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      ElectronixTutor: an intelligent tutoring system with multiple learning resources for electronics

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          Abstract

          Background

          The Office of Naval Research (ONR) organized a STEM Challenge initiative to explore how intelligent tutoring systems (ITSs) can be developed in a reasonable amount of time to help students learn STEM topics. This competitive initiative sponsored four teams that separately developed systems that covered topics in mathematics, electronics, and dynamical systems. After the teams shared their progress at the conclusion of an 18-month period, the ONR decided to fund a joint applied project in the Navy that integrated those systems on the subject matter of electronic circuits. The University of Memphis took the lead in integrating these systems in an intelligent tutoring system called ElectronixTutor. This article describes the architecture of ElectronixTutor, the learning resources that feed into it, and the empirical findings that support the effectiveness of its constituent ITS learning resources.

          Results

          A fully integrated ElectronixTutor was developed that included several intelligent learning resources (AutoTutor, Dragoon, LearnForm, ASSISTments, BEETLE-II) as well as texts and videos. The architecture includes a student model that has (a) a common set of knowledge components on electronic circuits to which individual learning resources contribute and (b) a record of student performance on the knowledge components as well as a set of cognitive and non-cognitive attributes. There is a recommender system that uses the student model to guide the student on a small set of sensible next steps in their training. The individual components of ElectronixTutor have shown learning gains in previous decades of research.

          Conclusions

          The ElectronixTutor system successfully combines multiple empirically based components into one system to teach a STEM topic (electronics) to students. A prototype of this intelligent tutoring system has been developed and is currently being tested. ElectronixTutor is unique in its assembling a group of well-tested intelligent tutoring systems into a single integrated learning environment.

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          Most cited references77

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          The ICAP Framework: Linking Cognitive Engagement to Active Learning Outcomes

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            The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems

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              Educational Outcomes of Tutoring: A Meta-analysis of Findings

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                Author and article information

                Contributors
                graesser@memphis.edu
                Journal
                Int J STEM Educ
                Int J STEM Educ
                International Journal of Stem Education
                Springer International Publishing (Cham )
                2196-7822
                16 April 2018
                16 April 2018
                2018
                : 5
                : 1
                : 15
                Affiliations
                [1 ]ISNI 0000 0000 9560 654X, GRID grid.56061.34, Institute for Intelligent Systems, University of Memphis, ; Memphis, USA
                [2 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Honorary Research Fellow, , University of Oxford, ; Oxford, UK
                [3 ]ISNI 0000 0001 2156 6853, GRID grid.42505.36, Institute for Creative Technologies, University of Southern California, ; Los Angeles, USA
                [4 ]ISNI 0000 0001 2151 2636, GRID grid.215654.1, School of Computing, Informatics and Decision Systems Engineering, , Arizona State University, ; Tempe, USA
                [5 ]ISNI 0000 0001 1957 0327, GRID grid.268323.e, Department of Mathematical Sciences, , Worcester Polytechnic Institute, ; Worcester, USA
                [6 ]ISNI 0000 0001 1957 0327, GRID grid.268323.e, Department of Computer Science, , Worcester Polytechnic Institute, ; Worcester, USA
                [7 ]ISNI 0000 0001 2184 9220, GRID grid.266683.f, Department of Information and Computer Sciences, , University of Massachusetts Amherst, ; Amherst, USA
                [8 ]ISNI 0000 0000 9560 654X, GRID grid.56061.34, Department of Electrical and Computer Engineering, , The University of Memphis, ; Memphis, USA
                Article
                110
                10.1186/s40594-018-0110-y
                6310412
                30631705
                f0874848-c0c8-4b32-9982-7d669bd5531a
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 18 December 2016
                : 25 May 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000006, Office of Naval Research;
                Award ID: N00014-00-1-0600
                Award ID: N00014-15-P-1184
                Award ID: N00014-12-C-0643
                Award ID: N00014-16-C-3027
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: ACI-1443068
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                assistments,autotutor,dragoon,electronics,intelligent tutoring systems,system integration

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