Problem-Solving Strategies in Stoichiometry Across Two Intelligent Tutoring Systems: A Cross-National Study

authored by: Conrad Borchers, Hendrik Fleischer, David J. Yaron, Bruce M. McLaren, Katharina Scheiter, Vincent Aleven, Sascha Schanze
Abstract: Intelligent tutoring system (ITS) provides learners with step-by-step problem-solving support through scaffolding. Most ITSs have been developed in the USA and incorporate American instructional strategies. How do non-American students perceive and use ITS with different native problem-solving strategies? The present study compares Stoich Tutor, an ITS with a high level of scaffolding, with ORCCA, an ITS with dynamic scaffolds that can support a range of problem-solving strate- gies. We conducted a think-aloud study with university students in the USA (N = 10) and Germany (N = 11), where students worked with either Stoich Tutor and ORCCA before solving stoichiometry problems on paper. Two human coders derived a coding scheme to investigate the strategies American and German students employ during problem solving on paper without instructional support. We derive a taxonomy of three stoichiometry problem-solving strategies. Next to the American fac- tor labeling method, this taxonomy includes a strategy based on equation transformations and a previously undocumented strategy using abstract symbols to isolate a target variable and then pluck in given values and compute the solution. German students exclusively used the latter strategy, which was not explicitly supported by any of the two tutoring systems. Further, students who did not use the factor-label method for paper-based problem solving, most of whom were German, initially had difficulty setting appropriate goals and working with fractions in the Stoich Tutor. While German students preferred ORCCA based on short interviews, they more often successfully solved problems in Stoich Tutor. Therefore, Stoich Tutor, although misaligned with German instruction, could still support German students’ learning. Still, revisions to ITS based on local instructional cultures could make them potentially more effective and aligned with curricular goals.
Organisation(s): Chemistry Education Section
Type: Article
Journal: Journal of Science Education and Technology
No. of pages: 17
ISSN: 1059-0145
Publication date: 11.01.2025
Publication status: E-pub ahead of print
Peer reviewed: Yes
ASJC Scopus subject areas: Education, General Engineering
Electronic version(s): https://doi.org/10.1007/s10956-024-10197-7 (Access: Open)

BibTeX

@article{2fa37c1b1ec940e09207b9aec93eb142,
title = "Problem-Solving Strategies in Stoichiometry Across Two Intelligent Tutoring Systems: A Cross-National Study",
abstract = "Intelligent tutoring system (ITS) provides learners with step-by-step problem-solving support through scaffolding. Most ITSs have been developed in the USA and incorporate American instructional strategies. How do non-American students perceive and use ITS with different native problem-solving strategies? The present study compares Stoich Tutor, an ITS with a high level of scaffolding, with ORCCA, an ITS with dynamic scaffolds that can support a range of problem-solving strate- gies. We conducted a think-aloud study with university students in the USA (N = 10) and Germany (N = 11), where students worked with either Stoich Tutor and ORCCA before solving stoichiometry problems on paper. Two human coders derived a coding scheme to investigate the strategies American and German students employ during problem solving on paper without instructional support. We derive a taxonomy of three stoichiometry problem-solving strategies. Next to the American fac- tor labeling method, this taxonomy includes a strategy based on equation transformations and a previously undocumented strategy using abstract symbols to isolate a target variable and then pluck in given values and compute the solution. German students exclusively used the latter strategy, which was not explicitly supported by any of the two tutoring systems. Further, students who did not use the factor-label method for paper-based problem solving, most of whom were German, initially had difficulty setting appropriate goals and working with fractions in the Stoich Tutor. While German students preferred ORCCA based on short interviews, they more often successfully solved problems in Stoich Tutor. Therefore, Stoich Tutor, although misaligned with German instruction, could still support German students{\textquoteright} learning. Still, revisions to ITS based on local instructional cultures could make them potentially more effective and aligned with curricular goals.",
keywords = "Chemistry Education, intelligent tutoring system (ITS), Scaffolding, Problem-Solving strategy, Stoichometry, Think-aloud protocols, Stoichiometry, Chemistry education, Problem-solving strategy, Intelligent tutoring systems",
author = "Conrad Borchers and Hendrik Fleischer and Yaron, {David J.} and McLaren, {Bruce M.} and Katharina Scheiter and Vincent Aleven and Sascha Schanze",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2025.",
year = "2025",
month = jan,
day = "11",
doi = "10.1007/s10956-024-10197-7",
language = "English",
journal = "Journal of Science Education and Technology",
issn = "1059-0145",
publisher = "Springer Netherlands",
}