Crowdsourcing Classroom Observations to Identify Misconceptions in Data Science

Web-browsing histories, online newspapers, streaming music, and stock prices all show that we live in an age of data. Extracting meaning from data is necessary in many fields to comprehend the information flow. This need has fueled rapid growth in data science education aiming to serve the next generation of policy makers, data science researchers, and global citizens. Initially, teaching practices have been drawn from data science\u27s parent disciplines (e.g., computer science and mathematics). This project addresses the early stages of developing a concept inventory of student difficulty within the newly emerging field of data science. In particular this project will address three primary research objectives: (1) identify student misconceptions in data science courses; (2) document students’ prior knowledge and identify courses that teach early data science concepts; and (3) confirm expert identification of data science concepts, and their importance for introductory-level data science curricula. During the first year of this grant, we have collected approximately 200 responses for a survey to confirm concepts from an existing body of knowledge presented by the Edison Project. Survey respondents are comprised of faculty and industry practitioners within data science and closely related fields. Preliminary analysis of these results will be presented with respect to our third research objective. In addition, we developed and launched a pilot assessment for identifying student difficulties within data science courses. The protocol includes regular responses to reflective questions by faculty, teaching assistants, and students from selected data science courses offered at the three participating institutions. Preliminary analyses will be presented along with implications for future data collection in year two of the project. In addition to the anticipated results, we expect that the data collection and analysis methodologies will be of interest to many scholars who have or will engage in discipline-based educational research

Using Concept Inventories to Measure Understanding

Measuring understanding is notoriously difficult. Indeed, in formulating learning outcomes the word “understanding” is usually avoided, but in the sciences, developing understanding is one of the main aims of instruction. Scientific knowledge is factual, having been tested against empirical observation and experimentation, but knowledge of facts alone is not enough. There are also models and theories containing complex ideas and inter-relationships that must be understood, and considerable attention has been devoted across a range of scientific disciplines to measuring understanding. This case study will focus on one of the main tools employed: the concept inventory and in particular the Force Concept Inventory. The success of concept inventories in physics has spawned concept inventories in chemistry, biology, astronomy, materials science and maths, to name a few. We focus here on the FCI, ask how useful concept inventories are for evaluating learning gains. Finally, we report on recent work by the authors to extend conceptual testing beyond the multiple-choice format

Investigating students seriousness during selected conceptual inventory surveys

Conceptual inventory surveys are routinely used in education research to identify student learning needs and assess instructional practices. Students might not fully engage with these instruments because of the low stakes attached to them. This paper explores tests that can be used to estimate the percentage of students in a population who might not have taken such surveys seriously. These three seriousness tests are the pattern recognition test, the easy questions test, and the uncommon answers test. These three tests are applied to sets of students who were assessed either by the Force Concept Inventory, the Conceptual Survey of Electricity and Magnetism, or the Brief Electricity and Magnetism Assessment. The results of our investigation are compared to computer simulated populations of random answers.Comment: 8 pages; submitted to Phys Rev PE

Information systems evaluation: Navigating through the problem domain

Information systems (IS) make it possible to improve organizational efficiency and effectiveness, which can provide competitive advantage. There is, however, a great deal of difficulty reported in the normative literature when it comes to the evaluation of investments in IS, with companies often finding themselves unable to assess the full implications of their IS infrastructure. Although many of the savings resulting from IS are considered suitable for inclusion within traditional accountancy frameworks, it is the intangible and non-financial benefits, together with indirect project costs that complicate the justification process. In exploring this phenomenon, the paper reviews the normative literature in the area of IS evaluation, and then proposes a set of conjectures. These were tested within a case study to analyze the investment justification process of a manufacturing IS investment. The idiosyncrasies of the case study and problems experienced during its attempts to evaluate, implement, and realize the holistic implications of the IS investment are presented and critically analyzed. The paper concludes by identifying lessons learnt and thus, proposes a number of empirical findings for consideration by decisionmakers during the investment evaluation process

Investigation of Attitudes Towards Security Behaviors

Cybersecurity attacks have increased as Internet technology has proliferated. Symantec’s 2013 Internet Security Report stated that two out of the top three causes of data breaches in 2012 were attributable to human error (Pelgrin, 2014). This suggests a need to educate end users so that they engage in behaviors that increase their cybersecurity. This study researched how a user’s knowledge affects their engagement in security behaviors. Security behaviors were operationalized into two categories: cyber hygiene and threat response behaviors. A sample of 194 San José State University students were recruited to participate in an observational study. Students completed a card sort, a semantic knowledge quiz, and a survey of their intention to perform security behaviors. A personality inventory was included to see if there would be any effects of personality on security behaviors. Multiple regression was used to see how card sorting and semantic knowledge quiz scores predicted security behaviors, but the results were not significant. Despite this, there was a correlation between cyber hygiene behaviors and threat response behaviors, as well as the Big Five personality traits. The results showed that many of the Big Five personality traits correlated with each other, which is consistent with other studies’ findings. The only personality trait that had a correlation with one of the knowledge measures was neuroticism, in which neuroticism had a negative correlation with the semantic knowledge quiz. Implications for future research are discussed to understand how knowledge, cyber hygiene behaviors, and threat response behaviors relate

A survey of simulation techniques in commerce and defence

Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches