Reasons for Student Engagement in Extra-Class Communication

This study extends instructional communication research on extra-class communication (ECC) by presenting an integrative analysis comparing the explanatory utility of student- and instructor-oriented reasons for student engagement in frequent ECC. Results from 495 college students suggested that student-oriented reasons, specifically the relational and functional student motives, were the only significant, positive predictors of students’ perceptions of frequent ECC engagement. Other student motives (excuse making, participation, sycophancy) and perceptions of instructor approachability did not significantly predict perceived frequency of ECC engagement.     

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.     

Scaling up Content Analysis

ABSTRACT

Employing a number of different standalone programs is a prevalent approach among communication scholars who use computational methods to analyze media content. For instance, a researcher might use a specific program or a paid service to scrape some content from the Web, then use another program to process the resulting data, and finally conduct statistical analysis or produce some visualizations in yet another program. This makes it hard to build reproducible workflows, and even harder to build on the work of earlier studies. To improve this situation, we propose and discuss four criteria that a framework for automated content analysis should fulfill: scalability, free and open source, adaptability, and accessibility via multiple interfaces. We also describe how to put these considerations into practice, discuss their feasibility, and point toward future developments.     

Neuroanatomy Learning: Augmented Reality vs. Cross-Sections

Neuroanatomy education is a challenging field which could benefit from modern innovations, such as augmented reality (AR) applications. This study investigates the differences on test scores, cognitive load, and motivation after neuroanatomy learning using AR applications or using cross-sections of the brain. Prior to two practical assignments, a pretest (extended matching questions, double-choice questions and a test on cross-sectional anatomy) and a mental rotation test (MRT) were completed. Sex and MRT scores were used to stratify students over the two groups. The two practical assignments were designed to study (1) general brain anatomy and (2) subcortical structures. Subsequently, participants completed a posttest similar to the pretest and a motivational questionnaire. Finally, a focus group interview was conducted to appraise participants’ perceptions. Medical and biomedical students (n = 31); 19 males (61.3%) and 12 females (38.7%), mean age 19.2 ± 1.7 years participated in this experiment. Students who worked with cross-sections (n = 16) showed significantly more improvement on test scores than students who worked with GreyMapp-AR (P = 0.035) (n = 15). Further analysis showed that this difference was primarily caused by significant improvement on the cross-sectional questions. Students in the cross-section group, moreover, experienced a significantly higher germane (P = 0.009) and extraneous cognitive load (P = 0.016) than students in the GreyMapp-AR group. No significant differences were found in motivational scores. To conclude, this study suggests that AR applications can play a role in future anatomy education as an add-on educational tool, especially in learning three-dimensional relations of anatomical structures.     

The University Experiences of Students with Learning Disabilities

To explore the university experiences of students with learning disabilities (LD), 63,802 responses to the 2014 Student Experience in the Research University Survey were analyzed. Compared to other students, those with self‐reported LD (5.96 percent) had difficulty with assignments and had more obstacles caused by nonacademic responsibilities and imposed by their skill levels. Students with self‐reported LD sensed more bias toward people with disabilities on campus, and they were less satisfied with their overall experience. Interactions between disability status and age suggested even more challenges for older students who self‐reported LD. Approximately one‐third of students who self‐reported LD received accommodations. The rate of accommodations was higher among individuals who were wealthy, who lived alone, and who were out‐of‐state students. Compared to students who self‐reported LD but reported no accommodations, those with accommodations had more contact with faculty and less difficulty with assignments.     

The power of refutational text: changing intuitions about the interpretation of box plots

European Journal of Psychology of Education - Graphicacy is an important skill in today’s society; however, the interpretation of graphs proofs to be more difficult than it might seem. In...