Ambient intelligence in a smart classroom for assessing students’ engagement levels
- 84 Downloads
The levels of student engagement refers to the degree to which students are immersed in learning when they are being taught in class. This paper deals with an ambient intelligence algorithm for a smart classroom; the algorithm provides information to the teacher by measuring the level of student engagement in real time. In this study, the algorithm for assessing student engagement levels has been presented; it evaluates the psychological states of students by measuring a thermal infrared image. The algorithm proposed in this study is innovative because it allows teachers to provide feedback to students while monitoring their students in real time. This study will provide the basis for applying the Internet of Things to the teaching and learning fields. Specifically, the measurement model for representing the student engagement level by using thermal infrared imaging is presented. The color of the teacher’s mobile phone application changes (like the traffic lights) in real time according to the immersion levels of the students in class.
KeywordsEngagement Immersion in class Intelligent algorithms Internet of things Thermal infrared image
This work was supported by the Incheon National University Research Grant in 2017.
- Figner B, Murphy RO (2011) Using skin conductance in judgment and decision making research. In: Schulte-Mecklenbeck M, Kuehberger A, Ranyard R (2011) A handbook of process tracing methods for decision research. Psychology Press, New York, pp 163–184Google Scholar
- Fox S (2008) Human physiology. McGraw-Hill Companies, BostonGoogle Scholar
- Lang A, Shin M, Bradley SD, Wang Z, Lee S, Potter D (2005) Wait! Don’t turn that dial! More excitement to come! The effects of story length and production pacing in local television news on channel changing behavior and information processing in a free choice environment. J Broadcast Electr Media 49(1):3–22. https://doi.org/10.1207/s15506878jobem4901_2 CrossRefGoogle Scholar
- Marton F, Saljo R (1976) On qualitative differences in learning-io outcome and process. Br J Educ Psychol 46(1):4–11. https://doi.org/10.1111/j.2044-8279.1976.tb02980.x CrossRefGoogle Scholar
- Schlechty PC (2001) Shaking up the schoolhouse: how to support and sustain educational innovation. Jossey-Bass, San FranciscoGoogle Scholar
- Solar (2016) A cool, minimalist weather app for iOS. https://solar-weather.en.softonic.com/iphone. Accessed 8 May 2018