Measuring learning progress for serving immediate feedback needs: Learning process quantification framework (lpqf)

Gayane Sedrakyan; Sebastian Dannerlein; Viktoria Pammer-Schindler; Stefanie Lindstaedt

doi:10.1007/978-3-030-57717-9_42

Measuring learning progress for serving immediate feedback needs: Learning process quantification framework (lpqf)

Gayane Sedrakyan^*, Sebastian Dannerlein, Viktoria Pammer-Schindler, Stefanie Lindstaedt

^*Corresponding author for this work

Industrial Engineering & Business Information Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

103 Downloads (Pure)

Abstract

Our earlier research attempts to close the gap between learning behavior analytics based dashboard feedback and learning theories by grounding the idea of dashboard feedback onto learning science concepts such as feedback, learning goals, (socio-/meta-) cognitive mechanisms underlying learning processes. This work extends the earlier research by proposing mechanisms for making those concepts and relationships measurable. The outcome is a complementary framework that allows identifying feedback needs and timing for their provision in a generic context that can be applied to a certain subject in a given LMS. The research serves as general guidelines for educators in designing educational dashboards, as well as a starting research platform in the direction of systematically matching learning sciences concepts with data and analytics concepts.

Original language	English
Title of host publication	Addressing Global Challenges and Quality Education
Subtitle of host publication	15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Proceedings
Editors	Carlos Alario-Hoyos, María Jesús Rodríguez-Triana, Maren Scheffel, Inmaculada Arnedillo-Sánchez, Sebastian Maximilian Dennerlein
Publisher	Springer
Pages	443-448
Number of pages	6
ISBN (Electronic)	978-3-030-57717-9
ISBN (Print)	978-3-030-57716-2
DOIs	https://doi.org/10.1007/978-3-030-57717-9_42
Publication status	Published - 7 Sept 2020
Event	15th European Conference on Technology Enhanced Learning, EC-TEL 2020 - Online Event, Heidelberg, Germany Duration: 14 Sept 2020 → 18 Sept 2020 Conference number: 15

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12315 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th European Conference on Technology Enhanced Learning, EC-TEL 2020
Abbreviated title	EC-TEL 2020
Country/Territory	Germany
City	Heidelberg
Period	14/09/20 → 18/09/20

Keywords

Dashboards
Feedback automation
Learning analytics
Measuring learning progress
Process-oriented feedback
22/2 OA procedure

Access to Document

10.1007/978-3-030-57717-9_42

Sedrakyan-2020-Measuring-learning-progress-for-serFinal published version, 783 KBLicence: Taverne

Cite this

Sedrakyan, G., Dannerlein, S., Pammer-Schindler, V., & Lindstaedt, S. (2020). Measuring learning progress for serving immediate feedback needs: Learning process quantification framework (lpqf). In C. Alario-Hoyos, M. J. Rodríguez-Triana, M. Scheffel, I. Arnedillo-Sánchez, & S. M. Dennerlein (Eds.), Addressing Global Challenges and Quality Education: 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Proceedings (pp. 443-448). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12315 LNCS). Springer. https://doi.org/10.1007/978-3-030-57717-9_42

Sedrakyan, Gayane ; Dannerlein, Sebastian ; Pammer-Schindler, Viktoria et al. / Measuring learning progress for serving immediate feedback needs : Learning process quantification framework (lpqf). Addressing Global Challenges and Quality Education: 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Proceedings. editor / Carlos Alario-Hoyos ; María Jesús Rodríguez-Triana ; Maren Scheffel ; Inmaculada Arnedillo-Sánchez ; Sebastian Maximilian Dennerlein. Springer, 2020. pp. 443-448 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Our earlier research attempts to close the gap between learning behavior analytics based dashboard feedback and learning theories by grounding the idea of dashboard feedback onto learning science concepts such as feedback, learning goals, (socio-/meta-) cognitive mechanisms underlying learning processes. This work extends the earlier research by proposing mechanisms for making those concepts and relationships measurable. The outcome is a complementary framework that allows identifying feedback needs and timing for their provision in a generic context that can be applied to a certain subject in a given LMS. The research serves as general guidelines for educators in designing educational dashboards, as well as a starting research platform in the direction of systematically matching learning sciences concepts with data and analytics concepts.",

keywords = "Dashboards, Feedback automation, Learning analytics, Measuring learning progress, Process-oriented feedback, 22/2 OA procedure",

author = "Gayane Sedrakyan and Sebastian Dannerlein and Viktoria Pammer-Schindler and Stefanie Lindstaedt",

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editor = "Carlos Alario-Hoyos and Rodr{\'i}guez-Triana, {Mar{\'i}a Jes{\'u}s} and Maren Scheffel and Inmaculada Arnedillo-S{\'a}nchez and Dennerlein, {Sebastian Maximilian}",

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Sedrakyan, G, Dannerlein, S, Pammer-Schindler, V & Lindstaedt, S 2020, Measuring learning progress for serving immediate feedback needs: Learning process quantification framework (lpqf). in C Alario-Hoyos, MJ Rodríguez-Triana, M Scheffel, I Arnedillo-Sánchez & SM Dennerlein (eds), Addressing Global Challenges and Quality Education: 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12315 LNCS, Springer, pp. 443-448, 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Heidelberg, Germany, 14/09/20. https://doi.org/10.1007/978-3-030-57717-9_42

Measuring learning progress for serving immediate feedback needs: Learning process quantification framework (lpqf). / Sedrakyan, Gayane; Dannerlein, Sebastian; Pammer-Schindler, Viktoria et al.
Addressing Global Challenges and Quality Education: 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Proceedings. ed. / Carlos Alario-Hoyos; María Jesús Rodríguez-Triana; Maren Scheffel; Inmaculada Arnedillo-Sánchez; Sebastian Maximilian Dennerlein. Springer, 2020. p. 443-448 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12315 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Lindstaedt, Stefanie

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ER -

Sedrakyan G, Dannerlein S, Pammer-Schindler V, Lindstaedt S. Measuring learning progress for serving immediate feedback needs: Learning process quantification framework (lpqf). In Alario-Hoyos C, Rodríguez-Triana MJ, Scheffel M, Arnedillo-Sánchez I, Dennerlein SM, editors, Addressing Global Challenges and Quality Education: 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Proceedings. Springer. 2020. p. 443-448. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-57717-9_42

Measuring learning progress for serving immediate feedback needs: Learning process quantification framework (lpqf)

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