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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  ...  Results indicated that neutral and sadness were the SDEs experienced most by students and also the most represented emotions in COE pairs.  ...  data collection.  ... 
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  
Emotions are a core factor of learning. Studies have shown that multiple emotions are co-experienced during learning and have a significant impact on learning outcomes.  ...  These results reveal the importance of negative emotions during learning with MetaTutor.  ...  FUNDING This study was supported by funding from the National Science Foundation (DRL#1660878, DRL#1661202, DUE#1761178, and DRL#1916417) and the Social Sciences and Humanities Research Council of Canada  ... 
doi:10.3389/fpsyg.2019.02678 pmid:31849780 pmcid:PMC6901792 fatcat:jfsjsekslvhejh5z7twrg7l6ie

Hipatia: a hypermedia learning environment in mathematics

Marisol Cueli, Paloma González-Castro, Jennifer Krawec, José C. Núñez, Julio A. González-Pienda
2015 Anales de Psicología  
It was targeted toward fifth and sixth grade students with and without learning difficulties in mathematics.  ...  After the development of the tool, we concluded that it aligned well with the logic underlying the principles of self-regulated learning.  ...  -This work is funded by the I+D+i project with reference EDU2010-19798, and the support of a grant from the Ministry of Science and Innovation (BES-2011-045582).  ... 
doi:10.6018/analesps.32.1.185641 fatcat:y2cjj3glufej7m65kl26sjkoeu

Discovering Behavior Patterns of Self-Regulated Learners in an Inquiry-Based Learning Environment [chapter]

Jennifer Sabourin, Bradford Mott, James Lester
2013 Lecture Notes in Computer Science  
Inquiry-based learning has been proposed as a natural and authentic way for students to engage with science.  ...  Inquiry-based learning environments typically require students to guide their own learning and inquiry processes as they gather data, make and test hypotheses and draw conclusions.  ...  and SDK.  ... 
doi:10.1007/978-3-642-39112-5_22 fatcat:tu4pww5445ejpdwbydmpq2s67a

Learning, thinking, and emoting with discourse technologies

Arthur C. Graesser
2011 American Psychologist  
AutoTutor and other systems with conversational agents (i.e., talking heads) help students learn by holding conversations in natural language.  ...  The technologies developed from this interdisciplinary fusion are helping students learn and think in ways that are sensitive to their cognitive and emotional states.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of these funding sources.  ... 
doi:10.1037/a0024974 pmid:22082403 fatcat:m6ksnptbonbfdpzvjpkedfjuiy

Data mining and education

Kenneth R. Koedinger, Sidney D'Mello, Elizabeth A. McLaughlin, Zachary A. Pardos, Carolyn P. Rosé
2015 Wiley Interdisciplinary Reviews: Cognitive Science  
and metacognition on learning, and analysis of language data and collaborative learning.  ...  We review how EDM has addressed the research questions that surround the psychology of learning with an emphasis on assessment, transfer of learning and model discovery, the role of affect, motivation  ...  and argument, and socio-emotional dispositions and strategies.  ... 
doi:10.1002/wcs.1350 pmid:26263424 fatcat:3olx4w3borhnlfptqksutuqyqa

Advances in the Science of Assessment

Valerie J. Shute, Jacqueline P. Leighton, Eunice E. Jang, Man-Wai Chu
2016 Educational Assessment  
acquisition) and noncognitive (e.g., dispositional and emotional) attributes, at one  ...  In this article, we consider how achievement testing and the science of assessing learning are progressing with advances in technology.  ...  data associated with public and internal assessments.  ... 
doi:10.1080/10627197.2015.1127752 fatcat:q7a3hs553fgczoo6ltbqxfvj5e

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  
on the knowledge components as well as a set of cognitive and non-cognitive attributes.  ...  The architecture includes a student model that has (a) a common set of knowledge components on electronic circuits to which individual learning resources contribute and (b) a record of student performance  ...  Empirical evidence supports the claim that AutoTutor and similar computer tutors with natural language dialog yield learning gains comparable to trained human tutors on STEM subject matters, with effect  ... 
doi:10.1186/s40594-018-0110-y pmid:30631705 pmcid:PMC6310412 fatcat:blfi7pb7gzd4rleo4biqj2u2ea

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

Byunghoon Ahn
Other emotions lead to mixed results, but emotions such as anger, on average, show loss in learning performance.  ...  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.  ...  Results also revealed that while participants experiencing positive emotion reported highest appraisals of task value and control, they had lower learning performance compared to learners with low emotions  ... 
doi:10.7939/r3-jv6j-p739 fatcat:kbww5fyhqjcprcq4pqjgekvugu

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

Shiming Kai
Findings from Study 1 demonstrate that both video data and interaction log data can be used to predict student affective states with significant accuracy.  ...  This dissertation research focuses on investigating the incidence of student self-regulated learning behavior, and examines patterns in student affective states that accompany such self-regulated behavior  ...  With the recent advancements in technology-based learning systems, native tools are now available to assess students' emotions and affective states during learning.  ... 
doi:10.7916/d8-z5be-xm41 fatcat:xinzfskwgnbchjuhoiqg7oymqu

Cognitive architecture of multimodal multidimensional dialogue management [article]

Andrei Malchanau, Universität Des Saarlandes, Universität Des Saarlandes
The manager operates on the multidimensional information state enriched with representations based on domain-and modality-specific semantics and performs context-driven dialogue acts interpretation and  ...  This work utilises recent advances in Instance-Based Learning of Theory of Mind skills and the established Cognitive Task Analysis and ACT-R models.  ...  My thanks go to the members of the Metalogue consortium: Jan Alexandersson, the whole DFKI coordinating and research team, Nick Campbell and Saturnino Luz (Trinity College Dublin), Alexander Stricker and  ... 
doi:10.22028/d291-27856 fatcat:wehwbyc5jvaftnpjceul4gela4

Supporting Learner-Controlled Problem Selection in Intelligent Tutoring Systems

Yanjin Long
Research has shown that appropriate problem selection that fit with students' knowledge level will lead to effective and efficient learning.  ...  However, it is an open question whether ITS can be designed to support students' learning of problem selection skills that will have lasting effects on their problem selection decisions and future learning  ...  Furthermore, I looked at process measures from the tutor log data to compare how the two conditions performed during the learning process in the tutor.  ... 
doi:10.1184/r1/6723413 fatcat:ltqdrgql3felzi6xrc7kvzcwpu