature of Learning 2.0, the new learning era that focuses on individual learning needs. The evolution of learning forces traditional Learning Management Systems (LMS) to incorporate more Web 2.0 features and slowly transform to Personal Learning Environments (PLEs). A Personal Learning Environment is a loosely structured collection of tools with strong social networking characteristics, which gives users the ability to create, maintain, and redistribute their own learning content. This paper is a field study of the most well-known and established LMSs and their support for specific features within several categories of tools of Web 2.0. The incorporation of Web 2.0 features within those LMSs differentiates them regarding their ability and potential to be used as PLEs.

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Fardinpour, Ali, Mir Mohsen Pedram, and Martha Burkle. "Intelligent Learning Management Systems." International Journal of Distance Education Technologies 12, no. 4 (October 2014): 19–31. http://dx.doi.org/10.4018/ijdet.2014100102.

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Virtual Learning Environments have been the center of attention in the last few decades and help educators tremendously with providing students with educational resources. Since artificial intelligence was used for educational proposes, learning management system developers showed much interest in making their products smarter and more intelligent. Nevertheless, the questions of what an intelligent learning management system (ILSM) is and which tools and features are needed to make such system intelligent, are not clearly answered, therefore educational institutes do not have a proper tool to decide upon the degree of intelligence they need for their LMSs. This paper proposes a prevalent, thorough definition of “Intelligent Learning Management Systems”, and the design of a fuzzy model to measure the intelligence of these systems. In order to devise a comprehensive definition of an Intelligent Learning Management System, experts from around the world were consulted. Following that, different proposed Intelligent Learning Management Systems were studied, and forty-one features and tools were found and analyzed. After the analysis, experts' opinions were taken into account to rank these features. The paper proposes thirteen most significant features and tools as criteria to be used in fuzzy analytic hierarchy process (AHP) as a fuzzy model to measure the intelligence of Learning Management System.

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Tkachenko, Olha, and Vladyslav Tyrkov. "Distance Learning Management Systems." Digital Platform: Information Technologies in Sociocultural Sphere 5, no. 1 (June 30, 2022): 67–81. http://dx.doi.org/10.31866/2617-796x.5.1.2022.261291.

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The purpose of the article is to research, analyze and consider general problems and prospects for the development of management systems for learning processes with the ability to support distance learners using the latest technologies. The research methodology consists in methods of semantic analysis of the basic concepts of this subject area (management systems of educational processes). The article considers the approaches to the development and operation of the learning management system. The scientific novelty of the research is the analysis of the functioning of modern learning management systems and learning systems, the results of which can be used in the development of their own learning management system, which is relevant in today’s online learning environment. Conclusions. The paper considers well-known views on distance learning and analyzes modern information systems for distance learning management. Taking into account the results of the analysis, the authors decided to develop an information system for managing educational processes in distance education.

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Ozkan, Sevgi, Refika Koseler, and Nazife Baykal. "Evaluating learning management systems." Transforming Government: People, Process and Policy 3, no. 2 (May 29, 2009): 111–30. http://dx.doi.org/10.1108/17506160910960522.

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8

Passerini, Katia. "Evaluating Learning Management Systems." International Journal of Web-Based Learning and Teaching Technologies 1, no. 3 (July 2006): 1–27. http://dx.doi.org/10.4018/jwltt.2006070101.

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9

Yamani, Hanaa A., Ahmed D. Alharthi, and Lassaad Kacem Smirani. "Evaluation of Learning Management Systems." International Journal of Emerging Technologies in Learning (iJET) 17, no. 07 (April 12, 2022): 125–44. http://dx.doi.org/10.3991/ijet.v17i07.28881.

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This study examined, by analysis and comparison, two Learning Management Systems (LMS): Blackboard and Brightspace. The field research sample consisted of 513 students at Umm Al-Qura University. The study attempted to answer central questions dealing with the evaluation level of Umm Al-Qura University students for the characteristics of these two LMS. The study concludes that most students agree on the benefits of Blackboard and Brightspace, and according to them, the most common advantages of these LMS are: Help to access shared data and files, record and monitor the learner's performance, help to control and customize the educational process, facilitate the exchange of experiences and scientific concepts with others, the stable interface in controlling and moving among other components, facilitate discussion with the teacher and with students, and interface easy to understand and learn and easy to use. The study revealed that there is a statistically significant difference between the mean scores of students who use the Blackboard system and students who use the Brightspace system in the overall score to evaluate the e-learning system characteristics in favor of students who use the Brightspace system. This means that students who use the Brightspace system are more sensitive to the advantages of an e-learning system compared to students who use the Blackboard system. The findings can be used to assist educators in producing the best process of implementing open and distance learning. The appropriate techniques must be chosen to ensure that no student drops behind and that the teaching and learning process works with sustainability.

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10

Chaw, Lee Yen, and Chun Meng Tang. "What Makes Learning Management Systems Effective for Learning?" Journal of Educational Technology Systems 47, no. 2 (August 28, 2018): 152–69. http://dx.doi.org/10.1177/0047239518795828.

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Learning management systems (LMSs) may provide learners with resources in various formats, such as videos, quizzes, and forum discussions to support their learning, but having access to an LMS does not necessarily mean that learning has occurred effectively. Despite its apparent usefulness, whether the use of the LMS can indeed help learners learn more effectively remains an interesting matter for course providers, LMS vendors, and learners. Therefore, this study adopted the updated DeLone and McLean information system success model to examine whether LMS system quality, information quality, and service quality affect learners’ system use and user satisfaction, and ultimately their learning effectiveness. Through a questionnaire survey, responses collected from 123 university students who studied in a blended learning environment at a university were analyzed. Findings showed that system quality and service quality, but not information quality, had a significant relationship with system use. In turn, system use had a significant relationship with learning effectiveness.

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Liyanage, M. Prabhani Pitigala, K. S. Lasith Gunawardena, and Masahito Hirakawa. "Using Learning Styles to Enhance Learning Management Systems." International Journal on Advances in ICT for Emerging Regions (ICTer) 7, no. 2 (April 20, 2015): 1. http://dx.doi.org/10.4038/icter.v7i2.7153.

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Liyanage, M. Prabhani Pitigala, K. S. Lasith Gunawardena, and Masahito Hirakawa. "Using learning styles to enhance learning management systems." International Journal on Advances in ICT for Emerging Regions (ICTer) 7, no. 2 (May 26, 2014): 47. http://dx.doi.org/10.4038/icter.v7i2.7177.

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Morgado, Erla Mariela Morales, Francisco Jose Garcia Penalvo, Hugo Rego, and Tiago Moreira. "Learning objects quality management for e-learning systems." International Journal of Technology Enhanced Learning 1, no. 3 (2009): 193. http://dx.doi.org/10.1504/ijtel.2009.024866.

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Ahmed, Khawlah, and Mujo Mesonovich. "Learning Management Systems and Student Performance." International Journal for e-Learning Security 8, no. 1 (March 30, 2019): 582–91. http://dx.doi.org/10.20533/ijels.2046.4568.2019.0073.

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15

Al Amoush, Abdeleh Bassam, and Kamaljeet Sandhu. "Digital Learning Management Systems Case Study." International Journal of Information Communication Technologies and Human Development 11, no. 3 (July 2019): 42–60. http://dx.doi.org/10.4018/ijicthd.2019070103.

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Digital learning management systems (DLMSs) are an important and a necessary educational tool for learning activities. The universities are using the digital LMS (DLMS) tools that are unique to their environment. Different universities have different DLMS tools that are software driven and allow the users (management, instructors, and students) to use them for regular tasks. This research discusses the qualitative data collected using the case study methodology. In this research, case study design was selected for the qualitative methodology and semi-structured interviews were employed as the data collection method. The research provides an analysis of the interviews, to gain insights into instructors' perspectives regarding the factors influencing the implementation of the digital learning management system in the higher education sector.

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N, Sai Tanishq. "Machine Learning for Database Management Systems." International Journal of Engineering and Computer Science 9, no. 08 (August 19, 2020): 25132–47. http://dx.doi.org/10.18535/ijecs/v9i08.4520.

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Machine Learning (ML) is transforming the world with research breakthroughs that are leading to the progress of every field. We are living in an era of data explosion. This further improves the output as data that can be fed to the models is more than it has ever been. Therefore, prediction algorithms are now capable of solving many of the complex problems that we face by leveraging the power of data. The models are capable of correlating a dataset and its features with an accuracy that humans fail to achieve. Bearing this in mind, this research takes an in-depth look into the of the problem- solving potential of ML in the area of Database Management Systems (DBMS). Although ML hallmarks significant scientific milestones, the field is still in its infancy. The limitations of ML models are also studied in this paper.

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17

Iqbal, Shakeel. "Learning Management Systems (LMS): Inside Matters." Information Management and Business Review 3, no. 4 (October 15, 2011): 206–16. http://dx.doi.org/10.22610/imbr.v3i4.935.

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By the end of last millennium, many universities and colleges started using internet to meet their distance learning needs. Different course management systems (CMS) were developed to meet the needs of online and hybrid courses. These CMS later on transformed into Learning Management Systems (LMS). Many educational institutions have already started using LMS and there are still many who are considering adopting one. The big question before the late adopters of this online learning technology is which LMS they should opt for? This study will be useful for those who are in the process of selecting an LMS as well as those who are in the business of designing one. A survey was conducted to get feedback from the faculty of higher education institutions to find out the major barriers in adoption of e-learning and to find out what kind of functionalities and teaching methodologies should be supported by LMSs. Results indicate lack of training, lack of incentives to use e-learning, lack of technical support and lack of time to develop e-courses are the major barriers in adoption of e-learning by the faculty members. As far as the desired functionalities in an LMS are concerned ability to create student groups for group activities, availability of discussion board, announcement board and online quizzes, file sharing/transfer functionality were the most sought functionalities. The most desired method of teaching that need to be supported by LMS had been group problem solving, discussion based strategies, problem based learning and simulation. The results of survey will be helpful for the adopter as well as designers of LMS.

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18

Porter, Gavin W. "Free choice of learning management systems." Interactive Technology and Smart Education 10, no. 2 (June 7, 2013): 84–94. http://dx.doi.org/10.1108/itse-07-2012-0019.

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Boehm, Matthias, Arun Kumar, and Jun Yang. "Data Management in Machine Learning Systems." Synthesis Lectures on Data Management 14, no. 1 (February 25, 2019): 1–173. http://dx.doi.org/10.2200/s00895ed1v01y201901dtm057.

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20

Alsaif, Suleiman Ali, Alice S. Li, Ben Soh, Mohammed A. AlZain, and Mehedi Masud. "From Learning Management Systems to a Social Learning Environment." International Journal of Smart Education and Urban Society 10, no. 1 (January 2019): 1–18. http://dx.doi.org/10.4018/ijseus.2019010101.

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Since the advances in information and communication technologies, educational technology has been a priority research topic for academics, technology specialists and educational system developers. The objective of the study in this article is to evaluate the current learning systems and to shed the light on applications of social networking sites in higher education environment. To this end, the authors review the available alternative learning models with a view to achieving the most appropriate comprehensive and integral learning model. This article explores and compares the current advanced web-based educational services. It then demonstrates and discourses on the available Web 2.0 tools and social networking applications that can be used to foster learning activities and informal learning environments.

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21

Drira, R., M. Laroussi, X. Le Pallec, and B. Warin. "Contextualizing Learning Scenarios According to Different Learning Management Systems." IEEE Transactions on Learning Technologies 5, no. 3 (July 2012): 213–25. http://dx.doi.org/10.1109/tlt.2011.35.

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22

Park, Ji Yong. "Course evaluation: reconfigurations for learning with learning management systems." Higher Education Research & Development 33, no. 5 (March 14, 2014): 992–1006. http://dx.doi.org/10.1080/07294360.2014.890564.

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23

A. Abu-Dawwas, Waheeb. "A new scoring method for multiple choice tests in learning management systems." International Journal of Academic Research 6, no. 1 (January 30, 2014): 274–80. http://dx.doi.org/10.7813/2075-4124.2014/6-1/a.36.

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24

Hjalager, Anne-Mette. "Interorganizational learning systems." Human Systems Management 18, no. 1 (April 12, 1999): 23–33. http://dx.doi.org/10.3233/hsm-1999-18104.

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The occurrence of organizational and interorganizational learning processes is not only the result of management endeavors. Industry structures and market related issues have substantial spill-over effects. The article reviews literature, and it establishes a learning model in which elements from organizational environments are included into a systematic conceptual framework. The model allows four types of learning to be identified: P-learning (professional/craft systems learning), T-learning (technology embedded learning), D-learning (dualistic learning systems, where part of the labor force is exclude from learning), and S-learning (learning in social networks or clans). The situation related to service industries illustrates the typology.

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Viotti, Eduardo B. "National Learning Systems." Technological Forecasting and Social Change 69, no. 7 (September 2002): 653–80. http://dx.doi.org/10.1016/s0040-1625(01)00167-6.

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Grace, Audrey, and Tom Butler. "Learning management systems: a new beginning in the management of learning and knowledge." International Journal of Knowledge and Learning 1, no. 1/2 (2005): 12. http://dx.doi.org/10.1504/ijkl.2005.006248.

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27

Kaasbøll, Jens, Marlen Stacey Chawani, Gro Alice Hamre, and Jon Sandvand. "Competencies and Learning for Management Information Systems." Journal of Information, Information Technology, and Organizations (Years 1-3) 5 (2010): 085–100. http://dx.doi.org/10.28945/1323.

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28

Kraleva, Radoslava, Mehrudin Sabani, and Velin Kralev. "An Analysis of Some Learning Management Systems." International Journal on Advanced Science, Engineering and Information Technology 9, no. 4 (August 14, 2019): 1190. http://dx.doi.org/10.18517/ijaseit.9.4.9437.

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29

YAREMKO, Svitlana, Olena KUZMINA, and Svitlana BEVZ. "DIRECTIONS OF DEVELOPMENT OF LEARNING MANAGEMENT SYSTEMS." Herald of Khmelnytskyi National University 302, no. 1 (January 2022): 252–55. http://dx.doi.org/10.31891/2307-5740-2022-302-1-42.

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The article considers the concept of a learning management system; examines the principles of a learning management system; highlights the features of Learning Management Systems; provides an analytical review of the most common learning management platforms. The article reveals a comparative analysis of both commercial and free integrated electronic management systems of the educational process with electronic management systems of their own development of higher educational institutions, as well as their functional capabilities in management educational process and their characteristics. Known educational management systems the process is focused on supporting the main functions of training. When analyzing the scientific literature on the development of control systems, we found that many scientists have dealt with this problem. The article discusses in detail the most popular learning management systems. We found that most users had such management systems as: Moodle, Claronline, ATutor, Mindflash, SkyPrep , Sakai, OpenACS. We analyzed each management system and found out how they differ, what software is needed to install the platform. For a visual example, we have inserted an image of each learning management system so that when describing it, we can see a real picture of the software. Visualization helps inform readers about the program. This made it possible to identify the advantages and disadvantages of modern learning management systems, develop a number of recommendations for improving the use of learning management systems. In our scientific work, we have systematized all learning management programs in a table. This allowed us to show them, compare them, and determine which one is the most effective. In general, it can be noted that the development and implementation of modern learning management systems is certainly one of the important issues of education, since they are a modern and effective means of ensuring the integrity and accessibility of training. This is especially true in recent years, when distance learning has become widespread. The transition to online learning is due to the spread of coronavirus infection. This situation was the impetus for the development of online learning platforms.

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Titchiev, Inga, and Veronica Iamandi. "The analysis of learning management systems features." Akademos, no. 3(62) (January 2022): 113–19. http://dx.doi.org/10.52673/18570461.21.3-62.14.

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The successful implementation of e-Learning is based on the correct choice of software that meets the specific requirements and objectives of the organization. Thus, the purpose of this article is to review and analyze existing learning management systems (LMS), in order to use their potential in streamlining the learning process. To achieve this goal, the LMS assessment criteria were selected, the most popular open-source distance learning platforms were analyzed; the current LMS Integration capabilities were assessed. For the LMS analysis the following criteria were proposed: Functionality; Reliability; Stability; Cost, Availability of content development tools; SCORM support; Knowledge testing system; Easy to use; Modularity; Ensuring access; Multimedia; Scalability and Extensibility; Multiplatform LMS. A comparative analysis of 8 electronic learning management systems was presented. All of them support the use of multimedia elements, content creating and editing, assessment possibilities

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31

Abdullah, Rusli, Shamsul Sahibudin, Rose Alinda Alias, and Mohd Hasan Selamat. "Collaborative Knowledge Management Systems for Learning Organisations." Journal of Information & Knowledge Management 04, no. 04 (December 2005): 237–45. http://dx.doi.org/10.1142/s0219649205001237.

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A knowledge management system (KMS) is a concept that can be used for creating knowledge repositories, improving knowledge access and sharing as well as communicating through collaboration, enhancing the knowledge environment and managing knowledge as an asset for an institution or organisation. In this paper, we propose a collaborative KMS framework for learning organisations (LOs) and discuss components in the framework that will help organisations to increase productivity and quality as well as to gain return on investment from a KMS. These components are KMS functionality, architecture, taxonomy, psychological, sociocultural and audit.

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32

White, Meagan, and Teresa Shellenbarger. "Harnessing the Power of Learning Management Systems." Journal for Nurses in Professional Development 33, no. 3 (2017): 138–41. http://dx.doi.org/10.1097/nnd.0000000000000348.

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Hermann, Thomas, and Katharina Just-Hahn. "Organizational learning with flexible workflow management systems." ACM SIGOIS Bulletin 17, no. 3 (December 1996): 54–57. http://dx.doi.org/10.1145/242206.242316.

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de Porto Alegre Muniz, Maria Isabella, and Anamaria de Moraes. "Usability issues in Learning Management Systems (LMS)." Work 41 (2012): 832–37. http://dx.doi.org/10.3233/wor-2012-0250-832.

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35

Brudan, Aurel. "Rediscovering performance management: systems, learning and integration." Measuring Business Excellence 14, no. 1 (March 23, 2010): 109–23. http://dx.doi.org/10.1108/13683041011027490.

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36

Avogadro, Paolo, Silvia Calegari, and Matteo Alessandro Dominoni. "Expert students in social learning management systems." Interactive Technology and Smart Education 13, no. 3 (September 19, 2016): 202–17. http://dx.doi.org/10.1108/itse-06-2016-0018.

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Purpose A social learning management system (social LMS) is a tool which favors social interactions and allows scholastic institutions to supervise and guide the learning process. The inclusion of the social feature to a “normal” LMS leads to the creation of educational social networks (EduSN), where the students interact and learn. The advantages derived from an augmented student-student interaction are counterbalanced by the difficulty to control the quality of the information. For this reason, the purpose of this study is to understand who is a source of reliable and high quality knowledge among the students. Design/methodology/approach The authors suggest to categorize the actions of the students within roles where the most natural formal role regards the academic performance of a student. Within the EduSN, a student can produce information − social contribution role − and evaluate the contents provided by other peers − social judge role. Aside from the free production, it provides a publication workflow which allows to certify and improve the quality of the material created by the peers. The publication workflow naturally leads to the definition of two additional roles – the editorial and leader roles. Findings The paper provides a new definition of expertise within a social LMS, where the key feature of an expert in an EduSN is to improve the quality and quantity of the knowledge flow in the network. The indicators which stem from the roles naturally lead to the definition of the figure of the anti-expert. Originality/value At variance with the spectrum of values usually associated with expertise (which ranges from novice to expert), in a social LMS, it becomes clear the need of the definition of a new figure – the anti-expert, who has a negative impact on the overall knowledge flow of the EduSN.

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Shannon, Li-Jen Y., and Marilyn Rice. "Scoring the Open Source Learning Management Systems." International Journal of Information and Education Technology 7, no. 6 (2017): 432–36. http://dx.doi.org/10.18178/ijiet.2017.7.6.907.

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Cavus, Nadire, and Muhammed Sharif Alhih. "Learning Management Systems Use in Science Education." Procedia - Social and Behavioral Sciences 143 (August 2014): 517–20. http://dx.doi.org/10.1016/j.sbspro.2014.07.429.

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Cavus, Nadire, and Ala’a M. Momani. "Computer aided evaluation of learning management systems." Procedia - Social and Behavioral Sciences 1, no. 1 (2009): 426–30. http://dx.doi.org/10.1016/j.sbspro.2009.01.076.

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Alves da Silva, Nuno Sotero, Gonçalo Jorge Morais da Costa, Mary Prior, and Simon Rogerson. "The Evolution of E-learning Management Systems." International Journal of Cyber Ethics in Education 1, no. 3 (July 2011): 12–24. http://dx.doi.org/10.4018/ijcee.2011070102.

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The development of educational technologies is enhancing a distinctive feature of learning environments: the learner’s personalized environment. However, the current literature in e-learning seems to neglect an important discussion: will individuals (learners and lecturers) and organizations face an enhancement concerning ethical dilemmas due to this evolution? To promote this discussion, this paper builds on a consideration of e-learning definition and its ethical dilemmas, and human-centred learning concept and its dimensions, to examine the implications of integrating social and cultural contexts. By examining the evolution of e-learning management systems the argument progresses to a discussion of the relationships between pedagogy and ethics. By framing evidence at different scales, the authors critically reflect on the ethical dilemmas embedded in e-learning systems. The discussion concludes with advocating the adoption of an extension of “three P” mode of pedagogy to become the “P3E” model: personalization, participation, productivity, lecturer’s ethics, learner’s ethics, and organizational ethics.

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41

Handal, B., C. Groenlund, and T. Gerzina. "Dentistry studentsâ perceptions of learning management systems." European Journal of Dental Education 14, no. 1 (February 2010): 50–54. http://dx.doi.org/10.1111/j.1600-0579.2009.00591.x.

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42

Joh, HyunChul. "Modeling Security Vulnerabilities in Learning Management Systems." International Journal of Learning Management Systems 1, no. 2 (July 1, 2013): 1–12. http://dx.doi.org/10.12785/ijlms/010201.

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43

Parslow, Graham R. "Commentary: For and against learning management systems." Biochemistry and Molecular Biology Education 34, no. 1 (January 2006): 53–54. http://dx.doi.org/10.1002/bmb.2006.49403401053.

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Babin, E. N. "IMPLEMENTATION OF LEARNING MANAGEMENT SYSTEMS: DISTANT LEARNING TECHNOLOGIES AS TEACHERS’AID." University Management: Practice and Analysis 21, no. 5 (2017): 103–12. http://dx.doi.org/10.15826/umpa.2017.05.066.

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45

Kumar Dutta, Ashit, Mazen Mushabab Alqahtani, Yasser Albagory, Abdul Rahaman Wahab Sait, and Majed Alsanea. "Optimal Machine Learning Enabled Performance Monitoring for Learning Management Systems." Computer Systems Science and Engineering 44, no. 3 (2023): 2277–92. http://dx.doi.org/10.32604/csse.2023.028107.

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Liyanage, Madura Prabhani Pitigala, K. S. Lasith Gunawardena, and Masahito Hirakawa. "Detecting Learning Styles in Learning Management Systems Using Data Mining." Journal of Information Processing 24, no. 4 (2016): 740–49. http://dx.doi.org/10.2197/ipsjjip.24.740.

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Marks, Adam, Maytha AL-Ali, and Kees Rietsema. "Learning Management Systems: A Shift Toward Learning and Academic Analytics." International Journal of Emerging Technologies in Learning (iJET) 11, no. 04 (April 5, 2016): 77. http://dx.doi.org/10.3991/ijet.v11i04.5419.

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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.

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Fertalj, Kresimir, Natasa Bozic-Hoic, and Hrvoje Jerkovic. "The integration of learning object repositories and learning management systems." Computer Science and Information Systems 7, no. 3 (2010): 387–407. http://dx.doi.org/10.2298/csis081127001f.

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The systems aimed for manipulating large number of courses and students are called Learning Management Systems (LMS). A LMS can have excellent performance implemented through advanced Web technologies but it is often accompanied by a poor or rarely used repository of institution?s educational content. It has still remained. Still remains a problem how to allow users of a LMS to easily modify and integrate the content from federated e-learning repositories into their courses. This article presents an analysis of present repository frameworks and projects. FEDORA (Flexible Extensible Digital Repository Object Architecture) framework is explained as an alternative repository solution. A pilot application has been developed to demonstrate the interaction between a LMS and its repository.

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Chou, Amy Y., and David C. Chou. "Course Management Systems and Blended Learning: An Innovative Learning Approach." Decision Sciences Journal of Innovative Education 9, no. 3 (September 2011): 463–84. http://dx.doi.org/10.1111/j.1540-4609.2011.00325.x.

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Zafra, Amelia, Cristóbal Romero, and Sebastián Ventura. "Multiple instance learning for classifying students in learning management systems." Expert Systems with Applications 38, no. 12 (November 2011): 15020–31. http://dx.doi.org/10.1016/j.eswa.2011.05.044.

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