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Original Articles

Some insights into the impact of affective information when delivering feedback to students

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Pages 1252-1263 | Received 20 Jun 2017, Accepted 24 Jun 2018, Published online: 26 Jul 2018

References

  • Ainley, Mary. 2006. “Connecting with Learning: Motivation, Affect and Cognition in Interest Processes.” Educational Psychology Review 18 (4): 391–405. doi: 10.1007/s10648-006-9033-0
  • Arevalillo-Herráez, Miguel, David Arnau, Francesc J. Ferri, and Olga C. Santos. 2017a. “Gui-driven Intelligent Tutoring System with Affective Support to Help Learning the Algebraic Method.” IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017, Banff, AB, Canada, October 5–8, 2017, 2867–2872. https://doi.org/10.1109/SMC.2017.8123062.
  • Arevalillo-Herráez, M., D. Arnau, and L. Marco-Giménez. 2013. “Domain-specific Knowledge Representation and Inference Engine for an Intelligent Tutoring System.” Knowledge-Based Systems 49: 97–105. doi: 10.1016/j.knosys.2013.04.017
  • Arevalillo-Herráez, Miguel, Luis Marco-Giménez, David Arnau, and José Antonio González-Calero. 2017b. “Adding Sensor-free Intention-based Affective Support to an Intelligent Tutoring System.” Knowledge-Based Systems 132: 85–93. https://doi.org/10.1016/j.knosys.2017.06.024.
  • Arnau, David, Miguel Arevalillo-Herráez, Luis Puig, and José Antonio González-Calero. 2013. “Fundamentals of the Design and the Operation of an Intelligent Tutoring System for the Learning of the Arithmetical and Algebraic Way of Solving Word Problems.” Computers & Education 63: 119–130. https://doi.org/10.1016/j.compedu.2012.11.020.
  • Arroyo, Ivon, Beverly Park Woolf, Winslow Burelson, Kasia Muldner, Dovan Rai, and Minghui Tai. 2014. “A Multimedia Adaptive Tutoring System for Mathematics that Addresses Cognition, Metacognition and Affect.” International Journal of Artificial Intelligence in Education 24 (4): 387–426. doi: 10.1007/s40593-014-0023-y
  • Boud, David, and Elizabeth Molloy. 2013. “Rethinking Models of Feedback for Learning: The Challenge of Design.” Assessment & Evaluation in Higher Education 38 (6): 698–712. http://dx.doi.org/10.1080/02602938.2012.691462.
  • Bradley, M., and P. J. Lang. 1994. "Measuring Emotion: The Self-assessment Manikin and the Semantic Differential." Journal of Behavior Therapy and Experimental Psychiatry 25: 49–59. doi: 10.1016/0005-7916(94)90063-9
  • Chanel, Guillaume, Cyril Rebetez, Mireille Bétrancourt, and Thierry Pun. 2008. “Boredom, Engagement and Anxiety as Indicators for Adaptation to Difficulty in Games.” Proceedings of the 12th International Conference on Entertainment and media in the ubiquitous era, Tampere, Finland, 13–17. ACM.
  • Cramp, Andy. 2011. “Developing First-year Engagement with Written Feedback.” Active Learning in Higher Education 12 (2): 113–124. doi: 10.1177/1469787411402484
  • Croteau, Ethan A., Neil T. Heffernan, and Kenneth R. Koedinger. 2004. "Why Are Algebra Word Problems Difficult? Using Tutorial Log Files and the Power Law of Learning to Select the Best Fitting Cognitive Model." In Intelligent Tutoring Systems: 7th International Conference on ITS 2004, edited by James C. Lester, Rosa M. Vicari, and Fábio Paraguacu, 240–250. Maceió Alagoas, Brazil: Springer.
  • Dillon, John, Nigel Bosch, Malolan Chetlur, Nirandika Wanigasekara, G. Alex Ambrose, Bikram Sengupta, and Sidney K. D'Mello. 2016. “Student Emotion, Co-occurrence, and Dropout in a MOOC Context.” Proceedings of the 9th International Conference on Educational Data Mining, Raleigh, NC, EDM 2016, 353–357
  • Fredricks, Jennifer A., Phyllis C. Blumenfeld, and Alison H. Paris. 2004. “School Engagement: Potential of the Concept, State of the Evidence.” Review of Educational Research 74 (1): 59–109. doi: 10.3102/00346543074001059
  • Fredricks, Jennifer A., and Wendy McColskey. 2012. “The Measurement of Student Engagement: A Comparative Analysis of Various Methods and Student Self-report Instruments.” In Handbook of Research on Student Engagement, edited by Sandra L. Christenson, Amy L. Reschly, and Cathy Wylie, 763–782. Boston, MA: Springer US.
  • Fridman, L. M. 1978. “Trinomial Graphs.” Matematicheskie Modeli Povedeniya 3: 47–53. Cited By 2
  • García, Ana I., Juan E. Jiménez, and Stephany Hess. 2006. “Solving Arithmetic Word Problems: An Analysis of Classification as a Function of Difficulty in Children with and Without Arithmetic LD.” Journal of Learning Disabilities 39 (3): 270–281. doi: 10.1177/00222194060390030601
  • González-Calero, J. A., D. Arnau, L. Puig, and M. Arevalillo-Herráez. 2015. “Intensive Scaffolding in an Intelligent Tutoring System for the Learning of Algebraic Word Problem Solving.” British Journal of Educational Technology 46 (6): 1189–1200. doi: 10.1111/bjet.12183
  • Grawemeyer, Beate, Manolis Mavrikis, Wayne Holmes, Sergio Gutiérrez-Santos, Michael Wiedmann, and Nikol Rummel. 2017. “Affective Learning: Improving Engagement and Enhancing Learning with Affect-aware Feedback.” User Modeling and User-Adapted Interaction 27 (1): 119–158. http://dx.doi.org/10.1007/s11257-017-9188-z.
  • Gutica, M., and C. Conati. 2013. “Student Emotions with an Edu-game: A Detailed Analysis.” 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction, Geneva, 534–539.
  • Hara, Noriko. 2000. “Student Distress in a Web-based Distance Education Course.” Information, Communication & Society 3 (4): 557–579. doi: 10.1080/13691180010002297
  • Henrie, Curtis R., Lisa R. Halverson, and Charles R. Graham. 2015. “Measuring student engagement in technology-mediated learning: A review.” Computers & Education 90: 36–53. doi: 10.1016/j.compedu.2015.09.005
  • Jamieson, Jeremy P., Brett J. Peters, Emily J. Greenwood, and Aaron J. Altose. 2016. “Reappraising Stress Arousal Improves Performance and Reduces Evaluation Anxiety in Classroom Exam Situations.” Social Psychological and Personality Science 7 (6): 579–587. https://doi.org/10.1177/1948550616644656.
  • Lin, Hao-Chiang Koong, Nian-Shing Chen, Rui-Ting Sun, and I-Hen Tsai. 2014. “Usability of Affective Interfaces for a Digital Arts Tutoring System.” Behaviour & Information Technology 33 (2): 105–116. doi: 10.1080/0144929X.2012.702356
  • Manassero-Más, Maria Antonia, and Ángel Vázquez-Alonso. 1998. “Validación de una escala de motivación de logro.” Psicothema 10 (2): 333–351.
  • McQuiggan, Scott W., Jennifer L. Robison, and James C. Lester. 2010. “Affective Transitions in Narrative-Centered Learning Environments.” Journal of Educational Technology & Society 13: 40–53.
  • O'Brien, Heather L., and Elaine G. Toms. 2008. “What is User Engagement? A Conceptual Framework for Defining User Engagement with Technology.” Journal of the American Society for Information Science and Technology 59 (6): 938–955. doi: 10.1002/asi.20801
  • Robison, Jennifer L., Scott W. Mcquiggan, and James C. Lester. 2009. “Modeling Task-based vs. Affect-based Feedback Behavior in Pedagogical Agents: An Inductive Approach.” In Proceedings of the 2009 Conference on Artificial Intelligence in Education: Building Learning Systems That Care: From Knowledge Representation to Affective Modelling, 25–32. Amsterdam, NL: IOS Press. http://dl.acm.org/citation.cfm?id=1659450.1659459.
  • Salmeron-Majadas, S., M. Arevalillo-Herráez, O. C. Santos, M. Saneiro, R. Cabestrero, P. Quirós, D. Arnau, and J. G. Boticario. 2015. "Filtering of Spontaneous and Low Intensity Emotions in Educational Contexts." In Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science. Vol. 9112., edited by C. Conati, N. Heffernan, A. Mitrovic, and M. Verdejo, 429–438. Madrid, Spain: Springer International Publishing.
  • Saneiro, Mar, Olga C. Santos, Sergio Salmeron-Majadas, and Jesus G. Boticario. 2014. "Towards Emotion Detection in Educational Scenarios from Facial Expressions and Body Movements through Multimodal Approaches." The Scientific World Journal 2014: 1–14. doi:10.1155/2014/484873.
  • Santos, Olga C. 2016. “Emotions and Personality in Adaptive e-Learning Systems: An Affective Computing Perspective.” In Emotions and Personality in Personalized Services: Models, Evaluation and Applications, edited by Marko Tkalčič, Berardina De Carolis, Marco de Gemmis, Ante Odić, and Andrej Košir, 263–285. Springer. htp://dx.doi.org/10.1007/978-3-319-31413-6_13.
  • Santos, Olga C., and Jesus G. Boticario. 2015. “Practical Guidelines for Designing and Evaluating Educationally Oriented Recommendations.” Computers & Education 81: 354–374. doi: 10.1016/j.compedu.2014.10.008
  • Santos, O. C., M. Saneiro, J. G. Boticario, and M. C. Rodriguez-Sanchez. 2015. “Toward Interactive Context-aware Affective Educational Recommendations in Computer-assisted Language Learning.” New Review of Hypermedia and Multimedia 21 (3): 1–31.
  • Santos, O. C., M. Saneiro, S. Salmeron-Majadas, and J. G. Boticario. 2014. “A Methodological Approach to Eliciting Affective Educational Recommendations.” 2014 IEEE 14th International Conference on Advanced Learning Technologies, Athens, Greece, 529–533.
  • Santos, Olga C., Raul Uria-Rivas, M. Cristina Rodriguez-Sanchez, and Jesus G. Boticario. 2016. “An Open Sensing and Acting Platform for Context-Aware Affective Support in Ambient Intelligent Educational Settings.” IEEE Sensors Journal 16 (10): 3865–3874. doi: 10.1109/JSEN.2016.2533266
  • Self, John. 1995. Computational Mathematics: Towards a Science of Learning Systems Design. Lancaster.Drakkar Press.
  • Shute, Valerie J. 2008. “Focus on Formative Feedback.” Review of Educational Research 78 (1): 153–189. doi: 10.3102/0034654307313795
  • Stevenson, Claire E., Wilma C. M. Resing, and Willem J. Heiser. 2013. “Individual Differences in the Effect of Feedback on Children's Change in Analogical Reasoning.” In Workshop proceedings of AIED 2013. Vol. 1009., edited by E. Walker, C.K. Looi, 33-38.
  • Tempelaar, Dirk T., Bart Rienties, and Bas Giesbers. 2015. “In Search for the Most Informative Data for Feedback Generation.” Computers in Human Behavior 47 (C): 157–167. doi: 10.1016/j.chb.2014.05.038
  • VanLehn, Kurt, Winslow Burleson, Sylvie Girard, Maria Elena Chavez-Echeagaray, Javier Gonzalez-Sanchez, Yoalli Hidalgo-Pontet, and Lishan Zhang. 2014. “The Affective Meta-Tutoring Project: Lessons Learned.” 84–93. Cham: Springer International Publishing. http://dx.doi.org/10.1007/978-3-319-07221-0_11.
  • Walker, Erin, Nikol Rummel, and Kenneth R. Koedinger. 2014. “Adaptive Intelligent Support to Improve Peer Tutoring in Algebra.” International Journal of Artificial Intelligence in Education 24 (1): 33–61. doi: 10.1007/s40593-013-0001-9
  • Weiner, Bernard. 1985. “An Attributional Theory of Achievement Motivation and Emotion.” Psychological Review 92 (4): 548–573. doi: 10.1037/0033-295X.92.4.548
  • Winstone, Naomi E., Robert A. Nash, Michael Parker, and James Rowntree. 2017. “Supporting Learners' Agentic Engagement With Feedback: A Systematic Review and a Taxonomy of Recipience Processes.” Educational Psychologist 52 (1): 17–37. http://dx.doi.org/10.1080/00461520.2016.1207538.

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