After working with 2 pairs of library student assistants, I made a few changes: students will only find 1-3 relevant articles, each team will keep track of their own score, and then score another team as evaluators. Scoring for relevance: 5 points for each article on topic. The students indicated that extra credit points are the most motivating.
More on higher education teaching and learning theory: this is a game (problem solving) in which students collaborate (work in teams) to apply concepts (advanced searching techniques) to get relevant results. They will negotiate meaning (provide each other feedback). The professor will track deep learning afterward by monitoring the follow-up transfer of learning to new situations (students will search their own topics, a.k.a., secondary research questions, both in databases and in Google).
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I can't wait to see how you apply this to post-graduate studies, as those students surely need a boost, too. ;-)
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