Research Article
Burçin Hasanbaşoğlu, Mustafa Baloglu
CONT ED TECHNOLOGY, Volume 18, Issue 2, Article No: ep637
ABSTRACT
The introduction of artificial intelligence-powered large language models has revolutionized academic writing and transformed conventional practices into richer experiences, which has opened new avenues for brainstorming, drafting, and revising written work. This study examined how academically gifted college students used ChatGPT in academic writing. The participants were nine academically gifted students enrolled in a freshman English course at a tier-one public university in Türkiye. To examine the purposes and stages of use, we subjected students’ ChatGPT conversations to content analysis. Drawing on 52 chat prompts and a structured focus group, we mapped when and why gifted students deployed ChatGPT across planning, drafting, and revision. The findings identified several potential contributions (i.e., efficiency, adaptability, and incidental learning) and risks (i.e., integrity, reliability, originality, and dependence) of using the large language model tools, informing AI literacy, and assessment design in higher education.
Keywords: ChatGPT, academically gifted, academic writing, college students, gifted
Research Article
Surachai Pimsalee, Aukkapong Sukkamart, Paitoon Pimdee, Chontawat Meedee
CONT ED TECHNOLOGY, Volume 18, Issue 2, Article No: ep638
ABSTRACT
This study aimed to evaluate the current and desired software development skills within the context of Thai undergraduate teacher education. Specifically, the study investigated pre-service computer technology students’ perceptions of secondary learners’ software skill needs in authentic classroom contexts. Seventy-nine participants, including pre-service students, instructors, and teaching mentors, were selected via simple random sampling in June 2025. Data were collected using a 5-point Likert-scale questionnaire measuring current (D) and ideal (I) skill levels, with internal consistency coefficients of 0.87 and 0.96, respectively. The PNImodified (priority needs index modified) method and paired t-tests were used to analyze the gaps. Results showed that participants perceived actual skill levels as generally ‘competent’, while the desired levels were rated as ‘proficient’. The highest training needs were observed in deployment & maintenance (GSA6), followed by programming (GSA4), requirements analysis (GSA2), testing (GSA5), design (GSA3), and planning (GSA1), respectively. These findings highlight the need to align educational curricula with real-world software development practices, including DevOps, secure coding, and testing frameworks.
Keywords: PNI, pre-service ICT teachers, priority needs assessment, software development life cycle, software development skills, perception gap