Studies without
Heffernan Authorship

Published or pending work without Neil Heffernan as an author,

conducted using E-TRIALS or its predecessor, the ASSISTments Testbed

Published Full/Short Papers // 13

ASSISTments closes achievement gaps (between lower and higher achieving students)

    • Fyfe, E. (2016). Providing feedback on computer-based algebra homework in middle-school classrooms. Computers in Human Behavior 63, 568-574. [PDF] University of Wisconsin-Madison

Using ASSISTments to study spatial features in mathematical expressions

    • Harrison, A., Smith, H., Hulse, T., & Ottmar, E. (2020). Spacing out!: Manipulating Spatial Features in Mathematical Expressions Affects Performance. Journal of Numerical Cognition, 6(2), 186-203. DOI: 10.5964/jnc.v6i2.243. [PDF] Worcester Polytechnic Institute

Comparing hints to step-by-step scaffolding questions, solutions, and worked examples

    • Andres-Bray, M., Hutt, S., Zhou, Y, Ostrow, K. & Baker K. (2021). A Comparison of Hints vs. Scaffolding in a MOOC with Adult Learners. AIED 2021. [PDF] University of Pennsylvania and Worcester Polytechnic Institute

    • McGuire, P., Tu, S., Logue., M., Mason, C., Ostrow, K. (2017). Counterintuitive effects of online feedback in middle school math: results from a randomized controlled trial in ASSISTments. Educational Media International, 54(3), 231-244, DOI: 10.1080/09523987.2017.1384161. [PDF] University of Colorado Colorado Springs and University of Maine

    • Chan, J. Y.-C., Lee, J.-E., Mason, C. A., Sawrey, K., & Ottmar, E. (2022). From Here to There! A dynamic algebraic notation system improves understanding of equivalence in middle-school students. Journal of Educational Psychology, 114(1), 56–71. [PDF] University of Maine

    • Smith, H., Closser, A. H., Ottmar, E. R., & Chan, J. Y. C. (2022). The impact of algebra worked example presentations on student learning. Applied Cognitive Psychology, 36(2), 363-377. [PDF] Worcester Polytechnic Institute

Comparing the difficulty of different problem types

    • Walkington, C., Clinton, V., & Sparks, A. (2019). The effect of language modification of mathematics story problems on problem-solving in online homework. Instructional Science. 47, 499-529. [PDF] Southern Methodist University and University of North Dakota

Comparing the format of difference problem types

    • Jiang, Y., Almeda, M. V., Kai, S., Baker, R. S., Ostrow, K., Inventado, P. S., & Scupelli, P. (2020). Single Template vs. Multiple Templates: Examining the Effects of Problem Format on Performance. In Gresalfi, M. & Horn, I. S. (Eds.), The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020, Volume 2 (1015-1022). Nashville, Tennessee: International Society of the Learning Sciences. [PDF] ETS, TERC, Teachers College Columbia University, University of Pennsylvania, Worcester Polytechnic Institute, California State University Fullerton, and Carnegie Mellon University

Comparing different instructional approaches

    • Unal, D. S., Arrington, C.M., Solovey, E., and Walker, E. (2020). Using Thinkalouds to Understand Rule Learning and Cognitive Control Mechanisms Within an Intelligent Tutoring System. In: Bitencourt I., Cukurova M., Muldner K., Luckin R., Millan E. (eds) Artificial Intelligence in Education. AIED 2020. Lecture Notes in Computer Science, vol 12163. Springer, Cham. https://doi.org/10.1007/978-3-030-52237-7_40. [PDF] University of Pittsburgh, Lehigh University, and Worcester Polytechnic Institute

    • Koedinger, K.R. & McLaughlin, E.A. (2010). Seeing language learning inside the math: Cognitive analysis yields transfer. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. (pp. 471-476.) Austin, TX: Cognitive Science Society. [PDF] Carnegie Mellon University

    • Koedinger, K. & McLaughlin, E. (2016) Closing the Loop with Quantitative Cognitive Task Analysis. In Barnes, Chi & Feng (eds) The 9th International Conference on Educational Data Mining. 412-417. [PDF] Carnegie Mellon University

    • Hurst, M. A., Cordes, S. (2018). Labeling Common and Uncommon Fractions Across Notation and Education. Proceedings of Cognitive Science, 1841-1846. [PDF] University of Chicago and Boston College

New Economics Journal uses ETRIALS

    • Duquennois, C. (2022). Fictional money, real costs: Impacts of financial salience on disadvantaged students. American Economic Review, 112(3), 798-826. [Author PDF][Journal version ] University of California Berkeley

Under Review // 6

    • Vahey, P., Feng, M., Algama, M., & Liu, J. (Under Review). Using rapid experimental techniques to design more effective environments. SRI International, WestEd

    • Ngo, V., Perez, L., Closser, A. H., & Ottmar, E. The effects of operand position and superfluous brackets on student performance in math problem-solving. Manuscript in preparation. (Under Review)

    • Iannacchione, A., Ottmar, E., Ngo, V., Mason, Chan, C., J. Y., Smith, H., Drzewiecki, K., & Shaw, S. Examining relations between math anxiety, prior knowledge, hint usage, and math performance in two different online learning contexts. (Under Review)

    • Finster, M., Decker-Woodrow, L., Booker, B., Mason, C. A., & Tu, S. Cost-effectiveness of algebraic technological applications. (Under Review)

    • Ottmar, E. & Colleagues. In-person vs. Virtual: Learning modality selections and movement during COVID-19 and their influence on student learning. (Under Review)

    • Ottmar, E. & Colleagues. The impacts of three educational technologies on algebraic understanding in the context of COVID-19. (Under Review)

Posters/Workshops/Etc // 6

  • Harrison, A., Smith, H., Hulse, T., & Ottmar, E. (2020). Spacing out: Manipulating spatial features in math expressions affects performance. Paper to be presented in a roundtable session on “Design Considerations in Mathematics Learning” at the 2020 American Educational Research Association Annual Meeting in San Francisco, California. Worcester Polytechnic Institute

  • Smith, H., Harrison, A., Chan, J. C., & Ottmar, E. (2020). Dynamic vs. static: Which worked examples work best? Poster submission to the 2020 meeting of The Mathematical Cognition and Learning Society. [pre-registration][Study Summary] Worcester Polytechnic Institute

  • Smith, H., Ramey, K., Heffernan, N., & Uttal, D. (June, 2022) Can mental rotation predict performance in an online geometry assignment? Proceedings of the 15th International Conference of the Learning Sciences.

  • Ottmar, E. & Colleagues. (2022). Does where you start matter? The interaction between prior knowledge and effectiveness of game-based interventions. Conference proposal accepted by International Society of the Learning Sciences.

  • Ottmar, E. & Colleagues. (2022). From performance to perception: A laboratory-based task to detect changes in students’ perception of math equivalence in technology interventions. Conference proposal accepted by American Educational Research Association.

  • Nasiar, N., Baker, R. S., Li, J., & Gong, W. (2022). How do A/B Testing and secondary data analysis on AIED systems influence future research? Paper accepted by AIED 2022.

In Preparation // 3

  • Smith, H., Damoah, K. (in preparation). Can Spatial Reasoning Predict Performance in an Online Geometry Assignment? [WPI] Worcester Polytechnic Institute

  • Closser, A. H., Sales, A., & Botelho, A. F. Should we account for classrooms? Analyzing online experimental data with student-level randomization. (Manuscript in preparation)

  • Smith, H., Ngo, V., Sales, A., Closser, A. H., Chan, J. Y. C., & Ottmar, E. R. To wait or not to wait: Adding to the debate on immediate vs. delayed feedback. (Manuscript in preparation)