Students’ Perceptions of Google Form Video Tasks for Digital Authentic Technical English Speaking Assessment
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2946-2956
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10.58578/mikailalsys.v4i2.10847
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Authors:
Yuliatri Novita1*, Yenni Rozimela2, Syahrul Ramadhan3 
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Abstract
Although digital assessment and video-based tasks have received increasing attention in English language teaching, studies specifically examining mechanical engineering students’ perceptions of video-based speaking assessment via Google Form in Technical English contexts remain limited. This study aims to describe mechanical engineering students’ perceptions of Google Form video tasks as a form of digital authentic assessment for Technical English speaking skills. A quantitative survey design was employed, involving 25 mechanical engineering students at Politeknik Negeri Padang. Data were collected using a 24-item Likert-scale questionnaire covering six perception dimensions: task authenticity, relevance to English for Mechanical Engineering, Google Form usability, speaking confidence and autonomy, assessment clarity and feedback, and technical challenges. The data were analyzed using descriptive statistics, including frequency counts, percentages, and mean scores. The findings indicate that students’ overall perceptions were very high (M = 3.30; 82.50%), with task authenticity (M = 3.43) and relevance to Mechanical Engineering contexts (M = 3.38) receiving the highest ratings. Google Form usability was also rated very high (M = 3.31), whereas speaking confidence and autonomy (M = 3.16) and assessment clarity and feedback (M = 3.22) were categorized as high. Technical challenges, particularly internet connectivity and video file size, emerged as moderate concerns (M = 2.74). This study concludes that video-based task assessment via Google Form has strong potential as a practical, contextually grounded, and digitally mediated authentic assessment approach for Technical English speaking skills in vocational higher education. The study contributes to English for Specific Purposes assessment literature by demonstrating how digital video tasks can support authentic speaking assessment in mechanical engineering contexts. Practically, the findings imply that instructors should provide model videos, clear rubrics, and flexible submission options to address students’ technical and affective challenges.
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