@article{mitas_mitasova_millar_boode_neveu_hover_eijnden_bastiaansen_2022, title={More is Not Better: The Emotional Dynamics of an Excellent Experience}, volume={46}, ISSN={["1557-7554"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85091030484&partnerID=MN8TOARS}, DOI={10.1177/1096348020957075}, abstractNote={ Emotions embody the value in tourism experiences and drive essential outcomes such as intent to recommend. Current models do not explain how the ebb and flow of emotional arousal during an experience relate to outcomes, however. We analyzed 15 participants’ experiences at the Vincentre museum and guided village tour in Nuenen, the Netherlands. This Vincent van Gogh-themed experience led to a wide range of intent to recommend and emotional arousal, measured as continuous phasic skin conductance, across participants and exhibits. Mixed-effects analyses modeled emotional arousal as a function of proximity to exhibits and intent to recommend. Experiences with the best outcomes featured moments of both high and low emotional arousal, not one continuous “high,” with more emotion during the middle of the experience. Tourist experience models should account for a complex relationship between emotions experienced and outcomes such as intent to recommend. Simply put, more emotion is not always better. }, number={1}, journal={JOURNAL OF HOSPITALITY & TOURISM RESEARCH}, author={Mitas, Ondrej and Mitasova, Helena and Millar, Garrett and Boode, Wilco and Neveu, Vincent and Hover, Moniek and Eijnden, Frank and Bastiaansen, Marcel}, year={2022}, month={Jan}, pages={78–99} }
 @article{gaydos_jones_jones_millar_petras_petrasova_mitasova_meentemeyer_2021, title={Evaluating online and tangible interfaces for engaging stakeholders in forecasting and control of biological invasions}, volume={9}, ISSN={["1939-5582"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85115251448&partnerID=MN8TOARS}, DOI={10.1002/eap.2446}, abstractNote={Abstract}, number={8}, journal={ECOLOGICAL APPLICATIONS}, publisher={Wiley}, author={Gaydos, Devon A. and Jones, Chris M. and Jones, Shannon K. and Millar, Garrett C. and Petras, Vaclav and Petrasova, Anna and Mitasova, Helena and Meentemeyer, Ross K.}, year={2021}, month={Sep} }
 @article{millar_mitas_boode_hoeke_kruijf_petrasova_mitasova_2021, title={Space-time analytics of human physiology for urban planning}, volume={85}, ISBN={1873-7587}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85092914107&partnerID=MN8TOARS}, DOI={10.1016/j.compenvurbsys.2020.101554}, abstractNote={Recent advancements in mobile sensing and wearable technologies create new opportunities to improve our understanding of how people experience their environment. This understanding can inform urban design decisions. Currently, an important urban design issue is the adaptation of infrastructure to increasing cycle and e-bike use. Using data collected from 12 cyclists on a cycle highway between two municipalities in The Netherlands, we coupled location and wearable emotion data at a high spatiotemporal resolution to model and examine relationships between cyclists' emotional arousal (operationalized as skin conductance responses) and visual stimuli from the environment (operationalized as extent of visible land cover type). We specifically took a within-participants multilevel modeling approach to determine relationships between different types of viewable land cover area and emotional arousal, while controlling for speed, direction, distance to roads, and directional change. Surprisingly, our model suggests ride segments with views of larger natural, recreational, agricultural, and forested areas were more emotionally arousing for participants. Conversely, segments with views of larger developed areas were less arousing. The presented methodological framework, spatial-emotional analyses, and findings from multilevel modeling provide new opportunities for spatial, data-driven approaches to portable sensing and urban planning research. Furthermore, our findings have implications for design of infrastructure to optimize cycling experiences.}, journal={COMPUTERS ENVIRONMENT AND URBAN SYSTEMS}, author={Millar, Garrett C. and Mitas, Ondrej and Boode, Wilco and Hoeke, Lisette and Kruijf, Joost and Petrasova, Anna and Mitasova, Helena}, year={2021}, month={Jan} }
 @article{taub_azevedo_bradbury_millar_lester_2018, title={Using sequence mining to reveal the efficiency in scientific reasoning during STEM learning with a game-based learning environment}, volume={54}, ISSN={["0959-4752"]}, DOI={10.1016/j.learninstruc.2017.08.005}, abstractNote={The goal of this study was to assess how metacognitive monitoring and scientific reasoning impacted the efficiency of game completion during learning with Crystal Island, a game-based learning environment that fosters self-regulated learning and scientific reasoning by having participants solve the mystery of what illness impacted inhabitants of the island. We conducted sequential pattern mining and differential sequence mining on 64 undergraduate participants' hypothesis testing behavior. Patterns were coded based on the relevancy of what items were being tested for, and the items themselves. Results revealed that participants who were more efficient at solving the mystery tested significantly fewer partially-relevant and irrelevant items than less efficient participants. Additionally, more efficient participants had fewer sequences of testing items overall, and significantly lower instance support values of the PartiallyRelevant--Relevant to Relevant--Relevant and PartiallyRelevant--PartiallyRelevant to Relevant--Partially Relevant sequences compared to less efficient participants. These findings have implications for designing adaptive GBLEs that scaffold participants based on in-game behaviors.}, journal={LEARNING AND INSTRUCTION}, author={Taub, Michelle and Azevedo, Roger and Bradbury, Amanda E. and Millar, Garrett C. and Lester, James}, year={2018}, month={Apr}, pages={93–103} }
 @article{taub_mudrick_azevedo_millar_rowe_lester_2017, title={Using multi-channel data with multi-level modeling to assess in-game performance during gameplay with CRYSTAL ISLAND}, volume={76}, ISSN={["1873-7692"]}, DOI={10.1016/j.chb.2017.01.038}, abstractNote={Game-based learning environments (GBLEs) have been touted as the solution for failing educational outcomes. In this study, we address some of these major issues by using multi-level modeling with data from eye movements and log files to examine the cognitive and metacognitive self-regulatory processes used by 50 college students as they read books and completed the associated in-game assessments (concept matrices) while playing the Crystal Island game-based learning environment. Results revealed that participants who read fewer books in total, but read each of them more frequently, and who had low proportions of fixations on books and concept matrices exhibited the strongest performance. Results stress the importance of assessing quality vs. quantity during gameplay, such that it is important to read books in-depth (i.e., quality), compared to reading books once (i.e., quantity). Implications for these findings involve designing adaptive GBLEs that scaffold participants based on their trace data, such that we can model efficient behaviors that lead to successful performance.}, journal={COMPUTERS IN HUMAN BEHAVIOR}, author={Taub, Michelle and Mudrick, Nicholas V. and Azevedo, Roger and Millar, Garrett C. and Rowe, Jonathan and Lester, James}, year={2017}, month={Nov}, pages={641–655} }
 @article{azevedo_martin_taub_mudrick_millar_grafsgaard_2016, title={Are Pedagogical Agents' External Regulation Effective in Fostering Learning with Intelligent Tutoring Systems?}, volume={9684}, ISBN={["978-3-319-39582-1"]}, ISSN={["0302-9743"]}, DOI={10.1007/978-3-319-39583-8_19}, abstractNote={In this study we tested whether external regulation provided by artificial pedagogical agents (PAs) was effective in facilitating learners' self-regulated learning (SRL) and can therefore foster complex learning with a hypermedia-based intelligent tutoring system. One hundred twenty (N = 120) college students learned about the human circulatory system with MetaTutor during a 2-hour session under one of two conditions: adaptive scaffolding (AS) or a control (C) condition. The AS condition received timely prompts from four PAs to deploy various cognitive and metacognitive SRL processes, and received immediate directive feedback concerning the deployment of the processes. By contrast, the C condition learned without assistance from the PAs. Results indicated that those in the AS condition gained significantly more knowledge about the science topic than those in the C condition. In addition, log-file data provided evidence of the effectiveness of the PAs' scaffolding and feedback in facilitating learners' (in the AS condition) metacognitive monitoring and regulation during learning. We discuss implications for the design of external regulation by PAs necessary to accurately detect, track, model, and foster learners' SRL by providing more accurate and intelligent prompting, scaffolding, and feedback regarding SRL processes.}, journal={INTELLIGENT TUTORING SYSTEMS, ITS 2016}, author={Azevedo, Roger and Martin, Seth A. and Taub, Michelle and Mudrick, Nicholas V. and Millar, Garrett C. and Grafsgaard, Joseph F.}, year={2016}, pages={197–207} }
 @article{taub_mudrick_azevedo_millar_rowe_lester_2016, title={Using Multi-level Modeling with Eye-Tracking Data to Predict Metacognitive Monitoring and Self-regulated Learning with CRYSTAL ISLAND}, volume={9684}, ISBN={["978-3-319-39582-1"]}, ISSN={["0302-9743"]}, DOI={10.1007/978-3-319-39583-8_24}, abstractNote={Studies investigating the effectiveness of game-based learning environments (GBLEs) have reported the effectiveness of these environments on learning and retention. However, there is limited research on using eye-tracking data to investigate metacognitive monitoring with GBLEs. We report on a study that investigated how college students' eye tracking behavior (n = 25) predicted performance on embedded assessments within the Crystal Island GBLE. Results revealed that the number of books, proportion of fixations on book and article content, and proportion of fixations on concept matrices—embedded assessments associated with each in-game book and article—significantly predicted the number of concept matrix attempts. These findings suggest that participants strategized when reading book and article content and completing assessments, which led to better performance. Implications for designing adaptive GBLEs include adapting to individual student needs based on eye-tracking behavior in order to foster efficient completion of in-game embedded assessments.}, journal={INTELLIGENT TUTORING SYSTEMS, ITS 2016}, author={Taub, Michelle and Mudrick, Nicholas V. and Azevedo, Roger and Millar, Garrett C. and Rowe, Jonathan and Lester, James}, year={2016}, pages={240–246} }
 @inproceedings{taub_mudrick_azevedo_millar_rowe_lester, title={Using multi-level modeling with eye-tracking data to predict metacognitive monitoring and self-regulated learning with CRYSTAL ISLAND}, volume={0684}, booktitle={Intelligent tutoring systems, its 2016}, author={Taub, M. and Mudrick, N. V. and Azevedo, R. and Millar, G. C. and Rowe, J. and Lester, J.}, pages={240–246} }
 @inproceedings{taub_mudrick_azevedo_millar_rowe_lester, title={Using multi-level modeling with eye-tracking data to predict metacognitive monitoring and self-regulated learning with crystal island}, volume={9684}, booktitle={Intelligent tutoring systems, its 2016}, author={Taub, M. and Mudrick, N. V. and Azevedo, R. and Millar, G. C. and Rowe, J. and Lester, J.}, pages={240–246} }