Pass/Fail Grading and Educational Practices in Computer Science

Binary (pass/fail) grading have been shown to have benefits with respect to mental health and collaboration, and is argued to promote a deep approach to learning. However, diverging results with respect to academic achievement suggests that the full benefits of binary grading are contingent on underlying factors, such as how the teaching and learning activities in the course are designed. We here present experiences and student feedback for an intermediate level course in computer science that is graded using pass/fail, and which is highly successful both in terms of of student enjoyment and academic achievement. Survey results also indicate that students apply a deeper learning approach towards the course than average. Drawing on examples and findings from this course, we argue that the following three practices makes a binary graded course in computer science successful: a) a sufficiently high bar for passing, b) clear course requirements, and c) the use of formative assessment

Time-inconsistent Planning: Simple Motivation Is Hard to Find

With the introduction of the graph-theoretic time-inconsistent planning model due to Kleinberg and Oren, it has been possible to investigate the computational complexity of how a task designer best can support a present-biased agent in completing the task. In this paper, we study the complexity of finding a choice reduction for the agent; that is, how to remove edges and vertices from the task graph such that a present-biased agent will remain motivated to reach his target even for a limited reward. While this problem is NP-complete in general, this is not necessarily true for instances which occur in practice, or for solutions which are of interest to task designers. For instance, a task designer may desire to find the best task graph which is not too complicated. We therefore investigate the problem of finding simple motivating subgraphs. These are structures where the agent will modify his plan at most $k$ times along the way. We quantify this simplicity in the time-inconsistency model as a structural parameter: The number of branching vertices (vertices with out-degree at least $2$) in a minimal motivating subgraph. Our results are as follows: We give a linear algorithm for finding an optimal motivating path, i.e. when $k=0$. On the negative side, we show that finding a simple motivating subgraph is NP-complete even if we allow only a single branching vertex --- revealing that simple motivating subgraphs are indeed hard to find. However, we give a pseudo-polynomial algorithm for the case when $k$ is fixed and edge weights are rationals, which might be a reasonable assumption in practice.Comment: An extended abstract of this paper is accepted at AAAI 202

Subgraph Complementation

A subgraph complement of the graph G is a graph obtained from G by complementing all the edges in one of its induced subgraphs. We study the following algorithmic question: for a given graph G and graph class G, is there a subgraph complement of G which is in G? We show that this problem can be solved in polynomial time for various choices of the graphs class G, such as bipartite, d-degenerate, or cographs. We complement these results by proving that the problem is NP-complete when G is the class of regular graphs.publishedVersio

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Subgraph Complementation

A subgraph complement of the graph G is a graph obtained from G by complementing all the edges in one of its induced subgraphs. We study the following algorithmic question: for a given graph G and graph class G, is there a subgraph complement of G which is in G? We show that this problem can be solved in polynomial time for various choices of the graphs class G, such as bipartite, d-degenerate, or cographs. We complement these results by proving that the problem is NP-complete when G is the class of regular graphs