Kenneth M. Ford

2.1k citations
63 papers · 1.2k indexed · h-index 20
Topics
AI-based Problem Solving and Planning (8 papers)Computability, Logic, AI Algorithms (7 papers)Innovative Teaching and Learning Methods (6 papers)
Partner nations
United StatesCanadaItaly

In The Last Decade

Kenneth M. Ford

61 papers receiving 1.0k citations

Peers

Kenneth M. Ford
Comparison fields: 5 of 140
  • Artificial Intelligence 412
  • Social Psychology 242
  • Developmental and Educational Psychology 163
  • Education 142
  • Cognitive Neuroscience 119
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Citations per field
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Countries citing papers authored by Kenneth M. Ford

Since Specialization
Citations

This map shows the geographic impact of Kenneth M. Ford's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kenneth M. Ford with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kenneth M. Ford more than expected).

Fields of papers citing papers by Kenneth M. Ford

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kenneth M. Ford. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kenneth M. Ford. The network helps show where Kenneth M. Ford may publish in the future.

Co-authorship network of co-authors of Kenneth M. Ford

This figure shows the co-authorship network connecting the top 25 collaborators of Kenneth M. Ford. A scholar is included among the top collaborators of Kenneth M. Ford based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kenneth M. Ford. Kenneth M. Ford is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 0
4 22
5 4
6
Online Concept Maps: Enhancing Collaborative Learning by Using Technology with Concept Maps
37
7
An Architecture for Smart Internet Agents
4
8
The Giant: An Agent-Based Approach to Knowledge Construction and Sharing
4
9 14
10
A general framework for conceiving of expertise and expert systems in context
15
11 1
12
Expertise in context: human and machine
212
13
Turing test considered harmful
78
14 3
15 4
16 18
17
Expertise in context: personally constructed, socially selected and reality-relevant?
38
18
Modeling Expert Decision Making: Paradox of Simple Versus Complex Models.
1
19
Advances in Human and Machine Cognition: Reasoning Agents in a Dynamic World: The Frame Problem
1
20 37

About Kenneth M. Ford

Kenneth M. Ford is a scholar working on Computer Science Applications, Artificial Intelligence and General Decision Sciences, having authored 63 papers that have together received 1.2k indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (8 papers), Computability, Logic, AI Algorithms (7 papers) and Innovative Teaching and Learning Methods (6 papers). The work is most often cited by research in Developmental and Educational Psychology (163 citations), Artificial Intelligence (412 citations) and Social Psychology (242 citations). Kenneth M. Ford has collaborated with scholars based in United States, Canada and Italy. Frequent co-authors include Patrick J. Hayes, Robert R. Hoffman, Paul J. Feltovich, Jack Adams‐Webber, Jeffrey M. Bradshaw, Neil McK. Agnew, Clark Glymour, Alberto J. Cañas, Joseph D. Novak and Thomas Reichherzer. Their work appears in journals such as American Journal of Physiology-Cell Physiology, Artificial Intelligence and Computer.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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