Accessibility evaluation of chats and forums in e-learning environments

Proceedings of: 2013 International Conference on Frontiers in Education: Computer Science & Computer Engineering (FECS'13): WORLDCOMP'13, July 22-25, 2013, Las Vegas, Nevada (USA)Collaborative learning is useful for students in their learning process. Nowadays, most e-learning systems include Computer Supported Collaborative Learning (CSCL) tools like chats and forums; however, are they accessible for everybody? This paper presents a heuristic evaluation of accessibility of two CSCL tools (chat and forum) in four web-based, open-source Learning Content Management Systems (LCMS): Moodle, ATutor, dotLRN and Claroline. The evaluation results show that the CSCL tools evaluated present accessibility barriers which are a handicap for many students who want to use the LCMSs Moreover, some recommendations are offered in order to improve the accessibility of the evaluated tools. Considering these recommendations in the development of the evaluated tools, all students could participate actively in the collaborative tasks proposed by teachersThis research work has been supported by the Regional Government of Madrid under the Research Network MA2VICMR (S2009/TIC-1542) and by the Spanish Ministry of Economy under the project MULTIMEDICA (TIN2010-20644-C03-01)Publicad

Associations between Opioid-Related Hospitalizations and Intravenous Drug Users

The opioid epidemic has led to a chain reaction of public health concerns, including an increase in heroin usage, injection drug abuse, incidence of hepatitis C virus (HCV), and HIV transmission. There have been few population-based studies investigating the clinical and socio- demographic data associated with opioid use in Nevada (Feng et al., 2016; Frank, 2000) and few studies investigating the intravenous drug user (IDU) population in Clark County. On February 2017, Clark County’s first syringe exchange program (SEP) opened its doors to the IDU population. This study provides an updated analysis of opioid-related injuries within Nevada and provides a first-time analysis of the IDU population within Clark County. According to the 2017 Center of Health Information Analysis (CHIA), there were 9,064 opioid-related injuries in the state of Nevada. The most common comorbidities associated with opioid-related injuries were chronic bodily pains (50.2%), malnutrition (47.3%), nicotine dependence (44.7%), affective disorders (32.4%), and hypertension (28.8%). There was a higher proportion of 18-35 year olds who used SEPs as compared to 18-35 year olds who used hospitals. One Clark County zip code had both high frequencies for opioid-related hospitalizations and injection drug use. In order to implement interventions and programs to battle the opioid epidemic and the consequent public health effects, we must first understand the associations between opioid-related hospitalizations and the IDU population

What Users See – Structures in Search Engine Results Pages

This paper investigates the composition of search engine results pages. We define what elements the most popular web search engines use on their results pages (e.g., organic results, advertisements, shortcuts) and to which degree they are used for popular vs. rare queries. Therefore, we send 500 queries of both types to the major search engines Google, Yahoo, Live.com and Ask. We count how often the different elements are used by the individual engines. In total, our study is based on 42,758 elements. Findings include that search engines use quite different approaches to results pages composition and therefore, the user gets to see quite different results sets depending on the search engine and search query used. Organic results still play the major role in the results pages, but different shortcuts are of some importance, too. Regarding the frequency of certain host within the results sets, we find that all search engines show Wikipedia results quite often, while other hosts shown depend on the search engine used. Both Google and Yahoo prefer results from their own offerings (such as YouTube or Yahoo Answers). Since we used the .com interfaces of the search engines, results may not be valid for other country-specific interfaces

Weaving Rules into [email protected] for Embedded Smart Systems

Smart systems are characterised by their ability to analyse measured data in live and to react to changes according to expert rules. Therefore, such systems exploit appropriate data models together with actions, triggered by domain-related conditions. The challenge at hand is that smart systems usually need to process thousands of updates to detect which rules need to be triggered, often even on restricted hardware like a Raspberry Pi. Despite various approaches have been investigated to efficiently check conditions on data models, they either assume to fit into main memory or rely on high latency persistence storage systems that severely damage the reactivity of smart systems. To tackle this challenge, we propose a novel composition process, which weaves executable rules into a data model with lazy loading abilities. We quantitatively show, on a smart building case study, that our approach can handle, at low latency, big sets of rules on top of large-scale data models on restricted hardware.Comment: pre-print version, published in the proceedings of MOMO-17 Worksho

The Archive Query Log: Mining Millions of Search Result Pages of Hundreds of Search Engines from 25 Years of Web Archives

The Archive Query Log (AQL) is a previously unused, comprehensive query log collected at the Internet Archive over the last 25 years. Its first version includes 356 million queries, 166 million search result pages, and 1.7 billion search results across 550 search providers. Although many query logs have been studied in the literature, the search providers that own them generally do not publish their logs to protect user privacy and vital business data. Of the few query logs publicly available, none combines size, scope, and diversity. The AQL is the first to do so, enabling research on new retrieval models and (diachronic) search engine analyses. Provided in a privacy-preserving manner, it promotes open research as well as more transparency and accountability in the search industry.Comment: SIGIR 2023 resource paper, 13 page

Users, Queries, and Bad Abandonment in Web Search

After a user submits a query and receives a list of search results, the user may abandon their query without clicking on any of the search results. A bad query abandonment is when a searcher abandons the SERP because they were dissatisfied with the quality of the search results, often making the user reformulate their query in the hope of receiving better search results. As we move closer to understanding when and what causes a user to abandon their query under different qualities of search results, we move forward in an overall understanding of user behavior with search engines. In this thesis, we describe three user studies to investigate bad query abandonment. First, we report on a study to investigate the rate and time at which users abandon their queries at different levels of search quality. We had users search for answers to questions, but showed users manipulated SERPs that contain one relevant document placed at different ranks. We show that as the quality of search results decreases, the probability of abandonment increases, and that users quickly decide to abandon their queries. Users make their decisions fast, but not all users are the same. We show that there appear to be two types of users that behave differently, with one group more likely to abandon their query and are quicker in finding answers than the group less likely to abandon their query. Second, we describe an eye-tracking experiment that focuses on understanding possible causes of users' willingness to examine SERPs and what motivates users to continue or discontinue their examination. Using eye-tracking data, we found that a user deciding to abandon a query is best understood by the user's examination pattern not including a relevant search result. If a user sees a relevant result, they are very likely to click it. However, users' examination of results are different and may be influenced by other factors. The key factors we found are the rank of search results, the user type, and the query quality. For example, we show that regardless of where the relevant document is placed in the SERP, the type of query submitted affects examination, and if a user enters an ambiguous query, they are likely to examine fewer results. Third, we show how the nature of non-relevant material affects users' willingness to further explore a ranked list of search results. We constructed and showed participants manipulated SERPs with different types of non-relevant documents. We found that user examination of search results and time to query abandonment is influenced by the coherence and type of non-relevant documents included in the SERP. For SERPs coherent on off-topic results, users spend the least amount of time before abandoning and are less likely to request to view more results. The time they spend increases as the SERP quality improves, and users are more likely to request to view more results when the SERP contains diversified non-relevant results on multiple subtopics