Using Local and Global Self-Evaluations to Predict Students' Problem Solving Behaviour

Lenka Schnaubert; Eric Andrès; Susanne Narciss; Sergey Sosnovsky; Anja Eichelmann; Giorgi Goguadze

doi:10.1007/978-3-642-33263-0_26

Using Local and Global Self-Evaluations to Predict Students' Problem Solving Behaviour

Lenka Schnaubert
, Eric Andrès
, Susanne Narciss
, Sergey Sosnovsky
, Anja Eichelmann
, Giorgi Goguadze

Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › Begutachtung

Abstract

This paper investigates how local and global self-evaluations of capabilities can be used to predict pupils’ problem-solving behaviour in the domain of fraction learning. To answer this question we analyzed logfiles of pupils who worked on multi-trial fraction tasks. Logistic regression analyses revealed that local confidence judgements assessed online improve the prediction of post-error solving, as well as skipping behaviour significantly, while pre-assessed global perception of competence failed to do so. Yet, for all computed models, the impact of our prediction is rather small. Further research is necessary to enrich these models with other relevant user- as well as task-characteristics to make them usable for adaptation.

Originalsprache	Englisch
Titel	21st Century Learning for 21st Century Skills : 7th European Conference of Technology Enhanced Learning, EC-TEL 2012, Saarbrücken, Germany, September 18-21, 2012. Proceedings
Redakteure/-innen	Andrew Ravenscroft, Stefanie Lindstaedt, Carlos Delgado Kloos, Davinia Hernández-Leo
Seitenumfang	14
Herausgeber (Verlag)	Springer Verlag
Erscheinungsdatum	2012
Seiten	334-347
ISBN (Print)	978-3-642-33262-3
ISBN (elektronisch)	978-3-642-33263-0
DOIs	https://doi.org/10.1007/978-3-642-33263-0_26
Publikationsstatus	Erschienen - 2012
Extern publiziert	Ja
Veranstaltung	7th European Conference for Technology-Enhanced Learning EC- TEL 2012 - Saarbrücken, Deutschland Dauer: 18.09.2012 → 21.09.2012 Konferenznummer: 7 http://www.prolearn-academy.org/Events/ec-tel-2012-seventh-european-conference-on-technology-enhanced-learning

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Empirische Bildungsforschung
Digitale Medien

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10.1007/978-3-642-33263-0_26

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Schnaubert, L., Andrès, E., Narciss, S., Sosnovsky, S., Eichelmann, A., & Goguadze, G. (2012). Using Local and Global Self-Evaluations to Predict Students' Problem Solving Behaviour. in A. Ravenscroft, S. Lindstaedt, C. Delgado Kloos, & D. Hernández-Leo (Hrsg.), 21st Century Learning for 21st Century Skills: 7th European Conference of Technology Enhanced Learning, EC-TEL 2012, Saarbrücken, Germany, September 18-21, 2012. Proceedings (S. 334-347). (Lecture Notes in Computer Science; Band 7563). Springer Verlag. https://doi.org/10.1007/978-3-642-33263-0_26

Schnaubert, Lenka ; Andrès, Eric ; Narciss, Susanne et al. / Using Local and Global Self-Evaluations to Predict Students' Problem Solving Behaviour. 21st Century Learning for 21st Century Skills: 7th European Conference of Technology Enhanced Learning, EC-TEL 2012, Saarbrücken, Germany, September 18-21, 2012. Proceedings. Hrsg. / Andrew Ravenscroft ; Stefanie Lindstaedt ; Carlos Delgado Kloos ; Davinia Hernández-Leo. Springer Verlag, 2012. S. 334-347 (Lecture Notes in Computer Science).

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title = "Using Local and Global Self-Evaluations to Predict Students' Problem Solving Behaviour",

abstract = "This paper investigates how local and global self-evaluations of capabilities can be used to predict pupils{\textquoteright} problem-solving behaviour in the domain of fraction learning. To answer this question we analyzed logfiles of pupils who worked on multi-trial fraction tasks. Logistic regression analyses revealed that local confidence judgements assessed online improve the prediction of post-error solving, as well as skipping behaviour significantly, while pre-assessed global perception of competence failed to do so. Yet, for all computed models, the impact of our prediction is rather small. Further research is necessary to enrich these models with other relevant user- as well as task-characteristics to make them usable for adaptation.",

keywords = "Empirical education research, Area Under Curve, Initial Error, Cognitive Load Theory, Educational Psychology Review, Mastery Motivation, Digital media",

author = "Lenka Schnaubert and Eric Andr{\`e}s and Susanne Narciss and Sergey Sosnovsky and Anja Eichelmann and Giorgi Goguadze",

year = "2012",

doi = "10.1007/978-3-642-33263-0\_26",

language = "English",

isbn = "978-3-642-33262-3",

series = "Lecture Notes in Computer Science",

publisher = "Springer Verlag",

pages = "334--347",

editor = "Andrew Ravenscroft and Stefanie Lindstaedt and \{Delgado Kloos\}, Carlos and Davinia Hern{\'a}ndez-Leo",

booktitle = "21st Century Learning for 21st Century Skills",

address = "Germany",

note = "7th European Conference for Technology-Enhanced Learning EC- TEL 2012, EC-TEL 2012 ; Conference date: 18-09-2012 Through 21-09-2012",

url = "http://www.prolearn-academy.org/Events/ec-tel-2012-seventh-european-conference-on-technology-enhanced-learning",

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Schnaubert, L, Andrès, E, Narciss, S, Sosnovsky, S, Eichelmann, A & Goguadze, G 2012, Using Local and Global Self-Evaluations to Predict Students' Problem Solving Behaviour. in A Ravenscroft, S Lindstaedt, C Delgado Kloos & D Hernández-Leo (Hrsg.), 21st Century Learning for 21st Century Skills: 7th European Conference of Technology Enhanced Learning, EC-TEL 2012, Saarbrücken, Germany, September 18-21, 2012. Proceedings. Lecture Notes in Computer Science, Bd. 7563, Springer Verlag, S. 334-347, 7th European Conference for Technology-Enhanced Learning EC- TEL 2012, Saarbrücken, Deutschland, 18.09.12. https://doi.org/10.1007/978-3-642-33263-0_26

Using Local and Global Self-Evaluations to Predict Students' Problem Solving Behaviour. / Schnaubert, Lenka; Andrès, Eric; Narciss, Susanne et al.
21st Century Learning for 21st Century Skills: 7th European Conference of Technology Enhanced Learning, EC-TEL 2012, Saarbrücken, Germany, September 18-21, 2012. Proceedings. Hrsg. / Andrew Ravenscroft; Stefanie Lindstaedt; Carlos Delgado Kloos; Davinia Hernández-Leo. Springer Verlag, 2012. S. 334-347 (Lecture Notes in Computer Science; Band 7563).

Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › Begutachtung

TY - CHAP

T1 - Using Local and Global Self-Evaluations to Predict Students' Problem Solving Behaviour

AU - Schnaubert, Lenka

AU - Andrès, Eric

AU - Narciss, Susanne

AU - Sosnovsky, Sergey

AU - Eichelmann, Anja

AU - Goguadze, Giorgi

N1 - Conference code: 7

PY - 2012

Y1 - 2012

N2 - This paper investigates how local and global self-evaluations of capabilities can be used to predict pupils’ problem-solving behaviour in the domain of fraction learning. To answer this question we analyzed logfiles of pupils who worked on multi-trial fraction tasks. Logistic regression analyses revealed that local confidence judgements assessed online improve the prediction of post-error solving, as well as skipping behaviour significantly, while pre-assessed global perception of competence failed to do so. Yet, for all computed models, the impact of our prediction is rather small. Further research is necessary to enrich these models with other relevant user- as well as task-characteristics to make them usable for adaptation.

AB - This paper investigates how local and global self-evaluations of capabilities can be used to predict pupils’ problem-solving behaviour in the domain of fraction learning. To answer this question we analyzed logfiles of pupils who worked on multi-trial fraction tasks. Logistic regression analyses revealed that local confidence judgements assessed online improve the prediction of post-error solving, as well as skipping behaviour significantly, while pre-assessed global perception of competence failed to do so. Yet, for all computed models, the impact of our prediction is rather small. Further research is necessary to enrich these models with other relevant user- as well as task-characteristics to make them usable for adaptation.

KW - Empirical education research

KW - Area Under Curve

KW - Initial Error

KW - Cognitive Load Theory

KW - Educational Psychology Review

KW - Mastery Motivation

KW - Digital media

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DO - 10.1007/978-3-642-33263-0_26

M3 - Article in conference proceedings

SN - 978-3-642-33262-3

T3 - Lecture Notes in Computer Science

SP - 334

EP - 347

BT - 21st Century Learning for 21st Century Skills

A2 - Ravenscroft, Andrew

A2 - Lindstaedt, Stefanie

A2 - Delgado Kloos, Carlos

A2 - Hernández-Leo, Davinia

PB - Springer Verlag

T2 - 7th European Conference for Technology-Enhanced Learning EC- TEL 2012

Y2 - 18 September 2012 through 21 September 2012

ER -

Schnaubert L, Andrès E, Narciss S, Sosnovsky S, Eichelmann A, Goguadze G. Using Local and Global Self-Evaluations to Predict Students' Problem Solving Behaviour. in Ravenscroft A, Lindstaedt S, Delgado Kloos C, Hernández-Leo D, Hrsg., 21st Century Learning for 21st Century Skills: 7th European Conference of Technology Enhanced Learning, EC-TEL 2012, Saarbrücken, Germany, September 18-21, 2012. Proceedings. Springer Verlag. 2012. S. 334-347. (Lecture Notes in Computer Science). doi: 10.1007/978-3-642-33263-0_26

Using Local and Global Self-Evaluations to Predict Students' Problem Solving Behaviour

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