Technology, Knowledge and Learning

Top Research Topics at Technology, Knowledge, and Learning?

Technology, Knowledge, and Learning is mainly concerned with subjects like Educational technology, Science education, Mathematics education, Teaching method and Learning analytics. It focuses on Educational technology but the discussions also offer insight into other areas such as Context (language use), Knowledge management, Multimedia, Instructional design and Data science. Research on Multimedia addressed in Technology, Knowledge, and Learning frequently intersections with the field of Mobile device.

The journal explores studies in Science education as part of the wider topic of Pedagogy. Topics in Mathematics education explored in the journal were investigated in conjunction with research in Class (computer programming) and Reading comprehension. Learning analytics research featured in Technology, Knowledge, and Learning incorporates concerns from various other topics such as Analytics, Educational research and Big data.

• Educational technology (88.37%)
• Science education (81.93%)
• Mathematics education (39.36%)

What are the most cited papers published in the journal?

• Educational Data Mining and Learning Analytics: Applications to Constructionist Research. (124 citations)
• Development and Validation of a Learning Analytics Framework: Two Case Studies Using Support Vector Machines (104 citations)
• Counter-Mapping the Neighborhood on Bicycles: Mobilizing Youth to Reimagine the City (86 citations)

Research areas of the most cited articles at Technology, Knowledge, and Learning:

The most cited articles aim to foster the development of research in Educational technology, Science education, Mathematics education, Learning analytics and Educational research. The most cited papers with studies in Educational technology featured incorporate elements of Experiential learning, Multimedia and Data science. In addition to Science education research, the most cited publications aim to explore topics under Context (language use), Emerging technologies, Technology integration, Knowledge management and Big data.

What topics the last edition of the journal is best known for?

• Artificial intelligence
• Educational technology
• Mathematics education

The previous edition focused in particular on these issues:

The objective of the journal is to combine knowledge in the areas of Educational technology, Science education, Mathematics education, Context (language use) and Information and Communications Technology. In addition to Educational technology research, it aims to explore topics under Knowledge management, Field (computer science), Learning analytics, Applied psychology and Learning Management. The research on Science education tackled can also make contributions to studies in the areas of Curriculum, Public relations, Reading (process), Usability and Qualitative research.

The concepts on Mathematics education presented in it can also apply to other research fields, including Reading comprehension and Comprehension. Issues in Context (language use) were discussed, taking into consideration concepts from other disciplines like Affordance and Adaptation (computer science). Some problems in Information and Communications Technology that were presented in the journal overlapped with concepts under Digital learning and Presentation.

The most cited articles from the last journal are:

• Covid-19 and Crisis-Prompted Distance Education in Sweden (22 citations)
• Analysis of Teachers’ Pedagogical Digital Competence: Identification of Factors Predicting Their Acquisition (19 citations)
• Teachers’ Readiness to Adopt Mobile Learning in Classrooms: A Study in Greece (9 citations)

Papers citation over time

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.

Top authors and change over time

The top authors publishing in Technology, Knowledge, and Learning (based on the number of publications) are:

• Dirk Ifenthaler (14 papers) published 1 paper at the last edition,
• Andrew A. Tawfik (8 papers) published 1 paper at the last edition, 1 less than at the previous edition,
• Benjamin E. Erlandson (5 papers) absent at the last edition,
• Ryan S. Baker (4 papers) absent at the last edition,
• Samuel Greiff (4 papers) absent at the last edition.

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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Technology, Knowledge, and Learning (based on the number of publications) are:

• Deakin University (10 papers) absent at the last edition,
• King's College London (9 papers) absent at the last edition,
• University of Memphis (9 papers) published 1 paper at the last edition, 3 less than at the previous edition,
• Utah State University (9 papers) published 1 paper at the last edition, 1 less than at the previous edition,
• Curtin University (9 papers) absent at the last edition.

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.

Publication chance based on affiliation

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, 6.90% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 6.48% were posted by at least one author from the top 10 institutions publishing in the journal. Another 14.81% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 18.52% of all publications and 60.19% were from other institutions.

Returning Authors Index

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.

Returning Institution Index

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.

The experience to innovation index

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:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Opportunities in the Field

For those who are interested in engaging themselves in the sectors of Technology, Knowledge, and Learning, various career opportunities await. The possibilities range from researchers in educational technology, learning analytics, and data science to educators in science and mathematics. For instance, given the focus on the overall mental well-being of learners, one such promising avenue is in mental health counseling.

One such pathway is to become a mental health counselor in the state of Georgia. Requirements for this professional track involve obtaining specific educational credits and going through mandated supervised experience. To learn more about joining this expanding field, do have a look at how to be a mental health therapist in Georgia. It should provide a comprehensive guide to understand the prerequisites, the process, and the potential opportunities that lay in being a mental health counselor in Georgia.

It is important to understand that the sectors of Technology, Knowledge, and Learning are vast and rapidly developing, allowing individuals to contribute and innovate. Grasping these opportunities can pave the way to a rewarding career. Therefore, staying informed about the prospects these fields are essential for individuals considering to make strides in these dynamic spheres.