Publication Date
In 2025 | 0 |
Since 2024 | 2 |
Since 2021 (last 5 years) | 3 |
Since 2016 (last 10 years) | 10 |
Descriptor
Cluster Grouping | 10 |
Teaching Methods | 10 |
Educational Practices | 3 |
Barriers | 2 |
Computer Simulation | 2 |
Electronic Learning | 2 |
Foreign Countries | 2 |
Online Courses | 2 |
Semantics | 2 |
Undergraduate Students | 2 |
Affective Measures | 1 |
More ▼ |
Source
Author
Publication Type
Journal Articles | 9 |
Reports - Research | 5 |
Reports - Descriptive | 3 |
Reports - Evaluative | 2 |
Information Analyses | 1 |
Speeches/Meeting Papers | 1 |
Education Level
Higher Education | 4 |
Postsecondary Education | 3 |
Secondary Education | 2 |
Elementary Education | 1 |
High Schools | 1 |
Junior High Schools | 1 |
Middle Schools | 1 |
Audience
Researchers | 1 |
Location
California | 1 |
Indonesia | 1 |
Spain | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Susan C. Mirabal; Darcy A. Reed; Yvonne Steinert; Cynthia R. Whitehead; Scott M. Wright; Sean Tackett – Advances in Health Sciences Education, 2024
While explicit conceptual models help to inform research, they are left out of much of the health professions education (HPE) literature. One reason may be the limited understanding about how to develop conceptual models with intention and rigor. Group concept mapping (GCM) is a mixed methods conceptualization approach that has been used to…
Descriptors: Allied Health Occupations Education, Medical Education, Concept Mapping, Learning Strategies
Ting Ding; Mengqi Zhang – International Journal of Web-Based Learning and Teaching Technologies, 2024
The level of information technology is increasing, and technology is developed. University English teaching has also changed under its influence. Different from the traditional teaching in the past, more and more students adopt the mode of "Internet + Smartphone" to learn English. This paper proposes a teaching mode evaluation method in…
Descriptors: English for Special Purposes, Educational Change, Business Administration Education, Data
Beena Joseph; Sajimon Abraham – Knowledge Management & E-Learning, 2023
Currently, the majority of e-learning lessons created and disseminated advocate a "one-size-fits-all" teaching philosophy. The e-learning environment, however, includes slow learners in a noticeable way, just like in traditional classroom settings. Learning analytics of educational data from a learning management system (LMS) have been…
Descriptors: Electronic Learning, Learning Management Systems, Slow Learners, Educational Environment
Sindhgatta, Renuka; Marvaniya, Smit; Dhamecha, Tejas I.; Sengupta, Bikram – International Educational Data Mining Society, 2017
Question answering forums in online learning environments provide a valuable opportunity to gain insights as to what students are asking. Understanding frequently asked questions and topics on which questions are asked can help instructors in focusing on specific areas in the course content and correct students' confusions or misconceptions. An…
Descriptors: Questioning Techniques, Interviews, Electronic Learning, Online Courses
Mayer, Robert V. – European Journal of Contemporary Education, 2016
The use of method of imitational modeling to study forming the empirical knowledge in pupil's consciousness is discussed. The offered model is based on division of the physical facts into three categories: 1) the facts established in everyday life; 2) the facts, which the pupil can experimentally establish at a physics lesson; 3) the facts which…
Descriptors: Physics, Computer Simulation, Inquiry, Cluster Grouping
Varlamova, Elena V.; Tulusina, Elena A.; Zaripova, Zarema M.; Gataullina, Veronika L. – Interchange: A Quarterly Review of Education, 2017
The article is devoted to the problem of the development of skills connected with the acquisition of foreign lexis (Lexis = all possible words or phrases in a language) on the basis of semantic fields (Semantic field = a lexical set of related items, e.g., colour, red, green, blue). This becomes possible due to grouping well-known and unknown to…
Descriptors: Second Language Instruction, Lexicology, Semantics, Language Acquisition
Farris, Frank A.; Tsao, Ryan – PRIMUS, 2016
The technique of "group-averaging" produces colorings of a sphere that have the symmetries of various polyhedra. The concepts are accessible at the undergraduate level, without being well-known in typical courses on algebra or geometry. The material makes an excellent discovery project, especially for students with some background in…
Descriptors: Undergraduate Students, Art Activities, Mathematical Concepts, Photography
Gunarhadi, Sunardi; Anwar, Mohammad; Andayani, Tri Rejeki; Shaari, Abdull Sukor – International Journal of Special Education, 2016
The research aimed to investigate the effect of Cluster-Based Instruction (CBI) on the academic achievement of Mathematics in inclusive schools. The sample was 68 students in two intact classes, including those with learning disabilities, selected using a cluster random technique among 17 inclusive schools in the regency of Surakarta. The two…
Descriptors: Mathematics Achievement, Inclusion, Mathematics Instruction, Cluster Grouping
Akuma, Fru Vitalis; Callaghan, Ronel – EURASIA Journal of Mathematics, Science & Technology Education, 2016
The science education budget of many secondary schools has decreased, while shortages and environmental concerns linked to conventional Science Education Equipment and Materials (SEEMs) have emerged. Thus, in some schools, resourceful educators produce low-cost equipment from basic materials and use these so-called improvised SEEMs in practical…
Descriptors: Science Education, Teaching Methods, Barriers, Media Adaptation
Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement