scholarly journals Using the Weighted Kendall Distance to Analyze Rank Data in Psychology

2021 ◽  
Author(s):  
Johnny van Doorn ◽  
Michael David Lee ◽  
Holly Westfall

Although the Kendall distance is a standard metric in computer science, it is less widely used in psychology. We demonstrate the usefulness of the Kendall distance for analyzing psychological data that take the form of ranks, lists, or orders of items. We focus on weighted extensions of the metric that allow for heterogeneity of item importance, item position, and item similarity, as well showing how the metric can accommodate missingness in the form of top-k lists. To demonstrate how the Kendall distance can help address research questions in psychology, we present four applications to previous data. These applications involve the recall of events on September 11, people's preference rankings for the months of the year, people's free recall of animal names in a clinical setting, and expert predictions involving American football outcomes.

2022 ◽  
Vol 22 (1) ◽  
pp. 1-46
Author(s):  
Sarah Heckman ◽  
Jeffrey C. Carver ◽  
Mark Sherriff ◽  
Ahmed Al-zubidy

Context. Computing Education Research (CER) is critical to help the computing education community and policy makers support the increasing population of students who need to learn computing skills for future careers. For a community to systematically advance knowledge about a topic, the members must be able to understand published work thoroughly enough to perform replications, conduct meta-analyses, and build theories. There is a need to understand whether published research allows the CER community to systematically advance knowledge and build theories. Objectives. The goal of this study is to characterize the reporting of empiricism in Computing Education Research literature by identifying whether publications include content necessary for researchers to perform replications, meta-analyses, and theory building. We answer three research questions related to this goal: (RQ1) What percentage of papers in CER venues have some form of empirical evaluation? (RQ2) Of the papers that have empirical evaluation, what are the characteristics of the empirical evaluation? (RQ3) Of the papers that have empirical evaluation, do they follow norms (both for inclusion and for labeling of information needed for replication, meta-analysis, and, eventually, theory-building) for reporting empirical work? Methods. We conducted a systematic literature review of the 2014 and 2015 proceedings or issues of five CER venues: Technical Symposium on Computer Science Education (SIGCSE TS), International Symposium on Computing Education Research (ICER), Conference on Innovation and Technology in Computer Science Education (ITiCSE), ACM Transactions on Computing Education (TOCE), and Computer Science Education (CSE). We developed and applied the CER Empiricism Assessment Rubric to the 427 papers accepted and published at these venues over 2014 and 2015. Two people evaluated each paper using the Base Rubric for characterizing the paper. An individual person applied the other rubrics to characterize the norms of reporting, as appropriate for the paper type. Any discrepancies or questions were discussed between multiple reviewers to resolve. Results. We found that over 80% of papers accepted across all five venues had some form of empirical evaluation. Quantitative evaluation methods were the most frequently reported. Papers most frequently reported results on interventions around pedagogical techniques, curriculum, community, or tools. There was a split in papers that had some type of comparison between an intervention and some other dataset or baseline. Most papers reported related work, following the expectations for doing so in the SIGCSE and CER community. However, many papers were lacking properly reported research objectives, goals, research questions, or hypotheses; description of participants; study design; data collection; and threats to validity. These results align with prior surveys of the CER literature. Conclusions. CER authors are contributing empirical results to the literature; however, not all norms for reporting are met. We encourage authors to provide clear, labeled details about their work so readers can use the study methodologies and results for replications and meta-analyses. As our community grows, our reporting of CER should mature to help establish computing education theory to support the next generation of computing learners.


1997 ◽  
Vol 21 (2) ◽  
pp. 229-252
Author(s):  
Melvin H. Marx ◽  
Yung Che Kim ◽  
Bruce B. Henderson

Four experiments were conducted to compare developmental changes in free recall and frequency judgement. In Experiment 1, 1012 Korean students were shown a series of animal names and then asked to recall them and to estimate the frequency with which they had occurred. The poorest performance on both tasks was by primary-school students and the best by secondary-school students; college students were intermediate in performance. Essentially similar results were obtained in Experiment 2, with an additional 288 Korean students, except that secondary-school students did not perform better than college students. In this experiment, there was complete control of item specificity over frequency and any possible clustering effect was eliminated by using unrelated words rather than animal names. In Experiment 3, the developmental trends in frequency judgement were replicated with 193 American students. Those developmental trends were obtained with another 186 American students in Experiment 4 using relative frequency judgements. Retrospective reports about how frequency judgements were made suggested a developmental shift from more literal counting strategies to more intuitive strength impression judgements. The results are interpreted as suggesting the need for some modification of the Hasher and Zacks (1979, 1984) age-invariance proposition for frequency judgement.


2021 ◽  
Vol 12 (1) ◽  
pp. 4
Author(s):  
Andrea C. Burrows ◽  
Mike Borowczak ◽  
Bekir Mugayitoglu

Computer science, cybersecurity education, and microcredentials are becoming more pervasive in all levels of the educational system. The purpose of this study was partnering with precollegiate teachers: (1) to investigate the self-efficacy of 30 precollegiate teacher participants towards computer science before, during, and after three iterations of a cybersecurity microcredential, and (2) to make changes to the cybersecurity microcredential to improve its effectiveness. The authors explored what teachers need in a microcredential. The first Cohort (n = 5) took the microcredential sequence over 28 days in the summer of 2020, the second Cohort (n = 16) took it over 42 days in the fall of 2020, and the third Cohort (n = 9) took it over 49 days in the summer of 2021. The authors investigated three research questions and used a systems thinking approach while developing, evaluating, and implementing the research study. The researchers used quantitative methods in the collection of a self-efficacy subscale survey to assess whether the precollegiate teachers’ beliefs about computer science changed, and then used qualitative methods when conducting semi-structured teacher participant interviews to address the research questions. The findings show that the precollegiate teachers’ self-efficacy scores towards computer science increased, and that there are areas in need of attention, such as resources and implementation, when creating microcredentials. The implications of this research include the importance of purposefully crafting microcredentials and professional developments, including aspects of creating effective partnerships.


Author(s):  
Heinrich C. Mayr ◽  
Bernhard Thalheim

AbstractWe understand this paper as a contribution to the “anatomy” of conceptual models. We propose a signature of conceptual models for their characterization, which allows a clear distinction from other types of models. The motivation for this work arose from the observation that conceptual models are widely discussed in science and practice, especially in computer science, but that their potential is far from being exploited. We combine our proposal of a more transparent explanation of the nature of conceptual models with an approach that classifies conceptual models as a link between the dimension of linguistic terms and the encyclopedic dimension of notions. As a paradigm we use the triptych, whose central tableau represents the model dimension. The effectiveness of this explanatory approach is illustrated by a number of examples. We derive a number of open research questions that should be answered to complete the anatomy of conceptual models.


2019 ◽  
Vol 9 (2) ◽  
pp. 69 ◽  
Author(s):  
Adrienne Decker ◽  
Monica McGill

There has been considerable investment in pre-college educational interventions for all areas of STEM (including computer science). The goal of many of these initiatives is to engage and interest students early in their educational career. In this study, a systematic literature review was undertaken to determine the demographic and program data collected and reported for the field of computing education and for other STEM disciplines for activities that were not designed as part of the formal in-class curriculum (e.g., outreach activities). A comparison-contrast analysis of the resulting 342 articles found similarities and key differences in the reporting of this data as well as overarching characteristics of missing or incomplete reporting across disciplines. Authors from both fields reported equally well in the four categories studied: information about evaluation, participant gender, participant race and/or ethnicity, and activity demographics. However, the computing education articles were more likely to have clearly stated research questions and comparative analysis based on demographic characteristics. They were less likely to include the number of participants in the study, participant age/grade level, socioeconomic status, disability information, location of intervention, and instructor demographics. Through this analysis, it was determined that reporting can be improved across all disciplines to improve the quantity of data needed to replicate studies and to provide complete data sets that provide for the comparison of collected data.


Author(s):  
Carmen Soler-Monreal

Abstract This study investigates the predominant moves and move patterns used in the separate final conclusion chapters of 48 PhD theses of computer science at a UK university. The focus is on the most salient connections of steps in the review of the study (Move 1) with steps for the consolidation of research space (Move 2). The most common combinations relate (1) a summary of the thesis work to the product and the evaluation of the product, (2) the purpose, thesis statement or hypothesis to the findings or results, (3) the research questions to the methodology, product or claim, (4) a problem or need to a specific methodology, a new product and/or a claim, and (5) a summary of the work done in each thesis chapter to the findings and claims. Some findings are specific of the field of computer science. The study has pedagogical implications for courses of English for Academic Purposes (EAP).


2001 ◽  
Vol 22 (3) ◽  
Author(s):  
Peter McBurney ◽  
Simon Parsons

Formal dialogue games have been studied in philosophy since at least the time of Aristotle. Recently they have been applied in various contexts in computer science and artificial intelligence, particularly as the basis for interaction between autonomous software agents. We review these applications and discuss the many open research questions and challenges at this exciting interface between philosophy and computer science.


2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Maja Van der Velden ◽  
Børge Kile Gjelsten ◽  
Gunnar Rye Bergersen ◽  
Siri Moe Jensen

Digitalisation creates opportunities and challenges, both socially and environmentally. Are computer science students interested in addressing these opportunities and challenges and is their education providing them the desired competencies? Theoretically, the paper focuses on the concept of competency and presents the eight sustainability competencies formulated in UNESCO’s Education for the Sustainable Development Goals. Two sets of data are analysed to address the research questions: data from a questionnaire focusing on their aspirations for future work and data from a deductive content analysis of the learning outcomes of six bachelor programmes in informatics. Sustainability-related factors scored important/very important in the aspirations for future work. The analysis of the learning outcomes indicates a very weak connection between learning goals and sustainability competencies. An integrative approach is proposed, which may contribute to the development of sustainability competencies that enable the students to take up normative and critical positions in digitalisation and sustainability discourses.


2021 ◽  
Vol 13 (24) ◽  
pp. 13677
Author(s):  
Mazaher Kianpour ◽  
Stewart J. Kowalski ◽  
Harald Øverby

Insights in the field of cybersecurity economics empower decision makers to make informed decisions that improve their evaluation and management of situations that may lead to catastrophic consequences and threaten the sustainability of digital ecosystems. By drawing on these insights, cybersecurity practitioners have been able to respond to many complex problems that have emerged within the context of cybersecurity over the last two decades. The academic field of cybersecurity economics is highly interdisciplinary since it combines core findings and tools from disciplines such as sociology, psychology, law, political science, and computer science. This study aims to develop an extensive and consistent survey based on a literature review and publicly available reports. This review contributes by aggregating the available knowledge from 28 studies, out of a collection of 628 scholarly articles, to answer five specific research questions. The focus is how identified topics have been conceptualized and studied variously. This review shows that most of the cybersecurity economics models are transitioning from unrealistic, unverifiable, or highly simplified fundamental premises toward dynamic, stochastic, and generalizable models.


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