Research Article
Zara Ersozlu, Susan Ledger, Mark Babic, Robert Parkes
CONT ED TECHNOLOGY, Volume 18, Issue 3, Article No: ep674
ABSTRACT
Artificial intelligence (AI) is increasingly being explored in educational assessment, but its use in high-stakes performance contexts requires careful design to support quality, consistency, and human accountability. This study designed and evaluated an AI-supported workflow to assist assessors in marking teaching performance assessment (TPA) portfolios. TPA assessors first described how they usually evaluate portfolios, and this process was used to develop a meta-level rubric logic, prompts, and workflow for the AI agent. The workflow was tested by comparing human-only marking with AI supported marking in relation to time, accuracy, cognitive load, feedback quality, usability, bias, and fairness. The findings showed that the AI-supported workflow reduced marking time and perceived workload while supporting more structured, evidence-based feedback. It also contributed to greater consistency and fairness in the moderation process. The AI agent is positioned as a “third eye” that supports human judgement. Human assessors remain responsible for making final decisions and may accept, adapt or override AI-generated suggestions.
Keywords: GenAI, human-in-the-loop, cognitive load, time efficiency, judgement support, moderation, teaching performance assessment
Research Article
Afif Ikhwanul Muslimin, Nur Mukminatien, Francisca Maria Ivone
CONT ED TECHNOLOGY, Volume 15, Issue 2, Article No: ep409
ABSTRACT
This study aimed to scrutinize the correlation between English as a foreign language (EFL) lecturers’ digital literacy competence (DLC) based on the TPACK-SAMR framework and their technostress. In addition, this study revealed how the variables correlated to the lecturers’ EFL teaching performances. Therefore, a correlational design with a descriptive explanation model was conducted. The participants were six EFL lecturers from six different universities in various cities in East Java Province, Indonesia. The data were collected by administering TPACK-SAMR DLC and technostress questionnaires, conducting a semi-structured interview, and documenting the teaching scenarios. The results showed that most participants were more confident with their pedagogical knowledge and content knowledge. They claimed it was hard to mingle them into harmonious teaching performances with technology that challenged them to achieve the higher TPACK-SAMR DLC level. Relevant to this finding, their DLC had a negative ‘very high’ correlation with technostress, shown by -.824 Pearson correlation coefficient. Henceforth, their EFL teaching performances reflected the minimum operation of technology, according to SAMR stages, to mediate EFL teaching by substituting and augmenting the technology. Therefore, this study highlights the importance of DLC training to escalate the positive outcomes of EFL teaching with technology and minimize technostress.
Keywords: digital literacy competence, EFL, TPACK-SAMR, teaching performance, technostress