Exploring feedback and student characteristics relevant for personalizing feedback strategies

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Susanne Narciss - , Chair of Psychology of Learning and Instruction, Dresden University of Technology (Author)
  • Sergey Sosnovsky - , German Research Center for Artificial Intelligence (Author)
  • Lenka Schnaubert - , University of Duisburg-Essen (Author)
  • Eric Andrès - , German Research Center for Artificial Intelligence (Author)
  • Anja Eichelmann - , Chair of Psychology of Learning and Instruction, Dresden University of Technology (Author)
  • George Goguadze - , Leuphana University of Lüneburg (Author)
  • Erica Melis - , German Research Center for Artificial Intelligence (Author)

Abstract

Personalized tutoring feedback is a powerful method that expert human tutors apply when helping students to optimize their learning. Thus, research on tutoring feedback strategies tailoring feedback according to important factors of the learning process has been recognized as a promising issue in the field of computer-based adaptive educational technologies. Our paper seeks to contribute to this area of research by addressing the following aspects: First, to investigate how students' gender, prior knowledge, and motivational characteristics relate to learning outcomes (knowledge gain and changes in motivation). Second, to investigate the impact of these student characteristics on how tutoring feedback strategies varying in content (procedural vs. conceptual) and specificity (concise hints vs. elaborated explanations) of tutoring feedback messages affect students' learning and motivation. Third, to explore the influence of the feedback parameters and student characteristics on students' immediate post-feedback behaviour (skipping vs. trying to accomplish a task, and failing vs. succeeding in providing a correct answer). To address these issues, detailed log-file analyses of an experimental study have been conducted. In this study, 124 sixth and seventh graders have been exposed to various tutoring feedback strategies while working on multi-trial error correction tasks in the domain of fraction arithmetic. The web-based intelligent learning environment ActiveMath was used to present the fraction tasks and trace students' progress and activities. The results reveal that gender is an important factor for feedback efficiency: Male students achieve significantly lower knowledge gains than female students under all tutoring feedback conditions (particularly, under feedback strategies starting with a conceptual hint). Moreover, perceived competence declines from pre- to post-test significantly more for boys than for girls. Yet, the decline in perceived competence is not accompanied by a decline in intrinsic motivation, which, instead, increases significantly from pre- to post-test. With regard to the post-feedback behaviour, the results indicate that students skip further attempts more frequently after conceptual than after procedural feedback messages.

Details

Original languageEnglish
Pages (from-to)56-76
Number of pages21
JournalComputers and education
Volume71
Publication statusPublished - 2014
Peer-reviewedYes

External IDs

ORCID /0000-0002-4280-6534/work/142251719

Keywords

ASJC Scopus subject areas

Keywords

  • Evaluation of CAL systems, Intelligent tutoring system, Tutoring feedback strategies