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Ulrike Cress; Joachim Kimmerle – International Journal of Computer-Supported Collaborative Learning, 2023
Generative Artificial Intelligence (AI) tools, such as ChatGPT, have received great attention from researchers, the media, and the public. They are gladly and frequently used for text production by many people. These tools have undeniable strengths but also weaknesses that must be addressed. In this squib we ask to what extent these tools can be…
Descriptors: Artificial Intelligence, Cognitive Style, Computer Assisted Instruction, Learning Strategies
Troussas, Christos; Giannakas, Filippos; Sgouropoulou, Cleo; Voyiatzis, Ioannis – Interactive Learning Environments, 2023
Computer-Supported Collaborative Learning is a promising innovation that ameliorates tutoring through modern technologies. However, the way of recommending collaborative activities to learners, by taking into account their learning needs and preferences, is an important issue of increasing interest. In this context, this paper presents a framework…
Descriptors: Computer Assisted Instruction, Cognitive Style, Cooperative Learning, Models
Marioara Pascu – Cogent Education, 2024
This study explored the relationship between students' learning styles and their learning process through Kahoot in developing competencies within a target group of 89 high school students from Technical College "Dimitrie Ghika", Romania. Initially, the students' learning styles were identified using Reid's VAK model. As a second step,…
Descriptors: Cognitive Style, Learning Management Systems, Geography Instruction, Experiential Learning
Kristi M. Bockorny; Theresa M. Giannavola; Shalini Mathew; Hannah D. Walters – Active Learning in Higher Education, 2024
In order to navigate enrollment challenges, universities are scheduling more online and blended courses including HyFlex courses which offer students flexibility in their method of attendance. The goal of this study is to explore student engagement in HyFlex courses. However, there is limited research supporting the effectiveness of HyFlex courses…
Descriptors: College Students, In Person Learning, Blended Learning, Asynchronous Communication
Bahari, Akbar – Interactive Learning Environments, 2023
Second language teaching approaches that were originally proposed for classroom context are used for blended learning context as well as distance learning contexts regardless of their fundamental differences in terms of applicability, accessibility, objectives, designs and theoretical bases. Such theoretical and practical incompatibilities served…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Second Language Learning, English (Second Language)
Rahma, Rezka Arina; Sucipto; Affriyenni, Yessi; Widyaswari, Monica – World Journal on Educational Technology: Current Issues, 2021
This research was aimed to test the effectiveness of cmaterials in improving the learning of the students. The development method used in this research is the ADDIE (Analysis, Design, Development or Production, Implementation or Delivery, and Evaluation) model. The subjects in this developmental research are the lecturers of the educational…
Descriptors: Educational Technology, Technology Uses in Education, Educational Benefits, Cognitive Style
Thang Van Le; Ha Le Nguyen; Hung Thanh Nguyen – Journal of Education and e-Learning Research, 2023
E-learning has gained popularity as a method of delivering education recently and offers many advantages to enhance the learning experience for students. Technology allows teachers to design more interactive and engaging lessons that cater to different learning styles. It can also provide opportunities for teachers to incorporate virtual…
Descriptors: Foreign Countries, High School Teachers, Teacher Attitudes, Teaching Methods
Elkhatat, Ahmed M.; Al-Muhtaseb, Shaheen A. – Chemical Engineering Education, 2022
A Computer-Aided Learning Package as Inquiry-Guided Learning (CALP/IGL) was implemented in a cooling tower experiment for 43 students enrolled in four sections of the Unit Operations Laboratory course in the chemical engineering program at Qatar University. The impact of this approach on the attainment of learning outcomes was evaluated. Results…
Descriptors: Inquiry, Active Learning, Engineering Education, Computer Assisted Instruction
Missaoui, Siwar; Maalel, Ahmed – Education and Information Technologies, 2021
A student's profile defines the best way a student chooses to learn. It comprises information on student's characteristics such as background knowledge, learning style preference, goals, personality etc. The foremost challenge that the students experience in learning system is that they are unable to bring back relevant information based on their…
Descriptors: Profiles, Models, Computer Games, Cognitive Style
Sridharan, Shwetha; Saravanan, Deepti; Srinivasan, Akshaya Kesarimangalam; Murugan, Brindha – Education and Information Technologies, 2021
There exist numerous resources online to gain the desired level of knowledge on any topic. However, this complicates the process of selecting the most appropriate resources. Every learner differs in terms of their learning speed, proficiency, and preferred mode of learning. This paper develops an adaptive learning management system to tackle this…
Descriptors: Integrated Learning Systems, Computer Assisted Instruction, Individualized Instruction, Learning Analytics
Pawlak, Miroslaw – Language Teaching Research Quarterly, 2022
Research into the role of individual difference (ID) factors in the process of second and foreign language (L2) learning and teaching has been one of the most robust lines of inquiry in the field of second language acquisition (SLA; Dörnyei & Ryan, 2015; Griffiths & Soruç, 2020; Pawlak & Kruk, 2022). Most of these empirical…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Teaching Methods
Koc-Januchta, Marta M.; Höffler, Tim N.; Prechtl, Helmut; Leutner, Detlev – Educational Technology Research and Development, 2020
The aim of this study was to investigate the role of visual/verbal cognitive style and interactivity level in dynamic and non-dynamic multimedia learning environments. A group of 235 biology students learned about photosynthesis either from a computer-based animation or a series of static pictures with spoken explanatory text. Participants were…
Descriptors: Cognitive Style, Interaction, Visualization, Multimedia Instruction
Alshammari, Mohammad T.; Qtaish, Amjad – Journal of Information Technology Education: Research, 2019
Aim/Purpose: Effective e-learning systems need to incorporate student characteristics such as learning style and knowledge level in order to provide a more personalized and adaptive learning experience. However, there is a need to investigate how and when to provide adaptivity based on student characteristics, and more importantly, to evaluate its…
Descriptors: Electronic Learning, Cognitive Style, Knowledge Level, Individualized Instruction
Aguilar, J.; Buendia, O.; Pinto, A.; Gutiérrez, J. – Interactive Learning Environments, 2022
Social Learning Analytics (SLA) seeks to obtain hidden information in large amounts of data, usually of an educational nature. SLA focuses mainly on the analysis of social networks (Social Network Analysis, SNA) and the Web, to discover patterns of interaction and behavior of educational social actors. This paper incorporates the SLA in a smart…
Descriptors: Learning Analytics, Cognitive Style, Socialization, Social Networks
Hariyanto, Didik; Triyono, Moch. Bruri; Köhler, Thomas – Knowledge Management & E-Learning, 2020
One of the advanced technologies in e-learning deals with the systems' ability to fit the students' preferences. It emerged based upon the common conception that every person has different learning style. However, despite the many options of learning style models toward using personalized elearning, there are considerable challenges to assess the…
Descriptors: Usability, Electronic Learning, Individualized Instruction, Computer Assisted Instruction