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Diagnosing collaboration in practice-based learning : Equality and intra-individual variability of physical interactivity. / Cukurova, Mutlu; Luckin, Rose; Millán, Eva; Mavrikis, Manolis; Spikol, Daniel.
Data Driven Approaches in Digital Education - 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Proceedings. red. / Julien Broisin; Elise Lavoue; Hendrik Drachsler; Katrien Verbert; Mar Perez-Sanagustin. Springer Verlag, 2017. s. 30-42 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 10474 LNCS).
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
Cukurova, M, Luckin, R, Millán, E, Mavrikis, M
& Spikol, D 2017,
Diagnosing collaboration in practice-based learning: Equality and intra-individual variability of physical interactivity. i J Broisin, E Lavoue, H Drachsler, K Verbert & M Perez-Sanagustin (red),
Data Driven Approaches in Digital Education - 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Proceedings. Springer Verlag, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), bind 10474 LNCS, s. 30-42, 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Tallinn, Estland,
12/09/2017.
https://doi.org/10.1007/978-3-319-66610-5_3APA
Cukurova, M., Luckin, R., Millán, E., Mavrikis, M.
, & Spikol, D. (2017).
Diagnosing collaboration in practice-based learning: Equality and intra-individual variability of physical interactivity. I J. Broisin, E. Lavoue, H. Drachsler, K. Verbert, & M. Perez-Sanagustin (red.),
Data Driven Approaches in Digital Education - 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Proceedings (s. 30-42). Springer Verlag,. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Bind 10474 LNCS
https://doi.org/10.1007/978-3-319-66610-5_3Vancouver
Cukurova M, Luckin R, Millán E, Mavrikis M
, Spikol D.
Diagnosing collaboration in practice-based learning: Equality and intra-individual variability of physical interactivity. I Broisin J, Lavoue E, Drachsler H, Verbert K, Perez-Sanagustin M, red., Data Driven Approaches in Digital Education - 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Proceedings. Springer Verlag,. 2017. s. 30-42. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 10474 LNCS).
https://doi.org/10.1007/978-3-319-66610-5_3Author
Cukurova, Mutlu ; Luckin, Rose ; Millán, Eva ; Mavrikis, Manolis ; Spikol, Daniel. / Diagnosing collaboration in practice-based learning : Equality and intra-individual variability of physical interactivity. Data Driven Approaches in Digital Education - 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Proceedings. red. / Julien Broisin ; Elise Lavoue ; Hendrik Drachsler ; Katrien Verbert ; Mar Perez-Sanagustin. Springer Verlag, 2017. s. 30-42 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 10474 LNCS).
Bibtex
@inproceedings{7c2eef40c4a742e184a96d5f1749dda0,
title = "Diagnosing collaboration in practice-based learning: Equality and intra-individual variability of physical interactivity",
abstract = "Collaborative problem solving (CPS), as a teaching and learning approach, is considered to have the potential to improve some of the most important skills to prepare students for their future. CPS often differs in its nature, practice, and learning outcomes from other kinds of peer learning approaches, including peer tutoring and cooperation; and it is important to establish what identifies collaboration in problem-solving situations. The identification of indicators of collaboration is a challenging task. However, students physical interactivity can hold clues of such indicators. In this paper, we investigate two non-verbal indexes of student physical interactivity to interpret collaboration in practice-based learning environments: equality and intra-individual variability. Our data was generated from twelve groups of three Engineering students working on open-ended tasks using a learning analytics system. The results show that high collaboration groups have member students who present high and equal amounts of physical interactivity and low and equal amounts of intra-individual variability.",
keywords = "Behaviour patterns, Collaborative learning, Indexes of physical interaction, Problem-solving",
author = "Mutlu Cukurova and Rose Luckin and Eva Mill{\'a}n and Manolis Mavrikis and Daniel Spikol",
year = "2017",
doi = "10.1007/978-3-319-66610-5_3",
language = "English",
isbn = "9783319666099",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag,",
pages = "30--42",
editor = "Julien Broisin and Elise Lavoue and Hendrik Drachsler and Katrien Verbert and Mar Perez-Sanagustin",
booktitle = "Data Driven Approaches in Digital Education - 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Proceedings",
note = "12th European Conference on Technology Enhanced Learning, EC-TEL 2017 ; Conference date: 12-09-2017 Through 15-09-2017",
}
RIS
TY - GEN
T1 - Diagnosing collaboration in practice-based learning
T2 - 12th European Conference on Technology Enhanced Learning, EC-TEL 2017
AU - Cukurova, Mutlu
AU - Luckin, Rose
AU - Millán, Eva
AU - Mavrikis, Manolis
AU - Spikol, Daniel
PY - 2017
Y1 - 2017
N2 - Collaborative problem solving (CPS), as a teaching and learning approach, is considered to have the potential to improve some of the most important skills to prepare students for their future. CPS often differs in its nature, practice, and learning outcomes from other kinds of peer learning approaches, including peer tutoring and cooperation; and it is important to establish what identifies collaboration in problem-solving situations. The identification of indicators of collaboration is a challenging task. However, students physical interactivity can hold clues of such indicators. In this paper, we investigate two non-verbal indexes of student physical interactivity to interpret collaboration in practice-based learning environments: equality and intra-individual variability. Our data was generated from twelve groups of three Engineering students working on open-ended tasks using a learning analytics system. The results show that high collaboration groups have member students who present high and equal amounts of physical interactivity and low and equal amounts of intra-individual variability.
AB - Collaborative problem solving (CPS), as a teaching and learning approach, is considered to have the potential to improve some of the most important skills to prepare students for their future. CPS often differs in its nature, practice, and learning outcomes from other kinds of peer learning approaches, including peer tutoring and cooperation; and it is important to establish what identifies collaboration in problem-solving situations. The identification of indicators of collaboration is a challenging task. However, students physical interactivity can hold clues of such indicators. In this paper, we investigate two non-verbal indexes of student physical interactivity to interpret collaboration in practice-based learning environments: equality and intra-individual variability. Our data was generated from twelve groups of three Engineering students working on open-ended tasks using a learning analytics system. The results show that high collaboration groups have member students who present high and equal amounts of physical interactivity and low and equal amounts of intra-individual variability.
KW - Behaviour patterns
KW - Collaborative learning
KW - Indexes of physical interaction
KW - Problem-solving
U2 - 10.1007/978-3-319-66610-5_3
DO - 10.1007/978-3-319-66610-5_3
M3 - Article in proceedings
AN - SCOPUS:85029586991
SN - 9783319666099
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 30
EP - 42
BT - Data Driven Approaches in Digital Education - 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Proceedings
A2 - Broisin, Julien
A2 - Lavoue, Elise
A2 - Drachsler, Hendrik
A2 - Verbert, Katrien
A2 - Perez-Sanagustin, Mar
PB - Springer Verlag,
Y2 - 12 September 2017 through 15 September 2017
ER -
