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Using contactless sensors to estimate learning difficulty in digital learning environments

Published: 09 September 2019 Publication History

Abstract

Digital learning environments provide rich and engaging experiences for students to develop different knowledge and skills. However, learning systems in these environments generally lack the capacity to assess student difficulties in realtime. The lack of timely assessment and guidance can result in unproductive floundering and associated frustration [3, 9]. Standard measures are mostly focused on the use of questionnaires, intervews or think-aloud protocols for capturing learners' subjective feedback on affect, mental-effort, perceived learning, and user preferences [5]. Though these instruments are effective in capturing overall sentiments and reactions, they do not provide enough granularity to conduct detailed analyses on how specific parts of the lecture affect the learning experience.

References

[1]
Yomna Abdelrahman, Eduardo Velloso, Tilman Dingier, Albrecht Schmidt, and Frank Vetere. 2017. Cognitive Heat: Exploring the Usage of Thermal Imaging to Unobtrusively Estimate Cognitive Load. Proceedings of IMWUT 1, 3 (2017), 33.
[2]
Amaël Arguel, Jason M Lodge, Mariya Pachman, and Paula G De Barba. 2016. Confidence drives exploration strategies in interactive simulations. In 33rd International Conference of Innovation, Practice and Research in the Use of Educational Technologies in Tertiary Education. 33.
[3]
Sidney D'Mello and Art Graesser. 2014. Confusion and its dynamics during device comprehension with breakdown scenarios. Acta psychologica 151 (2014), 106--116.
[4]
Myrthe Faber, Robert Bixler, and Sidney KD'Mello. 2017. An automated behavioral measure of mind wandering during computerized reading. Behavior Research Methods (2017), 1--17.
[5]
Jennifer A Fredricks 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. Springer, 763--782.
[6]
Martijn Haak, Steven Bos, Sacha Panic, and LJM Rothkrantz. 2009. Detecting stress using eye blinks and brain activity from EEG signals. Proceeding of the 1st driver car interaction and interface (DCII 2008) (2009), 35--60.
[7]
Elise Labbé, Nicholas Schmidt, Jonathan Babin, and Martha Pharr. 2007. Coping with stress: the effectiveness of different types of music. Applied psychophysiology and biofeedback 32, 3-4 (2007), 163--168.
[8]
Jason Lodge, Jared Cooney Horvath, Alex Horton, Gregor Kennedy, Sven Venema, and Shane Dawson. 2017. Designing videos for learning: Separating the good from the bad and the ugly. (01 2017).
[9]
Jason M Lodge, Gregor Kennedy, Lori Lockyer, Amael Arguel, and Mariya Pachman. 2018. Understanding difficulties and resulting confusion in learning: An integrative review. In Frontiers in Education, Vol. 3. Frontiers, 49.
[10]
Arcangelo Merla and Gian Luca Romani. 2007. Thermal signatures of emotional arousal: a functional infrared imaging study. In Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE. IEEE, 247--249.
[11]
Jacob L Orquin and Simone Mueller Loose. 2013. Attention and choice: A review on eye movements in decision making. Acta psychologica 144, 1 (2013), 190--206.
[12]
Mariya Pachman, Amaël Arguel, Lori Lockyer, Gregor Kennedy, and Jason M Lodge. 2016. Eye tracking and early detection of confusion in digital learning environments: Proof of concept. Australasian Journal of Educational Technology 32, 6 (2016).
[13]
Colin Puri, Leslie Olson, Ioannis Pavlidis, James Levine, and Justin Starren. 2005. StressCam: Non-contact Measurement of Users' Emotional States Through Thermal Imaging. In CHI '05 Extended Abstracts on Human Factors in Computing Systems (CHI EA '05). ACM, New York, NY, USA, 1725--1728.
[14]
Mijael Rodriguez and Albin Söderholm. 2016. Measuring Student Alertness Using the X2-30 Eye-Tracker: A study in the suitability of the X2-30 eye-tracker to measure alertness in a learning environment.
[15]
Rod D Roscoe, Scotty D Craig, and Ian Douglas. 2017. End-User Considerations in Educational Technology Design. IGI Global.
[16]
Yu Shi, Natalie Ruiz, Ronnie Taib, Eric Choi, and Fang Chen. 2007. Galvanic skin response (GSR) as an index of cognitive load. In CHI'07 extended abstracts on Human factors in computing systems. ACM, 2651--2656.
[17]
Saurabh Sonkusare, David Ahmedt-Aristizabal, Matthew J Aburn, Vinh Thai Nguyen, Tianji Pang, Sascha Frydman, Simon Denman, Clinton Fookes, Michael Breakspear, and Christine C Guo. 2019. Detecting changes in facial temperature induced by a sudden auditory stimulus based on deep learning-assisted face tracking. Scientific reports 9, 1 (2019), 4729.
[18]
Namrata Srivastava, Joshua Newn, and Eduardo Velloso. 2018. Combining Low and Mid-Level Gaze Features for Desktop Activity Recognition. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 4 (2018), 189.
[19]
Namrata Srivastava, Eduardo Velloso, Jason M. Lodge, Sarah Erfani, and James Bailey. 2019. Continuous Evaluation of Video Lectures from Real-Time Difficulty Self-Report. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). ACM, New York, NY, USA, Article 586, 12 pages.
[20]
Zhen Zhu, Panagiotis Tsiamyrtzis, and Ioannis Pavlidis. 2007. Forehead thermal signature extraction in lie detection. In Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE. IEEE, 243--246.

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  • (2023)Accelerating Knowledge Transfer by Sensing and Actuating Social-Cognitive StatesAdjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing10.1145/3594739.3610769(258-262)Online publication date: 8-Oct-2023
  • (2021)Inner Eye Canthus Localization for Human Body Temperature Screening2020 25th International Conference on Pattern Recognition (ICPR)10.1109/ICPR48806.2021.9412015(8833-8840)Online publication date: 10-Jan-2021
  • (2021)Analysis of Emotion in Socioenactive SystemsHuman-Computer Interaction. Theory, Methods and Tools10.1007/978-3-030-78462-1_41(535-544)Online publication date: 24-Jul-2021
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      cover image ACM Conferences
      UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers
      September 2019
      1234 pages
      ISBN:9781450368698
      DOI:10.1145/3341162
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Published: 09 September 2019

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      Author Tags

      1. education
      2. learning analytics
      3. online learning
      4. video lectures

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      View all
      • (2023)Accelerating Knowledge Transfer by Sensing and Actuating Social-Cognitive StatesAdjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing10.1145/3594739.3610769(258-262)Online publication date: 8-Oct-2023
      • (2021)Inner Eye Canthus Localization for Human Body Temperature Screening2020 25th International Conference on Pattern Recognition (ICPR)10.1109/ICPR48806.2021.9412015(8833-8840)Online publication date: 10-Jan-2021
      • (2021)Analysis of Emotion in Socioenactive SystemsHuman-Computer Interaction. Theory, Methods and Tools10.1007/978-3-030-78462-1_41(535-544)Online publication date: 24-Jul-2021
      • (2020)Multimodal Data Fusion in Learning Analytics: A Systematic ReviewSensors10.3390/s2023685620:23(6856)Online publication date: 30-Nov-2020
      • (2020)Accessibility in Pervasive Systems: An Exploratory StudyDistributed, Ambient and Pervasive Interactions10.1007/978-3-030-50344-4_3(25-38)Online publication date: 19-Jul-2020

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