| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 638 | 11 | 22 | 9 |
| Social Sciences and Humanities | 641 | 11 | 18 | 8 |
The discussions in Smart Learning Environments mainly cover the fields of Mathematics education, Context (language use), Multimedia, Knowledge management and Smart learning. The journal explores topics in Mathematics education which can be helpful for research in disciplines like Class (computer programming), Creativity and Curriculum. The subject of Higher education, which is connected to the field of Virtual learning environment, serves as the foundation of the Context (language use) research featured in Smart Learning Environments.
It holds forums on Multimedia that merges themes from other disciplines such as Personalization, Synchronous learning, Learning environment, Educational technology and Mobile device. The journal tackles studies in Active learning and the interrelated subject of Blended learning to gain insights into Synchronous learning. The study of Learning analytics and how it intertwines with concepts under Analytics and Adaptive learning were explored in the presented Learning environment research.
The studies in Educational technology featured incorporate elements of Experiential learning, Collaborative learning and Open learning. The journal explores issues in Knowledge management which can be linked to other research areas like Information and Communications Technology and Instructional design. The Learning sciences research presented in it explores the relationship between Data science and the closely related topic of Domain (software engineering).
The most cited papers mainly tackle studies in Knowledge management, Multimedia, Educational technology, Collaborative learning and Synchronous learning. Issues in Collaborative learning were discussed in the published articles, taking into consideration concepts from other disciplines like Class (computer programming), Differentiated instruction, Emerging technologies and Personalized learning. Experiential learning, Active learning, Open learning and Blended learning are some topics wherein Synchronous learning research discussed in the published papers has an impact.
Smart Learning Environments covers a variety of subjects, including Mathematics education, Higher education, Context (language use), Knowledge management and Smart learning. The studies on Mathematics education discussed can also contribute to research in the domains of Control (management), Predictive modelling, Grammar and Curriculum. It facilitates discussions on Context (language use) that incorporate concepts from other fields like Dreyfus model of skill acquisition, Usage data and Embodied cognition.
The featured Knowledge management research zeroes in on concepts in Collaborative learning but also tackles themes under Educational program. The featured Smart learning studies mainly concentrate on Delphi method but also cover areas of interest in Learning analytics and Data science. In addition to Class (computer programming) research, it aims to explore topics under Multimedia, Self-efficacy and Mobile device.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Smart Learning Environments (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Smart Learning Environments (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 4.17% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 21.74% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.70% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 21.74% of all publications and 47.83% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
For those who are interested in pursuing a career that aligns with the topics of smart learning environments, a wide range of opportunities are available. One possible avenue is becoming a substance abuse counselor, where smart learning concepts can be fruitfully applied. In this role, you would leverage your knowledge of technologies, methodologies, and theories related to smart learning to effect change in the lives of individuals struggling with addiction. This could involve designing intelligent educational programs tailored to each individual's needs—focusing on areas such as Mathematics education, Context (language use), Multimedia, and Knowledge management—or conducting impactful research in these areas.
Obtaining proper certification is a key step to becoming a successful substance abuse counselor. In Massachusetts, for instance, the certification process involves fulfilling specific educational and experiential requirements. To learn more about this, you can check out our guide on "[how to become a Substance Abuse Counselor in Massachusetts](https://research.com/careers/how-to-become-a-substance-abuse-counselor-in-massachusetts)". This resource presents an in-depth view of the entire process of becoming a substance abuse counselor in Massachusetts—from the required educational qualifications to the necessary work experience.
By building a career in applied smart learning research, you can help shape the future of education and make a critical impact on many lives.
Atikah Shemshack;Jonathan Michael Spector
(2020)Unknown
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