The Team Multiple Errands Test: A Platform to Evaluate Distributed Teams

Teams have the ability to achieve goals that are unobtainable by individuals alone. However, there is little agreement on a standard model for researching the performance of distributed teams. Initial pilot results suggest that the Multiple Errands Test (MET), when adapted to a team in a virtual environment, is a platform for evaluating the impact of feedback characteristics. To demonstrate the potential of the Team MET as a platform for future team research in the broader CSCW community, an example study is described in which team members are given feedback in one of four conditions: individual private, team private, individual public, and team public

Taxonomy of Teams, Team Tasks, and Tutors

While significant research has been done on teams and teaming (Salas, et al. 2004), less work has been done to characterize teams and team tasks in terms of the feasibility for them to benefit from intelligent tutoring. This theoretical paper begins to describe how the parameters of team structures addressed may affect the ways in which a team can accommodate external guidance. In addition, parameters of team tasks and resulting team tutors are also described. Examples of both team structures and team tasks are provided so that the resulting theoretical framework offers guidance for design decisions during the construction of intelligent tutoring systems (ITSs) for teams and the Generalized Intelligent Framework for Tutoring’s (GIFT) supporting team architecture. ITSs have been successful at improving performance in a wide variety of domains ranging from academic topics such as math (e.g., Koedinger, Anderson, Hadley & Mark, 1997) to work-based tasks such as management of power plants (Faria, Silva, Vale & Marques, 2009). However, there have been few ITSs designed for educating or training teams (Sottilare, Holden, Brawner & Goldberg, 2011). Despite much research on teaming since the 1970s, team performance is widely variable and difficult to predict (Sims & Salas, 2007), and there is a significant need for team-based ITSs. A taxonomy of team tutoring is present-ed (see Figure 29 for top level key elements). This paper describes three taxonomies: teams, team tasks, and relevant tutoring factors. The taxonomies are based on reviewing the teaming literature with a particular focus on the characteristics of each that would influence the design of a team-based intelligent tutoring system. This work leverages the extensive literature review of teaming by Burke et al. (in progress) as well as recent work that has sought to identify those major factors which impact team performance Salas, Shuffler, Thayer, Bedwell & Lazzara (in press). The taxonomies provided below are designed to help guide the design of software architecture to support team ITSs within GIFT. GIFT is a powerful software architecture designed to support a wide spectrum of intelligent tutoring. It supports the traditional components of most ITSs: the learner model, the domain model, the pedagogical model, and the learner interface, but does so generically (Sottilare, Brawner, Goldberg & Holden, 2012; Sottilare, Graesser, Hu & Holden, 2013). Thus, a multitude of learners might manipulate a wide range of user interfaces as they engage with various domains while being taught using 190 a variety of pedagogies. However, the GIFT architecture does not naturally support teams. Team compo-nents are necessary if GIFT is to support team tutoring, but they are not present in the current release. In their 2011 paper, Sottilare et al., the creators of GIFT, describe the challenges of creating team tutors in detail

Analysis of ligation and DNA binding by Escherichia coli DNA ligase (LigA).

NAD+-dependent DNA ligases are essential enzymes in bacteria, with the most widely studied of this class of enzymes being LigA from Escherichia coli. NAD+-dependent DNA ligases comprise several discrete structural domains, including a BRCT domain at the C-terminus that is highly-conserved in this group of proteins. The over-expression and purification of various fragments of E. coli LigA allowed the investigation of the different domains in DNA-binding and ligation by this enzyme. Compared to the full-length protein, the deletion of the BRCT domain from LigA reduced in vitro ligation activity by 3-fold and also reduced DNA binding. Using an E. coli strain harbouring a temperature-sensitive mutation of ligA, the over-expression of protein with its BRCT domain deleted enabled growth at the non-permissive temperature. In gel-mobility shift experiments, the isolated BRCT domain bound DNA in a stable manner and to a wider range of DNA molecules compared to full LigA. Thus, the BRCT domain of E. coli LigA can bind DNA, but it is not essential for DNA nick-joining activity in vitro or in vivo

Operationalizing the C’s of Teamwork in an Intelligent Tutoring System

One of the difficulties in creating a team-focused intelligent tutoring system (ITS) is defining the measures used to assess the team’s performance. While the team research literature offers nine C’s of teamwork to consider, e.g., cooperation, communication, etc., it can also be difficult to implement these in real-world practice. This paper reviews the approach used in three team ITSs in which the C’s were used, offering guidance for future implementation of team tutors