International Journal of
Information and Education Technology

Abstract—In the domain of Technology-Enhanced Language Learning (TELL), this research, grounded in Cognitive-Constructivist principles, explores the efficacy of Teacher-Mate Technology (TMT) in promoting English vocabulary acquisition among 144 non-English major students. Quantitative analysis using Statistical Product and Service Solutions (SPSS) V.29 on test scores and engagement data revealed substantial improvements in vocabulary retention and application. In contrast, qualitative analysis via Sojump indicated that 78.38% of learners reported enhanced vocabulary acquisition. TMT significantly enhanced vocabulary-dependent skills like writing and translation but had a restricted impact on overall language performance, particularly in reading comprehension. The results validate TMT’s alignment with the Constructivist tenets of active learning, social interaction, and personalized knowledge construction. However, the study also highlights the need for supplementary strategies to foster holistic language development, thus offering educators a theoretically grounded, technology-enhanced approach to vocabulary instruction and contributing to the growing body of knowledge in TELL.

Keywords—Teacher-Mate Technology (TMT), vocabulary acquisition, cognitive-constructivist pedagogy, Technology-Enhanced Language Learning (TELL)

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Cite: Pengbiao Zhang and Fengjunzi Wang, "Exploiting Teacher-Mate Technology for College English Vocabulary Augmentation: A Cognitive-Constructivist Empirical Research," International Journal of Information and Education Technology, vol. 15, no. 5, pp. 937-946, 2025.

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