Phillip J. Grimaldi

757 citations
14 papers · 519 · h-index 8

Impact in

Papers in

Phillip J. Grimaldi

14 papers receiving 487 citations

Peers

Phillip J. Grimaldi
Comparison fields: 5 of 63
  • Developmental and Educational Psychology 169
  • Computer Science Applications 70
  • Cognitive Neuroscience 224
  • Experimental and Cognitive Psychology 125
  • Artificial Intelligence 175
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Citations per year

Countries citing papers authored by Phillip J. Grimaldi

Since Specialization
Citations

This map shows the geographic impact of Phillip J. Grimaldi'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 Phillip J. Grimaldi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phillip J. Grimaldi more than expected).

Fields of papers citing papers by Phillip J. Grimaldi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Phillip J. Grimaldi. 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 Phillip J. Grimaldi. The network helps show where Phillip J. Grimaldi may publish in the future.

Co-authors

The 13 scholars most cited alongside Phillip J. Grimaldi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Phillip J. Grimaldi Line = papers co-authored together Phillip J. Grimaldi links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2012156
2 2012146
3 201953
4 201840
5 201333
6 201232
7 201031
8 20147
9
Can Textbook Annotations Serve as an Early Predictor of Student Learning
20185
10
A Meta-Learning Augmented Bidirectional Transformer Model for Automatic Short Answer Grading.
20195
11 20205
12
Inferring Student Comprehension from Highlighting Patterns in Digital Textbooks: An Exploration in an Authentic Learning Platform.
20204
13
Textbook annotations as an early predictor of student learning.
20181
14
Short-Answer Responses to STEM Exercises: Measuring Response Validity and Its Impact on Learning.
20171

About Phillip J. Grimaldi

Phillip J. Grimaldi is a scholar working on Artificial Intelligence, Computer Science Applications, Developmental and Educational Psychology, Cognitive Neuroscience and Education, having authored 14 papers that have together received 519 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (5 papers), Memory Processes and Influences (4 papers), Topic Modeling (4 papers), Innovative Teaching and Learning Methods (4 papers), Educational Strategies and Epistemologies (3 papers), Online Learning and Analytics (3 papers), Educational Assessment and Pedagogy (2 papers) and Visual and Cognitive Learning Processes (2 papers). The work is most often cited by research in Developmental and Educational Psychology (169 citations), Computer Science Applications (70 citations), Cognitive Neuroscience (224 citations), Experimental and Cognitive Psychology (125 citations) and Artificial Intelligence (175 citations). Phillip J. Grimaldi has collaborated with scholars based in United States and Czechia. Frequent co-authors include Jeffrey D. Karpicke, Andrew E. Waters, Richard G. Baraniuk, Debshila Basu Mallick, Jessica K. Witt, J. Eric T. Taylor, Katherine A. Rawson, Mary A. Pyc, Andrew Lan and Zichao Wang. Their work appears in journals such as Memory & Cognition, Cognition, Journal of Experimental Psychology Learning Memory and Cognition, Behavior Research Methods and PLoS ONE.

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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