Authoring Tools for Collaborative Intelligent Tutoring System Environments

Olsen, Jennifer K.; Belenky, Daniel M.; Aleven, Vincent; Rummel, Nikol; Sewall, Jonathan; Ringenberg, Michael A.

doi:10.1007/978-3-319-07221-0_66

Cited by 20 publications

(21 citation statements)

References 11 publications

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“…While detectors in CT+A operate client-side, within individual students' tutors, and thus can only compute analytics for individual students, it is often useful for learning analytics applications (e.g., teacher dashboards) to compute analytics at higher units of analysis, such as groups of students or whole classes. For example, in classrooms in which students work with CTAT tutors collaboratively (c.f., [31]), information about the relative performance and contributions of the students in a group might be useful to display to teachers. To address this need, the extended architecture provides an "aggregator" API to enable authors to compute custom group-or class-level analytics from student model variables across multiple students.…”

Section: Support For Using Learning Analytics In External Support Toolsmentioning

confidence: 99%

Opening Up an Intelligent Tutoring System Development Environment for Extensible Student Modeling

Holstein

Sewall

et al. 2018

Lecture Notes in Computer Science

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ITS authoring tools make creating intelligent tutoring systems more cost effective, but few authoring tools make it easy to flexibly incorporate an open-ended range of student modeling methods and learning analytics tools. To support a cumulative science of student modeling and enhance the impact of real-world tutoring systems, it is critical to extend ITS authoring tools so they easily accommodate novel student modeling methods. We report on extensions to the CTAT/Tutorshop architecture to support a plug-in approach to extensible student modeling, which gives an author full control over the content of the student model. The extensions enhance the range of adaptive tutoring behaviors that can be authored and support building external, student-or teacher-facing real-time analytics tools. The contributions of this work are: (1) an open architecture to support the plugging in, sharing, re-mixing, and use of advanced student modeling techniques, ITSs, and dashboards; and (2) case studies illustrating diverse ways authors have used the architecture.

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Section: Support For Using Learning Analytics In External Support Toolsmentioning

confidence: 99%

Opening Up an Intelligent Tutoring System Development Environment for Extensible Student Modeling

Holstein

Sewall

et al. 2018

Lecture Notes in Computer Science

Self Cite

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“…Beyond these basic behaviors CTAT's example-tracing technology supports a range of additional inner loop behaviors (see Table 1). Whereas CTAT originally supported tutors for individual learning only, we recently added support for authoring collaborative example-tracing tutors (Olsen et al 2014b), described in more detail below. We also added support for gradually fading worked examples, based on research that demonstrated the effectiveness of this way of transitioning from examples to problem solving (e.g., Atkinson et al 2003;Renkl et al 2003;Salden et al 2010a).…”

Section: Inner Loop: Using a Behavior Graph To Provide Tutoringmentioning

confidence: 99%

“…They have lowered the skill threshold for building tutors. Some studies have provided estimates of cost savings (Aleven et al 2009b;Razzaq et al 2009) or have empirically evaluated the authoring efficiency of ITS authoring tools (Aleven et al 2006b;Blessing and Gilbert 2008;Devasani et al 2012;Kodaganallur et al 2005;MacLellan et al 2014;Paquette et al 2010;Razzaq et al 2009).…”

Section: Introductionmentioning

confidence: 99%

Example-Tracing Tutors: Intelligent Tutor Development for Non-programmers

Aleven

McLaren

Sewall

et al. 2016

Int J Artif Intell Educ

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104

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In 2009, we reported on a new Intelligent Tutoring Systems (ITS) technology, example-tracing tutors, that can be built without programming using the Cognitive Tutor Authoring Tools (CTAT). Creating example-tracing tutors was shown to be 4-8 times as cost-effective as estimates for ITS development from the literature. Since 2009, CTAT and its associated learning management system, the Tutorshop, have been extended and have been used for both research and real-world instruction. As evidence that example-tracing tutors are an effective and mature ITS paradigm, CTAT-built tutors have been used by approximately 44,000 students and account for 40 % of the data sets in DataShop, a large open repository for educational technology data sets. We review 18 example-tracing tutors built since 2009, which have been shown to be effective in helping students learn in real educational settings, often with large pre/post effect sizes. These tutors support a variety of pedagogical approaches, beyond step-based problem solving, including collaborative learning, educational games, and guided invention activities. CTAT and other ITS authoring tools illustrate that non-programmer approaches to building ITS are viable and useful and will likely play a key role in making ITS widespread.

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“…CTAT has been shown to reduce development costs by a factor of 4 to 8 [2]. Olsen et al extended CTAT to support the authoring of collaborative ITSs built around collaborative scripts [18]. We take a different approach to improving the scaffolding authoring process.…”

Section: Intelligent Tutoring Systemsmentioning

confidence: 99%

A Framework for Automatically Generating Interactive Instructional Scaffolding

O’Rourke

Andersen

Gulwani

et al. 2015

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

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Interactive learning environments such as intelligent tutoring systems and software tutorials often teach procedures with step-by-step demonstrations. This instructional scaffolding is typically authored by hand, and little can be reused across problem domains. In this work, we present a framework for generating interactive tutorials from an algorithmic representation of the problem-solving thought process. Given a set of mappings between programming language constructs and user interface elements, we step through this algorithm lineby-line to trigger visual explanations of each step. This approach allows us to automatically generate tutorials for any example problem that can be solved with this algorithm. We describe two prototype implementations in the domains of K-12 mathematics and educational games, and present results from two user studies showing that educational technologists can author thought-process procedures and that generated tutorials can effectively teach a new procedure to students.

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Authoring Tools for Collaborative Intelligent Tutoring System Environments

Cited by 20 publications

References 11 publications

Opening Up an Intelligent Tutoring System Development Environment for Extensible Student Modeling

Opening Up an Intelligent Tutoring System Development Environment for Extensible Student Modeling

Example-Tracing Tutors: Intelligent Tutor Development for Non-programmers

A Framework for Automatically Generating Interactive Instructional Scaffolding

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