World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
9777
World Ranking
5372
National Ranking
2459

Neil T. Heffernan publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Neil T. Heffernan sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 284 publications — 70th percentile

70% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Neil T. Heffernan D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Neil T. Heffernan sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 51 D-Index — 63rd percentile

63% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Neil T. Heffernan is affiliated with Worcester Polytechnic Institute in the United States. Their research primarily focuses on the intersection of computer science and education, with extensive work in areas such as artificial intelligence, computer science applications, education, developmental and educational psychology, and statistics and probability.

Their research topics cover diverse domains including:

  • Online Learning and Analytics
  • Intelligent Tutoring Systems and Adaptive Learning
  • Innovative Teaching and Learning Methods
  • Topic Modeling
  • Student Assessment and Feedback
  • Natural Language Processing Techniques
  • Advanced Causal Inference Techniques

Neil T. Heffernan has contributed to a number of recent papers, which illustrate their engagement with advancing computational methods in educational contexts. Notable publications include:

  • "Leveraging natural language processing to support automated assessment and feedback for student open responses in mathematics," published in 2023 in the Journal of Computer Assisted Learning
  • "MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education," published in 2021 in arXiv (Cornell University)
  • "Facilitating Student Learning With a Chatbot in an Online Math Learning Platform," published in 2024 in the Journal of Educational Computing Research
  • "Generative AI for Education (GAIED): Advances, Opportunities, and Challenges," published in 2024 in arXiv (Cornell University)
  • "Reinforcement Learning for Education: Opportunities and Challenges," published in 2021 in arXiv (Cornell University)

Their frequent co-authors include:

  • Ethan Prihar
  • Anthony F. Botelho
  • Sami Baral
  • Adam Sales
  • Aaron Haim

Neil T. Heffernan's publications are often found in venues such as:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Arabixiv (OSF Preprints)
  • Educational Data Mining
  • Journal of Computer Assisted Learning

Their body of work demonstrates a strong emphasis on developing and analyzing intelligent systems that facilitate learning and assessment in mathematics and related fields. This includes leveraging natural language processing and reinforcement learning methods to enhance educational platforms and improve student feedback mechanisms.

Best Publications

  • The ASSISTments Ecosystem: Building a Platform that Brings Scientists and Teachers Together for Minimally Invasive Research on Human Learning and Teaching

    Neil T. Heffernan;Cristina Lindquist Heffernan

  • Addressing the assessment challenge with an online system that tutors as it assesses

    Mingyu Feng;Neil Heffernan;Kenneth Koedinger

  • Context-Aware Attentive Knowledge Tracing

    Aritra Ghosh;Neil Heffernan;Andrew S. Lan

  • Modeling individualization in a bayesian networks implementation of knowledge tracing

    Zachary A. Pardos;Neil T. Heffernan

  • Why Students Engage in “Gaming the System” Behavior in Interactive Learning Environments

    Ryan Baker;Jason Walonoski;Neil Heffernan;Ido Roll

  • A Comparison of Traditional Homework to Computer-Supported Homework.

    Michael Mendicino;Leena Razzaq;Neil T. Heffernan

  • Opening the door to non-programmers: Authoring Intelligent tutor behavior by demonstration

    Kenneth R. Koedinger;Vincent Aleven;Neil Heffernan;Bruce Mclaren

  • Population validity for educational data mining models: A case study in affect detection

    Jaclyn Ocumpaugh;Ryan Shaun Baker;Sujith M. Gowda;Neil T. Heffernan

  • KT-IDEM: introducing item difficulty to the knowledge tracing model

    Zachary A. Pardos;Neil T. Heffernan

  • Detection and analysis of off-task gaming behavior in intelligent tutoring systems

    Jason A. Walonoski;Neil T. Heffernan

  • AXIS: Generating Explanations at Scale with Learnersourcing and Machine Learning

    Joseph Jay Williams;Juho Kim;Anna Rafferty;Samuel Maldonado

  • Comparing knowledge tracing and performance factor analysis by using multiple model fitting procedures

    Yue Gong;Joseph E. Beck;Neil T. Heffernan

  • A QUASI-EXPERIMENTAL EVALUATION OF AN ON-LINE FORMATIVE ASSESSMENT AND TUTORING SYSTEM*

    Kenneth R. Koedinger;Elizabeth A. McLaughlin;Neil T. Heffernan

  • Predicting College Enrollment from Student Interaction with an Intelligent Tutoring System in Middle School.

    Maria Ofelia Clarissa Z. San Pedro;Ryan Shaun Baker;Alex J. Bowers;Neil T. Heffernan

  • An Intelligent Tutoring System Incorporating a Model of an Experienced Human Tutor

    Neil T. Heffernan;Kenneth R. Koedinger

  • Incorporating Rich Features into Deep Knowledge Tracing

    Liang Zhang;Xiaolu Xiong;Siyuan Zhao;Anthony Botelho

  • Improving Sensor-Free Affect Detection Using Deep Learning

    Anthony F. Botelho;Ryan S. Baker;Neil T. Heffernan

  • Predicting state test scores better with intelligent tutoring systems: developing metrics to measure assistance required

    Mingyu Feng;Neil T. Heffernan;Kenneth R. Koedinger

  • Using Fine-Grained Skill Models to Fit Student Performance with Bayesian Networks

    Zachary A. Pardos;Neil T. Heffernan;Brigham Anderson;Cristina L Heffernan

  • What are the Biases in My Word Embedding

    Nathaniel Swinger;Maria De-Arteaga;Neil Thomas Heffernan;Mark Dm Leiserson

Frequent Co-Authors

Ryan S. Baker
Ryan S. Baker University of Pennsylvania
Kenneth R. Koedinger
Kenneth R. Koedinger Carnegie Mellon University
Vincent Aleven
Vincent Aleven Carnegie Mellon University
Charles H. Lang
Charles H. Lang Pennsylvania State University
Carolyn Penstein Rosé
Carolyn Penstein Rosé Carnegie Mellon University
Jeremy Roschelle
Jeremy Roschelle Digital Promise
Antonija Mitrovic
Antonija Mitrovic University of Canterbury
Mykola Pechenizkiy
Mykola Pechenizkiy Eindhoven University of Technology
Arthur C. Graesser
Arthur C. Graesser University of Memphis
Susan R. Goldman
Susan R. Goldman University of Illinois at Chicago

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