#language_learning

Available at :https://doi.org/10.58803/jclr.v4i4.142

#education #language_learning #translation #applied #research

https://www.instagram.com/p/DUcyzkLCEcB/?igsh=MTN6cmttYTFzbGx5cQ==

Available at :https://doi.org/10.58803/jclr.v4i4.141

#education #language_learning #translation #applied #research

https://www.instagram.com/p/DT9sXKojohQ/?igsh=MTU5emg1b3Q2ZmNwdA==

Methodology: Drawing on Dressler’s (1987) Natural Morphology Theory, it highlights both the natural and innovative dimensions of blending in brand naming. Following Mathew’s 1974 model and Mattiello’s (2013) model, the analysis applies two main classification systems: word class and morphological structure. The word class classification includes brand names formed from Igbo nouns and verbs, combinations of loanwords and Igbo terms, English nouns and verbs, pseudo-morphemes, adjectives, and translated forms. The morphological classification distinguishes among morphotactical blends (total and partial), morphophonological blends (overlapping and non-overlapping), and morphosemantic blends (attributive and coordinate). Data were collected from the Onitsha Relief Market, Anambra State, Nigeria.

Available at :https://jclr.rovedar.com/index.php/JCLR/article/view/139

# s Vol. 4 No. 3 (2025): Journal of Contemporary Language Research Research Articles

https://www.instagram.com/p/DP5r-PtCA6a/?igsh=MW43dHplNXk1MjI1OA==

Methodology: Drawing on Dressler’s (1987) Natural Morphology Theory, it highlights both the natural and innovative dimensions of blending in brand naming. Following Mathew’s 1974 model and Mattiello’s (2013) model, the analysis applies two main classification systems: word class and morphological structure. The word class classification includes brand names formed from Igbo nouns and verbs, combinations of loanwords and Igbo terms, English nouns and verbs, pseudo-morphemes, adjectives, and translated forms. The morphological classification distinguishes among morphotactical blends (total and partial), morphophonological blends (overlapping and non-overlapping), and morphosemantic blends (attributive and coordinate). Data were collected from the Onitsha Relief Market, Anambra State, Nigeria.

Available at :https://jclr.rovedar.com/index.php/JCLR/article/view/139

https://www.instagram.com/p/DP5r-PtCA6a/?igsh=MW43dHplNXk1MjI1OA==

Methodology: A structured teacher-training course was implemented, during which participants created their own corpora and utilized NLP tools to develop teaching materials. Pre- and post-course questionnaires were administered to assess changes in attitudes towards CL. The chi-square tests were used to analyze the significance of the collected data.

Results: Findings indicated a significant positive shift in perceptions. Engagement with CL tools led to increased appreciation for data-driven methodologies, with participants expressing a greater likelihood of incorporating these tools into their future teaching practices. The chi-square analysis confirmed the statistical significance of these changes.

Conclusion: Practical engagement with CL and related technologies can effectively address initial skepticism among teacher trainees. These results advocate for the inclusion of CL components in teacher training curricula to promote innovative, data-driven language teaching practices and bridge the gap between skepticism and effective application.

https://www.instagram.com/p/DODMGEyCMOk/?igsh=cmJ3ZGV6MmdxaHpl