It’s More Than Self-Presentation: MUM Effects Can Reflect Private Discomfort and Concern for the Recipient

Is the reluctance to share bad news (i.e., the MUM effect) motivated more by a public display or private concern, and does it benefit mainly the messenger or the recipient? An experiment (N = 309) that crossed good/bad news with three communication channels (face-to-face, text messaging, e-mail) revealed that messenger reluctance was greatest under conditions of bad news and did not vary based on the channel through which the recipient contacted the messenger. In contrast with earlier work, this MUM effect was more consistent with a private fear of distressing the recipient. Theoretical implications and limitations are discussed.     

Retrieving and classifying instances of source code plagiarism

Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents.     

Science Instruction for Students with Learning Disabilities: A Meta‐Analysis

Although science has received much attention as a political and educational initiative, students with learning disabilities (LD) perform significantly lower than their nondisabled peers. This meta‐analysis evaluates the effectiveness of instructional strategies in science for students with LD. Twelve studies were examined, summarized, and grouped according to the type of strategy implemented. Effect sizes (ES) were calculated for each study. Across all studies, a mean ES of .78 was obtained, indicating a moderate positive effect on students with LD science achievement. Findings also align with past reviews of inquiry‐based instruction for students with special needs, indicating that students with LD need structure within an inquiry science approach in order to be successful. Additionally, results suggest that mnemonic instruction is highly effective at increasing learning disabled students' acquisition and retention of science facts.     

Symbolic Management of the Degree of Information Security by Integer Splitting

This paper demonstrates the application of module arithmetic for controlling the level of information security by a new technique referred as integer splitting. The basic definitions and concepts of the method are provided. The mathematical function of arising transformation is described in detail; its properties were studied and the basic theorems were proven that justify the use of splitting in practical applications. An active system was designed and characteristic cases of its operation are considered.     

A Campus-Wide Investigation of Clicker Implementation: The Status of Peer Discussion in STEM Classes

At the University of Maine, middle and high school teachers observed more than 250 university science, technology, engineering, and mathematics classes and collected information on the nature of instruction, including how clickers were being used. Comparisons of classes taught with (n = 80) and without (n = 184) clickers show that, while instructional behaviors differ, the use of clickers alone does not significantly impact the time instructors spend lecturing. One possible explanation stems from the observation of three distinct modes of clicker use: peer discussion, in which students had the opportunity to talk with one another during clicker questions; individual thinking, in which no peer discussion was observed; and alternative collaboration, in which students had time for discussion, but it was not paired with clicker questions. Investigation of these modes revealed differences in the range of behaviors, the amount of time instructors lecture, and how challenging the clicker questions were to answer. Because instructors can vary their instructional style from one clicker question to the next, we also explored differences in how individual instructors incorporated peer discussion during clicker questions. These findings provide new insights into the range of clicker implementation at a campus-wide level and how such findings can be used to inform targeted professional development for faculty.