TY - JOUR
T1 - Moodoo the tracker
T2 - spatial classroom analytics for characterising teachers’ pedagogical approaches
AU - Martinez-Maldonado, Roberto
AU - Echeverria, Vanessa
AU - Mangaroska, Katerina
AU - Shibani, Antonette
AU - Fernandez-Nieto, Gloria
AU - Schulte, Jurgen
AU - Buckingham Shum, Simon
N1 - Funding Information:
Roberto Martinez-Maldonado’s research is partly funded by Jacobs Foundation.
Publisher Copyright:
© 2021, International Artificial Intelligence in Education Society.
PY - 2022/12
Y1 - 2022/12
N2 - Teachers’ spatial behaviours in the classroom can strongly influence students’ engagement, motivation and other behaviours that shape their learning. However, classroom teaching behaviour is ephemeral, and has largely remained opaque to computational analysis. Inspired by the notion of Spatial Pedagogy, this paper presents a system called ‘Moodoo’ that automatically tracks and models how teachers make use of the classroom space by analysing indoor positioning traces. We illustrate the potential of the system through an authentic study with seven teachers enacting three distinct learning designs with more than 200 undergraduate students in the context of science education. The system automatically extracts spatial metrics (e.g. teacher-student ratios, frequency of visits to students’ personal spaces, presence in classroom spaces of interest, index of dispersion and entropy), mapping from the teachers’ low-level positioning data to higher-order spatial constructs. We illustrate how these spatial metrics can be used to generate a deeper understanding of how the pedagogical commitments embedded in the learning design, and personal teaching strategies, are reflected in the ways teachers use the learning space to provide support to students.
AB - Teachers’ spatial behaviours in the classroom can strongly influence students’ engagement, motivation and other behaviours that shape their learning. However, classroom teaching behaviour is ephemeral, and has largely remained opaque to computational analysis. Inspired by the notion of Spatial Pedagogy, this paper presents a system called ‘Moodoo’ that automatically tracks and models how teachers make use of the classroom space by analysing indoor positioning traces. We illustrate the potential of the system through an authentic study with seven teachers enacting three distinct learning designs with more than 200 undergraduate students in the context of science education. The system automatically extracts spatial metrics (e.g. teacher-student ratios, frequency of visits to students’ personal spaces, presence in classroom spaces of interest, index of dispersion and entropy), mapping from the teachers’ low-level positioning data to higher-order spatial constructs. We illustrate how these spatial metrics can be used to generate a deeper understanding of how the pedagogical commitments embedded in the learning design, and personal teaching strategies, are reflected in the ways teachers use the learning space to provide support to students.
KW - Indoor localisation
KW - Learning spaces
KW - Multimodal learning analytics
KW - Spatial modelling
KW - Teaching
UR - http://www.scopus.com/inward/record.url?scp=85118443696&partnerID=8YFLogxK
U2 - 10.1007/s40593-021-00276-w
DO - 10.1007/s40593-021-00276-w
M3 - Article
AN - SCOPUS:85118443696
SN - 1560-4292
VL - 32
SP - 1025
EP - 1051
JO - International Journal of Artificial Intelligence in Education
JF - International Journal of Artificial Intelligence in Education
ER -