Publications
Here are the most recent publications of the faculty associated with LIVE that reflect the core ideas behind our work.
Gautam Biswas
Xue, X., Shiwei, X., Mishra, S., Wright, A. M., Biswas, G., & Levin, D. T. (in press). A case study of prevalence and causes of eye tracking data loss in a middle school classroom. Educational Technology and Research Development. https://doi.org/10.1007/s11423-022-10154-4
Zhang, N., Biswas, G., & Hutchins, N. (2021). Measuring and Analyzing Students’ Strategic Learning Behaviors in Open-Ended Learning Environments. International Journal of Artificial Intelligence in Education, 32, 931-970. https://doi.org/10.1007/s40593-021-00275-x
McLoughlin, B., Bhandari, S., Henrick, E., Hotchkiss, E., Jha, M., Jiang, S., Kern, E., Marston, L., Vanags, C., Snyder, C., Naseri, M. Y., Aryal, N., Biswas, G., Dubey, A., Xia, K., & Lohani, V. (2022, June). A modular approach for integrating data science concepts into multiple undergraduate STEM+ C courses. In 2022 American Society Engineering Education Annual Meeting.
Cloude, E. B., Azevedo, R., Winne, P. H., Biswas, G., & Jang, E. E. (2022). System design for using multimodal trace data in modeling self-regulated learning. Frontiers in Education, 7, 928632. https://doi.org/10.3389/feduc.2022.928632
Zhang, Y., Paquette, L., Baker, R. S., Bosch, N., Ocumpaugh, J., & Biswas, G. (2022). How are feelings of difficulty and familiarity linked to learning behaviors and gains in a complex science learning task? European Journal of Psychology of Education, 1-24. https://doi.org/10.1007/s10212-022-00616-x
Zhang, Y., Paquette, L., Bosch, N., Ocumpaugh, J., Biswas, G., Hutt, S., & Baker, R. S. (2022). The evolution of metacognitive strategy use in an open-ended learning environment: Do prior domain knowledge and motivation play a role? Contemporary Educational Psychology, 69, 102064. https://doi.org/10.1016/j.cedpsych.2022.102064
Kong, S. C., Ogata, H., Shih, J. L., & Biswas, G. (2021, November). The role of Artificial Intelligence in STEM education. In Proceedings of 29th International Conference on Computers in Education Conference.
Corey Brady
Brady, C., & Jung, H. (2022). Modeling presentations: Towards an assessment of emerging classroom cultures of modeling. Educational Studies in Mathematics, 109, 237-261. https://doi.org/10.1007/s10649-021-10056-x
Pierson, A., Clark, D., & Brady, C. (2021). Scientific modeling and translanguaging: A multilingual and multimodal approach to support productive science discourse. Science Education, 105(4), 776-813. https://doi.org/10.1002/sce.21622
Brady, C. (2021). Patches as an Expressive Medium for Exploratory Agent-Based Modelling. British Journal of Education Technology, 52(3), 1024-1042. https://doi.org/10.1111/bjet.13087
Brady, C., & Lehrer, R. (2021). Sweeping Area across Physical and Virtual
Environments. Digital Experiences in Mathematics Education, 7(1), 66-98. https://doi.org/10.1007/s40751-020-00076-2
Hjorth, A., Head, B., Brady, C., & Wilensky, U. (2020). LevelSpace: A NetLogo
Extension for Multi-Level Agent-Based Modeling. Journal of Artificial Societies and Social Simulation, 23(1), 1-4. https://doi.org/10.18564/jasss.4130
Pierson, A., & Brady, C. (2020). Expanding Opportunities for Systems Thinking,
Conceptual Learning, and Participation through Embodied and Computational
Modeling. Systems, 8(4), 48. https://doi.org/10.3390/systems8040048
Pierson, A. E., Brady, C. E., & Clark, D. B. (2020). Balancing the environment:
Computational models as interactive participants in a STEM classroom. Journal of Science Education and Technology, 29(1), 101-119. https://doi.org/10.1007/s10956-019-09797-5
Brian Broll
Brady, C., Broll, B., Stein, G., Jean, D., Grover, S., Cateté, V., Barnes, T., & Lédeczi, Á. (2022). Block-based abstractions and expansive services to make advanced computing concepts accessible to novices. Journal of Computer Languages, 73, 101156. https://doi.org/10.1016/j.cola.2022.101156
Jean, D., Broll, B., Stein, G., & Lédeczi, Á. (2021, October). Your Phone as a Sensor: Making IoT Accessible for Novice Programmers. In 2021 IEEE Frontiers in Education Conference (FIE) (pp. 1-5). IEEE. https://doi.org/10.1109/FIE49875.2021.9637272
Broll, B., Timalsina, U., Völgyesi, P., Budavári, T., Lédeczi, Á., & Acacio Sanchez, M. E. (2020). A machine learning gateway for scientific workflow design. Scientific Programming, 2020, 1-15. https://doi.org/10.1155/2020/8867380
Scott Crossley
Crossley, S., & Holmes, L. (in press). Assessing receptive vocabulary using state‑of‑the‑art natural language processing techniques. Journal of Second Language Studies. https://doi.org/10.1075/jsls.22006.cro
Tighe, E. L., Kaldes, G., Talwar, A., Crossley, S. A., Greenberg, D., & Skalicky, S. (2023). Do Struggling Adult Readers Monitor Their Reading? Understanding the Role of Online and Offline Comprehension Monitoring Processes During Reading. Journal of Learning Disabilities, 56(1), 25-42. https://doi.org/10.1177/00222194221081473
Botarleanu, R. M., Dascalu, M., Watanabe, M., Crossley, S. A., & McNamara, D. S. (2022). Age of Exposure 2.0: Estimating word complexity using iterative models of word embeddings. Behavior Research Methods, 54, 3015-3042. https://doi.org/10.3758/s13428-022-01797-5
Brown, W., Balyan, R., Karter, A. J., Crossley, S. A., Wagahta, S., Duran, D., Lyles, C., Liu, J., Moffet, H., Daniels, R., McNamara, D. S., & Schillinger, D (2021). Challenges and Solutions to Employing Natural Language Processing and Machine Learning to Measure Patients’ Health Literacy and Physician Writing Complexity: The ECLIPPSE Study. Journal of Biomedical Informatics, 113, 103658. https://doi.org/10.1016/j.jbi.2020.103658
Crossley, S. A., Karumbaiah, S., Ocumpaugh, J., Labrum, M. J., & Baker, R. S. (2020). Predicting math identity through language and click-stream patterns in a blended learning mathematics program for elementary students. Journal of Learning Analytics, 7(1), 19-37. http://doi.org/10.18608/jla.2020.71.3
Corbette Doyle
Cannon, M., & Doyle, C. (2020). Challenges to Advancing Evidence-Based Management in Organizations: Lessons From Moneyball. Management Teaching Review, 5(4), 363-373. https://doi.org/10.1177/2379298120924371
Noel Enyedy
Pierson, A. E., Keifert, D. T., Lee, S. J., Henrie, A., Johnson, H. J., & Enyedy, N. (2022). Multiple Representations in Elementary Science: Building Shared Understanding while Leveraging Students’ Diverse Ideas and Practices. Journal of Science Teacher Education, 1-25. https://doi.org/10.1080/1046560X.2022.2143612
Tu, X., Georgen, C., Danish, J. A., & Enyedy, N. (2021). Elementary students learning science in an MR environment by constructing liminal blends through action on props. Information and Learning Sciences, 122(7/8), 525-545. https://doi.org/10.1108/ILS-10-2020-0235
DeLiema, D., Enyedy, N., Steen, F., & Danish, J. A. (2021). Integrating viewpoint and space: How lamination across gesture, body movement, language, and material resources shapes learning. Cognition and Instruction, 39(3), 328-365. https://doi.org/10.1080/07370008.2021.1928133
Keifert, D., Lee, C., Enyedy, N., Dahn, M., Lindberg, L., & Danish, J. (2020). Tracing bodies through liminal blends in a mixed reality learning environment. International Journal of Science Education, 42(18), 3093-3115. https://doi.org/10.1080/09500693.2020.1851423
Amanda Goodwin
Goodwin, A. P., Petscher, Y., & Reynolds, D. (2022). Unraveling Adolescent Language & Reading Comprehension: The Monster’s Data. Scientific Studies of Reading, 26(4), 305-326. https://doi.org/10.1080/10888438.2021.1989437
Goodwin, A. P., Petscher, Y., & Tock, J. (2021). Multidimensional morphological assessment for middle school students. Journal of Research in Reading, 44(1), 70-89. https://doi-org.proxy.library.vanderbilt.edu/10.1111/1467-9817.12335
Goodwin, A. P., Cho, S. J., Reynolds, D., Brady, K., & Salas, J. (2020). Digital versus paper reading processes and links to comprehension for middle school students. American Educational Research Journal, 57(4), 1837-1867. https://doi.org/10.3102/0002831219890300
Goodwin, A. P., Petscher, Y., Jones, S., McFadden, S., Reynolds, D., & Lantos, T. (2020). The monster in the classroom: Assessing language to inform instruction. The Reading Teacher, 73(5), 603-616. https://doi.org/10.1002/trtr.1870
Maithilee Kunda
Rashedi, R. N., Bonnet, K., Schulte, R. J., Schlundt, D. G., Swanson, A. R., Kinsman, A., Bardett, N., Juárez, P., Warren, Z. E., Biswas, G., & Kunda, M. (2022). Opportunities and Challenges in Developing Technology-Based Social Skills Interventions for Adolescents with Autism Spectrum Disorder: A Qualitative Analysis of Parent Perspectives. Journal of Autism and Developmental Disorders, 52(10), 4321-4336. https://doi.org/10.1007/s10803-021-05315-y
Yang, Y., McGreggor, K., & Kunda, M. (2022). Visual-Imagery-Based Analogical Construction in Geometric Matrix Reasoning Task. arXiv preprint arXiv:2208.13841. https://doi.org/10.48550/arXiv.2208.13841
Yang, Y., Sanyal, D., Michelson, J., Ainooson, J., & Kunda, M. (2022). An End-to-End Imagery-Based Modeling of Solving Geometric Analogy Problems. In Proceedings of the Annual Meeting of the Cognitive Science Society (Vol. 44, No. 44).
Yang, Y., Li, K., Eliott, F., & Kunda, M. (2021). Do Time Constraints Re-Prioritize Attention to Shapes During Visual Photo Inspection? arXiv preprint arXiv:2104.06984. https://doi.org/10.48550/arXiv.2104.06984
Akos Ledeczi
Tan, Y., Rizk, M., Stein, G., & Lédeczi, Á. (2022, March). User-Extensible Block-Based Interfaces for Internet of Things Devices as New Educational Tools. In SoutheastCon 2022 (pp. 711-717). IEEE. https://doi.org/10.1109/SoutheastCon48659.2022.9763937
Stein, G., & Lédeczi, Á. (2022, March). Shared Virtual Worlds for Accessible Classroom Robotics. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2 (pp. 1177-1177). https://doi.org/10.1145/3478432.3499259
Alvarez, L., Gransbury, I., Cateté, V., Barnes, T., Ledéczi, Á., & Grover, S. (2022). A Socially Relevant Focused AI Curriculum Designed for Female High School Students. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12698-12705. https://doi.org/10.1609/aaai.v36i11.21546
Stein, G., & Lédeczi, A. (2021, October). Enabling Collaborative Distance Robotics Education for Novice Programmers. In 2021 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) (pp. 1-5). IEEE. https://doi.org/10.1109/VL/HCC51201.2021.9576314
Hutchins, N. M., Biswas, G., Zhang, N., Snyder, C., Lédeczi, Á., & Maróti, M. (2020). Domain-specific modeling languages in computer-based learning environments: A systematic approach to support science learning through computational modeling. International Journal of Artificial Intelligence in Education, 30(4), 537-580. https://doi.org/10.1007/s40593-020-00209-z
Dan Levin
Xue, X., Shiwei, X., Mishra, S., Wright, A. M., Biswas, G., & Levin, D. T. (in press). A case study of prevalence and causes of eye tracking data loss in a middle school classroom. Educational Technology and Research Development. https://doi.org/10.1007/s11423-022-10154-4
Wright, A. M., Carter, K. E., Bibyk, S. A., Jaeger, C. B., Watson, D. G., & Levin, D. T. (in press). Video speeding can be efficient and learner preference can be improved by selective speeding. Journal of Experimental Psychology: Applied. https://doi.org/10.1037/xap0000290
Levin, D. T., Baker, L. J., Wright, A. M., & Jaeger, C. B. (in press). Perceiving vs. Scrutinizing: Viewers do not default to awareness of small spatiotemporal inconsistencies in movie edits, Psychology of Aesthetics, Creativity, and the Arts. https://doi.org/10.1037/aca0000462
Wright, A. M., Salas, J. A., Carter, K. E., & Levin, D. T. (2022). Eye Movement Modeling Examples guide viewer eye movements but do not improve learning, Learning and Instruction, 79, 101601. https://doi.org/10.1016/j.learninstruc.2022.101601
Jaeger, C. B., Little, J. W., & Levin, D. T. (2021). The prevalence and utility of formal features in YouTube screen-capture instructional videos. Technical Communication, 68(1), 56-72.
Levin, D. T., Salas, J. A., Wright, A. M., Seiffert, A. E., Carter, K. E., & Little, J. W. (2021). The incomplete tyranny of dynamic stimuli: Gaze similarity predicts response similarity in screen-captured instructional videos. Cognitive Science, 45(6), e12984. https://dio.org/10.1111/cogs.12984
Levin, D. T., Biswas, G., Lappin, J. S., Rushdy, M., & Seiffert, A. E. (2019). Optimistic metacognitive judgments predict poor performance in relatively complex visual tasks. Consciousness and Cognition, 74, 102781. https://doi.org/10.1016/j.concog.2019.102781
Jaeger, C. B., Hymel, A. M., Levin, D. T., Biswas, G., Paul, N., & Kinnebrew, J. (2019). The interrelationship between concepts about agency and students’ use of teachable-agent learning technology. Cognitive Research: Principles and Implications, 4(14). https://doi.org/10.1186/s41235-019-0163-6
Ole Molvig
Molvig, O., & Bodenheimer, B. (2020). Interdisciplinarity and Teamwork in Virtual Reality Design. The Journal of Interactive Technology and Pedagogy, 18.
Choi, K., Crumb, G., Li, R., Natarrajan, R., Tong, P., Molvig, O., & Bodenheimer, B. (2022, March). Experience Orchestra: Manipulating Musical Instruments in VR. In 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) (pp. 918-919). IEEE. https://doi.org/10.1109/VRW55335.2022.00310
Cristina Zepeda
Wang, M. T., Zepeda, C. D., Qin, X., Del Toro, J., & Binning, K. R. (2021). More than growth mindset: Individual and interactive links among socioeconomically disadvantage adolescents’ ability mindsets, metacognitive skills, and math engagement. Child Development 92, e957-e976. https://doi.org/10.1111/cdev.13560
Zepeda, C. D., & Nokes-Malach, T. J. (2021). Metacognitive study strategies in a college course and their relation to exam performance. Memory & Cognition. 49, 480-497. https://doi.org/10.3758/s13421-020-01106-5
Zepeda, C. D., Martin, R. S., & Butler, A. C. (2020). Motivational strategies to engage learners in desirable difficulties. Journal of Applied Research in Memory and Cognition, 9(4), 464-470. https://doi.org/10.1016/j.jarmac.2020.08.007
Boden, K. K., Zepeda, C. D., & Nokes-Malach, T. J. (2020). Achievement goals and conceptual learning: An examination of teacher talk. Journal of Educational Psychology, 12(6), 1221-1242. https://doi.org/10.1037/edu0000421
Zepeda, C. D., Hlutkowsky, C. O., Partika, A. C., & Nokes-Malach, T. J. (2019). Identifying teachers’ supports of metacognition through classroom talk and its relation to growth in conceptual learning. Journal of Educational Psychology, 111(3), 522-541. http://doi.org/10.1037/edu0000300
Zepeda, C. D., Richey, J. E., Ronevich, P., & Nokes-Malach, T. J. (2015). Direct instruction of metacognition benefits adolescent science learning, transfer, and motivation: An in-vivo study. Journal of Educational Psychology, 107(4), 954-970. http://doi.org/10.1037/edu0000022