This study investigates the utilization pattern, perception, and experience of Higher Education Institutes (HEIs) students towards the ChatGPT application in an academic context. It employs a quantitative approach utilizing a questionnaire as the research instrument. The study sample was selected using a simple random sampling method from Sunway University and Sunway College in Kuala Lumpur, Malaysia. The survey participants, enrolled in General Studies Subjects (MPU) during their short semester between September and December 2023, were selected using a simple random sampling method. Out of 150 students who received the survey via Google Forms, 119 provided complete responses suitable for analysis. The research primarily focused on calculating mean scores to assess three key dimensions: its use patterns of ChatGPT, perceptions and experiences among students towards its adoption in educational contexts. A descriptive analysis was conducted to determine student frequency and percentage values for ChatGPT usage. At the same time, mean scores were utilized to evaluate higher education institutes (HEIs) students' perceptions and experiences with the application in an academic context. This descriptive analysis revealed a spectrum of responses that ranged from low to very high levels across these dimensions. The findings of this study offer extensive insight into the current incorporation and perception of ChatGPT within Higher Education Institutions (HEIs), showcasing the diverse range of engagement and acceptance levels among students.
Choosing a career and educational path is a challenging decision for young people. Career planning conversational agents (CAs) can assist by identifying suitable occupations and educational paths. Trustworthiness is an important dimension for the acceptance of a career planning CA and is influenced by several factors. We conducted a user study with n=114 participants across three schools in Germany to explore the trustworthiness of different career planning CAs. We examined the correlation between trustworthiness and perceived competence, autonomy, and social relatedness from self-determination theory (SDT), as well as the explainability of interactions and several usability dimensions of the assistants. These dimensions included the ability to guide the conversation, onboarding quality, error tolerance, and information relevance. We tested three different variants of the career planning assistant: a form-based assistant, an intent-based CA, and a large language model (LLM)-based CA. The results showed that the LLM-based CA was on average significantly more trustworthy and was perceived as more explainable than the intent-based CA. Key trust factors included conversation flexibility, chatbot credibility, intent recognition, and maintenance of a secure conversation. Additionally, perceived autonomy was crucial for trust across all types of assistants and perceived relatedness for the two CAs. Our findings highlight key areas essential for developing trustworthy CAs.
The online coding tutorial systems offer learners a flexible and accessible platform to acquire coding skills, while educators benefit from the ability to monitor progress, provide personalised feedback, and facilitate effective instruction at scale. However, to develop truly effective and engaging online coding tutorial systems, it is crucial to understand the dual perspectives of both learners and educators. This paper presents learners and educators feedback on an initial list of supportive features that have been identified in a previous study to enhance the quality of designing online coding tutorial systems (OCTSs). An online questionnaire was distributed among 37 learners and educators from Saudi Arabia, the United Kingdom, and other locations to investigate their needs and measure their satisfaction with the list of supportive features that are provided by the current online coding tutorial system called LearnPython. Finally, this study offers some suggestions for supportive features to enhance the quality of designing OCTSs totally based on learners and educators experiences.
The integration of generative AI tools into education has the potential to revolutionize learning experiences, particularly in computer science. This paper explores the adoption and utilization of generative AI tools among computer science students at the University of Applied Sciences Campus Vienna in Austria through a comprehensive survey. The study aims to understand the extent to which AI tools like ChatGPT are integrated into students' academic routines, their perceptions of these tools, and the challenges and opportunities they present. The survey results indicate a high level of acceptance and frequent use of AI tools for tasks such as programming, exam preparation, and generating simplified explanations. However, concerns about the accuracy of AI-generated content and the potential impact on critical thinking skills were also highlighted. The findings underscore the need for clear institutional guidelines and ethical considerations in the use of AI tools in education. This paper contributes to the growing body of literature on AI in education and provides insights for educators and policymakers to enhance the responsible integration of AI technologies in computer science curricula.
The ability to draw syntactic tree diagrams shows students’ knowledge of sentence structures. This study aims to measure the students’ accuracy in drawing tree diagrams using a computer program and their opinions regarding the use of a computer tree generator. The participants were 30 English department students who had been learning English syntax. They were instructed to draw tree diagrams using a program called Syntax Tree Generator. The findings show that 84.56% of students can draw syntactic tree diagrams accurately using the program indicating their good knowledge of English sentence structure. However, they admit that using a computer program to draw tree diagrams is annoying and complicated. The results revealed that the computer tree generator helps produce neat and accurate tree diagrams, but the program should be made more accessible for the learners.
