Understanding and Supporting Cross-modal Collaborative Information Seeking

Most previous studies of users with visual impairments (VI) access to the web have focused solely on single user human-web interaction. This thesis explores the under investigated area of cross-modal collaborative information seeking (CCIS), that is the challenges and opportunities that exist in supporting visually impaired users to take an effective part in collaborative web search tasks with sighted peers. The thesis examines the overall question of what happens currently when people perform CCIS, and how might the CCIS process be improved? To motivate the work, we conducted a survey, the results of which showed that a significant amount of CCIS activity goes on. An exploratory study was conducted to investigate the challenges faced and behaviour patterns that occur when people perform CCIS. We observed 14 pairs of VI and sighted users in both co-located and distributed settings. In this study participants used their tools of choice, that is the web browser, note taker and preferred communications system. The study examines how concepts from the “mainstream” collaborative Information Seeking (CIS) literature, play out in the context of cross-modality. Based on the findings of this study, we produced design recommendations for features that can better support cross-modal collaborative search. Following this, we surveyed mainstream CIS systems and selected the most accessible software package that satisfied the design recommendations from the initial study. Due to the fact that the software was not built with accessibility in mind, we developed JAWS scripts and employed other JAWS features to improve its accessibility and VI user experience. We then performed a second study, using the same participants undertaking search tasks of a similar complexity as before, but this time using the CIS system. The aim of this study was to explore the impact on the CCIS process when introducing a mainstream CIS system, enhanced for accessibility. In this study we looked into CCIS from two perspectives: the collaboration and the individual interaction with the interface. The findings from this study provide an understanding of the process of CCIS when using a system that supports it. These findings assisted us in formulating a set of guidelines toward supporting collaborative search in a cross-modal context

Combating Fear of Missing Out (FoMO) on Social Media: The FoMO-R Method.

Background: The fear of missing out (FoMO) on social media refers to the apprehension that online content and interactions from others are unseen and reacted to in a timely fashion. FoMO can become problematic, leading to anxiety, interrupted sleep, lack of concentration and dependence on social media to generate gratification. The literature has mainly focused on understanding the FoMO experience, factors contributing to it and its consequences. Method: In this paper, we build on previous research and develop a FoMO Reduction (FoMO-R) approach that embraces technical elements such as autoreply, filtering, status, education on how FoMO occurs and skills on how to deal with it; e.g., self-talk and checklists. We evaluate the method through focus groups and a diary study involving 30 participants who self-declared to experience FoMO regularly. Results: The results show that the method was accepted by the participants and helped them to manage their FoMO. They also show that a set of extra functionalities in social media design is needed so that users can manage FoMO more effectively. Conclusion: FoMO can be reduced through socio-technical approaches, joining both social and technical skills, and literacy on how social media are designed and how social interactions should happen on them

Conceptual Interactive Search Engine Interface for Visually Impaired Web Users

The Internet is the main source of information nowadays. Consequently, end users need to be knowledgeable about how to use search engines in order to locate relevant information in a reasonable time with minimal effort. On the other hand, search engines must provide different and alternative ways to represent the search results to facilitate the user access to the information especially for the visually impaired (VI) users. Our research aim is to produce a new representational model for the search engine results targeting VI users. The result of this study will be a functional prototype that summarizes the search results as main ideas that are identified as concepts. Formal Concept Analysis (FCA) defines a concept as the maximum number of objects that are sharing the maximum number of features or attributes. Concepts are discovered by analyzing data patterns for the text of the study. The outcome of the first step of summarization concepts as keywords is used to minimize the number of listed websites and URLs that match the user selection of the multi-level tree of concepts. This scenario of summarization can give the user different directions for the shortest path to reach the target information with the minimum amount of time and effort required. The purpose of these directions can be either to proceed with reading the whole document in detail, or to continue the search for finding other related documents that match the user's inquiry. Experiments run on an iterative testing basis until VI users find proper results that satisfy their needs for the search context. User observations and interpretations based on the experiments are used for the user evaluation. This study will guide us for designing a new model for summarizing search results based on the FCA algorithm to the VI end users, and with a new representation interface based on the discovered concepts' weights.ACKNOWLEDGMENT This contribution was made possible by NPRP grant No. 07-794-1-145 and GSRA grant No. 04-1-0514-17066 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Investigating the Experience of Social Engineering Victims: Exploratory and User Testing Study

The advent of mobile technologies and social network applications has led to an increase in malicious scams and social engineering (SE) attacks which are causing loss of money and breaches of personal information. Understanding how SE attacks spread can provide useful information in curbing them. Artificial Intelligence (AI) has demonstrated efficacy in detecting SE attacks, but the acceptability of such a detection approach is yet to be investigated across users with different levels of SE awareness. This paper conducted two studies: (1) exploratory study where qualitative data were collected from 20 victims of SE attacks to inform the development of an AI-based tool for detecting fraudulent messages; and (2) a user testing study with 48 participants with different occupations to determine the detection tool acceptability. Overall, six major themes emerged from the victims’ actions “experiences: reasons for falling for attacks; attack methods; advice on preventing attacks; detection methods; attack context and victims”. The user testing study showed that the AI-based tool was accepted by all users irrespective of their occupation. The categories of users’ occupations can be attributed to the level of SE awareness. Information security awareness should not be limited to organizational levels but extend to social media platforms as public information

A Multimodal Messaging App (MAAN) for Adults With Autism Spectrum Disorder: Mixed Methods Evaluation Study

BackgroundIndividuals with autism spectrum disorder (ASD) often exhibit difficulties in social and communication skills. For more than 30 years, specialists, parents, and caregivers have used techniques, such as applied behavioral analysis, augmentative and alternative communication, and the picture exchange communication system to support the social and communication skills of people with ASD. Even though there are many techniques devised to enhance communication, these techniques are not considered in existing social media apps for people with ASD. ObjectiveThis study aimed to investigate the effect of adding accessibility features, such as text-to-speech (TTS), speech-to-text (STT), and communication symbols (CS), to a messaging app (MAAN). We hypothesized that these accessibility features can enhance the social and communication skills of adults with ASD. We also hypothesized that usage of this app can reduce social loneliness in adults with ASD. MethodsSemistructured interviews were conducted with 5 experts working in fields related to ASD to help design the app. Seven adults with ASD participated in the study for a period of 10 to 16 weeks. Data logs of participants’ interactions with the app were collected. Additionally, 6 participants’ parents and 1 caregiver were asked to complete a short version of the Social and Emotional Loneliness Scale for Adults (SELSA-S) questionnaire to compare pre-post study results. The Mobile Application Rating Scale: user version questionnaire was also used to evaluate the app’s usability. Following the study, interviews were conducted with participants to discuss their experiences with the app. ResultsThe SELSA-S questionnaire results showed no change in the family subscale; however, the social loneliness subscale showed a difference between prestudy and poststudy. The Wilcoxon signed-rank test indicated that poststudy SELSA-S results were statistically significantly higher than prestudy results (z=−2.047; P=.04). Point-biserial correlation indicated that the SELSA-S rate of change was strongly related to usage of the TTS feature (r=0.708; P=.04) and CS feature (r=−0.917; P=.002), and moderately related to usage of the STT feature (r=0.428; P=.17). Lastly, we adopted grounded theory to analyze the interview data, and the following 5 categories emerged: app support, feature relevance, user interface design, overall feedback, and recommendations. ConclusionsThis study discusses the potential for improving the communication skills of adults with ASD through special features in mobile messaging apps. The developed app aims to support the inclusion and independent life of adults with ASD. The study results showed the importance of using TTS, STT, and CS features to enhance social and communication skills, as well as reduce social loneliness in adults with ASD

Interpretation of a 12-Lead Electrocardiogram by Medical Students: Quantitative Eye-Tracking Approach

BackgroundAccurate interpretation of a 12-lead electrocardiogram (ECG) demands high levels of skill and expertise. Early training in medical school plays an important role in building the ECG interpretation skill. Thus, understanding how medical students perform the task of interpretation is important for improving this skill. ObjectiveWe aimed to use eye tracking as a tool to research how eye fixation can be used to gain a deeper understanding of how medical students interpret ECGs. MethodsIn total, 16 medical students were recruited to interpret 10 different ECGs each. Their eye movements were recorded using an eye tracker. Fixation heatmaps of where the students looked were generated from the collected data set. Statistical analysis was conducted on the fixation count and duration using the Mann-Whitney U test and the Kruskal-Wallis test. ResultsThe average percentage of correct interpretations was 55.63%, with an SD of 4.63%. After analyzing the average fixation duration, we found that medical students study the three lower leads (rhythm strips) the most using a top-down approach: lead II (mean=2727 ms, SD=456), followed by leads V1 (mean=1476 ms, SD=320) and V5 (mean=1301 ms, SD=236). We also found that medical students develop a personal system of interpretation that adapts to the nature and complexity of the diagnosis. In addition, we found that medical students consider some leads as their guiding point toward finding a hint leading to the correct interpretation. ConclusionsThe use of eye tracking successfully provides a quantitative explanation of how medical students learn to interpret a 12-lead ECG

Research on Older Persons’ Access and Use of Technology in the Arab Region: Critical Overview and Future Directions

This paper presents the findings of a scoping review that maps exploratory evidence and gaps in research on information and communication technology (ICT) access and use among older persons in the Arab region. This review is part of a larger project that studies ICT access and use and related challenges faced by older adults in Qatar. A search was conducted in eleven scientific databases and search engines covering empirical studies published in English and Arabic between January 2016 and June 2021. Eleven studies were retrieved in the final corpus. A thematic analysis alongside the PRISMA for scoping reviews (PRISMA-ScR) was used to retrieve the findings. Our analysis identifies smartphones and social media applications for communication and information sharing as the most accessed and used technologies by older persons in the region. Moreover, our review highlighted the importance of the sociocultural factors in shaping ICT access and use by older persons in the region. The functional limitations of older persons in interaction with certain technology factors such as usability, functionality, and accessibility were also highlighted as major challenges inhibiting ICT access and use by this population segment. This scoping review provides a comprehensive overview of ICT access and use, and the factors affecting them among older persons in the Arab region. It highlights the scarcity of research on the subject in the region. It also stresses the fact that there is a need for more research on older persons and their caregivers in the context of the Arab world. More culturally appropriate need-based and adapted technologies are also recommended. Our review is a comprehensive source for researchers and technology developers interested in targeting and engaging older adults in the Arab region

Explainable Recommendations and Calibrated Trust: Two Systematic User Errors

The increased adoption of collaborative human-artificial intelligence decision-making tools triggered a need to explain recommendations for safe and effective collaboration. We explore how users interact with explanations and why trust-calibration errors occur, taking clinical decision-support systems as a case study