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D-Index & Metrics

Social Sciences and Humanities

D-Index
40
Citations
8550
World Ranking
5278
National Ranking
2497

Eric N. Wiebe publication distribution in Social Sciences and Humanities in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Social Sciences and Humanities in 2026. The highlighted bar marks where Eric N. Wiebe sits on this spectrum.

44–53 publications: 28 scientists 54–63 publications: 61 scientists 64–73 publications: 161 scientists 74–83 publications: 225 scientists 84–93 publications: 301 scientists 94–103 publications: 390 scientists 104–113 publications: 406 scientists 114–123 publications: 474 scientists 124–133 publications: 453 scientists 134–143 publications: 434 scientists 144–153 publications: 407 scientists 154–163 publications: 411 scientists 164–173 publications: 391 scientists 174–183 publications: 313 scientists 184–193 publications: 319 scientists 194–203 publications: 304 scientists 204–213 publications: 285 scientists 214–223 publications: 246 scientists 224–233 publications: 213 scientists 234–243 publications: 170 scientists 244–253 publications: 167 scientists 254–263 publications: 162 scientists 264–273 publications: 138 scientists 274–283 publications: 138 scientists 284–293 publications: 113 scientists 294–303 publications: 106 scientists 304–313 publications: 95 scientists 314–323 publications: 101 scientists 324–333 publications: 81 scientists 334–343 publications: 69 scientists 344–353 publications: 56 scientists 354–363 publications: 36 scientists 364–373 publications: 42 scientists 374–383 publications: 41 scientists 384–393 publications: 44 scientists 394–403 publications: 27 scientists 404–413 publications: 30 scientists 414–423 publications: 20 scientists 424–433 publications: 29 scientists 434–443 publications: 29 scientists 444–453 publications: 25 scientists 454–463 publications: 19 scientists 464–473 publications: 21 scientists 474–483 publications: 11 scientists 484–493 publications: 17 scientists 494–503 publications: 7 scientists 504–513 publications: 6 scientists 514–523 publications: 12 scientists 524–533 publications: 10 scientists 534–543 publications: 7 scientists 544–553 publications: 6 scientists 554–563 publications: 12 scientists 564–569 publications: 8 scientists 570+ publications: 100 scientists
44 publications 570+

This scientist: 223 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 570 publications or more.

Eric N. Wiebe D-index placement in Social Sciences and Humanities in 2026

The chart shows the D-index (discipline H-index) distribution of Social Sciences and Humanities scientists ranked by Research.com in 2026. The highlighted bar marks where Eric N. Wiebe sits on this spectrum.

30 D-Index: 177 scientists 31 D-Index: 210 scientists 32 D-Index: 222 scientists 33 D-Index: 188 scientists 34 D-Index: 181 scientists 35 D-Index: 243 scientists 36 D-Index: 261 scientists 37 D-Index: 272 scientists 38 D-Index: 278 scientists 39 D-Index: 300 scientists 40 D-Index: 297 scientists 41 D-Index: 308 scientists 42 D-Index: 313 scientists 43 D-Index: 300 scientists 44 D-Index: 269 scientists 45 D-Index: 260 scientists 46 D-Index: 228 scientists 47 D-Index: 251 scientists 48 D-Index: 203 scientists 49 D-Index: 186 scientists 50 D-Index: 187 scientists 51 D-Index: 166 scientists 52 D-Index: 138 scientists 53 D-Index: 141 scientists 54 D-Index: 131 scientists 55 D-Index: 137 scientists 56 D-Index: 109 scientists 57 D-Index: 129 scientists 58 D-Index: 95 scientists 59 D-Index: 105 scientists 60 D-Index: 106 scientists 61 D-Index: 86 scientists 62 D-Index: 94 scientists 63 D-Index: 77 scientists 64 D-Index: 79 scientists 65 D-Index: 59 scientists 66 D-Index: 68 scientists 67 D-Index: 51 scientists 68 D-Index: 49 scientists 69 D-Index: 40 scientists 70 D-Index: 43 scientists 71 D-Index: 40 scientists 72 D-Index: 50 scientists 73 D-Index: 46 scientists 74 D-Index: 43 scientists 75 D-Index: 45 scientists 76 D-Index: 45 scientists 77 D-Index: 30 scientists 78 D-Index: 25 scientists 79 D-Index: 31 scientists 80 D-Index: 29 scientists 81 D-Index: 18 scientists 82 D-Index: 21 scientists 83 D-Index: 26 scientists 84 D-Index: 15 scientists 85 D-Index: 15 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 12 scientists 89 D-Index: 7 scientists 90 D-Index: 19 scientists 91 D-Index: 20 scientists 92 D-Index: 13 scientists 93 D-Index: 9 scientists 94 D-Index: 13 scientists 95 D-Index: 8 scientists 96 D-Index: 7 scientists 97 D-Index: 6 scientists 98 D-Index: 6 scientists 99 D-Index: 6 scientists 100+ D-Index: 97 scientists
30 D-Index 100+

This scientist: 40 D-Index — 34th percentile

34% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 100 D-Index or more.

Overview

Eric N. Wiebe is affiliated with North Carolina State University in the United States and has contributed extensively to the fields of computer science, psychology, and social sciences through research focused on educational technology and learning sciences. Their work bridges multiple disciplines with a distinctive emphasis on computational thinking, digital learning environments, and developmental psychology.

The scientist's research intersects several main fields of study: computer science, psychology, and social sciences. Within these fields, notable subfields include developmental and educational psychology, computer science applications, education, artificial intelligence, and experimental and cognitive psychology.

Key topics addressed in their publications concentrate on teaching and learning programming, innovative teaching and learning methods, educational games and gamification, online learning and analytics, intelligent tutoring systems and adaptive learning, gender and technology in education, and child development and digital technology.

Eric N. Wiebe's recent papers reflect a consistent focus on computational thinking and educational tools. Noteworthy recent publications include:

  • The Code-Centric Nature of Computational Thinking Education: A Review of Trends and Issues in Computational Thinking Education Research, 2021, SAGE Open
  • Building a computational model of food webs: Impacts on middle school students' computational and systems thinking skills, 2021, Journal of Research in Science Teaching
  • Measuring in-service teacher self-efficacy for teaching computational thinking: development and validation of the T-STEM CT, 2021, Education and Information Technologies
  • Modeling Secondary Students' Genetics Learning in a Game-Based Environment: Integrating the Expectancy-Value Theory of Achievement Motivation and Flow Theory, 2021, Journal of Science Education and Technology
  • Development and Validation of the Middle Grades Computer Science Concept Inventory (MG-CSCI) Assessment, 2020, Eurasia Journal of Mathematics Science and Technology Education

Frequent collaborators in their work include Kristy Elizabeth Boyer, Arif Rachmatullah, Bradford Mott, James C. Lester, and Collin Lynch. These partnerships highlight a network of researchers focused on computational thinking, educational games, and learning analytics.

Eric N. Wiebe's research has been published in various academic venues, with multiple papers appearing in the Proceedings of the Human Factors and Ergonomics Society Annual Meeting, International Journal of Child-Computer Interaction, Computer Science Education, ACM Transactions on Computing Education, and SAGE Open.

Best Publications

  • The viability of crowdsourcing for survey research.

    Tara S. Behrend;David J. Sharek;Adam W. Meade;Eric N. Wiebe

  • Cloud computing adoption and usage in community colleges

    Tara S. Behrend;Eric N. Wiebe;Jennifer E. London;Emily C. Johnson

  • Improving the CS1 experience with pair programming

    Nachiappan Nagappan;Laurie Williams;Miriam Ferzli;Eric Wiebe

  • In Support of Pair Programming in the Introductory Computer Science Course

    Laurie A. Williams;Eric N. Wiebe;Kai Yang;Miriam Ferzli

  • Measuring engagement in video game-based environments

    Eric N. Wiebe;Allison Lamb;Megan Hardy;David Sharek

  • The Development and Validation of a Measure of Student Attitudes Toward Science, Technology, Engineering, and Math (S-STEM)

    Alana Unfried;Malinda Faber;Daniel S. Stanhope;Eric Wiebe

  • Writing to Learn by Learning to Write in the Disciplines

    Michael Carter;Miriam G Ferzli;Eric N. Wiebe

  • Automatically Recognizing Facial Expression: Predicting Engagement and Frustration

    Joseph F. Grafsgaard;Joseph B. Wiggins;Kristy Elizabeth Boyer;Eric N. Wiebe

  • The influence of prior knowledge on viewing and interpreting graphics with macroscopic and molecular representations

    Michelle Cook;Eric N. Wiebe;Glenda Carter

  • On understanding compatibility of student pair programmers

    Neha Katira;Laurie Williams;Eric Wiebe;Carol Miller

  • Eye-Tracking Students' Attention to PowerPoint Photographs in a Science Education Setting.

    David A. Slykhuis;Eric N. Wiebe;Len A. Annetta

  • Student Attitudes toward STEM: The Development of Upper Elementary School and Middle/High School Student Surveys

    Malinda Faber;Alana Unfried;Eric N. Wiebe;Jeni Corn

  • An examination of two mental workload measurement approaches to understanding multimedia learning

    Eric N. Wiebe;Edward Roberts;Tara S. Behrend

  • Automatically Recognizing Facial Indicators of Frustration: A Learning-centric Analysis

    Joseph F. Grafsgaard;Joseph B. Wiggins;Kristy Elizabeth Boyer;Eric N. Wiebe

  • Visual Representations of DNA Replication: Middle Grades Students' Perceptions and Interpretations

    Michelle D. Patrick;Glenda Carter;Eric N. Wiebe

  • The Interpretation of Cellular Transport Graphics by Students with Low and High Prior Knowledge

    Michelle Cook;Glenda Carter;Eric N. Wiebe

  • Understanding Scale: Powers of Ten

    M. Gail Jones;Amy Taylor;James Minogue;Bethany Broadwell

  • Teaching Genre to English First-Language Adults: A Study of the Laboratory Report.

    Michael Carter;Miriam Ferzli;Eric Wiebe

  • The Relationship of STEM Attitudes and Career Interest

    Eric Wiebe;Alana Unfried;Malinda Faber

  • The Additive Value of Multimodal Features for Predicting Engagement, Frustration, and Learning during Tutoring

    Joseph F. Grafsgaard;Joseph B. Wiggins;Alexandria Katarina Vail;Kristy Elizabeth Boyer

  • Predicting Learning and Affect from Multimodal Data Streams in Task-Oriented Tutorial Dialogue.

    Joseph F. Grafsgaard;Joseph B. Wiggins;Kristy Elizabeth Boyer;Eric N. Wiebe

Frequent Co-Authors

James C. Lester
James C. Lester North Carolina State University
Tiffany Barnes
Tiffany Barnes North Carolina State University
Laurie Williams
Laurie Williams North Carolina State University
M. Gail Jones
M. Gail Jones North Carolina State University
Nachiappan Nagappan
Nachiappan Nagappan Facebook (United States)
Michael S. Wogalter
Michael S. Wogalter North Carolina State University
Mary Lou Maher
Mary Lou Maher University of North Carolina at Charlotte
Douglas B. Clark
Douglas B. Clark University of Calgary
Katharina Scheiter
Katharina Scheiter University of Potsdam
Claudia R. Benitez-Nelson
Claudia R. Benitez-Nelson University of South Carolina

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