A Strategic Implementation of the Average Tree Solution for Cycle-Free Graph Games

In this note we provide a strategic implementation of the Average Tree solution for zero-monotonic cycle-free graph games. That is, we propose a non-cooperative mechanism of which the unique subgame perfect equilibrium payoffs correspond to the average hierarchical outcome of the game. This mechanism takes into account that a player is only able to communicate with other players (i.e., to make proposals about a division of the surplus of cooperation) when they are connected in the graph. © 2013 Elsevier Inc

The Rapamycin-sensitive Phosphoproteome Reveals That TOR Controls Protein Kinase A Toward Some But Not All Substrates

In yeast TOR and PKA pathways both control cell growth but how TORC1 and PKA signaling are linked is unknown. Here we show that TORC1 inhibition prevents the phosphorylation of some but not all PKA targets. We further demonstrate that TORC1 controls PKA by inhibiting the phosphorylation of the PKA regulatory subunit BCY1 by the MAP kinase MPK1

IguideME: Supporting Self-Regulated Learning and Academic Achievement with Personalized Peer-Comparison Feedback in Higher Education

Personalized feedback is important for the learning process, but it is time consuming and particularly problematic in large-scale courses. While automatic feedback may help for self-regulated learning, not all forms of feedback are effective. Social comparison offers powerful feedback but is often loosely designed. We propose that intertwining meaningful feedback with well-designed peer comparison using a learning analytics dashboard provides a solution. Third-year bachelor students were randomly assigned to have access to the learning analytics dashboard IguideME (treatment, n=31) or no access (control, n=31). Dashboard users were asked to indicate their desired grade, which was used to construct peer-comparison groups. Personalized peer-comparison feedback was provided via the dashboard. The effects were studied using quantitative and qualitative data, including the Motivated Strategies for Learning Questionnaire (MSLQ) and the Achievement Goal Questionnaire (AGQ). Compared to the control group, the treatment group achieved higher scores for the MSLQ components “metacognitive self-regulation” and “peer learning,” and for the AGQ component “other-approach” (do better than others). The treatment group performed better on reading assignments and achieved higher grades for high-level Bloom exam questions. These data support the hypothesis that personalized peer-comparison feedback can be used to improve self-regulated learning and academic achievement