Emerging Frontiers: Exploring the Impact of Generative AI Platforms on University Quantitative Finance Examinations

This study evaluated three Artificial Intelligence (AI) large language model (LLM) enabled platforms - ChatGPT, BARD, and Bing AI - to answer an undergraduate finance exam with 20 quantitative questions across various difficulty levels. ChatGPT scored 30 percent, outperforming Bing AI, which scored 20 percent, while Bard lagged behind with a score of 15 percent. These models faced common challenges, such as inaccurate computations and formula selection. While they are currently insufficient for helping students pass the finance exam, they serve as valuable tools for dedicated learners. Future advancements are expected to overcome these limitations, allowing for improved formula selection and accurate computations and potentially enabling students to score 90 percent or higher

PENGARUH CONSUMER PERCEPTION FIT DAN CORE BRAND ATTITUDE TERHADAP PURCHASE INTENTION PRODUK PERLUASAN MICROSOFT DI SURABAYA

This research testing the influence od core brand attitude and consumer perception fit on purchase intention toward extended product Microsoft in Surabaya. Samples of study were selected using non- probability sampling especially convenience sampling and use 160 sample size. For data processing this research use Structural Equation Modeling (SEM) with LISREL 8.7 software. Result of this research is brand awareness and brand preference have significant and positive effect on Microsoft core brand image. Use Experience and core brand image have significant positive effect on Microsoft core brand attitude. Product connection have significant and positive effect on consumer perception fit of Microsoft. Brand association has no effect on consumer perception fit of Microsoft. Consumer perception fit and core brand attitude have significant and positive effect on purchase intention toward extended product Microsof

Enhancing STEM Learning with ChatGPT and Bing Chat as Objects to Think With: A Case Study

This study investigates the potential of ChatGPT and Bing Chat, advanced conversational AIs, as "objects-to-think-with," resources that foster reflective and critical thinking, and concept comprehension in enhancing STEM education, using a constructionist theoretical framework. A single-case study methodology was used to analyse extensive interaction logs between students and both AI systems in simulated STEM learning experiences. The results highlight the ability of ChatGPT and Bing Chat to help learners develop reflective and critical thinking, creativity, problem-solving skills, and concept comprehension. However, integrating AIs with collaborative learning and other educational activities is crucial, as is addressing potential limitations like concerns about AI information accuracy and reliability of the AIs' information and diminished human interaction. The study concludes that ChatGPT and Bing Chat as objects-to-think-with offer promising avenues to revolutionise STEM education through a constructionist lens, fostering engagement in inclusive and accessible learning environments

The Impact of Artificial Intelligence on the Evolution of Digital Education: A Comparative Study of OpenAI Text Generation Tools including ChatGPT, Bing Chat, Bard, and Ernie

In the digital era, the integration of artificial intelligence (AI) in education has ushered in transformative changes, redefining teaching methodologies, curriculum planning, and student engagement. This review paper delves deep into the rapidly evolving landscape of digital education by contrasting the capabilities and impact of OpenAI's pioneering text generation tools like Bing Chat, Bard, Ernie with a keen focus on the novel ChatGPT. Grounded in a typology that views education through the lenses of system, process, and result, the paper navigates the multifaceted applications of AI. From decentralizing global education and personalizing curriculums to digitally documenting competence-based outcomes, AI stands at the forefront of educational modernization. Highlighting ChatGPT's meteoric rise to one million users in just five days, the study underscores its role in democratizing education, fostering autodidacticism, and magnifying student engagement. However, with such transformative power comes the potential for misuse, as text-generation tools can inadvertently challenge academic integrity. By juxtaposing the promise and pitfalls of AI in education, this paper advocates for a harmonized synergy between AI tools and the educational community, emphasizing the urgent need for ethical guidelines, pedagogical adaptations, and strategic collaborations

Fact or Fiction

Fake news is increasingly pervasive, and we address its problematic aspects to help people intelligently consume news. In this project, we research machine learning models to extract objective sentences, encouraging unbiased discussions based on facts. The most accurate model, a convolutional neural network, achieves an accuracy of 85.69%. The team implemented an end-to-end web system that highlights objective sentences in user input to make our model publicly accessible. The system also provides additional information about user input, such as links to related web pages. We evaluate our system both qualitatively by interviewing users, and quantitatively with surveys consisting of rating scale questions. Received positive feedback indicates the usability of our platform

DESIGN WITH EMOTION: IMPROVING WEB SEARCH EXPERIENCE FOR OLDER ADULTS

Research indicates that older adults search for information all together about 15% less than younger adults prior to making decisions. Prior research findings associated such behavior mainly with age-related cognitive difficulties. However, recent studies indicate that emotion is linked to influence search decision quality. This research approaches questions about why older adults search less and how this search behavior could be improved. The research is motivated by the broader issues of older users\u27 search behavior, while focusing on the emotional usability of search engine user interfaces. Therefore, this research attempts to accomplish the following three objectives: a) to explore the usage of low level design elements as emotion manipulation tools b) to seamlessly integrate these design elements into currently existing search engine interfaces, and finally c) to evaluate the impact of emotional design elements on search performance and user satisfaction. To achieve these objectives, two usability studies were conducted. The aim of the first study was to explore emotion induction capabilities of colors, shapes, and combination of both. The study was required to determine if the proposed design elements have strong mood induction capabilities. The results demonstrated that low level design elements such as color and shape have high visceral effects that could be used as potentially viable alternatives to induce the emotional states of users without the users having knowledge of their presence. The purpose of the second study was to evaluate alternative search engine user interfaces, derived from this research, for search thoroughness and user preference. In general, search based performance variables showed that participants searched more thoroughly using interface types that integrate angular shape features. In addition, user preference variables also indicated that participants seemed to enjoy search tasks using search engine interfaces that used color/shape combinations. Overall, the results indicated that seamless integration of low level emotional design elements into currently existing search engine interfaces could potentially improve web search experience