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Liu, Mengchi; Yu, Dongmei – Education and Information Technologies, 2023
The prevalence of e-learning systems has made educational resources more accessible, interactive and effective to learners without the geographic and temporal boundaries. However, as the number of users increases and the volume of data grows, current e-learning systems face some technical and pedagogical challenges. This paper provides a…
Descriptors: Electronic Learning, Educational Technology, Literature Reviews, Client Server Architecture
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Salome H. Maro; Aron W. Kondoro; Joel S. Mtebe; Jamie Proctor; Aneth Komba; Björn Haßler – International Review of Research in Open and Distributed Learning, 2024
In low-income countries, the use of technology to enhance teacher continuous professional development (TCPD) activities has been increasing significantly. However, most technology initiatives related to TCPD require the installation of complex information and communications technology (ICT) infrastructure in schools or availability of reliable…
Descriptors: Foreign Countries, Faculty Development, Educational Technology, Developing Nations
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Maro, Marin Salome; Kondoro, Aron; Haßler, Björn; Mtebe, Joel; Proctor, Jamie – Journal of Learning for Development, 2023
Low-powered mobile devices such as Raspberry Pis and tablets can be used as microservers to implement offline Learning Management Systems (LMS). Despite their potential, especially for low-income countries, such as Tanzania, no research is available detailing the affordances of these devices for supporting LMS features. This study investigated the…
Descriptors: Foreign Countries, Learning Management Systems, Developing Nations, Costs
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Kärner, Tobias; Warwas, Julia; Schumann, Stephan – Technology, Knowledge and Learning, 2021
Addressing heterogeneity in the classroom by adapting instruction to learners' needs challenges teachers in their daily work. To provide adaptive instruction in the most flexible way, teachers face the problem of assessing students' individual characteristics (learning prerequisites and learning needs) and situational states (learning experiences…
Descriptors: Learning Analytics, Heterogeneous Grouping, Computer Uses in Education, Client Server Architecture
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Redondo, Jose Manuel – IEEE Transactions on Education, 2019
Contribution: This paper describes a highly flexible design for a master's-level server administration course that uses updated technologies, addresses the most important course design challenges and extracts useful feedback from student work. The main contribution of this design is eliminating the self-regulation challenge students encounter in…
Descriptors: Models, Foreign Countries, Student Evaluation, Student Motivation
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Graesser, Arthur C.; Hu, Xiangen; Nye, Benjamin D.; VanLehn, Kurt; Kumar, Rohit; Heffernan, Cristina; Heffernan, Neil; Woolf, Beverly; Olney, Andrew M.; Rus, Vasile; Andrasik, Frank; Pavlik, Philip; Cai, Zhiqiang; Wetzel, Jon; Morgan, Brent; Hampton, Andrew J.; Lippert, Anne M.; Wang, Lijia; Cheng, Qinyu; Vinson, Joseph E.; Kelly, Craig N.; McGlown, Cadarrius; Majmudar, Charvi A.; Morshed, Bashir; Baer, Whitney – International Journal of STEM Education, 2018
Background: The Office of Naval Research (ONR) organized a STEM Challenge initiative to explore how intelligent tutoring systems (ITSs) can be developed in a reasonable amount of time to help students learn STEM topics. This competitive initiative sponsored four teams that separately developed systems that covered topics in mathematics,…
Descriptors: Intelligent Tutoring Systems, STEM Education, Electronics, Integrated Curriculum
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Goldstein, Ira – Information Systems Education Journal, 2019
Computer Science students need to acquire knowledge about both the hardware and software aspects of computing systems. It is necessary for them to understand how each layer interacts with one another. However, since Graphical User Interfaces have become ubiquitous, the opportunities to interact with the computer via a command prompt as part of…
Descriptors: Computer Science Education, Computer Software, Introductory Courses, Programming
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Pardo, Abelardo; Bartimote-Aufflick, Kathryn; Shum, Simon Buckingham; Dawson, Shane; Gao, Jing; Gaševic, Dragan; Leichtweis, Steve; Liu, Danny; Martínez-Maldonado, Roberto; Mirriahi, Negin; Moskal, Adon Christian Michael; Schulte, Jurgen; Siemens, George; Vigentini, Lorenzo – Journal of Learning Analytics, 2018
The learning analytics community has matured significantly over the past few years as a middle space where technology and pedagogy combine to support learning experiences. To continue to grow and connect these perspectives, research needs to move beyond the level of basic support actions. This means exploring the use of data to prove richer forms…
Descriptors: Individualized Instruction, Data Analysis, Learning, Feedback (Response)
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Bhagat, Kaushal Kumar; Subheesh, N. P.; Bhattacharya, Bani; Chang, Chun-Yen – EURASIA Journal of Mathematics, Science & Technology Education, 2017
With the rapid development of technology, incorporation of Information Communication Technology (ICT) for formative assessment purpose has been increasing over the past decade. This article describes the design and development of identification of students' misconceptions in an individualized learning environment (iSMILE) system that includes…
Descriptors: Misconceptions, Information Technology, Formative Evaluation, Educational Environment
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Rodriguez-Gil, Luis; García-Zubia, Javier; Orduña, Pablo; López-de-Ipiña, Diego – IEEE Transactions on Learning Technologies, 2017
Online laboratories have traditionally been split between virtual labs, with simulated components; and remote labs, with real components. The former tend to provide less realism but to be easily scalable and less expensive to maintain, while the latter are fully real but tend to require a higher maintenance effort and be more error-prone. This…
Descriptors: Educational Technology, Technology Uses in Education, Laboratories, Simulated Environment
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Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2016
Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…
Descriptors: Intelligent Tutoring Systems, Models, Open Source Technology, Computers