The Challenges of Building Intelligent Tutoring Systems for Teams

Bonner, Desmond; Gilbert, Stephen B.; Dorneich, Michael C.; Winer, Eliot H.; Sinatra, Anne M.; Slavina, Anna; MacAllister, Anastacia; Holub, Joseph

doi:10.1177/1541931213601451

Cited by 13 publications

(8 citation statements)

References 20 publications

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“…In early implementations of this task, the members were required to use specific military phrases designated by the research personnel, but this requirement was sufficiently onerous to prevent some teams from reaching consistent performance levels, even after multiple trials. Additional details on the creation and military basis of this task are described in detail in Bonner et al (2015b), Bonner et al (2016a), and Bonner et al (2016b). While the task context was relatively simple, the Surveillance Scenario became a powerful research testbed because of the ability to explore numerous team tutor research questions using the same task, such as how cognitive load affects ability to perceive feedback, whether knowing one's team member previously affects performance, how consecutive trials form a learning curve, how that learning curve is affected by different forms of feedback, and many others.…”

Section: Goal 2: the Surveillance Scenariomentioning

confidence: 99%

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Creating a Team Tutor Using GIFT

Gilbert

Slavina

Dorneich

et al. 2017

Int J Artif Intell Educ

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With the movement in education towards collaborative learning, it is becoming more important that learners be able to work together in groups and teams. Intelligent tutoring systems (ITSs) have been used successfully to teach individuals, but so far only a few ITSs have been used for the purpose of training teams. This is due to the difficulty of creating such systems. An ITS for teams must be able to assess complex interactions between team members (team skills) as well as the way they interact with the system itself (task skills). Assessing team skills can be difficult because they contain social components such as communication and coordination that are not readily quantifiable. This article addresses these difficulties by developing a framework to guide the authoring process for team tutors. The framework is demonstrated using a case study about a particular team tutor that was developed using a military surveillance scenario for teams of two. The Generalized Intelligent Framework for Tutoring (GIFT) software provided the team tutoring infrastructure for this task. A new software architecture required to support the team tutor is described. This theoretical framework and the lessons learned from its implementation offer conceptual scaffolding for future authors of ITSs.

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Section: Goal 2: the Surveillance Scenariomentioning

confidence: 99%

“…The other elements are the ten steps for authoring a team tutor described below and in Fig. 5, which have been adapted and expanded from the eight steps described in Bonner et al (2016a).…”

Section: Goal 4: Team Tutor Framework -Steps Of Authoring a Team Tutormentioning

confidence: 99%

Creating a Team Tutor Using GIFT

Gilbert

Slavina

Dorneich

et al. 2017

Int J Artif Intell Educ

Self Cite

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“…Some of the effects are the cost of implementation by researchers, users become socially isolated, lack of communication skills by users, the exposure of users to harmful contents, and many more [19]. is is also supported by other research which stated that developing an intelligent tutoring system is not an easy task and can only be possible with lots of authoring guidelines, feedbacks, and a good team of researchers and developers surrounding the creation of an intelligent tutoring system and serves as its main resource [20].…”

Section: Current and Previous Researchmentioning

confidence: 84%

Intelligent Tutoring System: Learning Math for 6th-Grade Primary School Students

King

Thouvenot

Kelvin

et al. 2021

Education Research International

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This paper proposes a web-based application designed to help elementary school students who have difficulty learning online independently and also their parents who are currently having difficulty teaching their children to study at home online, especially at this time of difficulty with a pandemic outbreak like COVID-19; this time does not allow for physical meetings for the learning process in primary schools. In this paper, we only focus on mathematics because based on several other studies, it is very difficult and important to learn mathematics at the beginning of educational activities such as at the elementary school level. In this paper, the system is modeled using the Unified Modeling Language (UML) tool in the form of a use case diagram which is used to describe the proposed business process and uses class diagrams to describe the database model diagram. In this case, the class diagram is used to describe the data in the class diagram where each class refers to a table in the database. The web-based application user interface is shown at the end to show the communication between users and applications, where this web-based application is implemented using Personal Home Pages (PHP) as server programming and using MySQL to store database model designs. Moreover, for the Intelligent Tutoring System (ITS), content was created using the Cognitive Tutor Authoring Tools (CTAT) which is an authoring tool for learning mathematics created by Carnegie Mellon University. In the end, this web-based application is expected to be used and support teachers as a complement to online mathematics learning, especially during difficult times such as during the COVID-19 pandemic.

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“…Over the past several years, the authors and their colleagues developed and conducted research with the Surveillance Task (two-person team, both same role), the Surveillance with Sniper Task (three-person team, one sniper and two spotter roles), and the Team Multiple Errands Task (three-person team, all the same role). The Surveillance Task is described in more detail in Bonner et al (2016; and Gilbert et al (2017). Each of two team members play the role of a spotter atop a building in the center of a small town and must report to each other when people on the ground below move out of one member's zone into the other member's zone, e.g., "Two people entering your zone at the pole.…”

Section: Three Intelligent Team Tutoring Systemsmentioning

confidence: 99%

Five Lenses on Team Tutor Challenges: A Multidisciplinary Approach

Gilbert¹,

Dorneich²,

Walton³

et al. 2018

Research on Managing Groups and Teams

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This chapter describes five disciplinary domains of research or lenses that contribute to the design of a team tutor. We focus on four significant challenges in developing Intelligent Team Tutoring Systems (ITTSs), and explore how the five lenses can offer guidance for these challenges. The four challenges arise in the design of team member interactions, performance metrics and skill development, feedback, and tutor authoring. The five lenses or research domains that we apply to these four challenges are Tutor Engineering, Learning Sciences, Science of Teams, Data Analyst, and Human-Computer Interaction. This matrix of applications from each perspective offers a framework to guide designers in creating ITTSs.

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The Challenges of Building Intelligent Tutoring Systems for Teams

Cited by 13 publications

References 20 publications

Creating a Team Tutor Using GIFT

Creating a Team Tutor Using GIFT

Intelligent Tutoring System: Learning Math for 6th-Grade Primary School Students

Five Lenses on Team Tutor Challenges: A Multidisciplinary Approach

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