@inproceedings{ddb685df408e4c6bb02e7a1b1c204032,
title = "Worked examples are more efficient for learning than high-assistance instructional software",
abstract = "The {\textquoteleft}assistance dilemma{\textquoteright}, an important issue in the Learning Sciences, is concerned with how much guidance or assistance should be provided to help students learn. A recent study comparing three high-assistance approaches (worked examples, tutored problems, and erroneous examples) and one low-assistance (conventional problems) approach, in a multi-session classroom experiment, showed equal learning outcomes, with worked examples being much more efficient. To rule out that the surprising lack of differences in learning outcomes was due to too much feedback across the conditions, the present follow-up experiment was conducted, in which feedback was curtailed. Yet the results in the new experiment were the same: there were no differences in learning outcomes, but worked examples were much more efficient. These two experiments suggest that there are efficiency benefits of worked example study. Yet, questions remain. For instance, why didn{\textquoteright}t high instructional assistance benefit learning outcomes and would these results hold up in other domains?",
keywords = "Assistance dilemma, Classroom studies, Empirical studies, Worked examples, Erroneous examples, Tutored problems to solve, Problem solving",
author = "McLaren, {Bruce M.} and {van Gog}, Tamara and Craig Ganoe and David Yaron and Michael Karabinos",
year = "2015",
month = jun,
day = "17",
doi = "10.1007/978-3-319-19773-9_98",
language = "English",
isbn = "978-3-319-19772-2",
series = "Lecture Notes in Computer Science ",
publisher = "Springer",
pages = "710--713",
booktitle = "Artificial Intelligence in Education",
address = "Germany",
note = "Artificial Intelligence in Education (AIED) ; Conference date: 22-06-2015 Through 26-06-2015",
}