What is he best known for?
The fields of study he is best known for:
- The Internet
- Artificial intelligence
- Educational technology
Daniel D. Suthers mostly deals with Collaborative learning, Knowledge management, Argumentation theory, Mathematics education and Pedagogy.
His Collaborative learning research incorporates themes from Context, Human–computer interaction, Cooperative learning, Educational technology and Empirical research.
Daniel D. Suthers has included themes like Intelligent agent, Advice, Affordance and Team learning in his Knowledge management study.
His work is dedicated to discovering how Argumentation theory, Computer-supported collaborative learning are connected with Argumentative and Identification and other disciplines.
His Mathematics education research is multidisciplinary, incorporating perspectives in Multiple hypotheses and Relation.
His work in the fields of Pedagogy, such as Formative assessment, overlaps with other areas such as Critical discussion.
His most cited work include:
- Computer-supported collaborative learning: An historical perspective (856 citations)
- Arguing to Learn: Confronting Cognitions in Computer-Supported Collaborative Learning Environments (450 citations)
- Technology affordances for intersubjective meaning making: A research agenda for CSCL (406 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Collaborative learning, Knowledge management, Human–computer interaction, Multimedia and Mathematics education.
His Collaborative learning research includes themes of Affordance, Cognitive science, Educational technology, Learning sciences and Collaborative software.
His Educational technology research integrates issues from Experiential learning, Cooperative learning, Synchronous learning and World Wide Web.
His specific area of interest is Knowledge management, where Daniel D. Suthers studies Computer-supported collaborative learning.
His Human–computer interaction research incorporates elements of Artificial intelligence, Knowledge representation and reasoning, Face-to-face and Notation.
Daniel D. Suthers regularly links together related areas like Pedagogy in his Mathematics education studies.
He most often published in these fields:
- Collaborative learning (30.67%)
- Knowledge management (24.89%)
- Human–computer interaction (16.00%)
What were the highlights of his more recent work (between 2011-2021)?
- Social media (4.89%)
- Data science (8.89%)
- World Wide Web (10.22%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Social media, Data science, World Wide Web, Learning analytics and Sociotechnical system.
His Social media study combines topics in areas such as Internet privacy, Media studies, Affordance, The Internet and Focus.
His Data science study also includes
- Algorithm design most often made with reference to Graph,
- Phenomenon together with Engineering ethics.
The World Wide Web study combines topics in areas such as Educational technology and Usability.
His Educational technology research includes elements of Collaborative learning and Learning theory.
His Collaborative learning research is classified as research in Mathematics education.
Between 2011 and 2021, his most popular works were:
- Productive Multivocality in the Analysis of Group Interactions (56 citations)
- Learning analytics as a "middle space" (45 citations)
- Assessing intercultural communication competence as a relational construct using social network analysis (45 citations)
In his most recent research, the most cited papers focused on:
- The Internet
- Artificial intelligence
- World Wide Web
His scientific interests lie mostly in Data science, Learning analytics, World Wide Web, Knowledge management and Social network analysis.
His Data science research is multidisciplinary, relying on both Learning data, Educational research and Big data.
The concepts of his Learning analytics study are interwoven with issues in Field, Active learning, Agency and Analytics.
His Active learning study integrates concerns from other disciplines, such as Context, Educational technology, Blended learning and Software analytics.
Daniel D. Suthers interconnects Algorithm design, Graph and Learning sciences in the investigation of issues within Knowledge management.
His work in Social network analysis addresses issues such as Networked learning, which are connected to fields such as Multiple media, Affordance and Phenomenon.
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