Performance has many dimensions and judging performance of a team/company also depends on the point of view of the judge. Performance of innovative business groups can be measured in hard facts such as turnover, budget achievement or number of products marketed as key variables but their success can be judged by less well definable criteria such as communication levels between team members and others, which has been found to relate to performance (Allen, 1984, as cited in Ancona & Caldwell, 1992). Team potency (a team member’s belief in the team’s effectiveness) was positively related to individuals’ self-ratings of effectiveness as well as the team managers’ appraisals (Ilgen, Hollenbeck, Johnson & Jundt, 2005). Hence both team efficacy and potency are meaningful predictors of team performance.
In business settings many studies use performance ratings of team members from superior members of the company, either the supervisory or managerial team or the human resources department. These are often derived from post team event questionnaires assessing how the team performed in terms of efficiency, quality, technical innovation, adherence to schedules, adherence to budget and work excellence and the scores are either averaged or summed across all team members to get a team score (Ancona & Caldwell, 1992; Cohen & Ledford, 1994; Chowdhury,2005). For example, Choudhury (2005) studying diversity in building effective entrepreneurial teams, adapted a questionnaire to measure team effectiveness, including both team outcomes and team behaviours. Each person rated his/her team on a 5-point Likert
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scale and a composite score was calculated from team commitment, team-level cognitive comprehensiveness and team effectiveness scores. By averaging the scores from all the items, a single score was produced for each team. Cohen and Ledford (1994) studied the effectiveness of 84 self-managing teams within a telecommunications company. Three domains of group effectiveness were used: job satisfaction, group performance and group member behaviours. These were all measured by surveys given not only to the group members but also supervisors and higher-level managers. The higher level managers rated the performance differently to the group members and supervisors by rating the groups against all other groups in the organization that carried out similar work on quality, efficiency and overall performance. These management ratings were checked against company performance records to ensure they were grounded in performance data alongside on-job accidents, absenteeism and illness data.
Others have judged their performance in terms of commitment to team, interpersonal skills, initiative, knowledge of tasks, planning and allocation (Barrick, Stewart Neubert & Mount, 1998). Bray, Kerr and Atkin (1978) used the team members themselves to rate the team in terms of dyadic items such as pleasant-unpleasant, warm-cold, friendly-unfriendly, cooperative-uncooperative, serious-not-serious and goal oriented-not goal oriented. They used these six bipolar adjectives to assess the group atmosphere as well as testing the proportion of correct solutions to the tasks and the speed of solution.
Alternative methods have been used for judging team performance such as the team’s profit made in the task (Chong 2007) or teams pitted one against another and the winner noted (Jackson, 2002). Chong’s study (2007), although classroom based, was of team roles in relation to Belbin’s3 team role inventory (1993). The team worked on a variety of eight tasks whilst operating as a management group, planning the production of custom-made paper bags that were sold to customers. Jackson’s study
3 Belbin (1981): team success was dependent on having members who fulfilled eight specific
roles within the team. Some team members can take on more than one role in smaller teams. Later this was altered to include a ninth role (Belbin, 1993): specialist, co-ordinator, shaper, plant, monitor-evaluator, implementer, resource investigator, team worker and complete finisher.
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(2002) aimed to see if Kolb’s4 (1984) learning cycle or Belbin’s (1993) team role questionnaire were predictive of team performance. This was carried out on a two-day residential course from employees of a national insurance company. Therefore, although classroom based, this study was more reminiscent of a workplace study in that the participants worked together in their usual work groups within the organisation. Team performance was recorded by pitting two teams against each other answering a series of riddles, and from the answers, solving a clue and noting which team obtained the correct answer fastest. The main problem with this measure of performance success is that the dichotomy of the result (win: lose) meant that large or small differences in success were not recorded. Some of the differences between winning and losing were very small and yet were recorded in the same manner as a large difference.
Peeters, van Tuijl, Rutte and Reyment (2006) suggested that teams would differ based on whether they were a professional or a student team. In their view, professional teams would have greater experience leading to smoother co-operation between members and that the members would work together for longer periods of time, thereby building on longer term relationships. Teams that have been put together in classroom situations, as opposed to business settings, tend to have their performance judged by module grades or by member satisfaction either summed or averaged (Kamp, Dolmans, Van Berkel & Schmidt, 2012; Aggarwal & O’Brien, 2008; Barry & Stewart, 1997; Cogliser, Gardner, Gavin & Broberg, 2012; Dommeyer, 2007). On the whole, the method of aggregating the individual members’ grades of educational teams’ scores allows for subtle differences in teams’ performance to be noted. It is hard in an educational team task to evaluate students without rewarding a poor performing individual with a high grade or downgrading an engaged student in a poor team. So various strategies can be embedded in the course which includes peer assessment and individual effort analysis alongside the mean grade for the team
4 The Kolb (1984) learning cycle: people learn using four different learning modes: learning by
specific experience; learning by reflection, watching before judging; learning by thinking after having understood the issues intellectually; and learning by doing, taking risks. Kolb (1984) classified learners into different learning styles on how they combined these learning elements.
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members. Braender and Naples (2013) found that a student’s participation log which combined student usage (for example to upload journals, send emails and chat between team members) with teacher access correlated with team project grades and unearthed potential social loafers or free riders. This enabled teaching staff to objectively allocate grades to students.
Teams’ performance can be judged in many ways but for educational teams task work grades are an easy and accessible method to execute. However the grades should have some mechanism to expose those team members who have failed to engage with the team goals to be exposed.