William L. Romine

What Are People Tweeting About Zika? An Exploratory Study Concerning Its Symptoms, Treatment, Transmission, and Prevention

Background In order to harness what people are tweeting about Zika, there needs to be a computational framework that leverages machine learning techniques to recognize relevant Zika tweets and, further, categorize these into disease-specific categories to address specific societal concerns related to the prevention, transmission, symptoms, and treatment of Zika virus. Objective The purpose of this study was to determine the relevancy of the tweets and what people were tweeting about the 4 disease characteristics of Zika: symptoms, transmission, prevention, and treatment. Methods A combination of natural language processing and machine learning techniques was used to determine what people were tweeting about Zika. Specifically, a two-stage classifier system was built to find relevant tweets about Zika, and then the tweets were categorized into 4 disease categories. Tweets in each disease category were then examined using latent Dirichlet allocation (LDA) to determine the 5 main tweet topics for each disease characteristic. Results Over 4 months, 1,234,605 tweets were collected. The number of tweets by males and females was similar (28.47% [351,453/1,234,605] and 23.02% [284,207/1,234,605], respectively). The classifier performed well on the training and test data for relevancy (F1 score=0.87 and 0.99, respectively) and disease characteristics (F1 score=0.79 and 0.90, respectively). Five topics for each category were found and discussed, with a focus on the symptoms category. Conclusions We demonstrate how categories of discussion on Twitter about an epidemic can be discovered so that public health officials can understand specific societal concerns within the disease-specific categories. Our two-stage classifier was able to identify relevant tweets to enable more specific analysis, including the specific aspects of Zika that were being discussed as well as misinformation being expressed. Future studies can capture sentiments and opinions on epidemic outbreaks like Zika virus in real time, which will likely inform efforts to educate the public at large.

Development and Application of a Novel Rasch-Based Methodology for Evaluating Multi-Tiered Assessment Instruments: Validation and Utilization of an Undergraduate Diagnostic Test of the Water Cycle.

We describe the development and validation of a three-tiered diagnostic test of the water cycle (DTWC) and use it to evaluate the impact of prior learning experiences on undergraduates’ misconceptions. While most approaches to instrument validation take a positivist perspective using singular criteria such as reliability and fit with a measurement model, we extend this to a multi-tiered approach which supports multiple interpretations. Using a sample of 130 undergraduate students from two colleges, we utilize the Rasch model to place students and items along traditional one-, two-, and three-tiered scales as well as a misconceptions scale. In the three-tiered and misconceptions scales, high confidence was indicative of mastery. In the latter scale, a ‘misconception’ was defined as mastery of an incorrect concept. We found that integrating confidence into mastery did little to change item functioning; however, three-tiered usage resulted in higher reliability and lower student ability estimates than two-tiered usage. The misconceptions scale showed high efficacy in predicting items on which particular students were likely to express misconceptions, and revealed several tenacious misconceptions that all students were likely to express regardless of ability. Previous coursework on the water cycle did little to change the prevalence of undergraduates’ misconceptions.

Investigation of an Indoor Air Quality Sensor for Asthma Management in Children

Monitoring indoor air quality is critical because Americans spend 93 of their life indoors, and around 6.3 million children suffer from asthma. We want to passively and unobtrusively monitor the asthma patients environment to detect the presence of two asthma-exacerbating activities: smoking and cooking using the Foobot sensor. We propose a data-driven approach to develop a continuous monitoring-activity detection system aimed at understanding and improving indoor air quality in asthma management. In this study, we were successfully able to detect a high concentration of particulate matter, volatile organic compounds, and carbon dioxide during cooking and smoking activities. We detected 1) smoking with an error rate of 1; 2) cooking with an error rate of 11; and 3) obtained an overall 95.7 percent accuracy classification across all events (control, cooking and smoking). Such a system will allow doctors and clinicians to correlate potential asthma symptoms and exacerbation reports from patients with environmental factors without having to personally be present.

Validation of the Learning Progression-based Assessment of Modern Genetics in a college context

ABSTRACT Building upon a methodologically diverse research foundation, we adapted and validated the Learning Progression-based Assessment of Modern Genetics (LPA-MG) for college students’ knowledge of the domain. Toward collecting valid learning progression-based measures in a college majors context, we redeveloped and content validated a majority of a previous version of the LPA-MG which was developed for high school students. Using a Rasch model calibrated on 316 students from 2 sections of majors introductory biology, we demonstrate the validity of this version and describe how college students’ ideas of modern genetics are likely to change as the students progress from low to high understanding. We then utilize these findings to build theory around the connections college students at different levels of understanding make within and across the many ideas within the domain.

Learning science content through socio-scientific issues-based instruction: a multi-level assessment study

ABSTRACT Science educators have presented numerous conceptual and theoretical arguments in favor of teaching science through the exploration of socio-scientific issues (SSI). However, the empirical knowledge base regarding the extent to which SSI-based instruction supports student learning of science content is limited both in terms of the number of studies that have been conducted in this area and the quality of research. This research sought to answer two questions: (1) To what extent does SSI-based instruction support student learning of science content? and (2) How do assessments at variable distances from the curriculum reveal patterns of learning associated with SSI-based instruction? Sixty-nine secondary students taught by three teachers participated in the study. Three teachers implemented an SSI intervention focused on the use of biotechnology for identifying and treating sexually transmitted diseases. We found that students demonstrated statistically and practically significant gains in content knowledge as measured by both proximal and distal assessments. These findings support the claim that SSI-based teaching can foster content learning and improved performance on high-stakes tests.

Multilevel Assessment of Middle School Students’ Interest in the Health Sciences: Development and Validation of a New Measurement Tool

The authors utilize the frameworks of multilevel assessment and Rasch modeling to develop and validate the Assessment of Interest in Medicine and Science (AIMS), a three-subscale tool for measuring student interest in science and health careers at the middle school level.

Assessing the efficacy of the Measure of Understanding of Macroevolution as a valid tool for undergraduate non-science majors

Efficacy of the Measure of Understanding of Macroevolution (MUM) as a measurement tool has been a point of contention among scholars needing a valid measure for knowledge of macroevolution. We explored the structure and construct validity of the MUM using Rasch methodologies in the context of a general education biology course designed with an emphasis on macroevolution content. The Rasch model was utilized to quantify item- and test-level characteristics, including dimensionality, reliability, and fit with the Rasch model. Contrary to previous work, we found that the MUM provides a valid, reliable, and unidimensional scale for measuring knowledge of macroevolution in introductory non-science majors, and that its psychometric behavior does not exhibit large changes across time. While we found that all items provide productive measurement information, several depart substantially from ideal behavior, warranting a collective effort to improve these items. Suggestions for improving the measurement characteristics of the MUM at the item and test levels are put forward and discussed.

Empirical Validation of a Modern Genetics Progression Web for College Biology Students

ABSTRACT Research in learning progressions (LPs) has been essential towards building understanding of how students’ ideas change over time. There has been little work, however, into how ideas between separate but related constructs within a multi-faceted LP relate. The purpose of this paper is to elaborate on the idea of progression webs to model connections within and between related constructs simultaneously, and to explain and demonstrate the efficacy of path analysis towards validating a hypothesised progression web for understanding of modern genetics. Specifically, we evaluate strength of evidence for a progression web based upon multiple related constructs within a multi-faceted LP describing undergraduate biology students’ understanding of genetics. We then utilise the progression web to generalise theory around how undergraduate students understand relationships between related genetics concepts, and how they use simpler concepts to scaffold those which are more complex.

Measuring pedagogical agent persona and the influence of agent persona on learning

Pedagogical agents are virtual characters embedded within a learning environment to enhance student learning. Researchers are beginning to understand the conditions in which pedagogical agents can enhance learning, but many questions still remain. Namely, the field has few options in terms of measurement instruments, and limited research has investigated the influence of pedagogical agent persona, or the way the agent is perceived by students, on learning outcomes. In this study, we re-examine the Agent Persona Instrument (API) using confirmatory factor analysis and Rasch methods. We then examine the influence of agent persona on learning outcomes using path analysis. The results confirmed the four factor structure of the instrument, and the fit of items with the Rasch model demonstrates construct validity in our context. However, the analyses indicated that revisions to the instrument are warranted. The path analysis revealed that affective interaction significantly influenced information usefulness variables, however perceptions measured by the API had no significant impact on learning outcomes. Suggestions for revising the API are provided. The four factor structure of the Agent Persona Instrument is re-examined.Rasch methods were used to examine the construct validity of the instrument.Results indicate the instrument is a useful tool, but would benefit from revisions.Path analysis revealed perceptions did not significantly influence learning.

Depressed Synaptic Transmission and Reduced Vesicle Release Sites in Huntington's Disease Neuromuscular Junctions

Huntingtons disease (HD) is a progressive and fatal degenerative disorder that results in debilitating cognitive and motor dysfunction. Most HD studies have focused on degeneration of the CNS. We previously discovered that skeletal muscle from transgenic R6/2 HD mice is hyperexcitable due to decreased chloride and potassium conductances. The progressive and early onset of these defects suggest a primary myopathy in HD. In this study, we examined the relationship between neuromuscular transmission and skeletal muscle hyperexcitability. We used an ex vivo preparation of the levator auris longus muscle from male and female late-stage R6/2 mice and age-matched wild-type controls. Immunostaining of the synapses and molecular analyses revealed no evidence of denervation. Physiologically, we recorded spontaneous miniature endplate currents (mEPCs) and nerve-evoked EPCs (eEPCs) under voltage-clamp, which, unlike current-clamp records, were independent of the changes in muscle membrane properties. We found a reduction in the number of vesicles released per action potential (quantal content) in R6/2 muscle, which analysis of eEPC variance and morphology indicate is caused by a reduction in the number of vesicle release sites (n) rather than a change in the probability of release (prel). Furthermore, analysis of high-frequency stimulation trains suggests an impairment in vesicle mobilization. The depressed neuromuscular transmission in R6/2 muscle may help compensate for the muscle hyperexcitability and contribute to motor impersistence. SIGNIFICANCE STATEMENT Recent evidence indicates that Huntingtons disease (HD) is a multisystem disorder. Our examination of neuromuscular transmission in this study reveals defects in the motor nerve terminal that may compensate for the muscle hyperexcitability in HD. The technique we used eliminates the effects of the altered muscle membrane properties on synaptic currents and thus provides hitherto the most detailed analysis of synaptic transmission in HD. Clinically, the striking depression of neurotransmission we found may help explain the motor impersistence in HD patients. Therapies that target the highly accessible peripheral nerve and muscle system provide a promising new avenue to lessen the debilitating motor symptoms of HD.