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Measuring Learners' Co-Occurring Emotional Responses during Their Interaction with a Pedagogical Agent in MetaTutor [chapter]

Jason M. Harley, François Bouchet, Roger Azevedo
2012 Lecture Notes in Computer Science  
This analysis focuses on the sub goal setting task of learners' (N = 50) interaction with MetaTutor, during which a pedagogical agent assisted students to set three relevant sub goals for their learning  ...  This paper extends upon traditional emotional measurement frameworks used by ITSs in which emotions are analyzed as single, discrete psychological experiences by examining co-occurring emotions (COEs)  ...  We would like to thank Reza Feyzi-Behnagh, Melissa Duffy, Gregory Trevors, Melissa Stern, Amy Johnson, Amber Chauncey, Candice Burkett, Ashley Fike, Ronald Landis and Jonathan Burlison for their help with  ... 
doi:10.1007/978-3-642-30950-2_5 fatcat:wu2tj7vmvrbe3mzxmi2syrgab4

Multiple Negative Emotions During Learning With Digital Learning Environments – Evidence on Their Detrimental Effect on Learning From Two Methodological Approaches

Franz Wortha, Roger Azevedo, Michelle Taub, Susanne Narciss
2019 Frontiers in Psychology  
The present study investigated the importance of multiple, co-occurring emotions during learning about human biology with MetaTutor, a hypermedia-based tutoring system.  ...  These results reveal the importance of negative emotions during learning with MetaTutor.  ...  ACKNOWLEDGMENTS The authors would like to thank the members of the SMART Lab at UCF for their assistance and contributions.  ... 
doi:10.3389/fpsyg.2019.02678 pmid:31849780 pmcid:PMC6901792 fatcat:jfsjsekslvhejh5z7twrg7l6ie

AutoTutor and Family: A Review of 17 Years of Natural Language Tutoring

Benjamin D. Nye, Arthur C. Graesser, Xiangen Hu
2014 International Journal of Artificial Intelligence in Education  
The paper also considers advances in pedagogical agent roles (such as trialogs) and in tutoring technologies, such semantic processing and tutoring delivery platforms.  ...  Next, we review three central themes in AutoTutor's development: human-inspired tutoring strategies, pedagogical agents, and technologies that support natural-language tutoring.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of these funding sources.  ... 
doi:10.1007/s40593-014-0029-5 fatcat:4ykacwg665dzlgrtgmwq3kb3ua

Reflection-in-action markers for reflection-on-action in Computer-Supported Collaborative Learning settings

Élise Lavoué, Gaëlle Molinari, Yannick Prié, Safè Khezami
2015 Computers & Education  
We describe an exploratory study on the use of markers set during a synchronous collaborative interaction (reflection-in-action) for later construction of reflection reports upon the collaboration that  ...  to reflect on action, with an increase in the use of their partners' markers in the second reflection reports; (5) reflected mainly on their partner in the first reflection reports and more on themselves  ...  The MetaTutor platform (Azevedo, Witherspoon, Chauncey, Burkett, & Fike, 2009; Azevedo et al., 2012) offers an adaptive scaffolding and feedback provided by a human tutor or a pedagogical agent that  ... 
doi:10.1016/j.compedu.2015.05.001 fatcat:abz55niepzgq3ffdlcpy2oy5qq

Reflection-in-Action Markers for Reflection-on-Action in Computer-Supported Collaborative Learning Settings [article]

Élise Lavoué, Gaëlle Molinari, Yannick Prié, Safè Khezami
2015 arXiv   pre-print
We describe an exploratory study on the use of markers set during a synchronous collaborative interaction (reflection-in-action) for later construction of reflection reports upon the collaboration that  ...  to reflect on action, with an increase in the use of their partners's markers in the second reflection reports; (5) reflected mainly on their partner in the first reflection reports and more on themselves  ...  The MetaTutor platform (Azevedo, Witherspoon, Chauncey, Burkett, & Fike, 2009; Azevedo et al., 2012) offers an adaptive scaffolding and feedback provided by a human tutor or a pedagogical agent that  ... 
arXiv:1505.04609v1 fatcat:o6lxxeldsfe67fpactx5rjpxii

Advances in the Science of Assessment

Valerie J. Shute, Jacqueline P. Leighton, Eunice E. Jang, Man-Wai Chu
2016 Educational Assessment  
In the second section, we present a new feature of this landscape, technologically rich environments (TREs; see Bennett, Persky, Weiss, & Jenkins, 2007) and the pedagogical opportunities they afford for  ...  In this article, we consider how achievement testing and the science of assessing learning are progressing with advances in technology.  ...  This agent was tasked with gathering learner affective information-from sensors measuring learners' eyebrow position, skin conductance, and heart rate-during gameplay.  ... 
doi:10.1080/10627197.2015.1127752 fatcat:q7a3hs553fgczoo6ltbqxfvj5e

Affective learning: improving engagement and enhancing learning with affect-aware feedback

Beate Grawemeyer, Manolis Mavrikis, Wayne Holmes, Sergio Gutiérrez-Santos, Michael Wiedmann, Nikol Rummel
2017 User modeling and user-adapted interaction  
Two Bayesian networks trained with data gathered in a series of Wizard-of-Oz studies are used for the adaptation process.  ...  A core objective of the learner model is to adapt formative feedback based on students' affective states.  ...  Thanks to all our iTalk2Learn colleagues for their support and ideas.  ... 
doi:10.1007/s11257-017-9188-z fatcat:4eacmcwygbhfxcjgxt73n5jrc4

ElectronixTutor: an intelligent tutoring system with multiple learning resources for electronics

Arthur C. Graesser, Xiangen Hu, Benjamin D. Nye, Kurt VanLehn, Rohit Kumar, Cristina Heffernan, Neil Heffernan, Beverly Woolf, Andrew M. Olney, Vasile Rus, Frank Andrasik, Philip Pavlik (+13 others)
2018 International Journal of STEM Education  
There is a recommender system that uses the student model to guide the student on a small set of sensible next steps in their training.  ...  After the teams shared their progress at the conclusion of an 18-month period, the ONR decided to fund a joint applied project in the Navy that integrated those systems on the subject matter of electronic  ...  They can guide the interaction with the learner, instruct the learner what to do, and interact with other agents to model ideal behavior, strategies, reflections, and social interactions (Craig et al.  ... 
doi:10.1186/s40594-018-0110-y pmid:30631705 pmcid:PMC6310412 fatcat:blfi7pb7gzd4rleo4biqj2u2ea

A Framework for Facilitating Self-Regulation in Responsive Open Learning Environments [article]

Alexander Nussbaumer, Ralf Klamma Knowledge Technologies Institute, Graz University of Technology, Austria, ACIS Group, Informatik 5, RWTH Aachen University, Germany, Department of Psychology, University of Graz, Austria)
2014 arXiv   pre-print
With such a complex setting we are coming close to the realisation of Responsive Open Learning Environments (ROLE).  ...  On that basis we have implemented a system with a learner model, SRL widgets, monitoring and analytic tools, as well as recommendation functionalities.  ...  Habits can be defined as "response dispositions that are activated automatically by the context cues that co-occurred with responses during past performance" (Neal et al., 2006) .  ... 
arXiv:1407.5891v1 fatcat:xoj3khvl2vfhdasybk4nbztpfa

Towards Integration of Cognitive Models in Dialogue Management: Designing the Virtual Negotiation Coach Application

Andrei Malchanau, Volha Petukhova, Harry Bunt
2019 Dialogue and Discourse  
Artificial intelligent agents, based on the ACT-R cognitive architecture, together with human actors are participating in a (meta)cognitive skills training within a negotiation scenario.  ...  interaction pace.  ...  People with welldeveloped metacognitive skills are more concerned that their interactions will go well, and are able to flexibly modify their actions during interaction in order to better adapt to the  ... 
doi:10.5087/dad.2018.202 fatcat:fb5j4vzpprgtxicecntye6aqdq

Modeling Student Affective State Patterns during Self-Regulated Learning in Physics Playground

Shiming Kai
2019
Since the video data is a direct measure of student emotions, it shows better performance across most affective states.  ...  Findings from Study 1 demonstrate that both video data and interaction log data can be used to predict student affective states with significant accuracy.  ...  Instead of the four pedagogical agents present in the MetaTutor, however, Betty's Brain program consisted of two: a mentor agent Mr. Davis, as well as a teachable agent named Betty.  ... 
doi:10.7916/d8-z5be-xm41 fatcat:xinzfskwgnbchjuhoiqg7oymqu

Learning About Queer History with a Multimedia Mobile App: The Role of Emotions

Byunghoon Ahn
2019
This thesis investigated what emotions were generated as learners interacted with a multimedia mobile app to learn about queer history in a North American city: Edmonton.  ...  Learners that expressed anger as their dominant emotion, had the highest learning performance; one that was statistically significantly different from learners with a sad dominant emotion profile.  ...  Specifically, they recorded learner activities such as typing out notes, or the interaction with the pedagogical agent to assess learners' learning strategies (taking notes and summarizing), judgments  ... 
doi:10.7939/r3-jv6j-p739 fatcat:kbww5fyhqjcprcq4pqjgekvugu

Cognitive architecture of multimodal multidimensional dialogue management [article]

Andrei Malchanau, Universität Des Saarlandes, Universität Des Saarlandes
2019
This challenges the dialogue system designs based on a reactive interlocutor paradigm and calls for dialog systems that can be characterised as a proactive learner, accomplished multitasking planner and  ...  Cognitive Task Agents, producing detailed simulation of human learning, prediction, adaption and decision making, are integrated in the multi-agent Dialogue Manager.  ...  It was very inspiring and constructive collaboration which contributed to this thesis the most, thanks to their support in cognitive modelling tasks.  ... 
doi:10.22028/d291-27856 fatcat:wehwbyc5jvaftnpjceul4gela4