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Jamie Hanson quoted in January 14 Pittsburgh Post-Gazette

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Julie Fiez quoted in January 30 Scientific American

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Female Students Self-efficacy in Physics

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CNBC Alumni Lecture

4:00 PM, 328 Mellon Institute, CMU

Krishnan Padmanabhan, Department of Neuroscience, University of Rochester School of Medicine, presents "Experimental and Computational Approaches for Studying Neural Circuits and Modeling Diseases."



CAMeL Presentation

10:00 AM, 4125 Sennott Square

Aidan Wright, Assistant Professor, Psychology, presents "Registering Research Studies: An Overview and Demonstration."



Spring Day of Healing

1:00 PM - 4:00 PM, LRDC 9th Floor

Come relax and de-stress before finals, courtesy of the GSR Committee! Includes counseling resources, meditation sessions, zen spaces, and a massage therapist.

More Talks

New Publications

  • Colvin, M., Warren, T., & Dickey, M. W. (2019). Event knowledge and verb knowledge predict sensitivity to different aspects of semantic anomalies in aphasia. In K. Carlson, C. Clifton, Jr., J. Fodor (Eds), Grammatical approaches to language processing (pp. 241-259). Studies in Theoretical Psycholinguistics, vol 48. Springer, Cham.
  • Gor, K., Chrabaszcz, A., and Cook, S. (2018). Early and late learners decompose inflected nouns, but can they tell which ones are inflected correctly? Journal of Second Language Studies, 1(1), 106-140. DOI: 10.1075/jsls.17021.gor
  • Lubold, N., Walker, E., Pon-Barry, H., Flores, Y., & Ogan, A. (2018). Using iterative design to create efficacy-building social experiences with a teachable robot. In Proceedings of the International Conference for the Learning Sciences (ICLS 2018). AR: 32%
  • Frens, J., Walker, E., & Hsieh, G. (2018). Supporting answerers with feedback in social Q&A. In Proceedings of the Fifth Annual ACM Conference on Learning at Scale (p. 10). ACM.
  • Lubold, N., Walker, E., Pon-Barry, H., & Ogan, A. (2018). Automated pitch convergence improves learning in a social, teachable robot for middle school mathematics. In International Conference on Artificial Intelligence in Education (pp. 282-296). Springer, Cham. AR: 25%
  • Walker, E., Wylie, R., Danielescu, A., Rodriguez III, J. P., & Finn, E. (2018). Balancing student needs and learning theory in a social interactive postdigital textbook. In End-User Considerations in Educational Technology Design (pp. 141-159). IGI Global.
  • Degol, J. L., Wang, M. T., Zhang, Y., & Allerton, J. (2018). Do growth mindsets in math benefit females? Identifying pathways between gender, mindset, and motivation. Journal of Youth and Adolescence, 47(5), 976-990.
  • Tokowicz, N. (2018). The critical roles of errors and individual differences in bilingual translation. Bilingualism: Language and Cognition, 21(4).
  • Meigh, K., Shaiman, S., Tompkins, C., Verdolini Abbott, K., & Nokes-Malach, T. (2018). What memory representation is acquired during nonword speech production learning? The influence of stimulus features and training modality on nonword encoding. Cogent Psychology, 5, 1-24.
  • James, A., Fraundorf, S., Lee, E., & Watson, D. (2018). Individual differences in syntactic processing: Is there evidence for reader-text interactions? Journal of Memory and Language, 102, 155-181.
  • Schunn, C. et al. (2018). Adaptability of the US Engineering and Technical Workforce: Proceedings of a Workshop. Washington, DC: The National Academies Press.
  • Kersey, A., Braham, E., Csumsitta, K., Libertus, M., & Cantlon, J. (2018). No intrinsic gender differences in children's earliest numerical abilities. Science of Learning, 3(12).
  • Luo, W., Liu, F., Liu, Z., & Litman, D. (2018). A novel ILP framework for summarizing content with high lexical variety. Natural Language Engineering, 1-32.
  • Helder, A., Perfetti, C. A., van den Broek, P., Stafura, J. Z., & Calloway, R. C. (2018). ERP indicators of local and global text influences on word-to-text integration. Language, Cognition and Neuroscience, 33(8).
  • Rahimi, Z., Litman, D., & Paletz, S. (2018). Acoustic-prosodic entrainment in multi-party spoken dialogues: Does simple averaging extend existing pair measures properly? Advanced Social Interaction with Agents: 8th International Workshop on Spoken Dialog Systems, 510, 169 – 177.
  • Song, K., & Cho, B-Y. (2018). Exploring bilingual adolescents' translanguaging strategies during online reading. International Journal of Bilingual Education and Bilingualism, 21(5).
  • Mandala, M., Schunn, C., Dow, S., Goldberg, M., & Pearlman, J. (2018). Uncovering the practices, challenges, and incentives for engineering design faculty. International Journal of Engineering Education, 34(4), 1314–1324.
  • Dorph, R., & Schunn, C. D. (2018). Positioning youth for persistent success in jewish learning and living. Activating jewish learners. (pp. 8-24). Retrieved from http://www.lrdc.pitt.edu/schunn/papers/DorphSchunn-JLA-2018.pdf
  • Coutanche, M. N. & Koch, G. E. (2018). Creatures great and small: Real-world size of animals predicts visual cortex representations beyond taxonomic category. NeuroImage, 183, 627-634.
  • Schneider, W. et al. (2018). A preliminary high-definition fiber tracking study of the executive control network in blast-induced traumatic brain injury. Journal of Neurotrauma.
  • Schneider, W. et al. (2018). Improvement in sleep disturbances after targeted intervention in chronic traumatic brain injury: A Team-TBI study. The 3rd Joint Symposium of the International and National Neurotrauma Societies and AANS/CNS Section on Neurotrauma and Critical Care. pp. A-80. Toronto, Canada.
  • Baikadi, A., Demmans Epp, C., & Schunn, C. (2018). Participating by activity or by week in MOOCs. Information and Learning Science.
  • Meuris, J. & Leana, C. (2018). The price of financial precarity: Organizational costs of employee financial concerns. Organization Science, 29(3), 398-417.
  • Leana, C., Meuris, J. & Lamberton, C. (2018). More than a feeling: The role of empathetic care in promoting patient safety and worker attachment in healthcare. Industrial and Labor Relations Review, 71(2), 394-425.
  • Stiehl, E., Kossek & Leana, C. (2018). A multi-level model of care flow: Examining the generation and spread of care in organizations. Organizational Psychology Review, 8(1), 31-69.