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Lishan Zhang; Linyu Deng; Sixv Zhang; Ling Chen – IEEE Transactions on Learning Technologies, 2024
With the popularity of online one-to-one tutoring, there are emerging concerns about the quality and effectiveness of this kind of tutoring. Although there are some evaluation methods available, they are heavily relied on manual coding by experts, which is too costly. Therefore, using machine learning to predict instruction quality automatically…
Descriptors: Automation, Classification, Artificial Intelligence, Tutoring
Soomaiya Hamid; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
E-learning is the process of sharing knowledge out of the traditional classrooms through different online tools using internet. The availability and use of these tools are not easy for every student. Many institutions gather e-learning feedback to know the problems of students to improve their systems. In e-learning systems, typically a high…
Descriptors: Feedback (Response), Electronic Learning, Automation, Classification
Junfeng Man; Rongke Zeng; Xiangyang He; Hua Jiang – Knowledge Management & E-Learning, 2024
At present, the widespread use of online education platforms has attracted the attention of more and more people. The application of AI technology in online education platform makes multidimensional evaluation of students' ability become the trend of intelligent education in the future. Currently, most existing studies are based on traditional…
Descriptors: Cognitive Ability, Student Evaluation, Algorithms, Learning Processes
Ouissem, Benmesbah; Lamia, Mahnane; Hafidi, Mohamed – International Journal of Web-Based Learning and Teaching Technologies, 2021
Context modeling is the keystone to enable the intelligent system to adapt its functionalities properly to different situations. As such, a representation mechanism that allows an adequate manipulation of this kind of information is required, and diverse approaches have been introduced; however, what takes more value and is being positioned as a…
Descriptors: Electronic Learning, Educational Technology, Models, Educational Methods
Lu, Dang-Nhac; Le, Hong-Quang; Vu, Tuan-Ha – Education Sciences, 2020
The COVID-19 epidemic is affecting all areas of life, including the training activities of universities around the world. Therefore, the online learning method is an effective method in the present time and is used by many universities. However, not all training institutions have sufficient conditions, resources, and experience to carry out online…
Descriptors: Electronic Learning, Adoption (Ideas), Higher Education, Evaluation Methods
Gushchina, Oksana; Ochepovsky, Andrew – Turkish Online Journal of Distance Education, 2019
The article shows the role of data mining methods at the stages of the e-learning risk management for the various participants. The article proves the e-learning system fundamentally contains heterogeneous information, for its processing it is not enough to use the methods of mathematical analysis but it is necessary to apply the new educational…
Descriptors: Data Analysis, Information Retrieval, Electronic Learning, Risk Management
Mbaye, Baba – International Association for Development of the Information Society, 2018
The significant amount of information available on the web has led to difficulties for the learner to find useful information and relevant resources to carry out their training. The recommender systems have achieved significant success in the area of e-commerce, they still have difficulties in formulating relevant recommendations on e-learning…
Descriptors: Information Systems, Electronic Learning, Referral, Information Sources
Liyanagunawardena, Tharindu R.; Scalzavara, Sandra; Williams, Shirley A. – European Journal of Open, Distance and E-Learning, 2017
Open badges are a digital representation of skills or accomplishments recorded in a visual symbol that is embedded with verifiable data and evidence. They are created following a defined open standard, so that they can be shared online. Open badges have gained popularity around the world in recent years and have become a standard feature of many…
Descriptors: Recognition (Achievement), Information Storage, Evaluation Methods, Electronic Learning
Kazanidis, Ioannis; Theodosiou, Theodosios; Petasakis, Ioannis; Valsamidis, Stavros – Interactive Learning Environments, 2016
Database files and additional log files of Learning Management Systems (LMSs) contain an enormous volume of data which usually remain unexploited. A new methodology is proposed in order to analyse these data both on the level of both the courses and the learners. Specifically, "regression analysis" is proposed as a first step in the…
Descriptors: Foreign Countries, Online Courses, Course Evaluation, Electronic Learning
Bahreini, Kiavash; Nadolski, Rob; Westera, Wim – Education and Information Technologies, 2016
This paper presents the voice emotion recognition part of the FILTWAM framework for real-time emotion recognition in affective e-learning settings. FILTWAM (Framework for Improving Learning Through Webcams And Microphones) intends to offer timely and appropriate online feedback based upon learner's vocal intonations and facial expressions in order…
Descriptors: Affective Behavior, Emotional Response, Electronic Learning, Recognition (Psychology)
Romrell, Danae; Kidder, Lisa C.; Wood, Emma – Journal of Asynchronous Learning Networks, 2014
As mobile devices become more prominent in the lives of students, the use of mobile devices has the potential to transform learning. Mobile learning, or mLearning, is defined as learning that is personalized, situated, and connected through the use of a mobile device. As mLearning activities are developed, there is a need for a framework within…
Descriptors: Models, Evaluation Methods, Course Evaluation, Electronic Learning
Nallure Balasubramanian, Vineeth – ProQuest LLC, 2010
The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…
Descriptors: World Problems, Intelligence, Lifelong Learning, Prediction
Lin, Fu-Ren; Hsieh, Lu-Shih; Chuang, Fu-Tai – Computers & Education, 2009
As course management systems (CMS) gain popularity in facilitating teaching. A forum is a key component to facilitate the interactions among students and teachers. Content analysis is the most popular way to study a discussion forum. But content analysis is a human labor intensity process; for example, the coding process relies heavily on manual…
Descriptors: Secondary School Science, Online Courses, Earth Science, Classification
Padiotis, Ioannis; Mikropoulos, Tassos A. – Educational Technology & Society, 2010
The present research investigates the contribution of an interactive educational virtual environment on milk pasteurization to the learning outcomes of 40 students in a technical secondary school using SOLO taxonomy. After the interaction with the virtual environment the majority of the students moved to higher hierarchical levels of understanding…
Descriptors: Foreign Countries, Science Instruction, Technology Education, Misconceptions
Chang, Wen-Chih; Yang, Hsuan-Che; Shih, Timothy K.; Chao, Louis R. – International Journal of Distance Education Technologies, 2009
E-learning provides a convenient and efficient way for learning. Formative assessment not only guides student in instruction and learning, diagnose skill or knowledge gaps, but also measures progress and evaluation. An efficient and convenient e-learning formative assessment system is the key character for e-learning. However, most e-learning…
Descriptors: Electronic Learning, Student Evaluation, Formative Evaluation, Educational Objectives
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