Incorporating AI Tool Along with Traditional Method for Speaking Assessment

This work focused on incorporating AI tool with traditional method for speaking assessment. The descriptive qualitative has been implemented to complete this research. Problem encountered during English pronunciation was failing to distinguish between short vowel and long vowel. By employing traditional and AI tool, students got numerous benefits. They may enjoy learning with the flexibility of time and they also can engage face to face interaction while using traditional method furthermore, it is essential to acknowledge AI tool with the limitation and drawbacks. AI tool do not give the same stage of personal interconnection and on-going response as a human facilitator

Development of an evidence-based medicine mobile application for the use in medical education

BACKGROUND: Evidence-based medicine (EBM) is a methodology that is being incorporated into more medical school curricula. Boston University School of Medicine was one of early adopters of Evidence Based Medicine in the United States. A growing concern in the medical community was that the complexities of applying EBM might be lost when students enter into their clinical rotations, thus there is a need for development of a tool to help reinforce the EBM principles. METHODS: The research team in collaboration with the designers of the Finding Information Framework, a custom-made EBM finding information tool, worked to develop a mobile application to help reinforce the framework for medical students. The app was designed with both Apple and PC operating systems in mind. Key features that were identified from current literature to provide the most user-friendly mobile application. Thus, the research team specifically utilized iOS and Android platforms as both platforms have a centralized app store, possess the highest volume of medical apps available, and are most widely used in the United States by medical students. RESULTS: The Finding Information Framework was a custom-made tool developed to guide new users of EBM, and help them to apply the principles in practice. The mobile application served an added convenience by allowing easy access and fast utilization of the EBM tools. The app was designed on an Android platform first due to its open-source OS and ease in app development to new programmers. Initially, the user-friendly web-based tool, App Inventor (AI), powered by Massachusetts Institute of Technology was evaluated to program the pilot Android app. Using both the AI Component Designer and the Block Editor, several problems were encountered in AI, such as the simplicity of the program and the lack of freedom in design. This moved the project to create the app natively and with a collaborative effort with the BU's Global App Initiative club. Initially, a wireframe was built using Balsamiq. Subsequently, the Android app was built using Android SDK and the iOS app was built in XCode with Objective C; both platforms had design sections prepared in Sketch, Adobe Photoshop and Illustrator. The last and final step was to obtain Boston University branding privileges for the app. CONCLUSION: The research team identified necessary features based on research to build a user-friendly, professional mobile application of an information mastery framework that can be used off-line. The app is called FIF as it is the title of the information mastery tool designed by BUSM EBM-VIG. With a clear mobile interface, it will be beneficial to the learning and training of medical students in EBM

Putting a Face on Algorithms: Personas for Modeling Artificial Intelligence

We propose a new type of personas, artificial intelligence (AI) personas, as a tool for designing systems consisting of both human and AI agents. Personas are commonly used in design practices for modelling users. We argue that the personification of AI agents can help multidisciplinary teams in understanding and designing systems that include AI agents. We propose a process for creating AI personas and the properties they should include, and report on our first experience using them. The case we selected for our exploration of AI personas was the design of a highly automated decision support tool for air traffic control. Our first results indicate that AI personas helped designers to empathise with algorithms and enabled better communication within a team of designers and AI and domain experts. We call for a research agenda on AI personas and discussions on potential benefits and pitfalls of this approach.acceptedVersio

Image Generation through StyleGANs: is it Art?

I wanted to explore how the role of artificial intelligence is developing within the art world and how current attitudes surrounding AI as a creative tool are changing. I want to experiment with AI generated images using GANs and then seek feedback on them from art and non-art students alike before telling them that they had been generated by an AI. I focused my research on examining the emotional responses people had to AI generated art and the overall question of “can an AI make art?

Innovative Integration: Exploring AI Art Platforms in Architectural Education for Mosque Facade Design

This research aims to investigate the effectiveness of implementing the mentoring model in Mosque facade design presents a unique challenge in the field of architecture due to their importance as the mosque's front-facing feature and their role in representing Islamic identity. In this study, an AI art platform was introduced as a tool to improve the creativity and design process for architecture students and professionals. The study investigated the platform's novel application in the context of architectural learning for mosque façade design. The research methodology was divided into three parts: a description of the platforms used, identification of common use cases in mosque architectural design, and query analysis using NLP methods in Midjourney AI art platform. According to the findings of the study, the AI art platform is a valuable tool for architectural learning, allowing students and professionals to generate diverse and innovative designconcepts. The Midjourney AI art platform has flaws such as difficulty recognizing architectural styles from specific regions

Chatting with Confidence: A Review on the Impact of User Interface, Trust, and User Experience in Chatbots, and a Proposal of a Redesigned Prototype

As artificial intelligence (AI) becomes more prevalent in our daily lives, trust has become a critical issue in ensuring that AI systems are reliable, ethical, and beneficial to society. This paper explores the role of user experience (UX) in shaping users' trust in chat AI. Chat AI has become increasingly popular as a communication tool, but users often struggle with trusting the technology. The paper examines how different design elements, such as conversational style, interface, and feedback mechanisms, affect users' perception of trust in chat AI by analyzing previous literature written in this area. Research demonstrates that UX plays a critical role in users' trust in chat AI, with factors such as transparency, responsiveness, and empathy contributing to higher levels of trust. Using the results found in the research around this topic, a redesigned prototype of a popular chat AI software called chatGPT was created with the help of Figma

Game of Tones: Faculty detection of GPT-4 generated content in university assessments

This study explores the robustness of university assessments against the use of Open AI's Generative Pre-Trained Transformer 4 (GPT-4) generated content and evaluates the ability of academic staff to detect its use when supported by the Turnitin Artificial Intelligence (AI) detection tool. The research involved twenty-two GPT-4 generated submissions being created and included in the assessment process to be marked by fifteen different faculty members. The study reveals that although the detection tool identified 91% of the experimental submissions as containing some AI-generated content, the total detected content was only 54.8%. This suggests that the use of adversarial techniques regarding prompt engineering is an effective method in evading AI detection tools and highlights that improvements to AI detection software are needed. Using the Turnitin AI detect tool, faculty reported 54.5% of the experimental submissions to the academic misconduct process, suggesting the need for increased awareness and training into these tools. Genuine submissions received a mean score of 54.4, whereas AI-generated content scored 52.3, indicating the comparable performance of GPT-4 in real-life situations. Recommendations include adjusting assessment strategies to make them more resistant to the use of AI tools, using AI-inclusive assessment where possible, and providing comprehensive training programs for faculty and students. This research contributes to understanding the relationship between AI-generated content and academic assessment, urging further investigation to preserve academic integrity

Researching AI Legibility Through Design

Everyday interactions with computers are increasingly likely to involve elements of Artificial Intelligence (AI). Encompassing a broad spectrum of technologies and applications, AI poses many challenges for HCI and design. One such challenge is the need to make AI’s role in a given system legible to the user in a meaningful way. In this paper we employ a Research through Design (RtD) approach to explore how this might be achieved. Building on contemporary concerns and a thorough exploration of related research, our RtD process reflects on designing imagery intended to help increase AI legibility for users. The paper makes three contributions. First, we thoroughly explore prior research in order to critically unpack the AI legibility problem space. Second, we respond with design proposals whose aim is to enhance the legibility, to users, of systems using AI. Third, we explore the role of design-led enquiry as a tool for critically exploring the intersection between HCI and AI research