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Article

Assessing Efficiency of Prompts Based on Learner Characteristics

1
Medical Teaching and Medical Education Research, University Hospital Wuerzburg, 97080 Wuerzburg, Germany
2
School of Applied Psychology, University College Cork, T23 K208 Cork, Ireland
3
Faculty of Psychology, University of Vienna, A-1010 Vienna, Austria
*
Author to whom correspondence should be addressed.
Academic Editors: Marko Tkalčič, Berardina Nadja De Carolis, Marco de Gemmis and Andrej Košir
Computers 2017, 6(1), 7; https://doi.org/10.3390/computers6010007
Received: 28 November 2016 / Revised: 5 February 2017 / Accepted: 7 February 2017 / Published: 10 February 2017
(This article belongs to the Special Issue Advances in Affect- and Personality-based Personalized Systems)
Personalized prompting research has shown the significant learning benefit of prompting. The current paper outlines and examines a personalized prompting approach aimed at eliminating performance differences on the basis of a number of learner characteristics (capturing learning strategies and traits). The learner characteristics of interest were the need for cognition, work effort, computer self-efficacy, the use of surface learning, and the learner’s confidence in their learning. The approach was tested in two e-modules, using similar assessment forms (experimental n = 413; control group n = 243). Several prompts which corresponded to the learner characteristics were implemented, including an explanation prompt, a motivation prompt, a strategy prompt, and an assessment prompt. All learning characteristics were significant correlates of at least one of the outcome measures (test performance, errors, and omissions). However, only the assessment prompt increased test performance. On this basis, and drawing upon the testing effect, this prompt may be a particularly promising option to increase performance in e-learning and similar personalized systems. View Full-Text
Keywords: e-learning; assessment; prompting; personalization; self-regulation e-learning; assessment; prompting; personalization; self-regulation
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MDPI and ACS Style

Backhaus, J.; Jeske, D.; Poinstingl, H.; Koenig, S. Assessing Efficiency of Prompts Based on Learner Characteristics. Computers 2017, 6, 7. https://doi.org/10.3390/computers6010007

AMA Style

Backhaus J, Jeske D, Poinstingl H, Koenig S. Assessing Efficiency of Prompts Based on Learner Characteristics. Computers. 2017; 6(1):7. https://doi.org/10.3390/computers6010007

Chicago/Turabian Style

Backhaus, Joy, Debora Jeske, Herbert Poinstingl, and Sarah Koenig. 2017. "Assessing Efficiency of Prompts Based on Learner Characteristics" Computers 6, no. 1: 7. https://doi.org/10.3390/computers6010007

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