Moodle and Telegram to develop students’ language performance and knowledge co-construction in technology-enhanced CLIL

David Imamyartha, Utami Widiati, Mirjam Anugerahwati, Afendi Hamat


This study compared Moodle and Telegram as mobile-instant messaging (MIM) to understand how the platforms performed in technology-enhanced content and language integrated learning (TECLIL) settings. It involved 68 English for Academic Purpose (EAP) students enrolled in two groups, i.e., Moodle group and Telegram group. Using the mixed-method design, the study garnered quantitative data through pre- and post-tests of language performance coupled with post-tests of spoken presentation, content knowledge, and collective knowledge co-construction. Qualitative data concerning the interaction patterns in online discussion forums were amassed by retrieving students’ postings on both platforms. This study garnered additional quantitative data as covariates, which involved a survey of technology acceptance and a survey of teacher evaluation. Upon analysis, paired sample t-test was operative to identify noteworthy differences between groups with respect to technology acceptance, evaluation of teacher performance, language performance, and content knowledge. For the qualitative inquiry, thread analysis on the interaction patterns in both groups was conducted to scrutinize their depth of knowledge co-construction. Although the interaction trends in both platforms mark the dominance of knowledge sharing, the findings lend credence to the stronger potential of Moodle to empower students’ in-depth knowledge co-construction while exercising their subject-specific language performance. For deep engagement in knowledge co-construction and authentic language use, teachers need to provide appropriate scaffolding through modeling effective collaboration, making explicit the characteristics of quality discussion, and establishing a mutual understanding of what students need to achieve in the online discussion forum.


Knowledge co-construction; language performance; Moodle; TECLIL; Telegram

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