| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 229 | 59 | 97 | 24 |
| Social Sciences and Humanities | 345 | 15 | 28 | 12 |
The main points discussed in International Journal of Artificial Intelligence in Education deals with Educational technology, Mathematics education, Multimedia, Artificial intelligence and Human–computer interaction. Topics in Educational technology were tackled in line with various other fields like Context (language use), Knowledge management, TUTOR, Teaching method and Intelligent tutoring system. The majority of Knowledge management studies are focused on the issues of Collaborative learning.
Specifically, studies on Computer-supported collaborative learning are prevalent in the Collaborative learning works discussed. While Mathematics education is the focus of the journal, it also provided insights into the studies of Metacognition and Set (psychology). The in-depth study on Multimedia also explores topics in the intersecting field of Adaptive learning.
Issues in Artificial intelligence were discussed, taking into consideration concepts from other disciplines like Machine learning and Natural language processing. The research on Human–computer interaction discussed in International Journal of Artificial Intelligence in Education draws on the closely related field of Domain (software engineering).
The most cited publications are organized to reinforce research efforts on Educational technology, Mathematics education, Knowledge management, Multimedia and TUTOR. The journal publications focus on Educational technology but the discussions also offer insight into other areas such as Active learning, Educational research, Cooperative learning, Teaching method and Collaborative learning. The published papers focus on Knowledge management but sometimes tackle the closely related topic of Learning sciences which is concerned with Formative assessment.
International Journal of Artificial Intelligence in Education generally zeroes in on subjects such as Educational technology, Mathematics education, Context (language use), Learning analytics and Human–computer interaction. The studies in Educational technology featured incorporate elements of TUTOR, Adaptive learning, Artificial intelligence and Analytics, Data science. It facilitates discussions on Mathematics education that incorporate concepts from other fields like Metacognition, Control (management), Game mechanics and Class (computer programming).
The study of Context (language use) encompasses disciplines such as Lifelong learning, as well as fields such as Participatory design, Estonian and Face (sociological concept), all of which overlap with one another. The work on Learning analytics tackled in it brings together disciplines like Field (computer science), Educational data mining, Data collection and Collaborative learning. In addition to Human–computer interaction research, it aims to explore topics under Domain (software engineering), Learning by teaching, Cognitive skill, Data-driven and Source lines of code.
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 International Journal of Artificial Intelligence in Education (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 International Journal of Artificial Intelligence in Education (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, 13.33% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 30.77% were posted by at least one author from the top 10 institutions publishing in the journal. Another 7.69% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 30.77% of all publications and 30.77% 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.
While our earlier section discussed the broad topics researched in the International Journal of Artificial Intelligence in Education, an important perspective that could offer a comprehensive understanding of the subject goes into exploring the application and impact of AI in education. Various applications of AI in education sector provide promising results. The adaptive learning systems, for instance, allow a personalized learning pace suitable for unique student's needs. AI-powered tools, such as predictive analytics, help educators monitor students' performance, identifying their struggles early and providing them targeted support. In another example, the machine learning algorithms utilizing natural language processing can develop 'Virtual Personal Tutor' that assists students in their studies wherever and whenever they need. While the impacts of AI in Education are remarkable, there is still a requirement for continuous learning and enhancement in the field. For those interested in applying AI to education as private school teachers in New York, getting to know private school teacher requirements in New York {anchor} could be instrumental. Artificial Intelligence's transformative potential in education lies in its continual developments, and these promising results indicate a transformative future for the education sector when educators and AI can work hand in hand.
Wayne Holmes;Kaska Porayska-Pomsta;Ken Holstein;Emma Sutherland
(2021)Ryan S. Baker;Aaron Hawn
(2021)Ghader Kurdi;Jared Leo;Bijan Parsia;Uli Sattler
(2020)Nesra Yannier;Scott E. Hudson;Kenneth R. Koedinger
(2020)For students interested in Computer Science, exploring related online degrees can open up diverse career opportunities. Engineering degrees often form the foundation for many technology roles, and aspiring professionals can find programs with great value by considering an engineer degree online. These programs typically blend theoretical knowledge with practical skills.
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